Search results for: Data Mining.
6760 Model of Optimal Centroids Approach for Multivariate Data Classification
Authors: Pham Van Nha, Le Cam Binh
Abstract:
Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8846759 Application-Specific Instruction Sets Processor with Implicit Registers to Improve Register Bandwidth
Authors: Ginhsuan Li, Chiuyun Hung, Desheng Chen, Yiwen Wang
Abstract:
Application-Specific Instruction (ASI ) set Processors (ASIP) have become an important design choice for embedded systems due to runtime flexibility, which cannot be provided by custom ASIC solutions. One major bottleneck in maximizing ASIP performance is the limitation on the data bandwidth between the General Purpose Register File (GPRF) and ASIs. This paper presents the Implicit Registers (IRs) to provide the desirable data bandwidth. An ASI Input/Output model is proposed to formulate the overheads of the additional data transfer between the GPRF and IRs, therefore, an IRs allocation algorithm is used to achieve the better performance by minimizing the number of extra data transfer instructions. The experiment results show an up to 3.33x speedup compared to the results without using IRs.Keywords: Application-Specific Instruction-set Processors, data bandwidth, configurable processor, implicit register.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15296758 Performance Evaluation of Data Transfer Protocol GridFTP for Grid Computing
Authors: Hiroyuki Ohsaki, Makoto Imase
Abstract:
In Grid computing, a data transfer protocol called GridFTP has been widely used for efficiently transferring a large volume of data. Currently, two versions of GridFTP protocols, GridFTP version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have been proposed in the GGF. GridFTP v2 supports several advanced features such as data streaming, dynamic resource allocation, and checksum transfer, by defining a transfer mode called X-block mode. However, in the literature, effectiveness of GridFTP v2 has not been fully investigated. In this paper, we therefore quantitatively evaluate performance of GridFTP v1 and GridFTP v2 using mathematical analysis and simulation experiments. We reveal the performance limitation of GridFTP v1, and quantitatively show effectiveness of GridFTP v2. Through several numerical examples, we show that by utilizing the data streaming feature, the average file transfer time of GridFTP v2 is significantly smaller than that of GridFTP v1.Keywords: Grid Computing, GridFTP, Performance Evaluation, Queuing Theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13906757 Perception-Oriented Model Driven Development for Designing Data Acquisition Process in Wireless Sensor Networks
Authors: K. Indra Gandhi
Abstract:
Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.
Keywords: Model-driven development, wireless sensor networks, data acquisition, separation of concern, layered design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9436756 Secure Socket Layer in the Network and Web Security
Authors: Roza Dastres, Mohsen Soori
Abstract:
In order to electronically exchange information between network users in the web of data, different software such as outlook is presented. So, the traffic of users on a site or even the floors of a building can be decreased as a result of applying a secure and reliable data sharing software. It is essential to provide a fast, secure and reliable network system in the data sharing webs to create an advanced communication systems in the users of network. In the present research work, different encoding methods and algorithms in data sharing systems is studied in order to increase security of data sharing systems by preventing the access of hackers to the transferred data. To increase security in the networks, the possibility of textual conversation between customers of a local network is studied. Application of the encryption and decryption algorithms is studied in order to increase security in networks by preventing hackers from infiltrating. As a result, a reliable and secure communication system between members of a network can be provided by preventing additional traffic in the website environment in order to increase speed, accuracy and security in the network and web systems of data sharing.
Keywords: Secure Socket Layer, Security of networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4846755 Review of the Road Crash Data Availability in Iraq
Authors: Abeer K. Jameel, Harry Evdorides
Abstract:
Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.
Keywords: Data availability, Iraq, road safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9066754 Accurate HLA Typing at High-Digit Resolution from NGS Data
Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang
Abstract:
Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.
Keywords: Human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26096753 Consideration a Novel Manner for Data Sending Quality in Heterogeneous Radio Networks
Authors: Mohammadreza Amini, Omid Moradtalab, Ebadollah Zohrevandi
Abstract:
In real-time networks a large number of application programs are relying on video data and heterogeneous data transmission techniques. The aim of this research is presenting a method for end-to-end vouch quality service in surface applicationlayer for sending video data in comparison form in wireless heterogeneous networks. This method tries to improve the video sending over the wireless heterogeneous networks with used techniques in surface layer, link and application. The offered method is showing a considerable improvement in quality observing by user. In addition to this, other specifications such as shortage of data load that had require to resending and limited the relation period length to require time for second data sending, help to be used the offered method in the wireless devices that have a limited energy. The presented method and the achieved improvement is simulated and presented in the NS-2 software.
Keywords: Heterogeneous wireless networks, adaptation mechanism, multi-level, Handoff, stop mechanism, graceful degrades, application layer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16526752 An Efficient 3D Animation Data Reduction Using Frame Removal
Authors: Jinsuk Yang, Choongjae Joo, Kyoungsu Oh
Abstract:
Existing methods in which the animation data of all frames are stored and reproduced as with vertex animation cannot be used in mobile device environments because these methods use large amounts of the memory. So 3D animation data reduction methods aimed at solving this problem have been extensively studied thus far and we propose a new method as follows. First, we find and remove frames in which motion changes are small out of all animation frames and store only the animation data of remaining frames (involving large motion changes). When playing the animation, the removed frame areas are reconstructed using the interpolation of the remaining frames. Our key contribution is to calculate the accelerations of the joints of individual frames and the standard deviations of the accelerations using the information of joint locations in the relevant 3D model in order to find and delete frames in which motion changes are small. Our methods can reduce data sizes by approximately 50% or more while providing quality which is not much lower compared to original animations. Therefore, our method is expected to be usefully used in mobile device environments or other environments in which memory sizes are limited.
Keywords: Data Reduction, Interpolation, Vertex Animation, 3D Animation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16466751 Diagnosis of the Heart Rhythm Disorders by Using Hybrid Classifiers
Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen
Abstract:
In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.
As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.
Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19046750 Validation of Visibility Data from Road Weather Information Systems by Comparing Three Data Resources: Case Study in Ohio
Authors: Fan Ye
Abstract:
Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.
Keywords: Low visibility, RWIS, traffic safety, visibility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13196749 Web Usability : A Fuzzy Approach to the Navigation Structure Enhancement in a Website System, Case of Iranian Civil Aviation Organization Website
Authors: Hamed Qahri Saremi, Gholam Ali Montazer
Abstract:
With the proliferation of World Wide Web, development of web-based technologies and the growth in web content, the structure of a website becomes more complex and web navigation becomes a critical issue to both web designers and users. In this paper we define the content and web pages as two important and influential factors in website navigation and paraphrase the enhancement in the website navigation as making some useful changes in the link structure of the website based on the aforementioned factors. Then we suggest a new method for proposing the changes using fuzzy approach to optimize the website architecture. Applying the proposed method to a real case of Iranian Civil Aviation Organization (CAO) website, we discuss the results of the novel approach at the final section.Keywords: Web content, Web navigation, Website system, Webusage mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17756748 Implementation of Neural Network Based Electricity Load Forecasting
Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw
Abstract:
This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.Keywords: Neural network, Load forecast, Time series, wavelettransform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24806747 Integration of Big Data to Predict Transportation for Smart Cities
Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin
Abstract:
The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system. The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.
Keywords: Big data, bus headway prediction, machine learning, public transportation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15446746 Clustering Approach to Unveiling Relationships between Gene Regulatory Networks
Authors: Hiba Hasan, Khalid Raza
Abstract:
Reverse engineering of genetic regulatory network involves the modeling of the given gene expression data into a form of the network. Computationally it is possible to have the relationships between genes, so called gene regulatory networks (GRNs), that can help to find the genomics and proteomics based diagnostic approach for any disease. In this paper, clustering based method has been used to reconstruct genetic regulatory network from time series gene expression data. Supercoiled data set from Escherichia coli has been taken to demonstrate the proposed method.
Keywords: Gene expression, gene regulatory networks (GRNs), clustering, data preprocessing, network visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21336745 Estimating Bridge Deterioration for Small Data Sets Using Regression and Markov Models
Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales
Abstract:
The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.
Keywords: Concrete bridges, deterioration, Markov chains, probability matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14246744 Towards Achieving Energy Efficiency in Kazakhstan
Authors: Aigerim Uyzbayeva, Valeriya Tyo, Nurlan Ibrayev
Abstract:
Kazakhstan is currently one of the dynamically developing states in its region. The stable growth in all sectors of the economy leads to a corresponding increase in energy consumption. Thus country consumes significant amount of energy due to the high level of industrialisation and the presence of energy-intensive manufacturing such as mining and metallurgy which in turn leads to low energy efficiency. With allowance for this the Government has set several priorities to adopt a transition of Republic of Kazakhstan to a “green economy”. This article provides an overview of Kazakhstan’s energy efficiency situation in for the period of 1991- 2014. First, the dynamics of production and consumption of conventional energy resources are given. Second, the potential of renewable energy sources is summarised followed by the description of GHG emissions trends in the country. Third, Kazakhstan’ national initiatives, policies and locally implemented projects in the field of energy efficiency are described.
Keywords: Energy efficiency in Kazakhstan, greenhouse gases, renewable energy, sustainable development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35276743 A Conceptual Query-Driven Design Framework for Data Warehouse
Authors: Resmi Nair, Campbell Wilson, Bala Srinivasan
Abstract:
Data warehouse is a dedicated database used for querying and reporting. Queries in this environment show special characteristics such as multidimensionality and aggregation. Exploiting the nature of queries, in this paper we propose a query driven design framework. The proposed framework is general and allows a designer to generate a schema based on a set of queries.Keywords: Conceptual schema, data warehouse, queries, requirements.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19936742 A Prototype of Augmented Reality for Visualising Large Sensors’ Datasets
Authors: Folorunso Olufemi Ayinde, Mohd Shahrizal Sunar, Sarudin Kari, Dzulkifli Mohamad
Abstract:
In this paper we discuss the development of an Augmented Reality (AR) - based scientific visualization system prototype that supports identification, localisation, and 3D visualisation of oil leakages sensors datasets. Sensors generates significant amount of multivariate datasets during normal and leak situations. Therefore we have developed a data model to effectively manage such data and enhance the computational support needed for the effective data explorations. A challenge of this approach is to reduce the data inefficiency powered by the disparate, repeated, inconsistent and missing attributes of most available sensors datasets. To handle this challenge, this paper aim to develop an AR-based scientific visualization interface which automatically identifies, localise and visualizes all necessary data relevant to a particularly selected region of interest (ROI) along the virtual pipeline network. Necessary system architectural supports needed as well as the interface requirements for such visualizations are also discussed in this paper.
Keywords: Sensor Leakages Datasets, Augmented Reality, Sensor Data-Model, Scientific Visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16636741 Secure Cryptographic Operations on SIM Card for Mobile Financial Services
Authors: Kerem Ok, Serafettin Senturk, Serdar Aktas, Cem Cevikbas
Abstract:
Mobile technology is very popular nowadays and it provides a digital world where users can experience many value-added services. Service Providers are also eager to offer diverse value-added services to users such as digital identity, mobile financial services and so on. In this context, the security of data storage in smartphones and the security of communication between the smartphone and service provider are critical for the success of these services. In order to provide the required security functions, the SIM card is one acceptable alternative. Since SIM cards include a Secure Element, they are able to store sensitive data, create cryptographically secure keys, encrypt and decrypt data. In this paper, we design and implement a SIM and a smartphone framework that uses a SIM card for secure key generation, key storage, data encryption, data decryption and digital signing for mobile financial services. Our frameworks show that the SIM card can be used as a controlled Secure Element to provide required security functions for popular e-services such as mobile financial services.Keywords: SIM Card, mobile financial services, cryptography, secure data storage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20466740 A Soft Systems Methodology Perspective on Data Warehousing Education Improvement
Abstract:
This paper demonstrates how the soft systems methodology can be used to improve the delivery of a module in data warehousing for fourth year information technology students. Graduates in information technology needs to have academic skills but also needs to have good practical skills to meet the skills requirements of the information technology industry. In developing and improving current data warehousing education modules one has to find a balance in meeting the expectations of various role players such as the students themselves, industry and academia. The soft systems methodology, developed by Peter Checkland, provides a methodology for facilitating problem understanding from different world views. In this paper it is demonstrated how the soft systems methodology can be used to plan the improvement of data warehousing education for fourth year information technology students.Keywords: Data warehousing, education, soft systems methodology, stakeholders, systems thinking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16826739 Security Architecture for At-Home Medical Care Using Sensor Network
Authors: S.S.Mohanavalli, Sheila Anand
Abstract:
This paper proposes a novel architecture for At- Home medical care which enables senior citizens, patients with chronic ailments and patients requiring post- operative care to be remotely monitored in the comfort of their homes. This architecture is implemented using sensors and wireless networking for transmitting patient data to the hospitals, health- care centers for monitoring by medical professionals. Patients are equipped with sensors to measure their physiological parameters, like blood pressure, pulse rate etc. and a Wearable Data Acquisition Unit is used to transmit the patient sensor data. Medical professionals can be alerted to any abnormal variations in these values for diagnosis and suitable treatment. Security threats and challenges inherent to wireless communication and sensor network have been discussed and a security mechanism to ensure data confidentiality and source authentication has been proposed. Symmetric key algorithm AES has been used for encrypting the data and a patent-free, two-pass block cipher mode CCFB has been used for implementing semantic security.Keywords: data confidentiality, integrity, remotemonitoring, source authentication
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17226738 An Automatic Tool for Checking Consistency between Data Flow Diagrams (DFDs)
Authors: Rosziati Ibrahim, Siow Yen Yen
Abstract:
System development life cycle (SDLC) is a process uses during the development of any system. SDLC consists of four main phases: analysis, design, implement and testing. During analysis phase, context diagram and data flow diagrams are used to produce the process model of a system. A consistency of the context diagram to lower-level data flow diagrams is very important in smoothing up developing process of a system. However, manual consistency check from context diagram to lower-level data flow diagrams by using a checklist is time-consuming process. At the same time, the limitation of human ability to validate the errors is one of the factors that influence the correctness and balancing of the diagrams. This paper presents a tool that automates the consistency check between Data Flow Diagrams (DFDs) based on the rules of DFDs. The tool serves two purposes: as an editor to draw the diagrams and as a checker to check the correctness of the diagrams drawn. The consistency check from context diagram to lower-level data flow diagrams is embedded inside the tool to overcome the manual checking problem.Keywords: Data Flow Diagram, Context Diagram, ConsistencyCheck, Syntax and Semantic Rules
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34236737 Real-Time Implementation of STANAG 4539 High-Speed HF Modem
Authors: S. Saraç, F. Kara, C.Vural
Abstract:
High-frequency (HF) communications have been used by military organizations for more than 90 years. The opportunity of very long range communications without the need for advanced equipment makes HF a convenient and inexpensive alternative of satellite communications. Besides the advantages, voice and data transmission over HF is a challenging task, because the HF channel generally suffers from Doppler shift and spread, multi-path, cochannel interference, and many other sources of noise. In constructing an HF data modem, all these effects must be taken into account. STANAG 4539 is a NATO standard for high-speed data transmission over HF. It allows data rates up to 12800 bps over an HF channel of 3 kHz. In this work, an efficient implementation of STANAG 4539 on a single Texas Instruments- TMS320C6747 DSP chip is described. The state-of-the-art algorithms used in the receiver and the efficiency of the implementation enables real-time high-speed data / digitized voice transmission over poor HF channels.
Keywords: High frequency, modem, STANAG 4539.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53176736 Detection Efficient Enterprises via Data Envelopment Analysis
Authors: S. Turkan
Abstract:
In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.Keywords: Data envelopment analysis, super efficiency, financial ratios, BCC model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8656735 Fusion of ETM+ Multispectral and Panchromatic Texture for Remote Sensing Classification
Authors: Mahesh Pal
Abstract:
This paper proposes to use ETM+ multispectral data and panchromatic band as well as texture features derived from the panchromatic band for land cover classification. Four texture features including one 'internal texture' and three GLCM based textures namely correlation, entropy, and inverse different moment were used in combination with ETM+ multispectral data. Two data sets involving combination of multispectral, panchromatic band and its texture were used and results were compared with those obtained by using multispectral data alone. A decision tree classifier with and without boosting were used to classify different datasets. Results from this study suggest that the dataset consisting of panchromatic band, four of its texture features and multispectral data was able to increase the classification accuracy by about 2%. In comparison, a boosted decision tree was able to increase the classification accuracy by about 3% with the same dataset.Keywords: Internal texture; GLCM; decision tree; boosting; classification accuracy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17236734 Knowledge Acquisition for the Construction of an Evolving Ontology: Application to Augmented Surgery
Authors: Nora Taleb, Sellami Mokhtar, Michel Simonet
Abstract:
This work concerns the evolution and the maintenance of an ontological resource in relation with the evolution of the corpus of texts from which it had been built. The knowledge forming a text corpus, especially in dynamic domains, is in continuous evolution. When a change in the corpus occurs, the domain ontology must evolve accordingly. Most methods manage ontology evolution independently from the corpus from which it is built; in addition, they treat evolution just as a process of knowledge addition, not considering other knowledge changes. We propose a methodology for managing an evolving ontology from a text corpus that evolves over time, while preserving the consistency and the persistence of this ontology. Our methodology is based on the changes made on the corpus to reflect the evolution of the considered domain - augmented surgery in our case. In this context, the results of text mining techniques, as well as the ARCHONTE method slightly modified, are used to support the evolution process.Keywords: Corpus, Evolution, Ontology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14246733 A Formal Approach for Instructional Design Integrated with Data Visualization for Learning Analytics
Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel
Abstract:
Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.
Keywords: Educational data visualization, high-level petri nets, instructional design, learning analytics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8366732 Churn Prediction for Telecommunication Industry Using Artificial Neural Networks
Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz
Abstract:
Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7366731 A Technical Perspective on Roadway Safety in Eastern Province: Data Evaluation and Spatial Analysis
Authors: Muhammad Farhan, Sayed Faruque, Amr Mohammed, Sami Osman, Omar Al-Jabari, Abdul Almojil
Abstract:
Saudi Arabia in recent years has seen drastic increase in traffic related crashes. With population of over 29 million, Saudi Arabia is considered as a fast growing and emerging economy. The rapid population increase and economic growth has resulted in rapid expansion of transportation infrastructure, which has led to increase in road crashes. Saudi Ministry of Interior reported more than 7,000 people killed and 68,000 injured in 2011 ranking Saudi Arabia to be one of the worst worldwide in traffic safety. The traffic safety issues in the country also result in distress to road users and cause and economic loss exceeding 3.7 billion Euros annually. Keeping this in view, the researchers in Saudi Arabia are investigating ways to improve traffic safety conditions in the country. This paper presents a multilevel approach to collect traffic safety related data required to do traffic safety studies in the region. Two highway corridors including King Fahd Highway 39 kilometre and Gulf Cooperation Council Highway 42 kilometre long connecting the cities of Dammam and Khobar were selected as a study area. Traffic data collected included traffic counts, crash data, travel time data, and speed data. The collected data was analysed using geographic information system to evaluate any correlation. Further research is needed to investigate the effectiveness of traffic safety related data when collected in a concerted effort.
Keywords: Crash Data, Data Collection, Traffic Safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2339