Search results for: Behavior based navigation
7499 Capturing an Unknown Moving Target in Unknown Territory using Vision and Coordination
Authors: Kiran Ijaz, Umar Manzoor, Arshad Ali Shahid
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In this paper we present an extension to Vision Based LRTA* (VLRTA*) known as Vision Based Moving Target Search (VMTS) for capturing unknown moving target in unknown territory with randomly generated obstacles. Target position is unknown to the agents and they cannot predict its position using any probability method. Agents have omni directional vision but can see in one direction at some point in time. Agent-s vision will be blocked by the obstacles in the search space so agent can not see through the obstacles. Proposed algorithm is evaluated on large number of scenarios. Scenarios include grids of sizes from 10x10 to 100x100. Grids had obstacles randomly placed, occupying 0% to 50%, in increments of 10%, of the search space. Experiments used 2 to 9 agents for each randomly generated maze with same obstacle ratio. Observed results suggests that VMTS is effective in locate target time, solution quality and virtual target. In addition, VMTS becomes more efficient if the number of agents is increased with proportion to obstacle ratio.Keywords: Vision, MTS, Unknown Target, Coordination, VMTS, Multi-Agent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14647498 Unsupervised Outlier Detection in Streaming Data Using Weighted Clustering
Authors: Yogita, Durga Toshniwal
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Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Keywords: Concept Evolution, Irrelevant Attributes, Streaming Data, Unsupervised Outlier Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26377497 The Role of Contextual Ontologies in Enterprise Modeling
Authors: Ahmed Arara
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Information sharing and exchange, rather than information processing, is what characterizes information technology in the 21st century. Ontologies, as shared common understanding, gain increasing attention, as they appear as the most promising solution to enable information sharing both at a semantic level and in a machine-processable way. Domain Ontology-based modeling has been exploited to provide shareability and information exchange among diversified, heterogeneous applications of enterprises. Contextual ontologies are “an explicit specification of contextual conceptualization". That is: ontology is characterized by concepts that have multiple representations and they may exist in several contexts. Hence, contextual ontologies are a set of concepts and relationships, which are seen from different perspectives. Contextualization is to allow for ontologies to be partitioned according to their contexts. The need for contextual ontologies in enterprise modeling has become crucial due to the nature of today's competitive market. Information resources in enterprise is distributed and diversified and is in need to be shared and communicated locally through the intranet and globally though the internet. This paper discusses the roles that ontologies play in an enterprise modeling, and how ontologies assist in building a conceptual model in order to provide communicative and interoperable information systems. The issue of enterprise modeling based on contextual domain ontology is also investigated, and a framework is proposed for an enterprise model that consists of various applications.Keywords: Contextual ontologies, Enterprise model, domainontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18427496 The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications
Authors: Mohamed R. Mhereeg
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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.
Keywords: MACS, Implementation, Multi-Agent, SOA, Autonomous, WCF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17097495 A Study on Removal Characteristics of (Mn2+) from Aqueous Solution by CNT
Authors: Nassereldeen A. Kabashi, Suleyman A. Muyibi. Mohammed E. Saeed., Farhana I. Yahya
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It is important to remove manganese from water because of its effects on human and the environment. Human activities are one of the biggest contributors for excessive manganese concentration in the environment. The proposed method to remove manganese in aqueous solution by using adsorption as in carbon nanotubes (CNT) at different parameters: The parameters are CNT dosage, pH, agitation speed and contact time. Different pHs are pH 6.0, pH 6.5, pH 7.0, pH 7.5 and pH 8.0, CNT dosages are 5mg, 6.25mg, 7.5mg, 8.75mg or 10mg, contact time are 10 min, 32.5 min, 55 min, 87.5 min and 120 min while the agitation speeds are 100rpm, 150rpm, 200rpm, 250rpm and 300rpm. The parameters chosen for experiments are based on experimental design done by using Central Composite Design, Design Expert 6.0 with 4 parameters, 5 levels and 2 replications. Based on the results, condition set at pH 7.0, agitation speed of 300 rpm, 7.5mg and contact time 55 minutes gives the highest removal with 75.5%. From ANOVA analysis in Design Expert 6.0, the residual concentration will be very much affected by pH and CNT dosage. Initial manganese concentration is 1.2mg/L while the lowest residual concentration achieved is 0.294mg/L, which almost satisfy DOE Malaysia Standard B requirement. Therefore, further experiments must be done to remove manganese from model water to the required standard (0.2 mg/L) with the initial concentration set to 0.294 mg/L.Keywords: Adsorption, CNT, DOE, Manganese, Parameters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14717494 Effectiveness of ICT Training Workshop for Tutors of Allama Iqbal Open University, Pakistan
Authors: Muhammad Javid Qadir, Abdul Hameed
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The purpose of the study was to investigate the effectiveness of ICT training workshop of tutors of Allama Iqbal Open University Pakistan. The study was delimited to tutors of Multan region. The total sample comprised of 100 tutors. All the tutors who participated in ICT training workshop in Multan region were taken as sample in the study. A questionnaire having two parts, based on five point rating scale was developed by the researcher. Part one was about the competency level of computer skills while Part two was based on items related to training delivery, structure and content. Part One of questionnaire had five levels of competency about computer skills. The questionnaire was personally administered and collected back by the researcher himself on the last day of workshop. The collected data were analyzed by using descriptive statistics. Through this study it was found that majority of the tutors strongly agreed that training enhanced their computer skills. Majority of the respondents consider themselves to be generally competent in the use of computer. They also agreed that there was appropriate infrastructure and technical support in lab during training workshop. Moreover, it was found that the training imparted the knowledge of pedagogy of using computers for distance education.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21907493 Artificial Intelligence Support for Interferon Treatment Decision in Chronic Hepatitis B
Authors: Alexandru George Floares
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Chronic hepatitis B can evolve to cirrhosis and liver cancer. Interferon is the only effective treatment, for carefully selected patients, but it is very expensive. Some of the selection criteria are based on liver biopsy, an invasive, costly and painful medical procedure. Therefore, developing efficient non-invasive selection systems, could be in the patients benefit and also save money. We investigated the possibility to create intelligent systems to assist the Interferon therapeutical decision, mainly by predicting with acceptable accuracy the results of the biopsy. We used a knowledge discovery in integrated medical data - imaging, clinical, and laboratory data. The resulted intelligent systems, tested on 500 patients with chronic hepatitis B, based on C5.0 decision trees and boosting, predict with 100% accuracy the results of the liver biopsy. Also, by integrating the other patients selection criteria, they offer a non-invasive support for the correct Interferon therapeutic decision. To our best knowledge, these decision systems outperformed all similar systems published in the literature, and offer a realistic opportunity to replace liver biopsy in this medical context.Keywords: Interferon, chronic hepatitis B, intelligent virtualbiopsy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14587492 Role-Governed Categorization and Category Learning as a Result from Structural Alignment: The RoleMap Model
Authors: Yolina A. Petrova, Georgi I. Petkov
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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.
Keywords: Categorization, category learning, role-governed category, analogy-making, cognitive modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6627491 Detection of Actuator Faults for an Attitude Control System using Neural Network
Authors: S. Montenegro, W. Hu
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The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19927490 Side Effects of Dental Tooth Whitening: Data from Literature
Authors: Saimir Heta, Ilma Robo, Emela Dalloshi, Nevila Alliu, Vera Ostreni
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The dental whitening process, beyond the fact that it is a mini-invasive dental treatment, has effects on the dental structure or on the pulp of the tooth where it is applied. The electronic search was performed using keywords to find articles published within the last 10 years about side effects, assessed as such, of the minimally invasive dental bleaching treatment. The aim of the study was to evaluate the side effects of bleaching based on the percentage and type of solution used, where the latter was evaluated on the basic solution used for bleaching. The side effects of bleaching are evaluated in selected articles depending on the method of bleaching application, which means it is carried out with recommended solutions, or with mixtures of alternative solutions or substances based on Internet information. The dental bleaching process has side effects which have not yet been definitively evaluated, experimentally in large samples of individuals or animals (mice or cattle) to arrive at accurate numerical conclusions. The trend of publications about this topic is increasing in recent years, as long as the trend for aesthetic facial treatments, including dental ones, is increasing.
Keywords: Teeth whitening, side effects, permanent teeth, formed dental apex.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 287489 Optimal Supplementary Damping Controller Design for TCSC Employing RCGA
Authors: S. Panda, S. C. Swain, A. K. Baliarsingh, C. Ardil
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Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.
Keywords: Power System Oscillations, Real-Coded Genetic Algorithm (RCGA), Thyristor Controlled Series Compensator (TCSC), Damping Controller, Power System Stabilizer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22247488 Several Aspects of the Conceptual Framework of Financial Reporting
Authors: Nadezhda Kvatashidze
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The conceptual framework of International Financial Reporting Standards determines the basic principles of accounting. The said principles have multiple applications, with professional judgments being one of those. Recognition and assessment of the information contained in financial reporting, especially so the somewhat uncertain events and transactions and/or the ones regarding which there is no standard or interpretation are based on professional judgments. Professional judgments aim at the formulation of expert assumptions regarding the specifics of the circumstances and events to be entered into the report based on the conceptual framework terms and principles. Experts have to make a choice in favor of one of the aforesaid and simulate the situations applying multi-variant accounting estimates and judgment. In making the choice, one should consider all the factors, which may help represent the information in the best way possible. Professional judgment determines the relevance and faithful representation of the presented information, which makes it more useful for the existing and potential investors. In order to assess the prospected net cash flows, the information must be predictable and reliable. The publication contains critical analysis of the aforementioned problems. The fact that the International Financial Reporting Standards are developed continuously makes the issue all the more important and that is another point discussed in the study.
Keywords: Conceptual Framework for financial reporting, Qualitative characteristics of financial information, Professional judgement, Cost constraints, Financial reporting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16277487 Simultaneous Tuning of Static Var Compensator and Power System Stabilizer Employing Real- Coded Genetic Algorithm
Authors: S. Panda, N. P. Patidar, R. Singh
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Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.
Keywords: Real-Coded Genetic Algorithm (RCGA), Static Var Compensator (SVC), Power System Stabilizer (PSS), Low Frequency Oscillations, Power System Stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22557486 1Malaysia: National Education Challenge and Nation Building
Authors: Mohd Ridhuan Tee Abdullah, Ong Hai Liaw, Wan Norhasniah Wan Husin
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The main issue discussed is on the role of education system in the process of nation building as a means in uniting different community ethnics which later on, hoped to shape the future ethnic relation of this country. It is generally known that political socialization experienced by each ethnic community has given birth to a vernacular education system, separated along the ethnic line. Every community shapes their own education system based on their respective mother tongue language, however all are based on the same curriculum. As a result the role of education as a uniting force is not significantly effective. Historically, it has been shown that government efforts to unite the country education system under the wing of national education system (national school) is not that successful since every community (Chinese) will defend the existence of their community education system because they want to spur their mother tongue language. The clash between national education system and vernacular education system is the root cause of stalemate in the ethnic relation in Malaysia and it always becomes a flash point when the issue is raised. The question now is what is the best solution to enhance the national education system in multiethnic Malaysia?
Keywords: Political socialization, education, national unity, national school, vernacular school and 1Malaysia
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38437485 Determine of Constant Coefficients to RelateTotal Dissolved Solids to Electrical Conductivity
Authors: M. Siosemarde, F. Kave, E. Pazira, H. Sedghi, S. J. Ghaderi
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Salinity is a measure of the amount of salts in the water. Total Dissolved Solids (TDS) as salinity parameter are often determined using laborious and time consuming laboratory tests, but it may be more appropriate and economical to develop a method which uses a more simple soil salinity index. Because dissolved ions increase salinity as well as conductivity, the two measures are related. The aim of this research was determine of constant coefficients for predicting of Total Dissolved Solids (TDS) based on Electrical Conductivity (EC) with Statistics of Correlation coefficient, Root mean square error, Maximum error, Mean Bias error, Mean absolute error, Relative error and Coefficient of residual mass. For this purpose, two experimental areas (S1, S2) of Khuzestan province-IRAN were selected and four treatments with three replications by series of double rings were applied. The treatments were included 25cm, 50cm, 75cm and 100cm water application. The results showed the values 16.3 & 12.4 were the best constant coefficients for predicting of Total Dissolved Solids (TDS) based on EC in Pilot S1 and S2 with correlation coefficient 0.977 & 0.997 and 191.1 & 106.1 Root mean square errors (RMSE) respectively.Keywords: constant coefficients, electrical conductivity, Khuzestan plain and total dissolved solids.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39057484 Numerical Modelling of Shear Zone and Its Implications on Slope Instability at Letšeng Diamond Open Pit Mine, Lesotho
Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa
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Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.
Keywords: Numerical modeling, open pit mine, shear zone, slope stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17837483 Mordechai Vanunu: “The Atomic Spy” as a Nuclear Threat to Discourse in Israeli Society
Authors: Ada Yurman
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Using the case of Israeli Atomic Spy Mordechai Vanunu as an example, this study sought to examine social response to political deviance whereby social response can be mobilized in order to achieve social control. Mordechai Vanunu, a junior technician in the Dimona Atomic Research Center, played a normative role in the militaristic discourse while working in the “holy shrine” of the Israeli defense system for many years. At a certain stage, however, Vanunu decided to detach himself from this collective and launched an assault on this top-secret circle. Israeli society in general and the security establishment in particular found this attack intolerable and unforgivable. They presented Vanunu as a ticking time bomb, delegitimized him and portrayed him as “other”. In addition, Israeli enforcement authorities imposed myriad prohibitions and sanctions on Vanunu even after his release from prison – “as will be done to he who desecrates holiness.” Social response to Vanunu at the time of his capture and trial was studied by conducting a content analysis of six contemporary daily newspapers. The analysis focused on use of language and forms of expression. In contrast with traditional content analysis methodology, this study did not just look at frequency of expressions of ideas and terms in the text and covert content; rather, the text was analyzed as a structural whole, and included examination of style, tone and unusual use of imagery, and more, in order to uncover hidden messages within the text. The social response to this case was extraordinarily intense, not only because in this case of political deviance, involving espionage and treason, Vanunu’s actions comprised a real potential threat to the country, but also because of the threat his behavior posed to the symbolic universe of society. Therefore, the response to this instance of political deviance can be seen as being part of a mechanism of social control aiming to protect world view of society as a whole, as well as to punish the criminal.
Keywords: Militarism, political deviance, social construction, social control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6897482 A Nanosensor System Based On Disuccinimydyl–CYP2E1 for Amperometric Detection of the Anti-Tuberculosis Drug, Pyrazinamide
Authors: R. F. Ajayi, U. Sidwaba, U. Feleni, S. F. Douman, E. Nxusani, L. Wilson, C. Rassie, O. Tovide, P. G. L. Baker, S. L. Vilakazi, R. Tshikhudo, E. I. Iwuoha
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Pyrazinamide (PZA) is among the first-line pro-drugs in the tuberculosis (TB) combination chemotherapy used to treat Mycobacterium tuberculosis. Numerous reports have suggested that hepatotoxicity due to pyrazinamide in patients is due to inappropriate dosing. It is, therefore necessary to develop sensitive and reliable techniques for determining the PZA metabolic profile of diagnosed patients promptly and at point-of-care. This study reports the determination of PZA based on nanobiosensor systems developed from disuccinimidyl octanedioate modified Cytochrome P450-2E1 (CYP2E1) electrodeposited on gold substrates derivatised with (poly(8-anilino-1-napthalene sulphonic acid) PANSA/PVP-AgNPs nanocomposites. The rapid and sensitive amperometric PZA detection gave a dynamic linear range of 2µM to 16µM revealing a limit of detection of 0.044µM and a sensitivity of 1.38µA/µM. The Michaelis-Menten parameters; KM, KM app and IMAX were calculated to be 6.0µM, 1.41µM and 1.51x10-6 A, respectively, indicating a nanobiosensor suitable for use in serum.
Keywords: Cytochrome P450-2E1, Disuccinimidyl octanedioate, Pyrazinamide, Tuberculosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22247481 Evaluation of the Weight-Based and Fat-Based Indices in Relation to Basal Metabolic Rate-to-Weight Ratio
Authors: Orkide Donma, Mustafa M. Donma
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Basal metabolic rate is questioned as a risk factor for weight gain. The relations between basal metabolic rate and body composition have not been cleared yet. The impact of fat mass on basal metabolic rate is also uncertain. Within this context, indices based upon total body mass as well as total body fat mass are available. In this study, the aim is to investigate the potential clinical utility of these indices in the adult population. 287 individuals, aged from 18 to 79 years, were included into the scope of the study. Based upon body mass index values, 10 underweight, 88 normal, 88 overweight, 81 obese, and 20 morbid obese individuals participated. Anthropometric measurements including height (m), and weight (kg) were performed. Body mass index, diagnostic obesity notation model assessment index I, diagnostic obesity notation model assessment index II, basal metabolic rate-to-weight ratio were calculated. Total body fat mass (kg), fat percent (%), basal metabolic rate, metabolic age, visceral adiposity, fat mass of upper as well as lower extremities and trunk, obesity degree were measured by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical evaluations were performed by statistical package (SPSS) for Windows Version 16.0. Scatterplots of individual measurements for the parameters concerning correlations were drawn. Linear regression lines were displayed. The statistical significance degree was accepted as p < 0.05. The strong correlations between body mass index and diagnostic obesity notation model assessment index I as well as diagnostic obesity notation model assessment index II were obtained (p < 0.001). A much stronger correlation was detected between basal metabolic rate and diagnostic obesity notation model assessment index I in comparison with that calculated for basal metabolic rate and body mass index (p < 0.001). Upon consideration of the associations between basal metabolic rate-to-weight ratio and these three indices, the best association was observed between basal metabolic rate-to-weight and diagnostic obesity notation model assessment index II. In a similar manner, this index was highly correlated with fat percent (p < 0.001). Being independent of the indices, a strong correlation was found between fat percent and basal metabolic rate-to-weight ratio (p < 0.001). Visceral adiposity was much strongly correlated with metabolic age when compared to that with chronological age (p < 0.001). In conclusion, all three indices were associated with metabolic age, but not with chronological age. Diagnostic obesity notation model assessment index II values were highly correlated with body mass index values throughout all ranges starting with underweight going towards morbid obesity. This index is the best in terms of its association with basal metabolic rate-to-weight ratio, which can be interpreted as basal metabolic rate unit.
Keywords: Basal metabolic rate, body mass index, children, diagnostic obesity notation model assessment index, obesity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10567480 A Review on the Potential of Electric Vehicles in Reducing World CO2 Footprints
Authors: S. Alotaibi, S. Omer, Y. Su
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The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.
Keywords: Electric vehicle, fuel cell electric vehicle, hybrid electric vehicle, internal combustion engine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5407479 Investigations of Protein Aggregation Using Sequence and Structure Based Features
Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan
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The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.
Keywords: Aggregation prone regions, amyloids, thermophilic proteins, amino acid residues, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14987478 A Mesh Free Moving Node Method To Analyze Flow Through Spirals of Orbiting Scroll Pump
Authors: I.Banerjee, A.K.Mahendra, T.K.Bera, B.G.Chandresh
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The scroll pump belongs to the category of positive displacement pump can be used for continuous pumping of gases at low pressure apart from general vacuum application. The shape of volume occupied by the gas moves and deforms continuously as the spiral orbits. To capture flow features in such domain where mesh deformation varies with time in a complicated manner, mesh less solver was found to be very useful. Least Squares Kinetic Upwind Method (LSKUM) is a kinetic theory based mesh free Euler solver working on arbitrary distribution of points. Here upwind is enforced in molecular level based on kinetic flux vector splitting scheme (KFVS). In the present study we extended the LSKUM to moving node viscous flow application. This new code LSKUM-NS-MN for moving node viscous flow is validated for standard airfoil pitching test case. Simulation performed for flow through scroll pump using LSKUM-NS-MN code agrees well with the experimental pumping speed data.Keywords: Least Squares, Moving node, Pitching, Spirals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19047477 Binarization of Text Region based on Fuzzy Clustering and Histogram Distribution in Signboards
Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee
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In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.Keywords: Text detection, edge profile, signboard image, fuzzy clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22277476 A Framework for Scalable Autonomous P2P Resource Discovery for the Grid Implementation
Authors: Hesham A. Ali, Mofreh M. Salem, Ahmed A. Hamza
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Recently, there have been considerable efforts towards the convergence between P2P and Grid computing in order to reach a solution that takes the best of both worlds by exploiting the advantages that each offers. Augmenting the peer-to-peer model to the services of the Grid promises to eliminate bottlenecks and ensure greater scalability, availability, and fault-tolerance. The Grid Information Service (GIS) directly influences quality of service for grid platforms. Most of the proposed solutions for decentralizing the GIS are based on completely flat overlays. The main contributions for this paper are: the investigation of a novel resource discovery framework for Grid implementations based on a hierarchy of structured peer-to-peer overlay networks, and introducing a discovery algorithm utilizing the proposed framework. Validation of the framework-s performance is done via simulation. Experimental results show that the proposed organization has the advantage of being scalable while providing fault-isolation, effective bandwidth utilization, and hierarchical access control. In addition, it will lead to a reliable, guaranteed sub-linear search which returns results within a bounded interval of time and with a smaller amount of generated traffic within each domain.
Keywords: Grid computing, grid information service, P2P, resource discovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19767475 An Optimization of the New Die Design of Sheet Hydroforming by Taguchi Method
Authors: M. Hosseinzadeh, S. A. Zamani, A. Taheri
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During the last few years, several sheet hydroforming processes have been introduced. Despite the advantages of these methods, they have some limitations. Of the processes, the two main ones are the standard hydroforming and hydromechanical deep drawing. A new sheet hydroforming die set was proposed that has the advantages of both processes and eliminates their limitations. In this method, a polyurethane plate was used as a part of the die-set to control the blank holder force. This paper outlines the Taguchi optimization methodology, which is applied to optimize the effective parameters in forming cylindrical cups by the new die set of sheet hydroforming process. The process parameters evaluated in this research are polyurethane hardness, polyurethane thickness, forming pressure path and polyurethane hole diameter. The design of experiments based upon L9 orthogonal arrays by Taguchi was used and analysis of variance (ANOVA) was employed to analyze the effect of these parameters on the forming pressure. The analysis of the results showed that the optimal combination for low forming pressure is harder polyurethane, bigger diameter of polyurethane hole and thinner polyurethane. Finally, the confirmation test was derived based on the optimal combination of parameters and it was shown that the Taguchi method is suitable to examine the optimization process.Keywords: Sheet Hydroforming, Optimization, Taguchi Method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25967474 Multi-Layer Perceptron Neural Network Classifier with Binary Particle Swarm Optimization Based Feature Selection for Brain-Computer Interfaces
Authors: K. Akilandeswari, G. M. Nasira
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Brain-Computer Interfaces (BCIs) measure brain signals activity, intentionally and unintentionally induced by users, and provides a communication channel without depending on the brain’s normal peripheral nerves and muscles output pathway. Feature Selection (FS) is a global optimization machine learning problem that reduces features, removes irrelevant and noisy data resulting in acceptable recognition accuracy. It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm. Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.Keywords: Brain-Computer Interfaces (BCI), Feature Selection (FS), Walsh–Hadamard Transform (WHT), Binary Particle Swarm Optimization (BPSO), Multi-Layer Perceptron (MLP), Levenberg–Marquardt algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21857473 A Comparison of Adaline and MLP Neural Network based Predictors in SIR Estimation in Mobile DS/CDMA Systems
Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi
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In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25157472 Method of Intelligent Fault Diagnosis of Preload Loss for Single Nut Ball Screws through the Sensed Vibration Signals
Authors: Yi-Cheng Huang, Yan-Chen Shin
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This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform (HHT) and Multiscale entropy (MSE) process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition(EMD)with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.Keywords: Empirical Mode Decomposition, Hilbert-Huang Transform, Multi-scale Entropy, Preload Loss, Single-nut Ball Screw
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28437471 Near-Field Robust Adaptive Beamforming Based on Worst-Case Performance Optimization
Authors: Jing-ran Lin, Qi-cong Peng, Huai-zong Shao
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The performance of adaptive beamforming degrades substantially in the presence of steering vector mismatches. This degradation is especially severe in the near-field, for the 3-dimensional source location is more difficult to estimate than the 2-dimensional direction of arrival in far-field cases. As a solution, a novel approach of near-field robust adaptive beamforming (RABF) is proposed in this paper. It is a natural extension of the traditional far-field RABF and belongs to the class of diagonal loading approaches, with the loading level determined based on worst-case performance optimization. However, different from the methods solving the optimal loading by iteration, it suggests here a simple closed-form solution after some approximations, and consequently, the optimal weight vector can be expressed in a closed form. Besides simplicity and low computational cost, the proposed approach reveals how different factors affect the optimal loading as well as the weight vector. Its excellent performance in the near-field is confirmed via a number of numerical examples.Keywords: Robust adaptive beamforming (RABF), near-field, steering vector mismatches, diagonal loading, worst-case performanceoptimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18817470 FPGA Based Parallel Architecture for the Computation of Third-Order Cross Moments
Authors: Syed Manzoor Qasim, Shuja Abbasi, Saleh Alshebeili, Bandar Almashary, Ateeq Ahmad Khan
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Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.Keywords: Cross moments, Cumulants, FPGA, Hardware Implementation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1735