Search results for: multiple scales method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22970

Search results for: multiple scales method

22310 Qualitative Data Analysis for Health Care Services

Authors: Taner Ersoz, Filiz Ersoz

Abstract:

This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Keywords: multiple correspondence analysis, multivariate categorical data, health care services, health satisfaction survey

Procedia PDF Downloads 238
22309 Farmers’ Use of Indigenous Knowledge System (IKS) for Selected Arable Crops Production in Ondo State

Authors: A. M. Omoare, E. O. Fakoya

Abstract:

This study sought to determine the use of indigenous knowledge for selected arable crops production in Ondo Sate. A multistage sampling method was used and 112 arable crops farmers were systematically selected. Data were analyzed using both descriptive and inferential statistics. The results showed that majority of the sampled farmers were male (75.90%) About 75% were married with children. Large proportion of them (62.61%) were within the ages of 30-49 years. Most of them have spent about 10 years in farming (58.92%). The highest raw scores of use of indigenous knowledge were found in planting on mound in yam production, use of native medicine and scare-crow method in controlling birds in rice production, timely planting of locally developed resistant varieties in cassava production and soaking of maize seeds in water to determine their viability with raw scores of 313, 310, 305, 303, and 300 respectively, while the lowest raw scores was obtained in use of bell method in controlling birds in rice production with raw scores of 210. The findings established that proverbs (59.8%) and taboos (55.36%) were the most commonly used media in transmitting indigenous knowledge by arable crop farmers. The multiple regression analysis result revealed that age of the farmers and farming experience had a significant relationship with the use of indigenous knowledge of the farmers which gave R2=0.83 for semi-log function form of equation which is the land equation. The policy implication is that indigenous knowledge should provide a basis for designing modern technologies to enhance sustainable agricultural development.

Keywords: Arable Crop Production, extent of use, indigenous knowledge, farming experience

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22308 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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22307 Incorporating Multiple Supervised Learning Algorithms for Effective Intrusion Detection

Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

Abstract:

As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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22306 Multi-Temporal Cloud Detection and Removal in Satellite Imagery for Land Resources Investigation

Authors: Feng Yin

Abstract:

Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

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22305 Measuring Firms’ Patent Management: Conceptualization, Validation, and Interpretation

Authors: Mehari Teshome, Lara Agostini, Anna Nosella

Abstract:

The current knowledge-based economy extends intellectual property rights (IPRs) legal research themes into a more strategic and organizational perspectives. From the diverse types of IPRs, patents are the strongest and well-known form of legal protection that influences commercial success and market value. Indeed, from our pilot survey, we understood that firms are less likely to manage their patents and actively used it as a tool for achieving competitive advantage rather they invest resource and efforts for patent application. To this regard, the literature also confirms that insights into how firms manage their patents from a holistic, strategic perspective, and how the portfolio value of patents can be optimized are scarce. Though patent management is an important business tool and there exist few scales to measure some dimensions of patent management, at the best of our knowledge, no systematic attempt has been made to develop a valid and comprehensive measure of it. Considering this theoretical and practical point of view, the aim of this article is twofold: to develop a framework for patent management encompassing all relevant dimensions with their respective constructs and measurement items, and to validate the measurement using survey data from practitioners. Methodology: We used six-step methodological approach (i.e., specify the domain of construct, item generation, scale purification, internal consistency assessment, scale validation, and replication). Accordingly, we carried out a systematic review of 182 articles on patent management, from ISI Web of Science. For each article, we mapped relevant constructs, their definition, and associated features, as well as items used to measure these constructs, when provided. This theoretical analysis was complemented by interviews with experts in patent management to get feedbacks that are more practical on how patent management is carried out in firms. Afterwards, we carried out a questionnaire survey to purify our scales and statistical validation. Findings: The analysis allowed us to design a framework for patent management, identifying its core dimensions (i.e., generation, portfolio-management, exploitation and enforcement, intelligence) and support dimensions (i.e., strategy and organization). Moreover, we identified the relevant activities for each dimension, as well as the most suitable items to measure them. For example, the core dimension generation includes constructs as: state-of-the-art analysis, freedom-to-operate analysis, patent watching, securing freedom-to-operate, patent potential and patent-geographical-scope. Originality and the Study Contribution: This study represents a first step towards the development of sound scales to measure patent management with an overarching approach, thus laying the basis for developing a recognized landmark within the research area of patent management. Practical Implications: The new scale can be used to assess the level of sophistication of the patent management of a company and compare it with other firms in the industry to evaluate their ability to manage the different activities involved in patent management. In addition, the framework resulting from this analysis can be used as a guide that supports managers to improve patent management in firms.

Keywords: patent, management, scale, development, intellectual property rights (IPRs)

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22304 Simultaneous Determination of p-Phenylenediamine, N-Acetyl-p-phenylenediamine and N,N-Diacetyl-p-phenylenediamine in Human Urine by LC-MS/MS

Authors: Khaled M. Mohamed

Abstract:

Background: P-Phenylenediamine (PPD) is used in the manufacture of hair dyes and skin decoration. In some developing countries, suicidal, homicidal and accidental cases by PPD were recorded. In this work, a sensitive LC-MS/MS method for determination of PPD and its metabolites N-acetyl-p-phenylenediamine (MAPPD) and N,N-diacetyl-p-phenylenediamine (DAPPD) in human urine has been developed and validated. Methods: PPD, MAPPD and DAPPD were extracted from urine by methylene chloride at alkaline pH. Acetanilide was used as internal standard (IS). The analytes and IS were separated on an Eclipse XDB- C18 column (150 X 4.6 mm, 5 µm) using a mobile phase of acetonitrile-1% formic acid in gradient elution. Detection was performed by LC-MS/MS using electrospray positive ionization under multiple reaction-monitoring mode. The transition ions m/z 109 → 92, m/z 151 → 92, m/z 193 → 92, and m/z 136 → 77 were selected for the quantification of PPD, MAPPD, DAPPD, and IS, respectively. Results: Calibration curves were linear in the range 10–2000 ng/mL for all analytes. The mean recoveries for PPD, MAPPD and DAPPD were 57.62, 74.19 and 50.99%, respectively. Intra-assay and inter-assay imprecisions were within 1.58–9.52% and 5.43–9.45% respectively for PPD, MAPPD and DAPPD. Inter-assay accuracies were within -7.43 and 7.36 for all compounds. PPD, MAPPD and DAPPD were stable in urine at –20 degrees for 24 hours. Conclusions: The method was successfully applied to the analysis of PPD, MAPPD and DAPPD in urine samples collected from suicidal cases.

Keywords: p-Phenylenediamine, metabolites, urine, LC-MS/MS, validation

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22303 Support for Privilege Based on Nationality in Switched-At-Birth Scenario

Authors: Anne Lehner, Mostafa Salari Rad, Jeremy Ginges

Abstract:

Many of life’s privileges (and burdens) are thrust on us at birth. Someone born white or male in the United States is also born with a set of advantages over someone born non-white or female. One aspect of privileges conferred by birth is that they are so entrenched in social institutions and social norms that until they are robustly challenged, they can be seen as a moral good. While American society increasingly confronts privileges based on gender and race, other types of privileges, like one's nationality, see less attention. The nationality one is born into can have enormous effects on one’s personal life, work opportunities, and health outcomes. Yet, we predicted that although most Americans would regard it as absurd to think that white people have a right to protect their privileges and 'way of life', they would regard it as obvious that Americans have a right to protect the American way of life and associated privileges. In a preregistered study we presented 300 Americans randomly with one out of three 'privilege scales' in order to assess their agreement with certain statements. The domains for the privilege scales were nationality, race, and gender. Next, all participants completed the switched-at-birth task assessing ones tendency to essentialize nationality. We found that Americans are more approving of privilege based on nationality than of privilege based on gender and race. In addition, we found an interaction of condition with ideology, showing that conservatives are in general more approving of the privilege of any kind than liberals are, and they especially approve of privilege based on nationality. For the switched-at-birth task, we found that both, liberals as well as conservatives are equally willing to grant the child 100% American nationality. Whether or not one chose 100% is unrelated to the expressed approval of privilege based on nationality. One might hesitate to fully grant the child 100% American nationality in the task, yet disapprove of privilege based on nationality. This shows that as much as we see beholders of privilege being oblivious to their statuses within other social categories, like gender or race, we seem to detect the same blindness for the privilege based on nationality. Liberals showing relatively fewer support for privilege based on nationality compared to conservatives still refused to acknowledge the child as having become 100% American and thereby denying the privileges it potentially bestows upon them.

Keywords: thought experiment, anti-immigrant attitudes, privilege of nationality, immigration, moral circles, psychology

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22302 Identification and Quantification of Phenolic Compounds In Cassia tora Collected from Three Different Locations Using Ultra High Performance Liquid Chromatography – Electro Spray Ionization – Mass Spectrometry (UHPLC-ESI-MS-MS)

Authors: Shipra Shukla, Gaurav Chaudhary, S. K. Tewari, Mahesh Pal, D. K. Upreti

Abstract:

Cassia tora L. is widely distributed in tropical Asian countries, commonly known as sickle pod. Various parts of the plant are reported for their medicinal value due to presence of anthraquinones, phenolic compounds, emodin, β-sitosterol, and chrysophanol. Therefore a sensitive analytical procedure using UHPLC-ESI-MS/MS was developed and validated for simultaneous quantification of five phenolic compounds in leaf, stem and root extracts of Cassia tora. Rapid chromatographic separation of compounds was achieved on Acquity UHPLC BEH C18 column (50 mm×2.1 mm id, 1.7µm) column in 2.5 min. Quantification was carried out using negative electrospray ionization in multiple-reaction monitoring mode. The method was validated as per ICH guidelines and showed good linearity (r2 ≥ 0.9985) over the concentration range of 0.5-200 ng/mL. The intra- and inter-day precisions and accuracy were within RSDs ≤ 1.93% and ≤ 1.90%, respectively. The developed method was applied to investigate variation of five phenolic compounds in the three geographical collections. Results indicated significant variation among analyzed samples collected from different locations in India.

Keywords: Cassia tora, phenolic compounds, quantification, UHPLC-ESI-MS/MS

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22301 Stating Best Commercialization Method: An Unanswered Question from Scholars and Practitioners

Authors: Saheed A. Gbadegeshin

Abstract:

Commercialization method is a means to make inventions available at the market for final consumption. It is described as an important tool for keeping business enterprises sustainable and improving national economic growth. Thus, there are several scholarly publications on it, either presenting or testing different methods for commercialization. However, young entrepreneurs, technologists and scientists would like to know the best method to commercialize their innovations. Then, this question arises: What is the best commercialization method? To answer the question, a systematic literature review was conducted, and practitioners were interviewed. The literary results revealed that there are many methods but new methods are needed to improve commercialization especially during these times of economic crisis and political uncertainty. Similarly, the empirical results showed there are several methods, but the best method is the one that reduces costs, reduces the risks associated with uncertainty, and improves customer participation and acceptability. Therefore, it was concluded that new commercialization method is essential for today's high technologies and a method was presented.

Keywords: commercialization method, technology, knowledge, intellectual property, innovation, invention

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22300 Structural Analysis of Kamaluddin Behzad's Works Based on Roland Barthes' Theory of Communication, 'Text and Image'

Authors: Mahsa Khani Oushani, Mohammad Kazem Hasanvand

Abstract:

Text and image have always been two important components in Iranian layout. The interactive connection between text and image has shaped the art of book design with multiple patterns. In this research, first the structure and visual elements in the research data were analyzed and then the position of the text element and the image element in relation to each other based on Roland Barthes theory on the three theories of text and image, were studied and analyzed and the results were compared, and interpreted. The purpose of this study is to investigate the pattern of text and image in the works of Kamaluddin Behzad based on three Roland Barthes communication theories, 1. Descriptive communication, 2. Reference communication, 3. Matched communication. The questions of this research are what is the relationship between text and image in Behzad's works? And how is it defined according to Roland Barthes theory? The method of this research has been done with a structuralist approach with a descriptive-analytical method in a library collection method. The information has been collected in the form of documents (library) and is a tool for collecting online databases. Findings show that the dominant element in Behzad's drawings is with the image and has created a reference relationship in the layout of the drawings, but in some cases it achieves a different relationship that despite the preference of the image on the page, the text is dispersed proportionally on the page and plays a more active role, played within the image. The text and the image support each other equally on the page; Roland Barthes equates this connection.

Keywords: text, image, Kamaluddin Behzad, Roland Barthes, communication theory

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22299 On the Solution of Boundary Value Problems Blended with Hybrid Block Methods

Authors: Kizito Ugochukwu Nwajeri

Abstract:

This paper explores the application of hybrid block methods for solving boundary value problems (BVPs), which are prevalent in various fields such as science, engineering, and applied mathematics. Traditionally, numerical approaches such as finite difference and shooting methods, often encounter challenges related to stability and convergence, particularly in the context of complex and nonlinear BVPs. To address these challenges, we propose a hybrid block method that integrates features from both single-step and multi-step techniques. This method allows for the simultaneous computation of multiple solution points while maintaining high accuracy. Specifically, we employ a combination of polynomial interpolation and collocation strategies to derive a system of equations that captures the behavior of the solution across the entire domain. By directly incorporating boundary conditions into the formulation, we enhance the stability and convergence properties of the numerical solution. Furthermore, we introduce an adaptive step-size mechanism to optimize performance based on the local behavior of the solution. This adjustment allows the method to respond effectively to variations in solution behavior, improving both accuracy and computational efficiency. Numerical tests on a variety of boundary value problems demonstrate the effectiveness of the hybrid block methods. These tests showcase significant improvements in accuracy and computational efficiency compared to conventional methods, indicating that our approach is robust and versatile. The results suggest that this hybrid block method is suitable for a wide range of applications in real-world problems, offering a promising alternative to existing numerical techniques.

Keywords: hybrid block methods, boundary value problem, polynomial interpolation, adaptive step-size control, collocation methods

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22298 Critical Comparison of Two Teaching Methods: The Grammar Translation Method and the Communicative Teaching Method

Authors: Aicha Zohbie

Abstract:

The purpose of this paper is to critically compare two teaching methods: the communicative method and the grammar-translation method. The paper presents the importance of language awareness as an approach to teaching and learning language and some challenges that language teachers face. In addition, the paper strives to determine whether the adoption of communicative teaching methods or the grammar teaching method would be more effective to teach a language. A variety of features are considered for comparing the two methods: the purpose of each method, techniques used, teachers’ and students’ roles, the use of L1, the skills that are emphasized, the correction of students’ errors, and the students’ assessments. Finally, the paper includes suggestions and recommendations for implementing an approach that best meets the students’ needs in a classroom.

Keywords: language teaching methods, language awareness, communicative method grammar translation method, advantages and disadvantages

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22297 Main Control Factors of Fluid Loss in Drilling and Completion in Shunbei Oilfield by Unmanned Intervention Algorithm

Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

Abstract:

Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

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22296 Multimedia Data Fusion for Event Detection in Twitter by Using Dempster-Shafer Evidence Theory

Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

Abstract:

Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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22295 Genomics of Aquatic Adaptation

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: comparative genomics, adaptive evolution, bioinformatics, phylogenetics, genome mining

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22294 [Keynote Talk]: New Generations and Employment: An Exploratory Study about Tensions between the Psycho-Social Characteristics of the Generation Z and Expectations and Actions of Organizational Structures Related with Employment (CABA, 2016)

Authors: Esteban Maioli

Abstract:

Generational studies have an important research tradition in social and human sciences. On the one hand, the speed of social change in the context of globalization imposes the need to research the transformations are identified both the subjectivity of the agents involved and its inclusion in the institutional matrix, specifically employment. Generation Z, (generally considered as the population group whose birth occurs after 1995) have unique psycho-social characteristics. Gen Z is characterized by a different set of values, beliefs, attitudes and ambitions that impact in their concrete action in organizational structures. On the other hand, managers often have to deal with generational differences in the workplace. Organizations have members who belong to different generations; they had never before faced the challenge of having such a diverse group of members. The members of each historical generation are characterized by a different set of values, beliefs, attitudes and ambitions that are manifest in their concrete action in organizational structures. Gen Z it’s the only one who can fully be considered "global," while its members were born in the consolidated context of globalization. Some salient features of the Generation Z can be summarized as follows. They’re the first fully born into a digital world. Social networks and technology are integrated into their lives. They are concerned about the challenges of the modern world (poverty, inequality, climate change, among others). They are self-expressive, more liberal and open to change. They often bore easily, with short attention spans. They do not like routine tasks. They want to achieve a good life-work balance, and they are interested in a flexible work environment, as opposed to traditional work schedule. They are critical thinkers, who come with innovative and creative ideas to help. Research design considered methodological triangulation. Data was collected with two techniques: a self-administered survey with multiple choice questions and attitudinal scales applied over a non-probabilistic sample by reasoned decision. According to the multi-method strategy, also it was conducted in-depth interviews. Organizations constantly face new challenges. One of the biggest ones is to learn to manage a multi-generational scope of work. While Gen Z has not yet been fully incorporated (expected to do so in five years or so), many organizations have already begun to implement a series of changes in its recruitment and development. The main obstacle to retaining young talent is the gap between the expectations of iGen applicants and what companies offer. Members of the iGen expect not only a good salary and job stability but also a clear career plan. Generation Z needs to have immediate feedback on their tasks. However, many organizations have yet to improve both motivation and monitoring practices. It is essential for companies to take a review of organizational practices anchored in the culture of the organization.

Keywords: employment, expectations, generation Z, organizational culture, organizations, psycho-social characteristics

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22293 A Model of Foam Density Prediction for Expanded Perlite Composites

Authors: M. Arifuzzaman, H. S. Kim

Abstract:

Multiple sets of variables associated with expanded perlite particle consolidation in foam manufacturing were analyzed to develop a model for predicting perlite foam density. The consolidation of perlite particles based on the flotation method and compaction involves numerous variables leading to the final perlite foam density. The variables include binder content, compaction ratio, perlite particle size, various perlite particle densities and porosities, and various volumes of perlite at different stages of process. The developed model was found to be useful not only for prediction of foam density but also for optimization between compaction ratio and binder content to achieve a desired density. Experimental verification was conducted using a range of foam densities (0.15–0.5 g/cm3) produced with a range of compaction ratios (1.5-3.5), a range of sodium silicate contents (0.05–0.35 g/ml) in dilution, a range of expanded perlite particle sizes (1-4 mm), and various perlite densities (such as skeletal, material, bulk, and envelope densities). A close agreement between predictions and experimental results was found.

Keywords: expanded perlite, flotation method, foam density, model, prediction, sodium silicate

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22292 Numerical Iteration Method to Find New Formulas for Nonlinear Equations

Authors: Kholod Mohammad Abualnaja

Abstract:

A new algorithm is presented to find some new iterative methods for solving nonlinear equations F(x)=0 by using the variational iteration method. The efficiency of the considered method is illustrated by example. The results show that the proposed iteration technique, without linearization or small perturbation, is very effective and convenient.

Keywords: variational iteration method, nonlinear equations, Lagrange multiplier, algorithms

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22291 Optimization of Electric Vehicle (EV) Charging Station Allocation Based on Multiple Data - Taking Nanjing (China) as an Example

Authors: Yue Huang, Yiheng Feng

Abstract:

Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

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22290 Comparison of Finite-Element and IEC Methods for Cable Thermal Analysis under Various Operating Environments

Authors: M. S. Baazzim, M. S. Al-Saud, M. A. El-Kady

Abstract:

In this paper, steady-state ampacity (current carrying capacity) evaluation of underground power cable system by using analytical and numerical methods for different conditions (depth of cable, spacing between phases, soil thermal resistivity, ambient temperature, wind speed), for two system voltage level were used 132 and 380 kV. The analytical method or traditional method that was used is based on the thermal analysis method developed by Neher-McGrath and further enhanced by International Electrotechnical Commission (IEC) and published in standard IEC 60287. The numerical method that was used is finite element method and it was recourse commercial software based on finite element method.

Keywords: cable ampacity, finite element method, underground cable, thermal rating

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22289 Adaptive Swarm Balancing Algorithms for Rare-Event Prediction in Imbalanced Healthcare Data

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

Abstract:

Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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22288 Multistage Adomian Decomposition Method for Solving Linear and Non-Linear Stiff System of Ordinary Differential Equations

Authors: M. S. H. Chowdhury, Ishak Hashim

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In this paper, linear and non-linear stiff systems of ordinary differential equations are solved by the classical Adomian decomposition method (ADM) and the multi-stage Adomian decomposition method (MADM). The MADM is a technique adapted from the standard Adomian decomposition method (ADM) where standard ADM is converted into a hybrid numeric-analytic method called the multistage ADM (MADM). The MADM is tested for several examples. Comparisons with an explicit Runge-Kutta-type method (RK) and the classical ADM demonstrate the limitations of ADM and promising capability of the MADM for solving stiff initial value problems (IVPs).

Keywords: stiff system of ODEs, Runge-Kutta Type Method, Adomian decomposition method, Multistage ADM

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22287 Mobile Collaboration Learning Technique on Students in Developing Nations

Authors: Amah Nnachi Lofty, Oyefeso Olufemi, Ibiam Udu Ama

Abstract:

New and more powerful communications technologies continue to emerge at a rapid pace and their uses in education are widespread and the impact remarkable in the developing societies. This study investigates Mobile Collaboration Learning Technique (MCLT) on learners’ outcome among students in tertiary institutions of developing nations (a case of Nigeria students). It examines the significance of retention achievement scores of students taught using mobile collaboration and conventional method. The sample consisted of 120 students using Stratified random sampling method. Three research questions and hypotheses were formulated, and tested at a 0.05 level of significance. A student achievement test (SAT) was made of 40 items of multiple-choice objective type, developed and validated for data collection by professionals. The SAT was administered to students as pre-test and post-test. The data were analyzed using t-test statistic to test the hypotheses. The result indicated that students taught using MCLT performed significantly better than their counterparts using the conventional method of instruction. Also, there was no significant difference in the post-test performance scores of male and female students taught using MCLT. Based on the findings, the following recommendations was made that: Mobile collaboration system be encouraged in the institutions to boost knowledge sharing among learners, workshop and trainings should be organized to train teachers on the use of this technique and that schools and government should formulate policies and procedures towards responsible use of MCLT.

Keywords: education, communication, learning, mobile collaboration, technology

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22286 Investigation of a Novel Dual Band Microstrip/Waveguide Hybrid Antenna Element

Authors: Raoudane Bouziyan, Kawser Mohammad Tawhid

Abstract:

Microstrip antennas are low in profile, light in weight, conformable in structure and are now developed for many applications. The main difficulty of the microstrip antenna is its narrow bandwidth. Several modern applications like satellite communications, remote sensing, and multi-function radar systems will find it useful if there is dual-band antenna operating from a single aperture. Some applications require covering both transmitting and receiving frequency bands which are spaced apart. Providing multiple antennas to handle multiple frequencies and polarizations becomes especially difficult if the available space is limited as with airborne platforms and submarine periscopes. Dual band operation can be realized from a single feed using slot loaded or stacked microstrip antenna or two separately fed antennas sharing a common aperture. The former design, when used in arrays, has certain limitations like complicated beam forming or diplexing network and difficulty to realize good radiation patterns at both the bands. The second technique provides more flexibility with separate feed system as beams in each frequency band can be controlled independently. Another desirable feature of a dual band antenna is easy adjustability of upper and lower frequency bands. This thesis presents investigation of a new dual-band antenna, which is a hybrid of microstrip and waveguide radiating elements. The low band radiator is a Shorted Annular Ring (SAR) microstrip antenna and the high band radiator is an aperture antenna. The hybrid antenna is realized by forming a waveguide radiator in the shorted region of the SAR microstrip antenna. It is shown that the upper to lower frequency ratio can be controlled by the proper choice of various dimensions and dielectric material. Operation in both linear and circular polarization is possible in either band. Moreover, both broadside and conical beams can be generated in either band from this antenna element. Finite Element Method based software, HFSS and Method of Moments based software, FEKO were employed to perform parametric studies of the proposed dual-band antenna. The antenna was not tested physically. Therefore, in most cases, both HFSS and FEKO were employed to corroborate the simulation results.

Keywords: FEKO, HFSS, dual band, shorted annular ring patch

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22285 Automatic Multi-Label Image Annotation System Guided by Firefly Algorithm and Bayesian Method

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

Abstract:

Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

Procedia PDF Downloads 582
22284 Particle Size Distribution Estimation of a Mixture of Regular and Irregular Sized Particles Using Acoustic Emissions

Authors: Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz-Carcel

Abstract:

This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.

Keywords: acoustic emissions, particle sizing, process monitoring, signal processing

Procedia PDF Downloads 344
22283 Correlation between General Intelligence, Emotional Intelligence and Stress Response after One Month Practice of Moderate Intensity Physical Exercise

Authors: Mohita Singh, Sunil Sachdev, Amrita Singh

Abstract:

Background and Aim: Physical aerobic exercises promote positive changes in one’s mental health, intelligence, and ability to cope with stressful encounters. The present study was designed to explore the correlation between intelligence and stress parameters and to assess the correlation between the same parameters after the practice of one month of moderate-intensity physical exercise. Method: The study was conducted on thirty-five healthy male volunteer students to assess the correlation between stress parameters in subjects with varying level of general intelligence (GI) and emotional intelligence (EI). Correlation studies were again conducted after one month between the same parameters to evaluate the effect of moderate-intensity physical exercise (MIPE). Baseline values were recorded using standard scales. Result: IQ and EQ correlated negatively with both acute and chronic stress parameters and positively with each other. A positive correlation was found between acute and chronic stress. With the practice of one month of moderate-intensity physical exercise, there was significant increment between the parameters under study and hence improved results. Conclusion: MIPE improved correlation between GI, EI, stress parameters, and thus reduced stress and improved intelligence.

Keywords: emotional intelligence, general intelligence, moderate intensity physical exercise, stress response

Procedia PDF Downloads 141
22282 The Level of Job Satisfaction among English as a Foreign Language Instructors

Authors: Hashem A. Alsamadani

Abstract:

Identifying the level of job satisfaction has many positive benefits for both the worker and employer. The purpose of the study was to examine the overall level of job satisfaction among English as a Foreign Language (EFL) instructors. During the past years, multiple methods were utilized to collect data to determine the level of job satisfaction among teachers. This study was conducted using survey research method. A questionnaire was coded and analyzed using the SPSS. The findings revealed that the overall level of job satisfaction among EFL instructors is high. The study recommended improving conditions of instructors working at public universities so as to gain a high level of job satisfaction and improve outcomes of the teaching-learning process.

Keywords: job satisfaction, EFL teachers, Saudi Arabia, instruction

Procedia PDF Downloads 402
22281 Risk of Disrupted Eating Attitudes in Disabled Athletes

Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

Abstract:

Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

Procedia PDF Downloads 326