Search results for: data interpolating empirical orthogonal function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 29453

Search results for: data interpolating empirical orthogonal function

26813 Microarray Gene Expression Data Dimensionality Reduction Using PCA

Authors: Fuad M. Alkoot

Abstract:

Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

Procedia PDF Downloads 543
26812 A Monopole Intravascular Antenna with Three Parasitic Elements Optimized for Higher Tesla MRI Systems

Authors: Mohammad Mohammadzadeh, Alireza Ghasempour

Abstract:

In this paper, a new design of monopole antenna has been proposed that increases the contrast of intravascular magnetic resonance images through increasing the homogeneity of the intrinsic signal-to-noise ratio (ISNR) distribution around the antenna. The antenna is made of a coaxial cable with three parasitic elements. Lengths and positions of the elements are optimized by the improved genetic algorithm (IGA) for 1.5, 3, 4.7, and 7Tesla MRI systems based on a defined cost function. Simulations were also conducted to verify the performance of the designed antenna. Our simulation results show that each time IGA is executed different values for the parasitic elements are obtained so that the cost functions of those antennas are high. According to the obtained results, IGA can also find the best values for the parasitic elements (regarding cost function) in the next executions. Additionally, two dimensional and one-dimensional maps of ISNR were drawn for the proposed antenna and compared to the previously published monopole antenna with one parasitic element at the frequency of 64MHz inside a saline phantom. Results verified that in spite of ISNR decreasing, there is a considerable improvement in the homogeneity of ISNR distribution of the proposed antenna so that their multiplication increases.

Keywords: intravascular MR antenna, monopole antenna, parasitic elements, signal-to-noise ratio (SNR), genetic algorithm

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26811 The Role of Eclectic Approach to Teach Communicative Function at Secondary Level

Authors: Fariha Asif

Abstract:

The main purpose of this study was to investigate the effectiveness of eclectic approach in teaching of communicative functions. The objectives of the study were to get the information about the use of communicative functions through eclectic approach and to point out the most effective way of teaching functional communication and social interaction with the help of communicative activities through eclectic approach. The next step was to select sample from the selected population. As the research was descriptive so a questionnaire was developed on the basis of hypothesis and distributed to different selected schools of Lahore, Pakistan. Then data was tabulated, analyzed and interpreted through computer by finding percentages of different responses given by teachers to see the results. It was concluded that eclectic approach is effective in teaching communicative functions and communicative functions are better when taught through eclectic approach and communicative activities are more appropriate way of teaching communicative functions. It was found those teachers who were qualified in ELT gave better opinions as compare to those who did not have this degree. Techniques like presentations, dialogues and roleplay proved to be effective for teaching functional communication through communicative activities and also motivate the students not only in learning rules but also in using them to communicate with others.

Keywords: methodology, functions, teaching, ESP

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26810 Increasing Abundance of Jellyfish in the Shorelines of Bangladesh: Analyzing the Policy Framework for Facing the Challenges

Authors: Md Mizanur Rahman, M. Aslam Alam, Muhammad Abu Yusuf

Abstract:

The abundance of Jellyfish across the coasts of the Bay of Bengal is increasing sharply due to marine pollution, increased sea acidification and climate change. Jellyfish draws our attention to address the local and global stressors. This also indicates that something wrong is happening in this bay behind the scenes. This study aimed to investigate how the policy framework governing the sea can be reformed. To do so, this study evaluated the existing policy, regulatory and institutional framework. Empirical data were collected from the middle coastal zone of Bangladesh. The secondary literature on policy, legal documents, and institutional arrangements were reviewed. The causes of poor coordination among different public sectors and non-compliance of laws were identified. The key findings show that despite the existing of Department of Environment, poor coordination with other departments, and lack of logistics and technical staffs have resulted in severe marine pollution and degradation of coastal and marine living resources. The existing policies had no monitoring and evaluation mechanisms. Non-compliance of the existing laws has been fueling the problems. This study provides an integrated policy and a guideline for updating the legal and institutional mechanism to manage coastal and marine living resources sustainably in Bangladesh to achieve Sustainable Development Goal 14.

Keywords: legal, institutional, framework, jellyfish

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26809 Decoupled Dynamic Control of Unicycle Robot Using Integral Linear Quadratic Regulator and Sliding Mode Controller

Authors: Shweda Mohan, J. L. Nandagopal, S. Amritha

Abstract:

This paper focuses on the dynamic modelling of unicycle robot. Two main concepts used for balancing unicycle robot are: reaction wheel pendulum and inverted pendulum. The pitch axis is modelled as inverted pendulum and roll axis is modelled as reaction wheel pendulum. The unicycle yaw dynamics is not considered which makes the derivation of dynamics relatively simple. For the roll controller, sliding-mode controller has been adopted and optimal methods are used to minimize switching-function chattering. For pitch controller, an LQR controller has been implemented to drive the unicycle robot to follow the desired velocity trajectory. The pitching and rolling balance could be achieved by two DC motors. Unicycle robot is a non-holonomic, non-linear, static unbalance system that has the minimal number of point contact to the ground, therefore, it is a perfect platform for researchers to study motion and balance control. These real-time solutions will be a viable solution for advanced robotic systems and controls.

Keywords: decoupled dynamics, linear quadratic regulator (LQR) control, Lyapunov function sliding mode control, unicycle robot, velocity and trajectory control

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26808 Discriminant Analysis as a Function of Predictive Learning to Select Evolutionary Algorithms in Intelligent Transportation System

Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

Abstract:

In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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26807 Governing Urban Water Infrasystems: A Case Study of Los Angeles in the Context of Global Frameworks

Authors: Joachim Monkelbaan, Marcia Hale

Abstract:

Now that global frameworks for sustainability governance (e.g. the Sustainable Development Goals, Paris Climate Agreement and Sendai Framework for Disaster Risk Reduction) are in place, the question is how these aspirations that represent major transitions can be put into practice. Water ‘infrasystems’ can play an especially significant role in strengthening regional sustainability. Infrasystems include both hard and soft infrastructure, such as pipes and technology for delivering water, as well as the institutions and governance models that direct its delivery. As such, an integrated infrasystems view is crucial for Integrative Water Management (IWM). Due to frequently contested ownership of and responsibility for water resources, these infrasystems can also play an important role in facilitating conflict and catalysing community empowerment, especially through participatory approaches to governance. In this paper, we analyze the water infrasystem of the Los Angeles region through the lens of global frameworks for sustainability governance. By complementing a solid overview of governance theories with empirical data from interviews with water actors in the LA metropolitan region (including NGOs, water managers, scientists and elected officials), this paper elucidates ways for this infrasystem to be better aligned with global sustainability frameworks. In addition, it opens up the opportunity to scrutinize the appropriateness of global frameworks when it comes to fostering sustainability action at the local level.

Keywords: governance, transitions, global frameworks, infrasystems

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26806 Data Science-Based Key Factor Analysis and Risk Prediction of Diabetic

Authors: Fei Gao, Rodolfo C. Raga Jr.

Abstract:

This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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26805 Teacher's Gender and Primary School Pupils Achievement in Social Studies and Its Educational Implications on Pupils

Authors: Elizabeth Oyenike Abegunrin

Abstract:

This study is borne out of the dire need to improve the academic achievement of pupils in social studies. The paper attempted to reconcile the lacuna in teacher’s gender and primary school pupils’ achievement. With specific reference to Social Studies classroom, the aim of this study was to detail how pupils’ achievement is a function of the teacher’s gender as well as to establish the link (if any) between teacher’s gender and pupils’ educational achievement. The significance of this was to create gender-template standard for teachers, school owners, administrators and policy makers to follow in the course of engendering pupils’ achievement in Social Studies. By adopting a quasi-experimental research design, a sample of two hundred pupils was selected across five primary schools in Education District I, Lagos State and assigned to experimental and control groups. A 40-item Gender and Social Studies Achievement Test (GSSAT) was used to obtain data from the pupils. Having analyzed the data collected using Pearson Product Moment Correlation (PPMC), a reliability of 0.78 was obtained. Result revealed that teacher’s gender (male/female) had no significant effect on pupils’ achievement in Social Studies and that there was significant interaction effect of teacher’s commitment devoid of gender on the general education output of pupils in Social Studies. Taken together, the results revealed that there is a high degree correlation between teacher’s commitment and pupils academic achievement in social studies, and not gender-based. The study recommended that social studies teachers should re-assess their classroom instructional strategies and use more innovative instructional methods and techniques that will give the pupils equal opportunities to excel in social studies, rather than their gender differences.

Keywords: gender, academic achievement, social studies, primary school

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26804 A Methodology to Integrate Data in the Company Based on the Semantic Standard in the Context of Industry 4.0

Authors: Chang Qin, Daham Mustafa, Abderrahmane Khiat, Pierre Bienert, Paulo Zanini

Abstract:

Nowadays, companies are facing lots of challenges in the process of digital transformation, which can be a complex and costly undertaking. Digital transformation involves the collection and analysis of large amounts of data, which can create challenges around data management and governance. Furthermore, it is also challenged to integrate data from multiple systems and technologies. Although with these pains, companies are still pursuing digitalization because by embracing advanced technologies, companies can improve efficiency, quality, decision-making, and customer experience while also creating different business models and revenue streams. In this paper, the issue that data is stored in data silos with different schema and structures is focused. The conventional approaches to addressing this issue involve utilizing data warehousing, data integration tools, data standardization, and business intelligence tools. However, these approaches primarily focus on the grammar and structure of the data and neglect the importance of semantic modeling and semantic standardization, which are essential for achieving data interoperability. In this session, the challenge of data silos in Industry 4.0 is addressed by developing a semantic modeling approach compliant with Asset Administration Shell (AAS) models as an efficient standard for communication in Industry 4.0. The paper highlights how our approach can facilitate the data mapping process and semantic lifting according to existing industry standards such as ECLASS and other industrial dictionaries. It also incorporates the Asset Administration Shell technology to model and map the company’s data and utilize a knowledge graph for data storage and exploration.

Keywords: data interoperability in industry 4.0, digital integration, industrial dictionary, semantic modeling

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26803 Modelling and Simulation of Aero-Elastic Vibrations Using System Dynamic Approach

Authors: Cosmas Pandit Pagwiwoko, Ammar Khaled Abdelaziz Abdelsamia

Abstract:

Flutter as a phenomenon of flow-induced and self-excited vibration has to be recognized considering its harmful effect on the structure especially in a stage of aircraft design. This phenomenon is also important for a wind energy harvester based on the fluttering surface due to its effective operational velocity range. This multi-physics occurrence can be presented by two governing equations in both fluid and structure simultaneously in respecting certain boundary conditions on the surface of the body. In this work, the equations are resolved separately by two distinct solvers, one-time step of each domain. The modelling and simulation of this flow-structure interaction in ANSYS show the effectiveness of this loosely coupled method in representing flutter phenomenon however the process is time-consuming for design purposes. Therefore, another technique using the same weak coupled aero-structure is proposed by using system dynamics approach. In this technique, the aerodynamic forces were calculated using singularity function for a range of frequencies and certain natural mode shapes are transformed into time domain by employing an approximation model of fraction rational function in Laplace variable. The representation of structure in a multi-degree-of-freedom coupled with a transfer function of aerodynamic forces can then be simulated in time domain on a block-diagram platform such as Simulink MATLAB. The dynamic response of flutter at certain velocity can be evaluated with another established flutter calculation in frequency domain k-method. In this method, a parameter of artificial structural damping is inserted in the equation of motion to assure the energy balance of flow and vibrating structure. The simulation in time domain is particularly interested as it enables to apply the structural non-linear factors accurately. Experimental tests on a fluttering airfoil in the wind tunnel are also conducted to validate the method.

Keywords: flutter, flow-induced vibration, flow-structure interaction, non-linear structure

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26802 Viscoelastic Behaviour of Hyaluronic Acid Copolymers

Authors: Loredana Elena Nita, Maria Bercea, Aurica P. Chiriac, Iordana Neamtu

Abstract:

The paper is devoted to the behavior of gels based on poly(itaconic anhydride-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5) undecane) copolymers, with different ratio between the comonomers, and hyaluronic acid (HA). The gel formation was investigated by small-amplitude oscillatory shear measurements following the viscoelastic behavior as a function of gel composition, temperature and shear conditions. Hyaluronic acid was investigated in the same conditions and its rheological behavior is typical to viscous fluids. In the case of the copolymers, the ratio between the two comonomers influences the viscoelastic behavior, a higher content of itaconic anhydride favoring the gel formation. Also, the sol-gel transition was evaluated according to Winter-Chambon criterion that identifies the gelation point when the viscoelastic moduli (G’ and G”) behave similarly as a function of oscillation frequency. From rheological measurements, an optimum composition was evidenced for which the system presents a typical gel-like behavior at 37 °C: the elastic modulus is higher than the viscous modulus and they are not dependent on the oscillation frequency. The formation of the 3D macroporous network was also evidenced by FTIR spectra, SEM microscopy and chemical imaging. These hydrogels present a high potential as drug delivery systems.

Keywords: copolymer, viscoelasticity, gelation, 3D network

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26801 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption

Authors: Waziri Victor Onomza, John K. Alhassan, Idris Ismaila, Noel Dogonyaro Moses

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute theoretical presentations in high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, homomorphic, homomorphic encryption scheme

Procedia PDF Downloads 367
26800 A Review on Bearing Capacity Factor Nγ of Foundations with Different Shapes

Authors: R. Ziaie Moayed, S. Taghvamanesh

Abstract:

So far several methods by different researchers have been developed in order to calculate the bearing capacity factors of foundations and retaining walls. In this paper, the bearing capacity factor Ny (shape factor) for different types of foundation have been investigated. The formula for bearing capacity on c–φ–γ soil can still be expressed by Terzaghi’s equation except that the bearing capacity factor Ny depends on the surcharge ratio, and friction angle φ. Many empirical definitions have been used for measurement of the bearing capacity factors N

Keywords: bearing capacity, bearing capacity factor Nγ, irregular foundations, shape factor

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26799 Modeling of Surface Roughness in Hard Turning of DIN 1.2210 Cold Work Tool Steel with Ceramic Tools

Authors: Mehmet Erdi Korkmaz, Mustafa Günay

Abstract:

Nowadays, grinding is frequently replaced with hard turning for reducing set up time and higher accuracy. This paper focused on mathematical modeling of average surface roughness (Ra) in hard turning of AISI L2 grade (DIN 1.2210) cold work tool steel with ceramic tools. The steel was hardened to 60±1 HRC after the heat treatment process. Cutting speed, feed rate, depth of cut and tool nose radius was chosen as the cutting conditions. The uncoated ceramic cutting tools were used in the machining experiments. The machining experiments were performed according to Taguchi L27 orthogonal array on CNC lathe. Ra values were calculated by averaging three roughness values obtained from three different points of machined surface. The influences of cutting conditions on surface roughness were evaluated as statistical and experimental. The analysis of variance (ANOVA) with 95% confidence level was applied for statistical analysis of experimental results. Finally, mathematical models were developed using the artificial neural networks (ANN). ANOVA results show that feed rate is the dominant factor affecting surface roughness, followed by tool nose radius and cutting speed.

Keywords: ANN, hard turning, DIN 1.2210, surface roughness, Taguchi method

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26798 Smart Airport: Application of Internet of Things for Confronting Airport Challenges

Authors: Ali Safaeianpour, Nima Shamandi

Abstract:

As air traffic expands, many airports have evolved into transit centers for people, information, and commerce, and technology implementation is an absolute part of airport development. Several challenges are in the way of implementing technology in an airport. Airport 4.0 proposes the "Smart Airport" concept, which focuses on using modern technologies such as Big Data, the Internet of Things (IoT), advanced biometric systems, blockchain, and cloud computing to alter and enhance passengers' journeys. Several common IoT concrete topics as partial keys to smart airports are discussed and introduced, ranging from automated check-in systems to exterior tracking processes, with the goal of enlightening more and more insightful ideas and proposals about smart airport solutions. IoT will dramatically alter people's lives by infusing intelligence, boosting the quality of life, and assembling it smarter. This paper reviews the approaches to transforming an airport into a smart airport and describes several enabling components of IoT and challenges that can hinder the implementation of a smart airport's function, which require to be addressed.

Keywords: airport 4.0, digital airport, smart airport, IoT

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26797 Forecasting of COVID-19 Cases, Hospitalization Admissions, and Death Cases Based on Wastewater Sars-COV-2 Surveillance Using Copula Time Series Model

Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

Abstract:

Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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26796 On the Homology Modeling, Structural Function Relationship and Binding Site Prediction of Human Alsin Protein

Authors: Y. Ruchi, A. Prerna, S. Deepshikha

Abstract:

Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

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26795 Protecting Privacy and Data Security in Online Business

Authors: Bilquis Ferdousi

Abstract:

With the exponential growth of the online business, the threat to consumers’ privacy and data security has become a serious challenge. This literature review-based study focuses on a better understanding of those threats and what legislative measures have been taken to address those challenges. Research shows that people are increasingly involved in online business using different digital devices and platforms, although this practice varies based on age groups. The threat to consumers’ privacy and data security is a serious hindrance in developing trust among consumers in online businesses. There are some legislative measures taken at the federal and state level to protect consumers’ privacy and data security. The study was based on an extensive review of current literature on protecting consumers’ privacy and data security and legislative measures that have been taken.

Keywords: privacy, data security, legislation, online business

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26794 Flowing Online Vehicle GPS Data Clustering Using a New Parallel K-Means Algorithm

Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

Abstract:

This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

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26793 Taguchi-Based Six Sigma Approach to Optimize Surface Roughness for Milling Processes

Authors: Sky Chou, Joseph C. Chen

Abstract:

This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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26792 An Analysis of Privacy and Security for Internet of Things Applications

Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

Abstract:

The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

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26791 Perception of Customers towards Service Quality: A Comparative Analysis of Organized and Unorganised Retail Stores (with Special Reference to Bhopal City)

Authors: Abdul Rashid, Varsha Rokade

Abstract:

Service Quality within retail units is pivotal for satisfying customers and retaining them. This study on customer perception towards Service Quality variables in Retail aims to identify the dimensions and their impact on customers. An analytical study of the different retail service quality variables was done to understand the relationship between them. The study tries exploring the factors that attract the customers towards the organised and unorganised retail stores in the capital city of Madhya Pradesh, India. As organised retailers are seen as offering similar products in the outlets, improving service quality is seen as critical to ensuring competitive advantage over unorganised retailers. Data were collected through a structured questionnaire on a five-point Likert scale from existing walk-in customers of selected organised and unorganised retail stores in Bhopal City of Madhya Pradesh, India. The data was then analysed by factor analysis using (SPSS) Statistical Package for the Social Sciences especially Percentage analysis, ANOVA and Chi-Square. This study tries to find interrelationship between various Retail Service Quality dimensions, which will help the retailers to identify the steps needed to improve the overall quality of service. Thus, the findings of the study prove to be helpful in understanding the service quality variables which should be considered by organised and unorganised retail stores in Capital city of Madhya Pradesh, India.Also, findings of this empirical research reiterate the point of view that dimensions of Service Quality in Retail play an important role in enhancing customer satisfaction – a sector with high growth potential and tremendous opportunities in rapidly growing economies like India’s. With the introduction of FDI in multi-brand retailing, a large number of international retail players are expected to enter the Indian market, this intern will bring more competition in the retail sector. For benchmarking themselves with global standards, the Indian retailers will have to improve their service quality.

Keywords: organized retail, unorganised retail, retail service quality, service quality dimension

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26790 Additive Manufacturing Optimization Via Integrated Taguchi-Gray Relation Methodology for Oil and Gas Component Fabrication

Authors: Meshal Alsaiari

Abstract:

Fused Deposition Modeling is one of the additive manufacturing technologies the industry is shifting to nowadays due to its simplicity and low affordable cost. The fabrication processing parameters predominantly influence FDM part strength and mechanical properties. This presentation will demonstrate the influences of the two manufacturing parameters on the tensile testing evaluation indexes, infill density, and Printing Orientation, which were analyzed to create a piping spacer suitable for oil and gas applications. The tensile specimens are made of two polymers, Acrylonitrile Styrene Acrylate (ASA) and High high-impact polystyrene (HIPS), to characterize the mechanical properties performance for creating the final product. The mechanical testing was carried out per the ASTM D638 testing standard, following Type IV requirements. Taguchi's experiment design using an L-9 orthogonal array was used to evaluate the performance output and identify the optimal manufacturing factors. The experimental results demonstrate that the tensile test is more pronounced with 100% infill for ASA and HIPS samples. However, the printing orientations varied in reactions; ASA is maximum at 0 degrees while HIPS shows almost similar percentages between 45 and 90 degrees. Taguchi-Gray integrated methodology was adopted to minimize the response and recognize optimal fabrication factors combinations.

Keywords: FDM, ASTM D638, tensile testing, acrylonitrile styrene acrylate

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26789 Does Trade and Institutional Quality Play Any Significant Role on Environmental Quality in Sub-Saharan Africa?

Authors: Luqman Afolabi

Abstract:

This paper measures the impacts of trade and institutions on environmental quality in Sub-Saharan Africa (SSA). To examine the direction and the magnitude of the effects, the study employs the pooled mean group (PMG) estimation technique on the panel data obtained from the World Bank’s World Development and Governance Indicators, between 1996 and 2018. The empirical estimates validate the environmental Kuznets curve hypothesis (EKC) for the region, even though there have been inconclusive results on the environment – growth nexus. Similarly, a positive coefficient is obtained on the impact of trade on the environment, while the impact of the institutional indicators produce mixed results. A significant policy implication is that the governments of the SSA countries pursue policies that tend to increase economic growth, so that pollutants may be reduced. Such policies may include the provision of incentives for sustainable growth-driven industries in the region. In addition, the governance infrastructures should be improved in such a way that appropriate penalties are imposed on the pollutants, while advanced technologies that have the potentials to reduce environmental degradation should be encouraged. Finally, it is imperative from these findings that the governments of the region should promote their trade relations and the competitiveness of their local industries in order to keep pace with the global markets.

Keywords: environmental quality, institutional quality sustainable development goals, trade

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26788 Academic Literacy: Semantic-Discursive Resource and the Relationship with the Constitution of Genre for the Development of Writing

Authors: Lucia Rottava

Abstract:

The present study focuses on academic literacy and addresses the impact of semantic-discursive resources on the constitution of genres that are produced in such context. The research considers the development of writing in the academic context in Portuguese. Researches that address academic literacy and the characteristics of the texts produced in this context are rare, mainly with focus on the development of writing, considering three variables: the constitution of the writer, the perception of the reader/interlocutor and the organization of the informational text flow. The research aims to map the semantic-discursive resources of the written register in texts of several genres and produced by students in the first semester of the undergraduate course in letters. The hypothesis raised is that writing in the academic environment is not a recurrent literacy practice for these learners and can be explained by the ontogenetic and phylogenetic nature of language development. Qualitative in nature, the present research has as empirical data texts produced in a half-yearly course of Reading and Textual Production; these data result from the proposition of four different writing proposals, in a total of 600 texts. The corpus is analyzed based on semantic-discursive resources, seeking to contemplate relevant aspects of language (grammar, discourse and social context) that reveal the choices made in the reader/writer interrelationship and the organizational flow of the text. Among the semantic-discursive resources, the analysis includes three resources, including (a) appraisal and negotiation to understand the attitudes negotiated (roles of the participants of the discourse and their relationship with the other); (b) ideation to explain the construction of the experience (activities performed and participants); and (c) periodicity to outline the flow of information in the organization of the text according to the genre it instantiates. The results indicate the organizational difficulties of the flow of the text information. Cartography contributes to the understanding of the way writers use language in an effort to present themselves, evaluate someone else’s work, and communicate with readers.

Keywords: academic writing, portuguese mother tongue, semantic-discursive resources, sistemic funcional linguistic

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26787 Assessing Functional Structure in European Marine Ecosystems Using a Vector-Autoregressive Spatio-Temporal Model

Authors: Katyana A. Vert-Pre, James T. Thorson, Thomas Trancart, Eric Feunteun

Abstract:

In marine ecosystems, spatial and temporal species structure is an important component of ecosystems’ response to anthropological and environmental factors. Although spatial distribution patterns and fish temporal series of abundance have been studied in the past, little research has been allocated to the joint dynamic spatio-temporal functional patterns in marine ecosystems and their use in multispecies management and conservation. Each species represents a function to the ecosystem, and the distribution of these species might not be random. A heterogeneous functional distribution will lead to a more resilient ecosystem to external factors. Applying a Vector-Autoregressive Spatio-Temporal (VAST) model for count data, we estimate the spatio-temporal distribution, shift in time, and abundance of 140 species of the Eastern English Chanel, Bay of Biscay and Mediterranean Sea. From the model outputs, we determined spatio-temporal clusters, calculating p-values for hierarchical clustering via multiscale bootstrap resampling. Then, we designed a functional map given the defined cluster. We found that the species distribution within the ecosystem was not random. Indeed, species evolved in space and time in clusters. Moreover, these clusters remained similar over time deriving from the fact that species of a same cluster often shifted in sync, keeping the overall structure of the ecosystem similar overtime. Knowing the co-existing species within these clusters could help with predicting data-poor species distribution and abundance. Further analysis is being performed to assess the ecological functions represented in each cluster.

Keywords: cluster distribution shift, European marine ecosystems, functional distribution, spatio-temporal model

Procedia PDF Downloads 181
26786 Cognitive Science Based Scheduling in Grid Environment

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

Abstract:

Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

Procedia PDF Downloads 381
26785 Heritage and Tourism in the Era of Big Data: Analysis of Chinese Cultural Tourism in Catalonia

Authors: Xinge Liao, Francesc Xavier Roige Ventura, Dolores Sanchez Aguilera

Abstract:

With the development of the Internet, the study of tourism behavior has rapidly expanded from the traditional physical market to the online market. Data on the Internet is characterized by dynamic changes, and new data appear all the time. In recent years the generation of a large volume of data was characterized, such as forums, blogs, and other sources, which have expanded over time and space, together they constitute large-scale Internet data, known as Big Data. This data of technological origin that derives from the use of devices and the activity of multiple users is becoming a source of great importance for the study of geography and the behavior of tourists. The study will focus on cultural heritage tourist practices in the context of Big Data. The research will focus on exploring the characteristics and behavior of Chinese tourists in relation to the cultural heritage of Catalonia. Geographical information, target image, perceptions in user-generated content will be studied through data analysis from Weibo -the largest social networks of blogs in China. Through the analysis of the behavior of heritage tourists in the Big Data environment, this study will understand the practices (activities, motivations, perceptions) of cultural tourists and then understand the needs and preferences of tourists in order to better guide the sustainable development of tourism in heritage sites.

Keywords: Barcelona, Big Data, Catalonia, cultural heritage, Chinese tourism market, tourists’ behavior

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26784 The Cult of St. Agata as Cultural Mark of Heritage Community Resilience in Abruzzo (Italy, Central Apennine)

Authors: Carmen Soria

Abstract:

The aim of this paper is the study of the cultural and anthropological consequences of the historical natural disasters in Abruzzo (Italy, Central Apennine). These events have left cultural marks in local traditions as well as mythological stories, specific cults, or sanctuary areas in apotropaic function to prevent catastrophic events. Despite the difficult to find archaeological evidence of natural disasters, neverthless, the analisys of micro placenames, directly or indirectly related to such events, represents an integrated and interdisciplinary approach between seismology studies and landscape analysis. Toponymic data, indeed, highlight the strong relation between geomorphological features of areas affected by natural disasters and heritage community resilience, such as, for example, the cult of St. Agatha, widespread in the nearby of healing spring-water and ancient caves as a place of worship, in continuity with pagan rituals.

Keywords: abruzzo, heritage community resilience, seismic planames, St. agata

Procedia PDF Downloads 81