Search results for: data analysis.

Authors: Punitha Periyasamy, Mahalingam Sudalaimuthu, Sachikanta Nanda, Arasu Sundaram

Abstract:

India holds 17.5% of the world’s population but has only 2% of the total geographical area of the world where 27.35% of the area is categorized as wasteland due to lack of or less groundwater. So there is a demand for excessive groundwater for agricultural and non agricultural activities to balance its growth rate. With this in mind, an attempt is made to find the groundwater potential zone in Gomukhi Nadhi sub basin of Vellar River basin, TamilNadu, India covering an area of 1146.6 Sq.Km consists of 9 blocks from Peddanaickanpalayam to Virudhachalam in the sub basin. The thematic maps such as Geology, Geomorphology, Lineament, Landuse and Landcover and Drainage are prepared for the study area using IRS P6 data. The collateral data includes rainfall, water level, soil map are collected for analysis and inference. The digital elevation model (DEM) is generated using Shuttle Radar Topographic Mission (SRTM) and the slope of the study area is obtained. ArcGIS 10.1 acts as a powerful spatial analysis tool to find out the ground water potential zones in the study area by means of weighted overlay analysis. Each individual parameter of the thematic maps are ranked and weighted in accordance with their influence to increase the water level in the ground. The potential zones in the study area are classified viz., Very Good, Good, Moderate, Poor with its aerial extent of 15.67, 381.06, 575.38, 174.49 Sq.Km respectively.

Keywords: ArcGIS, DEM, Groundwater, Recharge, Weighted Overlay.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2998

Authors: Anthony Spiteri Staines

Abstract:

This paper examines the modeling and analysis of a cruise control system using a Petri net based approach, task graphs, invariant analysis and behavioral properties. It shows how the structures used can be verified and optimized.

Keywords: Software Engineering, Real Time Analysis andDesign, Petri Nets, Task Graphs, Parallelism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2365

Authors: Antonino Greco, Nadia Mammone, Francesco Carlo Morabito, Mario Versaci

Abstract:

The goal of this work is to improve the efficiency and the reliability of the automatic artifact rejection, in particular from the Electroencephalographic (EEG) recordings. Artifact rejection is a key topic in signal processing. The artifacts are unwelcome signals that may occur during the signal acquisition and that may alter the analysis of the signals themselves. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we enhance this technique introducing the Renyi-s entropy. The performance of our method was tested exploiting the Independent Component scalp maps and it was compared to the performance of the method in literature and it showed to outperform it.

Keywords: Artifact, EEG, Renyi's entropy, independent component analysis, kurtosis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2433

Authors: Shanthi Thomas

Abstract:

This research paper presents the current practices of teacher professional development, perceived as beneficial by teachers themselves, in a private secondary school in Brunei Darussalam. This is part of the findings of a larger qualitative study on teacher empowerment, using ethnographic methods for data collection, i.e. participant observation, interviews and document analysis. The field work was carried out over a period of six months in 2013. An analysis of the field data revealed multiple pathways of teacher professional development existing in the school. The results indicate that school leaders, the teacher community in the school, students, and the teachers themselves were the agents in a school that facilitated teacher empowerment. Besides contributing to the knowledge base on teacher professional development, the results of this study provide directions for educational policy makers in their efforts to enhance professional development in secondary schools of similar characteristics. For school leaders and the teacher community, these findings offer guidelines for maximizing the opportunities for these professional development practices, by strengthening collegiality and by using the existing structures optimally for the benefit of all concerned.

Keywords: Colleagues and the wider teacher community, school leaders, self-driven professional development, teacher professional development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2698

Authors: M. K. Witek-Hajduk, T. M. Napiórkowski

Abstract:

A number of studies discussed the topic of benefits of retailers-manufacturers cooperation and coopetition. However, there are only few publications focused on the benefits of cooperation and coopetition between retailers and their suppliers of durable consumer goods; especially in the context of business model of cooperating partners. This paper aims to provide a clustering approach to segment retailers selling consumer durables according to the benefits they obtain from their cooperation with key manufacturers and differentiate the said retailers’ in term of the business models of cooperating partners. For the purpose of the study, a survey (with a CATI method) collected data on 603 consumer durables retailers present on the Polish market. Retailers are clustered both, with hierarchical and non-hierarchical methods. Five distinctive groups of consumer durables’ retailers are (based on the studied benefits) identified using the two-stage clustering approach. The clusters are then characterized with a set of exogenous variables, key of which are business models employed by the retailer and its partnering key manufacturer. The paper finds that the a combination of a medium sized retailer classified as an Integrator with a chiefly domestic capital and a manufacturer categorized as a Market Player will yield the highest benefits. On the other side of the spectrum is medium sized Distributor retailer with solely domestic capital – in this case, the business model of the cooperating manufactrer appears to be irreleveant. This paper is the one of the first empirical study using cluster analysis on primary data that defines the types of cooperation between consumer durables’ retailers and manufacturers – their key suppliers. The analysis integrates a perspective of both retailers’ and manufacturers’ business models and matches them with individual and joint benefits.

Keywords: Business model, cooperation, cluster analysis, retailer-manufacturer relationships.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1123

Authors: Alpha Agape Gopalai, S. M. N. Arosha Senanayake

Abstract:

This paper explores the opportunity of using tri-axial wireless accelerometers for supervised monitoring of sports movements. A motion analysis system for the upper extremities of lawn bowlers in particular is developed. Accelerometers are placed on parts of human body such as the chest to represent the shoulder movements, the back to capture the trunk motion, back of the hand, the wrist and one above the elbow, to capture arm movements. These sensors placement are carefully designed in order to avoid restricting bowler-s movements. Data is acquired from these sensors in soft-real time using virtual instrumentation; the acquired data is then conditioned and converted into required parameters for motion regeneration. A user interface was also created to facilitate in the acquisition of data, and broadcasting of commands to the wireless accelerometers. All motion regeneration in this paper deals with the motion of the human body segment in the X and Y direction, looking into the motion of the anterior/ posterior and lateral directions respectively.

Keywords: Motion Regeneration, Virtual Instrumentation, Wireless Accelerometers.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1831

Authors: Nadia Belu, Laurentiu M. Ionescu, Agnieszka Misztal

Abstract:

In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: Automotive industry, control plan, FMEA.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2880

Authors: Yung-Chien Sun, O. Grant Clark

Abstract:

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1386

Authors: Sevgi Birsel Nemlioğlu, Hasan Atak

Abstract:

Emerging adulthood, between the ages of 18 and 25, as a new developmental stage extending from adolescence to young adulthood. According to Arnett [2004], there are experiments related to identity in three basic fields which are love, work and view of the world in emerging adulthood. When the literature related to identity is examined, it is seen that identity has been studied more with adolescent, and studies were concentrated on the relationship of identity with many demographic variables neglecting important variables such as marital status, parental status and SES. Thus, the main aim of this study is to determine whether identity statuses differenciate with marital status, parental status and SES. A total of 700 emerging adults participated in this study, and the mean age was 22,45 years [SD = 3.76]. The sample was made up of 347 female and 353 male. All participants in the study were students from colleges. Student responses to the Extended Version of the Objective Measure of Ego Identity Status [EOM-EIS-2] used to classify students into one of the four identity statuses. SPSS 15.00 program wasa used to analyse data. Percentage, frequency and X2 analysis were used in the analysis of data. When the findings of the study is viewed as a whole, the most frequently observed identity status in the group is found to be moratorium. Also, identity statuses differenciate with marital status, parental status and SES. Findings were discussed in the context of emerging adulthood.

Keywords: Identity statuses, emerging adulthood, Turkey.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1709

Authors: K. Qonono

Abstract:

Despite the significance and economic benefits of petrol stations in South Africa, these still pose a huge risk of fire and explosion threatening public safety. This research paper examines the extent to which land-use planning in Stellenbosch, South Africa, considers the fire risk posed by petrol stations and the implications for public safety as well as preparedness for large fires or explosions. To achieve this, the research identified the land-use types around petrol stations in Stellenbosch and determined the extent to which their locations comply with the local, national, and international land-use planning regulations. A mixed research method consisting of the collection and analysis of geospatial data and qualitative data was applied, where petrol stations within a six-kilometre radius of Stellenbosch’s town centre were utilised as study sites. The research examined the risk of fires/explosions at these petrol stations. The research investigated Stellenbosch Municipality’s institutional preparedness to respond in the event of a fire/explosion at these petrol stations. The research observed that siting of petrol stations does not comply with local, national, and international good practices, thus exposing the surrounding developments to fires and explosions. Land-use planning practice does not consider hazards created by petrol stations. Despite the potential for major fires at petrol stations, Stellenbosch Municipality’s level of preparedness to respond to petrol station fires appears low due to the prioritisation of more frequent events.

Keywords: Petrol stations, technological hazard, DRR, land-use planning, risk analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 150

Authors: Sheng-Min Cheng

Abstract:

The purpose of this study was to investigate the relationship between parent involvement and preschool disabled children’s development. Parents of 3 year old disabled children (N=440) and 5 year old disabled children (N=937) participating in the Special Needs Education Longitudinal Study were interviewed or answered the web design questionnaire about their actions in parenting their disabled children. These children’s developments were also evaluated by their teachers. Data were analyzed using Structural Equation Modeling. Results were showed by tables and figures. Based on the results, the researcher made some suggestions for future studies.

Keywords: Child development, longitudinal data analysis, parent involvement, preschool disabled children.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2243

Authors: Hongzhi Wang, Jianzhong Li, Hong Gao

Abstract:

XML is an important standard of data exchange and representation. As a mature database system, using relational database to support XML data may bring some advantages. But storing XML in relational database has obvious redundancy that wastes disk space, bandwidth and disk I/O when querying XML data. For the efficiency of storage and query XML, it is necessary to use compressed XML data in relational database. In this paper, a compressed relational database technology supporting XML data is presented. Original relational storage structure is adaptive to XPath query process. The compression method keeps this feature. Besides traditional relational database techniques, additional query process technologies on compressed relations and for special structure for XML are presented. In this paper, technologies for XQuery process in compressed relational database are presented..

Keywords: XML, compression, query processing

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1807

Authors: P. Kaladevi, N. Giridharan

Abstract:

The system for analyzing and eliciting public grievances serves its main purpose to receive and process all sorts of complaints from the public and respond to users. Due to the more number of complaint data becomes big data which is difficult to store and process. The proposed system uses HDFS to store the big data and uses MapReduce to process the big data. The concept of cache was applied in the system to provide immediate response and timely action using big data analytics. Cache enabled big data increases the response time of the system. The unstructured data provided by the users are efficiently handled through map reduce algorithm. The processing of complaints takes place in the order of the hierarchy of the authority. The drawbacks of the traditional database system used in the existing system are set forth by our system by using Cache enabled Hadoop Distributed File System. MapReduce framework codes have the possible to leak the sensitive data through computation process. We propose a system that add noise to the output of the reduce phase to avoid signaling the presence of sensitive data. If the complaints are not processed in the ample time, then automatically it is forwarded to the higher authority. Hence it ensures assurance in processing. A copy of the filed complaint is sent as a digitally signed PDF document to the user mail id which serves as a proof. The system report serves to be an essential data while making important decisions based on legislation.

Keywords: Big Data, Hadoop, HDFS, Caching, MapReduce, web personalization, e-governance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1595

Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant Kumar Srivastava

Abstract:

An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373 and 0.9428 respectively.

Keywords: Bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3231

Authors: S. Pirrello

Abstract:

Sydney’s booming real estate market has pushed property developers to invest in historically “no-go” areas, which were previously too expensive to develop. These areas are usually near rivers where the sites are underlain by deep alluvial and estuarine sediments. In these ground conditions, conventional bored pile techniques are often not competitive. Contiguous Flight Auger (CFA) and Drilled Displacement (DD) Piles techniques are on the other hand suitable for these ground conditions. This paper deals with the design and construction challenges encountered with these piling techniques for a series of high-rise towers in Sydney’s West. The advantages of DD over CFA piles such as reduced overall spoil with substantial cost savings and achievable rock sockets in medium strength bedrock are discussed. Design performances were assessed with PIGLET. Pile performances are validated in two stages, during constructions with the interpretation of real-time data from the piling rigs’ on-board computer data, and after construction with analyses of results from high strain pile dynamic testing (PDA). Results are then presented and discussed. High Strain testing data are presented as Case Pile Wave Analysis Program (CAPWAP) analyses.

Keywords: Contiguous flight auger, case pile wave analysis, high strain pile, drilled displacement, pile performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 988

Authors: Vandana Sharma, Parvinder S. Sandhu, Satwinder Singh, Baljit Saini

Abstract:

In field of Computer Science and Mathematics, sorting algorithm is an algorithm that puts elements of a list in a certain order i.e. ascending or descending. Sorting is perhaps the most widely studied problem in computer science and is frequently used as a benchmark of a system-s performance. This paper presented the comparative performance study of four sorting algorithms on different platform. For each machine, it is found that the algorithm depends upon the number of elements to be sorted. In addition, as expected, results show that the relative performance of the algorithms differed on the various machines. So, algorithm performance is dependent on data size and there exists impact of hardware also.

Keywords: Algorithm, Analysis, Complexity, Sorting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2415

Authors: S. Shanthi, V. Muralibhaskaran

Abstract:

Mammography has been one of the most reliable methods for early detection of breast cancer. There are different lesions which are breast cancer characteristic such as microcalcifications, masses, architectural distortions and bilateral asymmetry. One of the major challenges of analysing digital mammogram is how to extract efficient features from it for accurate cancer classification. In this paper we proposed a hybrid feature extraction method to detect and classify all four signs of breast cancer. The proposed method is based on multiscale surrounding region dependence method, Gabor filters, multi fractal analysis, directional and morphological analysis. The extracted features are input to self adaptive resource allocation network (SRAN) classifier for classification. The validity of our approach is extensively demonstrated using the two benchmark data sets Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammograph (DDSM) and the results have been proved to be progressive.

Keywords: Feature extraction, fractal analysis, Gabor filters, multiscale surrounding region dependence method, SRAN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2949

Authors: Humberto N. Teixeira, Isabel S. Lopes, Sérgio D. Sousa

Abstract:

This article proposes a new methodology to be used by SMEs (Small and Medium enterprises) to characterize their performance in quality, highlighting weaknesses and area for improvement. The methodology aims to identify the principal causes of quality problems and help to prioritize improvement initiatives. This is a self-assessment methodology that intends to be easy to implement by companies with low maturity level in quality. The methodology is organized in six different steps which includes gathering information about predetermined processes and subprocesses of quality management, defined based on the well-known Juran-s trilogy for quality management (Quality planning, quality control and quality improvement) and, predetermined results categories, defined based on quality concept. A set of tools for data collecting and analysis, such as interviews, flowcharts, process analysis diagrams and Failure Mode and effects Analysis (FMEA) are used. The article also presents the conclusions obtained in the application of the methodology in two cases studies.

Keywords: Continuous improvement, Diagnosis, Quality Management, Self-assessment, SMEs

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2506

Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri

Abstract:

In this study, ¹⁷⁷Lu-DOTATOC was prepared under optimized conditions (radiochemical purity: > 99%, radionuclidic purity: > 99%). The percentage of injected dose per gram (%ID/g) was calculated for organs up to 168 h post injection. Compartmental model was applied to mathematical description of the drug behaviour in tissue at different times. The biodistribution data showed the significant excretion of the radioactivity from the kidneys. The adrenal and pancreas, as major expression sites for somatostatin receptor (SSTR), had significant uptake. A pharmacokinetic model of ¹⁷⁷Lu-DOTATOC was presented by compartmental analysis which demonstrates the behavior of the complex.

Keywords: Biodistribution, compartmental modeling, 177Lu, octreotide.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 824

Authors: S.Aranganayagi, K.Thangavel

Abstract:

K-Modes is an extension of K-Means clustering algorithm, developed to cluster the categorical data, where the mean is replaced by the mode. The similarity measure proposed by Huang is the simple matching or mismatching measure. Weight of attribute values contribute much in clustering; thus in this paper we propose a new weighted dissimilarity measure for K-Modes, based on the ratio of frequency of attribute values in the cluster and in the data set. The new weighted measure is experimented with the data sets obtained from the UCI data repository. The results are compared with K-Modes and K-representative, which show that the new measure generates clusters with high purity.

Keywords: Clustering, categorical data, K-Modes, weighted dissimilarity measure

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3694

Authors: D. R. Delgado Sobrino, P. Košťál, J. Oravcová

Abstract:

Lately, significant work in the area of Intelligent Manufacturing has become public and mainly applied within the frame of industrial purposes. Special efforts have been made in the implementation of new technologies, management and control systems, among many others which have all evolved the field. Aware of all this and due to the scope of new projects and the need of turning the existing flexible ideas into more autonomous and intelligent ones, i.e.: Intelligent Manufacturing, the present paper emerges with the main aim of contributing to the design and analysis of the material flow in either systems, cells or work stations under this new “intelligent" denomination. For this, besides offering a conceptual basis in some of the key points to be taken into account and some general principles to consider in the design and analysis of the material flow, also some tips on how to define other possible alternative material flow scenarios and a classification of the states a system, cell or workstation are offered as well. All this is done with the intentions of relating it with the use of simulation tools, for which these have been briefly addressed with a special focus on the Witness simulation package. For a better comprehension, the previous elements are supported by a detailed layout, other figures and a few expressions which could help obtaining necessary data. Such data and others will be used in the future, when simulating the scenarios in the search of the best material flow configurations.

Keywords: Flexible/Intelligent Manufacturing System/Cell (F/IMS/C), material flow/design/configuration (MF/D/C), workstation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614

Authors: Anil Kumar Pandey

Abstract:

Power plane noise is the most significant source of signal integrity (SI) issues in a high-speed digital design. In this paper, power integrity (PI) analysis of multiple power planes in a power delivery system of a 12-layer high-speed FPGA board is presented. All 10 power planes of HSD board are analyzed separately by using 3D Electromagnetic based PI solver, then the transient simulation is performed on combined PI data of all planes along with voltage regulator modules (VRMs) and 70 current drawing chips to get the board level power noise coupling on different high-speed signals. De-coupling capacitors are placed between power planes and ground to reduce power noise coupling with signals.

Keywords: Channel simulation, electromagnetic simulation, power-aware signal integrity analysis, power integrity, PIPro.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2292

Authors: Cristina Sá, Carlos Gomes, António Martins

Abstract:

The reasons that explain different behaviors towards tax obligations in similar countries are not completely understood yet. The main purpose of this paper is to identify and compare the factors that influence tax morale levels in Portugal and Spain. We use data from European Values Study (EVS). Using a sample of 2,652 individuals, a factor analysis was used to extract the underlying dimensions of tax morale of Portuguese and Spanish taxpayers. Based on a factor analysis, the results of this paper show that sociological and behavioral factors, psychological factors and political factors are important for a good understanding of taxpayers’ behavior in Iberian Peninsula. This paper added value relies on the analyses of a wide range of variables and on the comparison between Portugal and Spain. Our conclusions provided insights that tax authorities and politicians can use to better focus their strategies and actions in order to increase compliance, reduce tax evasion, fight underground economy and increase country´s competitiveness.

Keywords: Compliance, tax morale, Portugal, Spain.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1004

Authors: Kanda Runapongsa Saikaew, Patcharaporn Jiranuwattanawong, Patinya Taearak

Abstract:

Currently, there is excessively growing information about places on Facebook, which is the largest social network but such information is not explicitly organized and ranked. Therefore users cannot exploit such data to recommend places conveniently and quickly. This paper proposes a Facebook application and an Android application that recommend places based on the number of check-ins of those places, the distance of those places from the current location, the number of people who like Facebook page of those places, and the number of talking about of those places. Related Facebook data is gathered via Facebook API requests. The experimental results of the developed applications show that the applications can recommend places and rank interesting places from the most to the least. We have found that the average satisfied score of the proposed Facebook application is 4.8 out of 5. The users’ satisfaction can increase by adding the app features that support personalization in terms of interests and preferences.

Keywords: Mobile computing, location-based services, recommendation system, social network analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1783

Authors: Danielle Shackley, Yetunde Folajimi

Abstract:

As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 498

Authors: S. Esfandeh, M. Sedighizadeh

Abstract:

Weather systems use enormously complex combinations of numerical tools for study and forecasting. Unfortunately, due to phenomena in the world climate, such as the greenhouse effect, classical models may become insufficient mostly because they lack adaptation. Therefore, the weather forecast problem is matched for heuristic approaches, such as Evolutionary Algorithms. Experimentation with heuristic methods like Particle Swarm Optimization (PSO) algorithm can lead to the development of new insights or promising models that can be fine tuned with more focused techniques. This paper describes a PSO approach for analysis and prediction of data and provides experimental results of the aforementioned method on realworld meteorological time series.

Keywords: Weather, Climate, PSO, Prediction, Meteorological

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2080

Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem

Abstract:

The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.

Keywords: Connectivism, data visualization, informal learning, learning analytics, semantic web, social web.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 817

Authors: Mudjiastuti Handajani

Abstract:

The national economy development affects the vehicle ownership which ultimately increases fuel consumption. The rise of the vehicle ownership is dominated by the increasing number of motorcycles. This research aims to analyze and identify the characteristics of fuel consumption, the city transportation system, and to analyze the relationship and the effect of the city transportation system on the fuel consumption. A multivariable analysis is used in this study. The data analysis techniques include: a Multivariate Multivariable Analysis by using the R software. More than 84% of fuel on Java is consumed in metropolitan and large cities. The city transportation system variables that strongly effect the fuel consumption are population, public vehicles, private vehicles and private bus. This method can be developed to control the fuel consumption by considering the urban transport system and city tipology. The effect can reducing subsidy on the fuel consumption, increasing state economic.

Keywords: city, consumption, fuel, transportation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1955

Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

Abstract:

Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: Wavelet transform, computational error, computational duration, strong ground motion data.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1377

Authors: Archit Yajnik

Abstract:

Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: Hidden Markov model, Viterbi algorithm, POS tagging, natural language processing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1714