Search results for: Data protection
6497 The Carbon Trading Price and Trading Volume Forecast in Shanghai City by BP Neural Network
Authors: Liu Zhiyuan, Sun Zongdi
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In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network model. Finally, after the training of BP neural network, the prediction values of Shanghai carbon trading price and trading volume are obtained, and the model is tested.
Keywords: Carbon trading price, carbon trading volume, BP neural network model, Shanghai City.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13906496 Dynamic Decompression for Text Files
Authors: Ananth Kamath, Ankit Kant, Aravind Srivatsa, Harisha J.A
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Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv (LZ) family, Dynamic Markov Compression (DMC), Prediction by Partial Matching (PPM), and Burrows-Wheeler Transform (BWT) based algorithms. Decompression is also required to retrieve the original data by lossless means. A compression scheme for text files coupled with the principle of dynamic decompression, which decompresses only the section of the compressed text file required by the user instead of decompressing the entire text file. Dynamic decompressed files offer better disk space utilization due to higher compression ratios compared to most of the currently available text file formats.Keywords: Compression, Dynamic Decompression, Text file format, Portable Document Format, Compression Ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17556495 Deriving Generic Transformation Matrices for Multi-Axis Milling Machine
Authors: Alan C. Lin, Tzu-Kuan Lin, Tsong Der Lin
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This paper proposes a new method to find the equations of transformation matrix for the rotation angles of the two rotational axes and the coordinates of the three linear axes of an orthogonal multi-axis milling machine. This approach provides intuitive physical meanings for rotation angles of multi-axis machines, which can be used to evaluate the accuracy of the conversion from CL data to NC data.
Keywords: CAM, multi-axis milling machining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35766494 Consumer Product Demand Forecasting based on Artificial Neural Network and Support Vector Machine
Authors: Karin Kandananond
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The nature of consumer products causes the difficulty in forecasting the future demands and the accuracy of the forecasts significantly affects the overall performance of the supply chain system. In this study, two data mining methods, artificial neural network (ANN) and support vector machine (SVM), were utilized to predict the demand of consumer products. The training data used was the actual demand of six different products from a consumer product company in Thailand. The results indicated that SVM had a better forecast quality (in term of MAPE) than ANN in every category of products. Moreover, another important finding was the margin difference of MAPE from these two methods was significantly high when the data was highly correlated.Keywords: Artificial neural network (ANN), Bullwhip effect, Consumer products, Demand forecasting, Supply chain, Support vector machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30026493 Comparison of Security Challenges and Issues of Mobile Computing and Internet of Things
Authors: Aabiah Nayeem, Fariha Shafiq, Mustabshra Aftab, Rabia Saman Pirzada, Samia Ghazala
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In this modern era of technology, the concept of Internet of Things is very popular in every domain. It is a widely distributed system of things in which the data collected from sensory devices is transmitted, analyzed locally/collectively then broadcasted to network where action can be taken remotely via mobile/web apps. Today’s mobile computing is also gaining importance as the services are provided during mobility. Through mobile computing, data are transmitted via computer without physically connected to a fixed point. The challenge is to provide services with high speed and security. Also, the data gathered from the mobiles must be processed in a secured way. Mobile computing is strongly influenced by internet of things. In this paper, we have discussed security issues and challenges of internet of things and mobile computing and we have compared both of them on the basis of similarities and dissimilarities.
Keywords: Embedded computing, internet of things, mobile computing, and wireless technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13116492 Analysis of Lead Time Delays in Supply Chain: A Case Study
Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry
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Lead time is a critical measure of a supply chain's performance. It impacts both the customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages respectively: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines was extracted from the company's records to use for this study. The sample data entails information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each stage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered later than the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impacts on lead time. Data analysis on the stages of lead time indicates that stage 2 consumed over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each stage. Recommendation was given to resolve the problem.Keywords: Lead time reduction, customer satisfaction, service quality, statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 66816491 Enhanced Clustering Analysis and Visualization Using Kohonen's Self-Organizing Feature Map Networks
Authors: Kasthurirangan Gopalakrishnan, Siddhartha Khaitan, Anshu Manik
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Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Keywords: Artificial neural networks, cluster analysis, Kohonen maps, wine recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21156490 Automation System for Optimization of Electrical and Thermal Energy Production in Cogenerative Gas Power Plants
Authors: Ion Miciu
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The system is made with main distributed components: First Level: Industrial Computers placed in Control Room (monitors thermal and electrical processes based on the data provided by the second level); Second Level: PLCs which collects data from process and transmits information on the first level; also takes commands from this level which are further, passed to execution elements from third level; Third Level: field elements consisting in 3 categories: data collecting elements; data transfer elements from the third level to the second; execution elements which take commands from the second level PLCs and executes them after which transmits the confirmation of execution to them. The purpose of the automatic functioning is the optimization of the co-generative electrical energy commissioning in the national energy system and the commissioning of thermal energy to the consumers. The integrated system treats the functioning of all the equipments and devices as a whole: Gas Turbine Units (GTU); MT 20kV Medium Voltage Station (MVS); 0,4 kV Low Voltage Station (LVS); Main Hot Water Boilers (MHW); Auxiliary Hot Water Boilers (AHW); Gas Compressor Unit (GCU); Thermal Agent Circulation Pumping Unit (TPU); Water Treating Station (WTS).Keywords: Automation System, Cogenerative Power Plant, Control, Monitoring, Real Time
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19716489 Ensembling Classifiers – An Application toImage Data Classification from Cherenkov Telescope Experiment
Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti
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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 with classifiers such as random forests, neural networks and support vector machines. The data sets are from MAGIC, a Cherenkov telescope experiment. The task is to classify gamma signals from overwhelmingly hadron and muon signals representing a rare class classification problem. We compare the individual classifiers with their ensemble counterparts and discuss the results. WEKA a wonderful tool for machine learning has been used for making the experiments.Keywords: Ensembles, WEKA, Neural networks [NN], SupportVector Machines [SVM], Random Forests [RF].
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17616488 A Consideration on the Offset Frontal Impact Modeling Using Spring-Mass Model
Authors: Jaemoon Lim
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To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.Keywords: Chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26646487 A Review of Test Protocols for Assessing Coating Performance of Water Ballast Tank Coatings
Authors: Emmanuel A. Oriaifo, Noel Perera, Alan Guy, Pak. S. Leung, Kian T. Tan
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Concerns on corrosion and effective coating protection of double hull tankers and bulk carriers in service have been raised especially in water ballast tanks (WBTs). Test protocols/methodologies specifically that which is incorporated in the International Maritime Organisation (IMO), Performance Standard for Protective Coatings for Dedicated Sea Water ballast tanks (PSPC) are being used to assess and evaluate the performance of the coatings for type approval prior to their application in WBTs. However, some of the type approved coatings may be applied as very thick films to less than ideally prepared steel substrates in the WBT. As such films experience hygrothermal cycling from operating and environmental conditions, they become embrittled which may ultimately result in cracking. This embrittlement of the coatings is identified as an undesirable feature in the PSPC but is not mentioned in the test protocols within it. There is therefore renewed industrial research aimed at understanding this issue in order to eliminate cracking and achieve the intended coating lifespan of 15 years in good condition. This paper will critically review test protocols currently used for assessing and evaluating coating performance, particularly the IMO PSPC.
Keywords: Corrosion Test, Hygrothermal Cycling, Coating Test Protocols, Water Ballast Tanks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42136486 Using Historical Data for Stock Prediction of a Tech Company
Authors: Sofia Stoica
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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.
Keywords: Finance, machine learning, opening price, stock market.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5926485 Evaluation of Energy-Aware QoS Routing Protocol for Ad Hoc Wireless Sensor Networks
Authors: M.K.Jeya Kumar
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Many advanced Routing protocols for wireless sensor networks have been implemented for the effective routing of data. Energy awareness is an essential design issue and almost all of these routing protocols are considered as energy efficient and its ultimate objective is to maximize the whole network lifetime. However, the introductions of video and imaging sensors have posed additional challenges. Transmission of video and imaging data requires both energy and QoS aware routing in order to ensure efficient usage of the sensors and effective access to the gathered measurements. In this paper, the performance of the energy-aware QoS routing Protocol are analyzed in different performance metrics like average lifetime of a node, average delay per packet and network throughput. The parameters considered in this study are end-to-end delay, real time data generation/capture rates, packet drop probability and buffer size. The network throughput for realtime and non-realtime data was also has been analyzed. The simulation has been done in NS2 simulation environment and the simulation results were analyzed with respect to different metrics.
Keywords: Cluster nodes, end-to-end delay, QoS routing, routing protocols, sensor networks, least-cost-path.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19356484 A New Hardware Implementation of Manchester Line Decoder
Authors: Ibrahim A. Khorwat, Nabil Naas
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In this paper, we present a simple circuit for Manchester decoding and without using any complicated or programmable devices. This circuit can decode 90kbps of transmitted encoded data; however, greater than this transmission rate can be decoded if high speed devices were used. We also present a new method for extracting the embedded clock from Manchester data in order to use it for serial-to-parallel conversion. All of our experimental measurements have been done using simulation.Keywords: High threshold level, level segregation, lowthreshold level, smoothing circuit synchronization..
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37776483 Long Term Evolution Multiple-Input Multiple-Output Network in Unmanned Air Vehicles Platform
Authors: Ashagrie Getnet Flattie
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Line-of-sight (LOS) information, data rates, good quality, and flexible network service are limited by the fact that, for the duration of any given connection, they experience severe variation in signal strength due to fading and path loss. Wireless system faces major challenges in achieving wide coverage and capacity without affecting the system performance and to access data everywhere, all the time. In this paper, the cell coverage and edge rate of different Multiple-input multiple-output (MIMO) schemes in 20 MHz Long Term Evolution (LTE) system under Unmanned Air Vehicles (UAV) platform are investigated. After some background on the enormous potential of UAV, MIMO, and LTE in wireless links, the paper highlights the presented system model which attempts to realize the various benefits of MIMO being incorporated into UAV platform. The performances of the three MIMO LTE schemes are compared with the performance of 4x4 MIMO LTE in UAV scheme carried out to evaluate the improvement in cell radius, BER, and data throughput of the system in different morphology. The results show that significant performance gains such as bit error rate (BER), data rate, and coverage can be achieved by using the presented scenario.Keywords: BER, LTE, MIMO, path loss, UAV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13846482 A Forecast Model for Projecting the Amount of Hazardous Waste
Authors: J. Vilgerts, L. Timma, D. Blumberga
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The objective of the paper is to develop the forecast model for the HW flows. The methodology of the research included 6 modules: historical data, assumptions, choose of indicators, data processing, and data analysis with STATGRAPHICS, and forecast models. The proposed methodology was validated for the case study for Latvia. Hypothesis on the changes in HW for time period of 2010-2020 have been developed and mathematically described with confidence level of 95.0% and 50.0%. Sensitivity analysis for the analyzed scenarios was done. The results show that the growth of GDP affects the total amount of HW in the country. The total amount of the HW is projected to be within the corridor of – 27.7% in the optimistic scenario up to +87.8% in the pessimistic scenario with confidence level of 50.0% for period of 2010-2020. The optimistic scenario has shown to be the least flexible to the changes in the GDP growth.Keywords: Forecast models, hazardous waste management, sustainable development, waste management indicators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18526481 A Performance Study of Fixed, Single-Axis and Dual-Axis Photovoltaic Systems in Kuwait
Authors: A. Al-Rashidi, A. El-Hamalawi
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In this paper, a performance study was conducted to investigate single and dual-axis PV systems to generate electricity in five different sites in Kuwait. Relevant data were obtained by using two sources for validation purposes. A commercial software, PVsyst, was used to analyse the data, such as metrological data and other input parameters, and compute the performance parameters such as capacity factor (CF) and final yield (YF). The results indicated that single and dual-axis PV systems would be very beneficial to electricity generation in Kuwait as an alternative source to conventional power plants, especially with the increased demand over time. The ranges were also found to be competitive in comparison to leading countries using similar systems. A significant increase in CF and YF values around 24% and 28.8% was achieved related to the use of single and dual systems, respectively.Keywords: Single-axis and dual-axis photovoltaic systems, capacity factor, final yield, renewable energy, Kuwait.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15506480 Network Intrusion Detection Design Using Feature Selection of Soft Computing Paradigms
Authors: T. S. Chou, K. K. Yen, J. Luo
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The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users- activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information from the original high dimensional database. Next, we design an intrusion detection method to solve the problems of uncertainty caused by limited and ambiguous information. In the experiments, we choose six UCI databases and DARPA KDD99 intrusion detection data set as our evaluation tools. Empirical studies indicate that our feature selection algorithm is capable of reducing the size of data set. Our intrusion detection method achieves a better performance than those of participating intrusion detectors.Keywords: Intrusion detection, feature selection, k-nearest neighbors, fuzzy clustering, Dempster-Shafer theory
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19246479 Estimation of Natural Convection Heat Transfer from Plate-Fin Heat Sinks in a Closed Enclosure
Authors: Han-Taw Chen, Chung-Hou Lai, Tzu-Hsiang Lin, Ge-Jang He
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This study applies the inverse method and three- dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a closed rectangular enclosure for various values of fin height. The inverse method with the finite difference method and the experimental temperature data is applied to determine the heat transfer coefficient. The k-ε turbulence model is used to obtain the heat transfer and fluid flow characteristics within the fins. To validate the accuracy of the results obtained, the comparison of the average heat transfer coefficient is made. The calculated temperature at selected measurement locations on the plate-fin is also compared with experimental data.
Keywords: Inverse method, FLUENT, k-ε model, Heat transfer characteristics, Plate-fin heat sink.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38336478 Improvement of Ground Truth Data for Eye Location on Infrared Driver Recordings
Authors: Sorin Valcan, Mihail Găianu
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Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need of labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to a ground truth data generation algorithm for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual labels adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.
Keywords: Labeling automation, infrared camera, driver monitoring, eye detection, Convolutional Neural Networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4046477 Structural Sustainability Techniques for RC High Rise Buildings
Authors: Mohamed A. Azab
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Over the early years of the 21st century, cities throughout the Middle East, particularly in the Gulf region have expanded more rapidly than ever before. Given the presence of a large volume of high-rise buildings allover the region, the local authority aims to set a new standard for sustainable development; with an integrated approach to maintain a balance between economy, quality, environmental protection and safety of life. In the very near future, as mandatory requirements, sustainability will be the criteria that should be included in all building projects. It is well known in the building sustainability topics that structural design engineers do not have a key role in this matter. In addition, the LEED (Leadership in Energy and Environmental Design) has looked almost exclusively on the environmental components and materials specifications. The objective of this paper is to focus and establish groundwork for sustainability techniques and applications related to the RC high-rise buildings design, from the structural point of view. A set of recommendations related to local conditions, structural modeling and analysis is given, and some helpful suggestions for structural design team work are addressed. This paper attempts to help structural engineers in identifying the building sustainability design, in order to meet local needs and achieve alternative solutions at an early stage of project design.Keywords: Building, Design, High-rise, Middle East, Structural, Sustainability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34656476 A New Authenticable Steganographic Method via the Use of Numeric Data on Public Websites
Authors: Che-Wei Lee, Bay-Erl Lai
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A new steganographic method via the use of numeric data on public websites with a self-authentication capability is proposed. The proposed technique transforms a secret message into partial shares by Shamir’s (k, n)-threshold secret sharing scheme with n = k + 1. The generated k+1 partial shares then are embedded into the numeric items to be disguised as part of the website’s numeric content, yielding the stego numeric content. Afterward, a receiver links to the website and extracts every k shares among the k+1 ones from the stego numeric content to compute k+1 copies of the secret, and the phenomenon of value consistency of the computed k+1 copies is taken as an evidence to determine whether the extracted message is authentic or not, attaining the goal of self-authentication of the extracted secret message. Experimental results and discussions are provided to show the feasibility and effectiveness of the proposed method.Keywords: Steganography, data hiding, secret authentication, secret sharing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16626475 Corporate Social Responsibility Disclosure, Tax Aggressiveness and Sustainability Report Assurance: Evidence from Thailand
Authors: Eko Budi Santoso, Kazia Laturette, Stanislaus Adnanto Mastan
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This study aims to examine the association between disclosure of social responsibility and tax aggressiveness in developing countries, namely Thailand. This is due to the increasing trend of disclosure of social responsibility in developing countries, even though this disclosure of information is still voluntary. On the other hand, developing countries have low taxation rate and investor protection infrastructures that allow the disclosure of social responsibility to be used opportunistically as a tool to fool the attainment of interests. This study also examines the role of assurance on the association between corporate social responsibility disclosure and tax aggressiveness. The assurance aims to provide confidence that the disclosure of social responsibility by the company is valid. This research builds an index to measure the disclosure of social responsibility based on the rules issued by the innovative Global Reporting. The results of the study are based on a sample of publicly traded companies in Thailand, which showed a positive association between disclosure of corporate social responsibility and tax aggressiveness, but it was further discovered that these results were mitigated by the existence of assurance against disclosure of corporate social responsibility. The results of this study indicate that the disclosure of corporate social responsibility can show that the company cares about the issue of social responsibility but does not automatically make the company as one that holds ethical values in its business practices.Keywords: Corporate Social Responsibility disclosure, tax aggressiveness, sustainability assurance, business ethics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15016474 Providing On-Demand Path and Arrival Time Information Considering Realtime Delays of Buses
Authors: Yoshifumi Ishizaki, Naoki Kanatani, Masaki Ito, Toshihiko Sasama, Takao Kawamura, Kazunori Sugahara
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This paper demonstrates the bus location system for the route bus through the experiment in the real environment. A bus location system is a system that provides information such as the bus delay and positions. This system uses actual services and positions data of buses, and those information should match data on the database. The system has two possible problems. One, the system could cost high in preparing devices to get bus positions. Two, it could be difficult to match services data of buses. To avoid these problems, we have developed this system at low cost and short time by using the smart phone with GPS and the bus route system. This system realizes the path planning considering bus delay and displaying position of buses on the map. The bus location system was demonstrated on route buses with smart phones for two months.Keywords: Route Bus, Path Planning System, GPS, Smart Phone.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14436473 Kinematic Analysis of an Assistive Robotic Leg for Hemiplegic and Hemiparetic Patients
Authors: M.R. Safizadeh, M. Hussein, K. F. Samat, M.S. Che Kob, M.S. Yaacob, M.Z. Md Zain
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The aim of this paper is to present the kinematic analysis and mechanism design of an assistive robotic leg for hemiplegic and hemiparetic patients. In this work, the priority is to design and develop the lightweight, effective and single driver mechanism on the basis of experimental hip and knee angles- data for walking speed of 1 km/h. A mechanism of cam-follower with three links is suggested for this purpose. The kinematic analysis is carried out and analysed using commercialized MATLAB software based on the prototype-s links sizes and kinematic relationships. In order to verify the kinematic analysis of the prototype, kinematic analysis data are compared with the experimental data. A good agreement between them proves that the anthropomorphic design of the lower extremity exoskeleton follows the human walking gait.Keywords: Kinematic analysis, assistive robotic leg, lower extremity exoskeleton, cam-follower mechanism.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19026472 Using Artificial Neural Network and Leudeking-Piret Model in the Kinetic Modeling of Microbial Production of Poly-β- Hydroxybutyrate
Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand
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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 48036471 Information Extraction from Unstructured and Ungrammatical Data Sources for Semantic Annotation
Authors: Quratulain N. Rajput, Sajjad Haider, Nasir Touheed
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The internet has become an attractive avenue for global e-business, e-learning, knowledge sharing, etc. Due to continuous increase in the volume of web content, it is not practically possible for a user to extract information by browsing and integrating data from a huge amount of web sources retrieved by the existing search engines. The semantic web technology enables advancement in information extraction by providing a suite of tools to integrate data from different sources. To take full advantage of semantic web, it is necessary to annotate existing web pages into semantic web pages. This research develops a tool, named OWIE (Ontology-based Web Information Extraction), for semantic web annotation using domain specific ontologies. The tool automatically extracts information from html pages with the help of pre-defined ontologies and gives them semantic representation. Two case studies have been conducted to analyze the accuracy of OWIE.Keywords: Ontology, Semantic Annotation, Wrapper, Information Extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21036470 The Evaluation of Production Line Performance by Using ARENA – A Case Study
Authors: Muhammad Marsudi, Hani Shafeek
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The purpose of this paper is to simulate the production process of a metal stamping industry and to evaluate the utilization of the production line by using ARENA simulation software. The process time and the standard time for each process of the production line is obtained from data given by the company management. Other data are collected through direct observation of the line. There are three work stations performing ten different types of processes in order to produce a single product type. Arena simulation model is then developed based on the collected data. Verification and validation are done to the Arena model, and finally the result of Arena simulation can be analyzed. It is found that utilization at each workstation will increase if batch size is increased although throughput rate remains/is kept constant. This study is very useful for the company because the company needs to improve the efficiency and utilization of its production lines.
Keywords: Arena software, case study, production line, utilization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53646469 A Large Ion Collider Experiment (ALICE) Diffractive Detector Control System for RUN-II at the Large Hadron Collider
Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón
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The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.Keywords: AD0, ALICE, DCS, LHC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13856468 Applications of Genetic Programming in Data Mining
Authors: Saleh Mesbah Elkaffas, Ahmed A. Toony
Abstract:
This paper details the application of a genetic programming framework for induction of useful classification rules from a database of income statements, balance sheets, and cash flow statements for North American public companies. Potentially interesting classification rules are discovered. Anomalies in the discovery process merit further investigation of the application of genetic programming to the dataset for the problem domain.Keywords: Genetic programming, data mining classification rule.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1538