Search results for: big data markets

Authors: Chhabi Nigam, S. Ramakrishnan

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

Procedia PDF Downloads 218

Authors: Tshaudi Motsima

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Class attendance is key at all levels of education. At tertiary level many students develop a tendency of not attending all classes without being aware of the repercussions of not attending all classes. It is important for all students to attend all classes as they can receive first-hand information and they can benefit more. The student who attends classes is likely to perform better academically than the student who does not. The aim of this paper is to assess the relationship between class attendance and academic performance of industrial engineering students. The data for this study were collected through the attendance register of students and the other data were accessed from the Integrated Tertiary Software and the Higher Education Data Analyzer Portal. Data analysis was conducted on a sample of 93 students. The results revealed that students with medium predicate scores (OR = 3.8; p = 0.027) and students with low predicate scores (OR = 21.4, p < 0.001) were significantly likely to attend less than 80% of the classes as compared to students with high predicate scores. Students with examination performance of less than 50% were likely to attend less than 80% of classes than students with examination performance of 50% and above, but the differences were not statistically significant (OR = 1.3; p = 0.750).

Keywords: class attendance, examination performance, final outcome, logistic regression

Procedia PDF Downloads 134

Authors: Kristian Bautista, Ruben A. Idoy

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A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

Procedia PDF Downloads 231

Authors: G. B. Hong

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Liquid-Liquid Equilibrium (LLE) data are measured for the ternary mixtures of water + 1-butanol + butyl acetate and quaternary mixtures of water + 1-butanol + butyl acetate + glycerol at atmospheric pressure at 313.15 K. In addition, isothermal Vapor–Liquid–Liquid Equilibrium (VLLE) data are determined experimentally at 333.15 K. The region of heterogeneity is found to increase as the hydrophilic agent (glycerol) is introduced into the aqueous mixtures. The experimental data are correlated with the NRTL model. The predicted results from the solution model with the model parameters determined from the constituent binaries are also compared with the experimental values.

Keywords: LLE, VLLE, hydrophilic agent, NRTL

Procedia PDF Downloads 243

Authors: Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan, Erik van Nimwegen

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Understanding the key players and interactions in the regulatory networks that control gene expression and chromatin state across different cell types and tissues in metazoans remains one of the central challenges in systems biology. Our laboratory has pioneered a number of methods for automatically inferring core gene regulatory networks directly from high-throughput data by modeling gene expression (RNA-seq) and chromatin state (ChIP-seq) measurements in terms of genome-wide computational predictions of regulatory sites for hundreds of transcription factors and micro-RNAs. These methods have now been completely automated in an integrated webserver called ISMARA that allows researchers to analyze their own data by simply uploading RNA-seq or ChIP-seq data sets and provides results in an integrated web interface as well as in downloadable flat form. For any data set, ISMARA infers the key regulators in the system, their activities across the input samples, the genes and pathways they target, and the core interactions between the regulators. We believe that by empowering experimental researchers to apply cutting-edge computational systems biology tools to their data in a completely automated manner, ISMARA can play an important role in developing our understanding of regulatory networks across metazoans.

Keywords: gene expression analysis, high-throughput sequencing analysis, transcription factor activity, transcription regulation

Procedia PDF Downloads 65

Authors: Charles Lee

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The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

Procedia PDF Downloads 84

Authors: Van Huong Mai, Kanokwan Nithiratphat, Adool Booncham

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The Movement of Contemporary Life consisted of two purposes, which were to study the movement and development of the modern life and to create the visual arts, which were paintings expressed via the form of apartment buildings was used from mixed media (digital printing and acrylic painting on canvas) which conveyed the rapid pace of modern life leading to diverse movements in viewer’s feeling. The operation of this creation was collected field data, documentary data, and influence from creative work. The data analysis was analyzed in order to theme, form, technique, and process to satisfy of concept and special character of the pieces.

Keywords: movement, contemporary life, visual art, acrylic painting, digital art, urban space

Procedia PDF Downloads 98

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

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

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

Procedia PDF Downloads 423

Authors: Aaron Zhang, Alimire Kahaer, Gerald Weber, Nalin Arachchilage

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Access control is an essential safeguard for the security of enterprise data, which controls users’ access to information resources and ensures the confidentiality and integrity of information resources [1]. Research shows that the more common types of access control now have shortcomings [2]. In this direction, to improve the existing access control, we have studied the current technologies in the field of data security, deeply investigated the previous data access control policies and their problems, identified the existing deficiencies, and proposed a new extension structure of SPBAC. SPBAC extension proposed in this paper aims to combine Policy-Based Access Control (PBAC) with semantics to provide logically connected, real-time data access functionality by establishing associations between enterprise data through semantics. Our design combines policies with linked data through semantics to create a "Semantic link" so that access control is no longer per-database and determines that users in each role should be granted access based on the instance policy, and improves the SPBAC implementation by constructing policies and defined attributes through the XACML specification, which is designed to extend on the original XACML model. While providing relevant design solutions, this paper hopes to continue to study the feasibility and subsequent implementation of related work at a later stage.

Keywords: access control, semantic policy-based access control, semantic link, access control model, instance policy, XACML

Procedia PDF Downloads 93

Authors: Ali Aydin, Mert Sudagidan, Aysen Coban, Alparslan Kadir Devrim

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Pseudomonas spp. (specifically, P. fluorescens and P. fragi) are considered the principal spoilage microorganisms of refrigerated poultry meats. The higher the level psychrophilic spoilage Pseudomonas spp. on carcasses at the end of processing lead to decrease the shelf life of the refrigerated product. The aim of the study was the identification of psychrophilic Pseudomonas spp. having proteolytic and lipolytic activities from poultry meats by 16S rRNA and rpoB gene sequencing, investigation of protease and lipase related genes and determination of proteolytic activity of Pseudomonas spp. In the of isolation procedure, collected chicken meat samples from local markets and slaughterhouses were homogenized and the lysates were incubated on Standard method agar and Skim Milk agar for selection of proteolytic bacteria and tributyrin agar for selection of lipolytic bacteria at +4 °C for 7 days. After detection of proteolytic and lipolytic colonies, the isolates were firstly analyzed by biochemical tests such as Gram staining, catalase and oxidase tests. DNA gene sequencing analysis and comparison with GenBank revealed that 126 strong enzyme Pseudomonas spp. were identified as predominantly P. fluorescens (n=55), P. fragi (n=42), Pseudomonas spp. (n=24), P. cedrina (n=2), P. poae (n=1), P. koreensis (n=1), and P. gessardi (n=1). Additionally, protease related aprX gene was screened in the strains and it was detected in 69/126 strains, whereas, lipase related lipA gene was found in 9 Pseudomonas strains. Protease activity was determined using commercially available protease assay kit and 5 strains showed high protease activity. The results showed that psychrophilic Pseudomonas strains were present in chicken meat samples and they can produce important levels of proteases and lipases for food spoilage to decrease food quality and safety.

Keywords: Pseudomonas, chicken meat, protease, lipase

Procedia PDF Downloads 387

Authors: Chul Park, Youngseok Kim, Sangsik Choi

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This study developed an electric jig for underwater structure inspection in order to solve the problem of the application of side scan sonar to underwater inspection, and analyzed correlations of empirical data in order to enhance sonar data resolution. For the application of tow-typed sonar to underwater structure inspection, an electric jig was developed. In fact, it was difficult to inspect a cross-section at the time of inspection with tow-typed equipment. With the development of the electric jig for underwater structure inspection, it was possible to shorten an inspection time over 20%, compared to conventional tow-typed side scan sonar, and to inspect a proper cross-section through accurate angle control. The indoor test conducted to enhance sonar data resolution proved that a water depth, the distance from an underwater structure, and a filming angle influenced a resolution and data quality. Based on the data accumulated through field experience, multiple regression analysis was conducted on correlations between three variables. As a result, the relational equation of sonar operation according to a water depth was drawn.

Keywords: underwater structure, SONAR, safety inspection, resolution

Procedia PDF Downloads 265

Authors: S. H. Borghei, E. Teymourian, M. Mobin, G. M. Komaki, S. Sheikh

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Imperialist competitive algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population based algorithm which has achieved a great performance in comparison to other meta-heuristics. This study is about developing enhanced ICA approach to solve the cell formation problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Keywords: cell formation problem, group technology, imperialist competitive algorithm, sequence data

Procedia PDF Downloads 455

Authors: Amarpreet Singh, Kimi Manchanda

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Intended for providing the security in the VANETS (Vehicular Ad hoc Network) scenario, the covert storage channel is implemented through data transmitted between the sender and the receiver. Covert channels are the logical links which are used for the communication purpose and hiding the secure data from the intruders. This paper refers to the Establishment of bit selective mode covert storage channels in VANETS. In this scenario, the data is being transmitted with two modes i.e. the normal mode and the covert mode. During the communication between vehicles in this scenario, the controlling of bits is possible through the optional bits of IPV6 Header Format. This implementation is fulfilled with the help of Network simulator.

Keywords: covert mode, normal mode, VANET, OBU, on-board unit

Procedia PDF Downloads 366

Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

Procedia PDF Downloads 136

Authors: Edwaldo R. B. Monteiro, Patricia D. M. Plentz, Edson R. De Pieri

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Mobile robotics is gaining an increasingly important role in modern society. Several potentially dangerous or laborious tasks for human are assigned to mobile robots, which are increasingly capable. Many of these tasks need to be performed within a specified period, i.e., meet a deadline. Missing the deadline can result in financial and/or material losses. Mechanisms for predicting the missing of deadlines are fundamental because corrective actions can be taken to avoid or minimize the losses resulting from missing the deadline. In this work we propose a simple but reliable deadline missing prediction mechanism for mobile robots through the use of historical data and we use the Pioneer 3-DX robot for experiments and simulations, one of the most popular robots in academia.

Keywords: deadline missing, historical data, mobile robots, prediction mechanism

Procedia PDF Downloads 401

Authors: Melissa Dickinson

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In the context of intense global competitiveness and urban transformations, today’s cities are faced with enormous challenges. There is increasing pressure among cities and regions to respond promptly and efficiently to fierce market progressions, to offer a competitive advantage, higher flexibility, and to be pro-active in creating future markets. Consequently, competition among cities and regions within the dynamics of a worldwide spatial economic system is growing fiercer, amplifying the importance of intangible capital in shaping the competitive and dynamic economic performance of organisations and firms. Accordingly, this study addresses how intangible capital influences urban economic development within an urban environment. Despite substantial research on the economic, and strategic determinants of urban economic development this multidimensional phenomenon remains to be one of the greatest challenges for economic geographers. The research provides a unique contribution, exploring intangible capital through the lenses of entrepreneurial capital and social-network capital. Drawing on business surveys and in-depth interviews with key stakeholders in the case of the three UK Core Cities Birmingham, Bristol and Cardiff. This paper critically considers how entrepreneurial capital and social-network capital is a crucial source of competitiveness and urban economic development. This paper deals with questions concerning the complexity of operationalizing ‘network capital’ in different urban settings and the challenges that reside in characterising its effects. The paper will highlight the role of institutions in facilitating urban economic development. Particular emphasis will be placed on exploring the roles formal and informal institutions have in delivering, supporting and nurturing entrepreneurial capital and social-network capital, to facilitate urban economic development. Discussions will then consider how institutions moderate and contribute to the economic development of urban areas, to provide implications in terms of future policy formulation in the context of large and medium sized cities.

Keywords: urban economic development, network capital, entrepreneurialism, institutions

Procedia PDF Downloads 276

Authors: Guenther Schuh, Stephan Schroeder, Marcel Faulhaber

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Companies are facing an increasing pressure to innovate faster, cheaper and more radical in last years, due to shrinking product lifecycles and higher volatility of markets and customer demands. Especially established companies struggle meeting those demands. Thus, many producing companies are adapting their development processes to address this increasing pressure. One approach taken by many companies is the use of agile, highly iterative development processes to reduce development times and costs as well as to increase the fulfilled customer requirements and the realized level of innovation. At the same time decreasing depths of added value and increasing focus on core competencies as well as a growing product complexity result in a high dependency on suppliers and external development partners during the product development. Thus, a successful introduction of agile development methods into the development of physical products requires also a successful integration of the necessary external partners and suppliers into the new processes and procedures and an adaption of the organizational interfaces to external partners according to the new circumstances and requirements of agile development processes. For an effective and efficient product development, the design of customer-supplier-relationships should be demand-oriented. A significant influence on the required design has the characteristics of the procurement object. Examples therefore are the complexity of technical interfaces between supply object and final product or the importance of the supplied component for the major product functionalities. Thus, this paper presents an approach to derive general requirements on the design of supplier integration according to the characteristics of supply objects. First, therefore the most relevant evaluation criteria and characteristics have been identified based on a thorough literature review. Subsequently the resulting requirements on the design of the supplier integration were derived depending on the different possible values of these criteria.

Keywords: iterative development processes, agile new product development, procurement, supplier integration

Procedia PDF Downloads 172

Authors: Jui-Chen Huang, Shou-Hsiung Cheng

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This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.

Keywords: fall, fuzzy neural network, health belief model, telecare, willingness

Procedia PDF Downloads 201

Authors: Bandari Shanker, Alfunsa Prathiba

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The influence of viscous dissipation on MHD Casson 3-D fluid flow in two perpendicular directions past a linearly stretching sheet in the presence of a chemical reaction is explored in this work. For exceptional circumstances, self-similar solutions are obtained and compared to the given data. The enhancement in the values Ecert number the temperature boundary layer increases. Further, the current findings are observed to be in great accord with the existing data. In both directions, non - dimensional velocities and stress distribution are achieved. The relevant data are graphed and explained quantitatively in relation to changes in the Casson fluid parameter as well as other fluid flow parameters.

Keywords: viscous dissipation, 3-D Casson flow, chemical reaction, Ecert number

Procedia PDF Downloads 193

Authors: Yeganeh Faraji, Ned Faraji

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The aim of the present study is to search for the effects of training on improving fine hand skills in children with autistic spectrum disorder through the case study statistic method. The sample group was selected by the available sampling method and included four participants. The methodology of this research was a single-subject semi-experimental of AB design. The data were gathered by natural observation. In the next stage, the data were recorded on data record sheets and then presented on diagrams. The sample group was evaluated by an assessment which the researcher created based on Lincoln-Oseretsky’ motor development scale in two pre-test and post-test phases. In order to promote fingers’ fine movement, the Montessori method was applied. Collecting and analyzing data which were shown by the data presentation method and diagrams, proved that it had no significant effect on improving fingers’ fine movement. Therefore, based on the current research findings, it is suggested that future researchers can apply various teaching methods and different tests for improving fine hand skills or increasing the period of training.

Keywords: autism spectrum disorder, Montessori method, fine motor skills, Lincoln-Oseretsky assessment

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Authors: Ahmad Shayeq Azizi, Yuji Toda

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In Afghanistan, floods are the most frequent and recurrent events among other natural disasters. On the other hand, lack of monitoring data is a severe problem, which increases the difficulty of making the appropriate flood countermeasures of flood forecasting. This study is carried out to simulate the flood inundation in Harirud River Basin by application of distributed hydrological model, Integrated Flood Analysis System (IFAS) and 2D hydrodynamic model, International River Interface Cooperative (iRIC) based on satellite rainfall combined with historical peak discharge and global accessed data. The results of the simulation can predict the inundation area, depth and velocity, and the hardware countermeasures such as the impact of levee installation can be discussed by using the present method. The methodology proposed in this study is suitable for the area where hydrological and geographical data including river survey data are poorly observed.

Keywords: distributed hydrological model, flood inundation, hydrodynamic model, ungauged basins

Procedia PDF Downloads 166

Authors: Yuan Long, Fabrizio Ceschin, David Harrison

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Environmental sustainability is under the threat of excessive single-use plastic packaging waste, and current waste management fails to address this issue. Therefore, it has led to a reidentification of the alternative, which can curb the packaging waste without reducing social needs. Reusable packaging represents a circular approach to close the loop of consumption in which packaging can stay longer in the system to satisfy social needs. However, the implementation of reusable packaging is fragmented and lacks systematic approaches. The product-service system (PSS) is widely regarded as a sustainable business model innovation for embracing circular consumption. As a result, applying PSS to reusable packaging solutions will be promising to address the packaging waste issue. This paper aims at filling the knowledge gap relating to apply PSS to reusable packaging solutions and provide a strategic design tool that could support packaging professionals to design reusable packaging solutions. The methodology of this paper is case studies and workshops to provide a design tool. The respondents are packaging professionals who are packaging consultants, NGO professionals, and entrepreneurs. 57 cases collected show that 15 archetypal models operate in the market. Subsequently, a polarity diagram is developed to embrace those 15 archetypal models, and a total number of 24 experts were invited for the workshop to evaluate the design tool. This research finally provides a strategic design tool to support packaging professionals to design reusable packaging solutions. The application of the tool is to support the understanding of the reusable packaging solutions, analyzing the markets, identifying new opportunities, and generate new business models. The implication of this research is to provide insights for academics and businesses in terms of tackling single-use packaging waste and build a foundation for further development of the reusable packaging solution tool.

Keywords: environmental sustainability, product-service system, reusable packaging, design tool

Procedia PDF Downloads 148

Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

Procedia PDF Downloads 162

Authors: Matej Komanec, Jan Bohata, Stanislav Zvanovec, Tomas Nemecek, Jan Broucek, Josef Beran

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With the exponential growth of social networks, video streaming and increasing demands on data rates, the number of newly built data centers rises proportionately. The data centers, however, have to adjust to the rapidly increased amount of data that has to be processed. For this purpose, multi-mode (MM) fiber based infrastructures are often employed. It stems from the fact, the connections in data centers are typically realized within a short distance, and the application of MM fibers and components considerably reduces costs. On the other hand, the usage of MM components brings specific requirements for installation service conditions. Moreover, it has to be taken into account that MM fiber components have a higher production tolerance for parameters like core and cladding diameters, eccentricity, etc. Due to the high demands for the reliability of data center components, the determination of properly excited optical field inside the MM fiber core belongs to the key parameters while designing such an MM optical system architecture. Appropriately excited mode field of the MM fiber provides optimal power budget in connections, leads to the decrease of insertion losses (IL) and achieves effective modal bandwidth (EMB). The main parameter, in this case, is the encircled flux (EF), which should be properly defined for variable optical sources and consequent different mode-field distribution. In this paper, we present detailed investigation and measurements of the mode field distribution for short MM links purposed in particular for data centers with the emphasis on reliability and safety. These measurements are essential for large MM network design. The various scenarios, containing different fibers and connectors, were tested in terms of IL and mode-field distribution to reveal potential challenges. Furthermore, we focused on estimation of particular defects and errors, which can realistically occur like eccentricity, connector shifting or dust, were simulated and measured, and their dependence to EF statistics and functionality of data center infrastructure was evaluated. The experimental tests were performed at two wavelengths, commonly used in MM networks, of 850 nm and 1310 nm to verify EF statistics. Finally, we provide recommendations for data center systems and networks, using OM3 and OM4 MM fiber connections.

Keywords: optical fiber, multi-mode, data centers, encircled flux

Procedia PDF Downloads 375

Authors: Eun Hak Lee, Young-Hyun Seo, Hosuk Shin, Seung-Young Kho

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Among traffic crashes, driving under the influence (DUI) of alcohol is the most dangerous behavior in Seoul, South Korea. In 2016 alone 40 deaths occurred on of 2,857 cases of DUI. Since DUI is one of the major factors in increasing the severity of crashes, the intensive management of DUI required to reduce traffic crash deaths and the crash damages. This study aims to investigate the relationship between DUI and traffic safety in order to establish countermeasures for traffic safety improvement. The analysis was conducted on the habitual drivers who drove under the influence. Information of habitual drivers is matched to crash data and fine data. The descriptive statistics on data used in this study, which consists of driver license acquisition, traffic fine, and crash data provided by the Korean National Police Agency, are described. The drivers under the influence are classified by statistically significant criteria, such as driver’s age, license type, driving experience, and crash reasons. With the results of the analysis, we propose some countermeasures to enhance traffic safety.

Keywords: driving under influence, traffic safety, traffic crash, traffic fine

Procedia PDF Downloads 222

Authors: J. Wicks

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Aim: To develop a simple methodology to allow collected heart rate (HR) data from inexpensive wearable devices to be expressed in a suitable format (METs) to quantitate occupational (and recreational) activity. Introduction: Assessment of occupational activity is commonly done by utilizing questionnaires in combination with prescribed MET levels of a vast range of previously measured activities. However for any individual the intensity of performing a specific activity can vary significantly. Ideally objective measurement of individual activity is preferred. Though there are a wide range of HR recording devices there is a distinct lack methodology to allow processing of collected data to quantitate energy expenditure (EE). The HR index equation expresses METs in relation to relative HR i.e. the ratio of activity HR to resting HR. The use of this equation provides a simple utility for objective measurement of EE. Methods: During a typical occupational work period of approximately 8 hours HR data was recorded using a Polar RS 400 wrist monitor. Recorded data was downloaded to a Windows PC and non HR data was stripped from the ASCII file using ‘Notepad’. The HR data was exported to a spread sheet program and sorted by HR range into a histogram format. Three HRs were determined, namely a resting HR (the HR delimiting the lowest 30 minutes of recorded data), a mean HR and a peak HR (the HR delimiting the highest 30 minutes of recorded data). HR indices were calculated (mean index equals mean HR/rest HR and peak index equals peak HR/rest HR) with mean and peak indices being converted to METs using the HR index equation. Conclusion: Inexpensive HR recording devices can be utilized to make reasonable estimates of occupational (or recreational) EE suitable for large scale demographic screening by utilizing the HR index equation. The intrinsic value of the HR index equation is that it is independent of factors that influence absolute HR, namely fitness, smoking and beta-blockade.

Keywords: energy expenditure, heart rate histograms, heart rate index, occupational activity

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Authors: Weisi Guo

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It is well established that there may be running correlations in sequential exam marks due to students sitting in the order of course registration patterns. As such, a random and non-sequential sampling of exam marks is a standard recommended practice. Here, the paper examines a large number of exam data stretching several years across different modules to see the degree to which it is true. Using the real mark distribution as a generative process, it was found that random simulated data had no more sequential randomness than the real data. That is to say, the running correlations that one often observes are statistically identical to chance. Digging deeper, it was found that some high running correlations have students that indeed share a common course history and make similar mistakes. However, at the statistical scale of a module question, the combined effect is statistically similar to the random shuffling of papers. As such, there may not be the need to take random samples for marks, but it still remains good practice to mark papers in a random sequence to reduce the repetitive marking bias and errors.

Keywords: data analysis, empirical study, exams, marking

Procedia PDF Downloads 181

Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

Abstract:

The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

Procedia PDF Downloads 35

Authors: Ágoston Nagy

Abstract:

This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

Procedia PDF Downloads 354

Authors: Sourabh Yaduvanshi, Varsha Namdeo, Namrata Yaduvanshi

Abstract:

This study delves into the design and development intricacies of crafting detailed 2D bar charts via d3.js, recognizing its limitations in generating 3D visuals within the Document Object Model (DOM). The study combines three.js with d3.js, facilitating a smooth evolution from 2D to immersive 3D representations. This fusion epitomizes the synergy between front-end technologies, expanding horizons in data visualization. Beyond technical expertise, it symbolizes a creative convergence, pushing boundaries in visual representation. The abstract illuminates methodologies, unraveling the intricate integration of this fusion and guiding enthusiasts. It narrates a compelling story of transcending 2D constraints, propelling data visualization into captivating three-dimensional realms, and igniting creativity in front-end visualization endeavors.

Keywords: design, development, front-end technologies, visualization

Procedia PDF Downloads 36