Search results for: electric mining shovel
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2388

Search results for: electric mining shovel

2148 Efficient Frequent Itemset Mining Methods over Real-Time Spatial Big Data

Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

Abstract:

In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

Procedia PDF Downloads 133
2147 Summarizing Data Sets for Data Mining by Using Statistical Methods in Coastal Engineering

Authors: Yunus Doğan, Ahmet Durap

Abstract:

Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

Procedia PDF Downloads 339
2146 Human Immunodeficiency Virus (HIV) Test Predictive Modeling and Identify Determinants of HIV Testing for People with Age above Fourteen Years in Ethiopia Using Data Mining Techniques: EDHS 2011

Authors: S. Abera, T. Gidey, W. Terefe

Abstract:

Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

Procedia PDF Downloads 467
2145 In vivo Spectroscopic Study on the Effects of Ionising and Non-Ionising Radiation on Some Biophysical Properties of Rat Blood

Authors: S. H. Allehyani, H. S. Ibrahim, F. M. Ali, E. Sayd, T. Abou Aiad

Abstract:

The present study aimed to analyse the radiation risk associated with the exposure of haemoglobin (Hb) of rat red blood cells (rbcs) exposed to a 50-Hz 6-kV/m electric field, a fast neutron dose of 1 mSv, and mixed radiation from fast neutrons and an electric field distributed over a period of three weeks at a rate of 5 days/week and 8 hours/day. The dielectric measurements and the absorption spectra for the haemoglobin molecule in the frequency range of 1 kHz to 5 MHz were measured for all of the samples. The dielectric relaxation results demonstrated an increase in the dielectric increment (∆ε) for the rbcs from all of the irradiated animals, which indicates an increase in the electric dipole. Moreover, the results revealed a decrease in the relaxation time (τ) and the molecular radius (r) of the irradiated molecules, which indicates that the increase in ∆ε is mainly due to a pronounced increase in the centre of mass of the charge on the electric dipole of the Hb molecule. The results from the absorption spectra indicate that the ratio of met-haemoglobin to oxy-haemoglobin is altered by irradiation. Moreover, the results from the delayed effect studies show that the structure and function of the newly generated Hb molecules are altered and dissimilar to that of healthy Hb.

Keywords: rat red blood cell haemoglobin, dielectric properties, absorption spectra, biochemical analysis

Procedia PDF Downloads 343
2144 Analysis of Users’ Behavior on Book Loan Log Based on Association Rule Mining

Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

Abstract:

This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

Procedia PDF Downloads 380
2143 Analysis Mechanized Boring (TBM) of Tehran Subway Line 7

Authors: Shahin Shabani, Pouya Pourmadadi

Abstract:

Tunnel boring machines (TBMs) have been used for the construction of various tunnels for mining projects for the purpose of access, conveyance of ore and waste, drainage, exploration, water supply and water diversion. Several mining projects have seen the successful and economic beneficial use of TBMs, and there is an increasing awareness of the benefits of TBMs for mining projects. Key technical considerations for the use of TBMs for the construction of tunnels for mining projects include geological issues (rock type, rock alteration, rock strength, rock abrasivity, durability, ground water inflows), depth of cover and the potential for overstressing/rockbursts, site access and terrain, portal locations, TBM constraints, minimum tunnel size, tunnel support requirements, contractor and labor experience, and project schedule demands. This study focuses on tunnelling mining, with the goal to develop methods and tools to be used to gain understanding of these processes, and to analyze metro of Tehran. The Metro Line 7 of Tehran is one of the Longest (26 Km) and deepest (27m) of projects that’s under implementation. Because of major differences like passing under all geotechnical layers of the town and encountering part of it with underground water table and also using mechanized excavation system, is one of special metro projects.

Keywords: TBM, tunnel boring machines economic, metro, line 7

Procedia PDF Downloads 357
2142 A Hybrid Data Mining Algorithm Based System for Intelligent Defence Mission Readiness and Maintenance Scheduling

Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

Abstract:

It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

Procedia PDF Downloads 269
2141 Possible Exposure of Persons with Cardiac Pacemakers to Extremely Low Frequency (ELF) Electric and Magnetic Fields

Authors: Leena Korpinen, Rauno Pääkkönen, Fabriziomaria Gobba, Vesa Virtanen

Abstract:

The number of persons with implanted cardiac pacemakers (PM) has increased in Western countries. The aim of this paper is to investigate the possible situations where persons with a PM may be exposed to extremely low frequency (ELF) electric (EF) and magnetic fields (MF) that may disturb their PM. Based on our earlier studies, it is possible to find such high public exposure to EFs only in some places near 400 kV power lines, where an EF may disturb a PM in unipolar mode. Such EFs cannot be found near 110 kV power lines. Disturbing MFs can be found near welding machines. However, we do not have measurement data from welding. Based on literature and earlier studies at Tampere University of Technology, it is difficult to find public EF or MF exposure that is high enough to interfere with PMs.

Keywords: cardiac pacemaker, electric field, magnetic field, electrical engineering

Procedia PDF Downloads 405
2140 Decision Support System for Optimal Placement of Wind Turbines in Electric Distribution Grid

Authors: Ahmed Ouammi

Abstract:

This paper presents an integrated decision framework to support decision makers in the selection and optimal allocation of wind power plants in the electric grid. The developed approach intends to maximize the benefice related to the project investment during the planning period. The proposed decision model considers the main cost components, meteorological data, environmental impacts, operation and regulation constraints, and territorial information. The decision framework is expressed as a stochastic constrained optimization problem with the aim to identify the suitable locations and related optimal wind turbine technology considering the operational constraints and maximizing the benefice. The developed decision support system is applied to a case study to demonstrate and validate its performance.

Keywords: decision support systems, electric power grid, optimization, wind energy

Procedia PDF Downloads 123
2139 Raman and Dielectric Relaxation Investigations of Polyester-CoFe₂O₄ Nanocomposites

Authors: Alhulw H. Alshammari, Ahmed Iraqi, S. A. Saad, T. A. Taha

Abstract:

In this work, we present for the first time the study of Raman spectra and dielectric relaxation of polyester polymer-CoFe₂O₄ (5.0, 10.0, 15.0, and 20.0 wt%) nanocomposites. Raman spectroscopy was applied as a sensitive structural identification technique to characterize the polyester-CoFe₂O₄ nanocomposites. The images of AFM confirmed the uniform distribution of CoFe₂O₄ inside the polymer matrix. Dielectric relaxation was employed as an important analytical technique to obtain information about the ability of the polymer nanocomposites to store and filter electrical signals. The dielectric relaxation analyses were carried out on the polyester-CoFe₂O₄ nanocomposites at different temperatures. An increase in dielectric constant ε₁ was observed for all samples with increasing temperatures due to the alignment of the electric dipoles with the applied electric field. In contrast, ε₁ decreased with increasing frequency. This is attributed to the difficulty for the electric dipoles to follow the electric field. The α relaxation peak that appeared at a high frequency shifted to higher frequencies when increasing the temperature. The activation energies for Maxwell-Wagner Sillar (MWS) changed from 0.84 to 1.01 eV, while the activation energies for α relaxations were 0.54 – 0.94 eV. The conduction mechanism for the polyester- CoFe₂O₄ nanocomposites followed the correlated barrier hopping (CBH) model.

Keywords: AC conductivity, activation energy, dielectric permittivity, polyester nanocomposites

Procedia PDF Downloads 84
2138 Emotion Mining and Attribute Selection for Actionable Recommendations to Improve Customer Satisfaction

Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

Abstract:

In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

Procedia PDF Downloads 172
2137 An Optimized Association Rule Mining Algorithm

Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

Abstract:

Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

Procedia PDF Downloads 391
2136 Assessment of Indigenous People Living Condition in Coal Mining Region: An Evidence from Dhanbad, India

Authors: Arun Kumar Yadav

Abstract:

Coal contributes a significant role in India’s developmental mission. But, ironically, on the other side it causes large scale population displacement and significant changes in indigenous people’s livelihood mechanism. Dhanbad which is regarded as one of the oldest and large mining area, as well as a “Coal Capital of India”. Here, mining exploration work started nearly a century ago. But with the passage of time, mining brings a lot of changes in the life of local people. In this context, study tries to do comparative situational analysis of the changes in the living condition of dwellers living in mines affected and non-mines affected villages based on livelihood approach. Since, this place has long history of mining so it is very difficult to conduct before and after comparison between mines and non-mines affected areas. Consequently, the present study is based on relative comparison approach to elucidate the actual scenario. By using primary survey data which was collected by the author during the month of September 2014 to March 2015 at Dhanbad, Jharkhand. The data were collected from eight villages, these were categorised broadly into mines and non-mines affected villages. Further at micro level, mines affected villages has been categorised into open cast and underground mines. This categorization will help us to capture the deeper understanding about the issues of mine affected villages group. Total of 400 household were surveyed. Result depicts that in every sphere mining affected villages are more vulnerable. Regarding financial capital, although mine affected villages are engaged in mining work and get higher mean income. But in contrast, non-mine affected villages are more occupationally diversified. They have an opportunity to earn money from diversified extents like agricultural land, working in mining area, selling coal informally as well as receiving remittances. Non-mines affected villages are in better physical capital which comprises of basic infrastructure to support livelihood. They have an access to secured shelter, adequate water supply & sanitation, and affordable information and transport. Mining affected villages are more prone to health risks. Regarding social capital, it shows that in comparison to last five years, law and order has been improved in mine affected villages.

Keywords: displacement, indigenous, livelihood, mining

Procedia PDF Downloads 285
2135 The Impact of Gold Mining on Disability: Experiences from the Obuasi Municipal Area

Authors: Mavis Yaa Konadu Agyemang

Abstract:

Despite provisions to uphold and safeguard the rights of persons with disability in Ghana, there is evidence that they still encounter several challenges which limit their full and effective involvement in mainstream society, including the gold mining sector. The study sought to explore how persons with physical disability (PWPDs) experience gold mining in the Obuasi Municipal Area. A qualitative research design was used to discover and understand the experiences of PWPDs regarding mining. The purposive sampling technique was used to select five key informants for the study with the age range of (24-52 years) while snowball sampling aided the selection of 16 persons with various forms of physical disability with the age range of (24-60 years). In-depth interviews were used to gather data. The interviews lasted from forty-five minutes to an hour. In relation to the setting, the interviews of thirteen (13) of the participants with disability were done in their houses, two (2) were done on the phone, and one (1) was done in the office. Whereas the interviews of the five (5) key informants were all done in their offices. Data were analyzed using Creswell’s (2009) concept of thematic analysis. The findings suggest that even though land degradation affected everyone in the area, persons with mobility and visual impairment experienced many difficulties trekking the undulating land for long distances in search of arable land. Also, although mining activities are mostly labour-intensive, PWPDs were not employed even in areas where they could work. Further, the cost of items, in general, was high, affecting PWPDs more due to their economic immobility and paying for other sources of water due to land degradation and water pollution. The study also discovered that the peculiar conditions of PWPDs were not factored into compensation payments, and neither were females with physical disability engaged in compensation negotiations. Also, although some of the infrastructure provided by the gold mining companies in the area was physically accessible to some extent, it was not accessible in terms of information delivery. There is a need to educate the public on the effects of mining on PWPDs, their needs as well as disability issues in general. The Minerals and Mining Act (703) should be amended to include provisions that would consider the peculiar needs of PWPDs in compensation payment.

Keywords: mining, resettlement, compensation, environmental, social, disability

Procedia PDF Downloads 28
2134 Enhancement of Mass Transport and Separations of Species in a Electroosmotic Flow by Distinct Oscillatory Signals

Authors: Carlos Teodoro, Oscar Bautista

Abstract:

In this work, we analyze theoretically the mass transport in a time-periodic electroosmotic flow through a parallel flat plate microchannel under different periodic functions of the applied external electric field. The microchannel connects two reservoirs having different constant concentrations of an electro-neutral solute, and the zeta potential of the microchannel walls are assumed to be uniform. The governing equations that allow determining the mass transport in the microchannel are given by the Poisson-Boltzmann equation, the modified Navier-Stokes equations, where the Debye-Hückel approximation is considered (the zeta potential is less than 25 mV), and the species conservation. These equations are nondimensionalized and four dimensionless parameters appear which control the mass transport phenomenon. In this sense, these parameters are an angular Reynolds, the Schmidt and the Péclet numbers, and an electrokinetic parameter representing the ratio of the half-height of the microchannel to the Debye length. To solve the mathematical model, first, the electric potential is determined from the Poisson-Boltzmann equation, which allows determining the electric force for various periodic functions of the external electric field expressed as Fourier series. In particular, three different excitation wave forms of the external electric field are assumed, a) sawteeth, b) step, and c) a periodic irregular functions. The periodic electric forces are substituted in the modified Navier-Stokes equations, and the hydrodynamic field is derived for each case of the electric force. From the obtained velocity fields, the species conservation equation is solved and the concentration fields are found. Numerical calculations were done by considering several binary systems where two dilute species are transported in the presence of a carrier. It is observed that there are different angular frequencies of the imposed external electric signal where the total mass transport of each species is the same, independently of the molecular diffusion coefficient. These frequencies are called crossover frequencies and are obtained graphically at the intersection when the total mass transport is plotted against the imposed frequency. The crossover frequencies are different depending on the Schmidt number, the electrokinetic parameter, the angular Reynolds number, and on the type of signal of the external electric field. It is demonstrated that the mass transport through the microchannel is strongly dependent on the modulation frequency of the applied particular alternating electric field. Possible extensions of the analysis to more complicated pulsation profiles are also outlined.

Keywords: electroosmotic flow, mass transport, oscillatory flow, species separation

Procedia PDF Downloads 196
2133 Using Mining Methods of WEKA to Predict Quran Verb Tense and Aspect in Translations from Arabic to English: Experimental Results and Analysis

Authors: Jawharah Alasmari

Abstract:

In verb inflection, tense marks past/present/future action, and aspect marks progressive/continues perfect/completed actions. This usage and meaning of tense and aspect differ in Arabic and English. In this research, we applied data mining methods to test the predictive function of candidate features by using our dataset of Arabic verbs in-context, and their 7 translations. Weka machine learning classifiers is used in this experiment in order to examine the key features that can be used to provide guidance to enable a translator’s appropriate English translation of the Arabic verb tense and aspect.

Keywords: Arabic verb, English translations, mining methods, Weka software

Procedia PDF Downloads 249
2132 Mining Educational Data to Support Students’ Major Selection

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well.

Keywords: data mining technique, the decision support system, knowledge and decision rules, education

Procedia PDF Downloads 400
2131 Spatio-Temporal Data Mining with Association Rules for Lake Van

Authors: Tolga Aydin, M. Fatih Alaeddinoğlu

Abstract:

People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatio-temporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newly-formed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: apriori algorithm, association rules, data mining, spatio-temporal data

Procedia PDF Downloads 345
2130 Spatial Data Mining by Decision Trees

Authors: Sihem Oujdi, Hafida Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

Procedia PDF Downloads 594
2129 Evaluating 8D Reports Using Text-Mining

Authors: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

Abstract:

Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining

Procedia PDF Downloads 281
2128 Effective Scheduling of Hybrid Reconfigurable Microgrids Considering High Penetration of Renewable Sources

Authors: Abdollah Kavousi Fard

Abstract:

This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

Procedia PDF Downloads 247
2127 Model Evaluation of Thermal Effects Created by Cell Membrane Electroporation

Authors: Jiahui Song

Abstract:

The use of very high electric fields (~ 100kV/cm or higher) with pulse durations in the nanosecond range has been a recent development. The electric pulses have been used as tools to generate electroporation which has many biomedical applications. Most of the studies of electroporation have ignored possible thermal effects because of the small duration of the applied voltage pulses. However, it has been predicted membrane temperature gradients ranging from 0.2×109 to 109 K/m. This research focuses on thermal gradients that drives for electroporative enhancements, even though the actual temperature values might not have changed appreciably from their equilibrium levels. The dynamics of pore formation with the application of an externally applied electric field is studied on the basis of molecular dynamics (MD) simulations using the GROMACS package. Different temperatures are assigned to various regions to simulate the appropriate temperature gradients. The GROMACS provides the force fields for the lipid membranes, which is taken to comprise of dipalmitoyl-phosphatidyl-choline (DPPC) molecules. The water model mimicks the aqueous environment surrounding the membrane. Velocities of water and membrane molecules are generated randomly at each simulation run according to a Maxwellian distribution. For statistical significance, a total of eight MD simulations are carried out with different starting molecular velocities for each simulation. MD simulation shows no pore is formed in a 10-ns snapshot for a DPPC membrane set at a uniform temperature of 295 K after a 0.4 V/nm electric field is applied. A nano-sized pore is clearly seen in a 10-ns snapshot on the same geometry but with the top and bottom membrane surfaces kept at temperatures of 300 and 295 K, respectively. For the same applied electric field, the formation of nanopores is clearly demonstrated, but only in the presence of a temperature gradient. MD simulation results show enhanced electroporative effects arising from thermal gradients. The study suggests the temperature gradient is a secondary driver, with the electric field being the primary cause for electroporation.

Keywords: nanosecond, electroporation, thermal effects, molecular dynamics

Procedia PDF Downloads 51
2126 Analysis of Causality between Defect Causes Using Association Rule Mining

Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

Abstract:

Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

Procedia PDF Downloads 336
2125 Biofouling Control during the Wastewater Treatment in Self-Support Carbon Nanotubes Membrane: Role of Low Voltage Electric Potential

Authors: Chidambaram Thamaraiselvan, Carlos Dosoretz

Abstract:

This work will explore the influence of low voltage electric field, both alternating (AC) and direct (DC) currents, on biofouling control to highly electrically conductive self-supporting carbon nanotubes (CNT) membranes at conditions which encourage bacterial growth. A mutant strain of Pseudomonas putida S12 was used a model bacterium. The antibiofouling studies were performed with flow-through mode connecting an electric circuit in resistive mode. Major emphasis was placed on AC due to its ability of repulsing and inactivating bacteria. The observations indicate that an AC potential >1500 mV, 1 kHz frequency, 100 Ω external resistance on ground side and pulse wave above the offset (+0.45) almost completely prevented attachment of bacteria (>98.5%) and bacterial inactivation (95.3±2.5%). Findings suggest that at the conditions applied, direct electron transfer might be dominant in a decrease of cell viability. AC resulted more effective than DC, both in terms of biofouling reduction compared to cathodic DC and in terms of cell inactivation compared to anodic DC. This electrically polarized CNT membranes offer a viable antibiofouling strategy to hinder biofouling and simplify membrane care during filtration.

Keywords: bacterial attachment, biofouling control, low electric potential, water treatment

Procedia PDF Downloads 246
2124 Design and Development of Data Mining Application for Medical Centers in Remote Areas

Authors: Grace Omowunmi Soyebi

Abstract:

Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

Procedia PDF Downloads 184
2123 Electric Vehicle Market Penetration Impact on Greenhouse Gas Emissions for Policy-Making: A Case Study of United Arab Emirates

Authors: Ahmed Kiani

Abstract:

The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations

Procedia PDF Downloads 289
2122 Improved FP-Growth Algorithm with Multiple Minimum Supports Using Maximum Constraints

Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

Abstract:

Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.

Keywords: association rules, FP-growth, multiple minimum supports, Weka tool

Procedia PDF Downloads 452
2121 Electromagnetic Simulation of Underground Cable Perforation by Nail

Authors: Ahmed Nour El Islam Ayad, Tahar Rouibah, Wafa Krika, Houari Boudjella, Larab Moulay, Farid Benhamida, Selma Benmoussa

Abstract:

The purpose of this study is to evaluate the electromagnetic field of an underground cable of very high voltage perforated by nail. The aim of this work shows a numerical simulation of the electromagnetic field of 400 kV line after perforation through a ferrous nail in four positions for the pinch pin at different distances. From results for a longitudinal section, we observe and evaluate the distribution and the variation of the electromagnetic field in the cable and the earth. When the nail approaches the underground power cable, the distribution of the magnetic field changes and takes several forms, the magnetic field increase and become very important when the nail breaks the metal screen and will produce a significant leak of the electric field, characterized by a large electric arc and or electric discharge to earth and then a fault in the electrical network. These electromagnetic analysis results help to detect defects in underground cables.

Keywords: underground, electromagnetic, nail, defect

Procedia PDF Downloads 193
2120 Feature-Based Summarizing and Ranking from Customer Reviews

Authors: Dim En Nyaung, Thin Lai Lai Thein

Abstract:

Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

Procedia PDF Downloads 309
2119 Improvement of Ride Comfort of Turning Electric Vehicle Using Optimal Speed Control

Authors: Yingyi Zhou, Tohru Kawabe

Abstract:

With the spread of EVs (electric Vehicles), the ride comfort has been gaining a lot of attention. The influence of the lateral acceleration is important for the improvement of ride comfort of EVs as well as the longitudinal acceleration, especially upon turning of the vehicle. Therefore, this paper proposes a practical optimal speed control method to greatly improve the ride comfort in the vehicle turning situation. For consturcting this method, effective criteria that can appropriately evaluate deterioration of ride comfort is derived. The method can reduce the influence of both the longitudinal and the lateral speed changes for providing a confortable ride. From several simulation results, we can see the fact that the method can prevent aggravation of the ride comfort by suppressing the influence of longitudinal speed change in the turning situation. Hence, the effectiveness of the method is recognized.

Keywords: electric vehicle, speed control, ride comfort, optimal control theory, driving support system

Procedia PDF Downloads 186