Search results for: single instruction multiple data

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 2479

Authors: Rauza Sukma Rita, Katsuya Dezaki, Yuko Maejima, Toshihiko Yada

Abstract:

Oxytocin is a nine-amino acid peptide synthesized in the paraventricular nucleus (PVN) and supraoptic nucleus (SON) of the hypothalamus. Oxytocin promotes contraction of the uterus during birth and milk ejection during breast feeding. Although oxytocin receptors are found predominantly in the breasts and uterus of females, many tissues and organs express oxytocin receptors, including the pituitary, heart, kidney, thymus, vascular endothelium, adipocytes, osteoblasts, adrenal gland, pancreatic islets, and many cell lines. On the other hand, in pancreatic islets, oxytocin receptors are expressed in both α-cells and β-cells with stronger expression in α- cells. However, to our knowledge there are no reports yet about the effect of oxytocin on cytosolic calcium reaction on α and β-cell. This study aims to investigate the effect of oxytocin on α-cells and β-cells and its oscillation pattern. Islet of Langerhans from wild type mice were isolated by collagenase digestion. Isolated and dissociated single cells either α-cells or β-cells on coverslips were mounted in an open chamber and superfused in HKRB. Cytosolic concentration ([Ca2+]i) in single cells were measured by fura-2 microfluorimetry. After measurement of [Ca2+]i, α-cells were identified by subsequent immunocytochemical staining using an anti-glucagon antiserum. In β-cells, the [Ca2+]i increase in response to oxytocin was observed only under 8.3 mM glucose condition, whereas in α-cells, [Ca2+]i an increase induced by oxytocin was observed in both 2.8 mM and 8.3 mM glucose. The oscillation incidence was induced more frequently in β-cells compared to α-cells. In conclusion, the present study demonstrated that oxytocin directly interacts with both α-cells and β-cells and induces increase of [Ca2+]i and its specific patterns.

Keywords: α-cells, β-cells, cytosolic calcium concentration, oscillation, oxytocin.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1067

Authors: Tingke Wu, Man Yuan

Abstract:

“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: Driving forces, Hubei, optimizing strategies, spatial pattern, territory.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 595

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 1542

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 2131

Authors: Kyung Jin Ryu, Makhsuda Juraeva, Sang-Hyun Jeong, Dong Joo Song

Abstract:

The Platform Screen Doors improve Indoor Air Quality (IAQ) in the subway station; however, and the air quality is degraded in the subway tunnel. CO2 concentration and indoor particulate matter value are high in the tunnel. The IAQ level in subway tunnel degrades by increasing the train movements. Air-curtain installation reduces dusts, particles and moving toxic smokes and permits traffic by generating virtual wall. The ventilation systems of the subway tunnel need improvements to have better air-quality. Numerical analyses might be effective tools analyze the flowfield inside the air-curtain installed subway tunnel. The ANSYS CFX software is used for steady computations of the airflow inside the tunnel. The single-track subway tunnel has the natural shaft, the mechanical shaft, and the PSDs installed stations. The height and width of the tunnel are 6.0 m and 4.0 m respectively. The tunnel is 400 m long and the air-curtain is installed at the top of the tunnel. The thickness and the width of the air-curtain are 0.08 m and 4 m respectively. The velocity of the air-curtain changes between 20 - 30 m/s. Three cases are analyzed depending on the installing location of the air-curtain. The discharged-air through the natural shafts increases as the velocity of the air-curtain increases when the air-curtain is installed between the mechanical and the natural shafts. The pollutant-air is exhausted by the mechanical and the natural shafts and remained air is pushed toward tunnel end. The discharged-air through the natural shaft is low when the air-curtain installed before the natural shaft. The mass flow rate decreases in the tunnel after the mechanical shaft as the air-curtain velocity increases. The computational results of the air-curtain installed tunnel become basis for the optimum design study. The air-curtain installing location is chosen between the mechanical and the natural shafts. The velocity of the air-curtain is fixed as 25 m/s. The thickness and the blowing angles of the air-curtain are the design variables for the optimum design study. The object function of the design optimization is maximizing the discharged air through the natural shaft.

Keywords: air-curtain, indoor air quality, single-track subway tunnel

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2630

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 1423

Authors: Abbas Alli Taghipoor Bafghi, Hosein Bakhoda, Fateme Khodaei Chegeni

Abstract:

An experimental investigation is carried out to establish the performance characteristics of a compression ignition engine while using cerium oxide nanoparticles as additive in neat diesel and diesel-biodiesel blends. In the first phase of the experiments, stability of neat diesel and diesel-biodiesel fuel blends with the addition of cerium oxide nanoparticles is analyzed. After series of experiments, it is found that the blends subjected to high speed blending followed by ultrasonic bath stabilization improves the stability. In the second phase, performance characteristics are studied using the stable fuel blends in a single cylinder four stroke engine coupled with an electrical dynamometer and a data acquisition system. The cerium oxide acts as an oxygen donating catalyst and provides oxygen for combustion. The activation energy of cerium oxide acts to burn off carbon deposits within the engine cylinder at the wall temperature and prevents the deposition of non-polar compounds on the cylinder wall results reduction in HC emissions. The tests revealed that cerium oxide nanoparticles can be used as additive in diesel and diesel-biodiesel blends to improve complete combustion of the fuel significantly.

Keywords: Diesel engine, cerium oxide, diesel-biodiesel blends, nanoparticles.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4795

Authors: C. Ardil

Abstract:

The purpose of this paper is to present fuzzy TOPSIS in an entropic fuzzy environment. Due to the ambiguous concepts often represented in decision data, exact values are insufficient to model real-life situations. In this paper, the rating of each alternative is defined in fuzzy linguistic terms, which can be expressed with triangular fuzzy numbers. The weight of each criterion is then derived from the decision matrix using the entropy weighting method. Next, a vertex method is proposed to calculate the distance between two triangular fuzzy numbers. According to the TOPSIS concept, a closeness coefficient is defined to determine the ranking order of all alternatives by simultaneously calculating the distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). Finally, an illustrative example of selecting stealth fighter aircraft is shown at the end of this article to highlight the procedure of the proposed method. Correlation analysis and validation analysis using TOPSIS, WSM, and WPM methods were performed to compare the ranking order of the alternatives.

Keywords: stealth fighter aircraft selection, fuzzy uncertainty theory (FUT), fuzzy entropic decision (FED), fuzzy linguistic variables, triangular fuzzy numbers, multiple criteria decision making analysis, MCDMA, TOPSIS, WSM, WPM

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 568

Authors: Maryam Khalili, Fateme Ghanei

Abstract:

As one of the most significant phenomena of industrialized societies, tourism plays a key role in encouraging regional developments and enhancing higher standards of living for local communities in particular. Traveling is a formative experience endowed with lessons on various aspects of life. It allows us learning how to enhance the social position as well as the social relationships. However, people forget the need to travel and gain first-hand experiences as they have to cope with the ever-increasing rate of stress created by the disorders and routines of the urban dwelling style. In this paper, various spaces of such experiences were explored through a virtual tour with two underlying aims: 1) encouraging, informing, and educating the community in terms of tourism development, and 2) introducing a temporary release from the routines. This study enjoyed a practical-qualitative research methodology, and the required data were collected through observation and using a multiple-response questionnaire. The participants (19-48 years old) included 41 citizens of both genders (63.4% male and 36.6% female) from two regions in Tehran, selected by cluster-probability sampling. The results led to development of a spatial design for a virtual tour experience in Tehran where different areas are explored to both raise people’s awareness and educate them on their cultural heritage.

Keywords: Ecotourism, education, gamification, social interaction, urban design, virtual tour.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1496

Authors: M. Senthil Arumugam, M.V.C. Rao

Abstract:

This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1886

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 1992

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 1661

Authors: Venkatesh Kumar, Kasun Hewage, Rehan Sadiq

Abstract:

Residential buildings consume significant amounts of energy and produce large amount of emissions and waste. However, there is a substantial potential for energy savings in this sector which needs to be evaluated over the life cycle of residential buildings. Life Cycle Assessment (LCA) methodology has been employed to study the primary energy uses and associated environmental impacts of different phases (i.e., product, construction, use, end of life, and beyond building life) for residential buildings. Four different alternatives of residential buildings in Vancouver (BC, Canada) with a 50-year lifespan have been evaluated, including High Rise Apartment (HRA), Low Rise Apartment (LRA), Single family Attached House (SAH), and Single family Detached House (SDH). Life cycle performance of the buildings is evaluated for embodied energy, embodied environmental impacts, operational energy, operational environmental impacts, total life-cycle energy, and total life cycle environmental impacts. Estimation of operational energy and LCA are performed using DesignBuilder software and Athena Impact estimator software respectively. The study results revealed that over the life span of the buildings, the relationship between the energy use and the environmental impacts are identical. LRA is found to be the best alternative in terms of embodied energy use and embodied environmental impacts; while, HRA showed the best life-cycle performance in terms of minimum energy use and environmental impacts. Sensitivity analysis has also been carried out to study the influence of building service lifespan over 50, 75, and 100 years on the relative significance of embodied energy and total life cycle energy. The life-cycle energy requirements for SDH are found to be a significant component among the four types of residential buildings. The overall disclose that the primary operations of these buildings accounts for 90% of the total life cycle energy which far outweighs minor differences in embodied effects between the buildings.

Keywords: Building simulation, environmental impacts, life cycle assessment, life cycle energy analysis, residential buildings.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5142

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 2043

Authors: R. Goede, E. Taylor

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 1681

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 1721

Authors: Salma Ainine, Colin Ritchie, Tracey McFee

Abstract:

Background: The societal impact of antibiotic resistance is a major public health concern. The increase in incidence of resistant bacteria can ultimately be fatal. Objective: To analyse the appropriateness of antibiotic prescribing in Dundee Dental Hospital, ultimately improving the safety and quality of patient care. Methods: Two examiners independently crosschecked approximately fifty consecutive prescriptions, and corresponding patient case notes, for three data collection cycles between August 2014 – September 2015. The Scottish Dental Clinical Effectiveness Program (SDCEP) Drug Prescribing for Dentistry guidelines was the standard utilised. The criteria: clinical justification, regime justification and review arrangements was measured, and compared to the standard. Results: Cycle one revealed 42% of antibiotic prescriptions were appropriate. Interventions included: multiple staff meetings, introduction of a checklist attached to the prescription pack, and production of patient leaflets explaining indications for antibiotics. Cycle two and three revealed 44%, and 30% compliance, respectively. Conclusion: The results of the audit have yet to meet target standards set out in prescribing guidelines. However, steps are being taken and change has occurred on a cultural level.

Keywords: Antibiotic resistance, antibiotic stewardship, dental infection and hygiene standards.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1956

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

Abstract:

With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: Machine learning, Imbalanced data, Data mining, Big data.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1114

Authors: Mansour Tarafdar, Mohammad Saniee Abade

Abstract:

This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.

Keywords: Sampling, data streams, closed frequent item set mining.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1691

Authors: Pandaba Patro, Brundaban Patro

Abstract:

The numerical simulation of fully developed gas–solid flow in a horizontal pipe is done using the eulerian-eulerian approach, also known as two fluids modeling as both phases are treated as continuum and inter-penetrating continua. The solid phase stresses are modeled using kinetic theory of granular flow (KTGF). The computed results for velocity profiles and pressure drop are compared with the experimental data. We observe that the convection and diffusion terms in the granular temperature cannot be neglected in gas solid flow simulation along a horizontal pipe. The particle-wall collision and lift also play important role in eulerian modeling. We also investigated the effect of flow parameters like gas velocity, particle properties and particle loading on pressure drop prediction in different pipe diameters. Pressure drop increases with gas velocity and particle loading. The gas velocity has the same effect ((proportional toU2 ) as single phase flow on pressure drop prediction. With respect to particle diameter, pressure drop first increases, reaches a peak and then decreases. The peak is a strong function of pipe bore.

Keywords: CFD, Eulerian modeling, gas solid flow, KTGF.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3157

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 3422

Authors: Hasmayadi Abdul Majid, Yuzman Yusoff, Noor Shelida Salleh

Abstract:

This paper presents the development of a single-ended 38.5 kS/s 10-bit programmable reference SAR ADC which is realized in MIMOS’s 0.35 µm CMOS process. The design uses a resistive DAC, a dynamic comparator with pre-amplifier and a SAR digital logic to create 10 effective bits ADC. A programmable reference circuitry allows the ADC to operate with different input range from 0.6 V to 2.1 V. The ADC consumed less than 7.5 mW power with a 3 V supply.

Keywords: Successive Approximation Register Analog-to- Digital Converter, SAR ADC, Resistive DAC, Programmable Reference.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2104

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 863

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 1721

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 835

Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

Abstract:

New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: Information visualization, visual analytics, text mining, visual text analytics tools, big data visualization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 989

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 733

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 2338

Authors: Wimalin S. Laosiritaworn, Pongsak Holimchayachotikul

Abstract:

this article proposed a methodology for computer numerical control (CNC) machine scoring. The case study company is a manufacturer of hard disk drive parts in Thailand. In this company, sample of parts manufactured from CNC machine are usually taken randomly for quality inspection. These inspection data were used to make a decision to shut down the machine if it has tendency to produce parts that are out of specification. Large amount of data are produced in this process and data mining could be very useful technique in analyzing them. In this research, data mining techniques were used to construct a machine scoring model called 'machine priority assessment model (MPAM)'. This model helps to ensure that the machine with higher risk of producing defective parts be inspected before those with lower risk. If the defective prone machine is identified sooner, defective part and rework could be reduced hence improving the overall productivity. The results showed that the proposed method can be successfully implemented and approximately 351,000 baht of opportunity cost could have saved in the case study company.

Keywords: Computer Numerical Control, Data Mining, HardDisk Drive.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1381