Search results for: generalized random graphs
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3124

Search results for: generalized random graphs

2584 Synthesis and Characterization of Zeolite/Fe3O4 Nanocomposite Material and Investigation of Its Catalytic Reaction

Authors: Mojgan Zendehdel, Safura Molla Mohammad Zamani

Abstract:

In this paper, Fe3O4/NaY zeolite nanocomposite with different molar ratio were successfully synthesized and characterized using FT-IR, XRD, TGA, SEM and VSM techniques. The SEM graphs showed that much of Fe3O4 was successfully coated by the NaY zeolite layer. Also, the results show that the magnetism of the products is stable with added zeolite. The catalytic effect of nanocomposite investigated for esterification reaction under solvent-free conditions. Hence, the effect of the catalyst amount, reaction time, reaction temperature and reusability of catalyst were considered and nanocomposite that created from zeolite and 16.6 percent of Fe3O4 showed the highest yield. The catalyst can be easily separated from reaction with the magnet and it can also be used for several times.

Keywords: zeolite, magnetic, nanocompsite, esterification

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2583 The Staff Performance Efficiency of the Faculty of Management Science, Suan Sunandha Rajabhat University

Authors: Nipawan Tharasak, Ladda Hirunyava

Abstract:

The objective of the research was to study factors affecting working efficiency and the relationship between working environment, satisfaction to human resources management and operation employees’ working efficiency of Faculty of Management Science, Suan Sunandha Rajabhat University. The sample size of the research was based on 33 employees of Faculty of Management Science. The researcher had classified the support employees into 4 divisions by using Stratified Random Sampling. Individual sample was randomized by using Simple Random Sampling. Data was collected through the instrument. The Statistical Package for the Windows was utilized for data processing. Percentage, mean, standard deviation, the t-test, One-way ANOVA, and Pearson product moment correlation coefficient were applied. The result found the support employees’ satisfaction in human resources management of Faculty of Management Science in following areas: remuneration; employee recruitment & selection; manpower planning; performance evaluation; staff training & developing; and spirit & fairness were overall in good level.

Keywords: faculty of management science, operational factors, practice performance, staff working

Procedia PDF Downloads 235
2582 The Effect of Penalizing Wrong Answers in the Computerized Modified Multiple Choice Testing System

Authors: Min Hae Song, Jooyong Park

Abstract:

Even though assessment using information and communication technology will most likely lead the future of educational assessment, there is little research on this topic. Computerized assessment will not only cut costs but also measure students' performance in ways not possible before. In this context, this study introduces a tool which can overcome the problems of multiple choice tests. Multiple-choice tests (MC) are efficient in automatic grading, however structural problems of multiple-choice tests allow students to find the correct answer from options even though they do not know the answer. A computerized modified multiple-choice testing system (CMMT) was developed using the interactivity of computers, that presents questions first, and options later for a short time when the student requests for them. This study was conducted to find out whether penalizing for wrong answers in CMMT could lower random guessing. In this study, we checked whether students knew the answers by having them respond to the short-answer tests before choosing the given options in CMMT or MC format. Ninety-four students were tested with the directions that they will be penalized for wrong answers, but not for no response. There were 4 experimental conditions: two conditions of high or low percentage of penalizing, each in traditional multiple-choice or CMMT format. In the low penalty condition, the penalty rate was the probability of getting the correct answer by random guessing. In the high penalty condition, students were penalized at twice the percentage of the low penalty condition. The results showed that the number of no response was significantly higher for the CMMT format and the number of random guesses was significantly lower for the CMMT format. There were no significant between the two penalty conditions. This result may be due to the fact that the actual score difference between the two conditions was too small. In the discussion, the possibility of applying CMMT format tests while penalizing wrong answers in actual testing settings was addressed.

Keywords: computerized modified multiple choice test format, multiple-choice test format, penalizing, test format

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2581 Differential Approach to Technology Aided English Language Teaching: A Case Study in a Multilingual Setting

Authors: Sweta Sinha

Abstract:

Rapid evolution of technology has changed language pedagogy as well as perspectives on language use, leading to strategic changes in discourse studies. We are now firmly embedded in a time when digital technologies have become an integral part of our daily lives. This has led to generalized approaches to English Language Teaching (ELT) which has raised two-pronged concerns in linguistically diverse settings: a) the diverse linguistic background of the learner might interfere/ intervene with the learning process and b) the differential level of already acquired knowledge of target language might make the classroom practices too easy or too difficult for the target group of learners. ELT needs a more systematic and differential pedagogical approach for greater efficiency and accuracy. The present research analyses the need of identifying learner groups based on different levels of target language proficiency based on a longitudinal study done on 150 undergraduate students. The learners were divided into five groups based on their performance on a twenty point scale in Listening Speaking Reading and Writing (LSRW). The groups were then subjected to varying durations of technology aided language learning sessions and their performance was recorded again on the same scale. Identifying groups and introducing differential teaching and learning strategies led to better results compared to generalized teaching strategies. Language teaching includes different aspects: the organizational, the technological, the sociological, the psychological, the pedagogical and the linguistic. And a facilitator must account for all these aspects in a carefully devised differential approach meeting the challenge of learner diversity. Apart from the justification of the formation of differential groups the paper attempts to devise framework to account for all these aspects in order to make ELT in multilingual setting much more effective.

Keywords: differential groups, English language teaching, language pedagogy, multilingualism, technology aided language learning

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2580 Powers of Class p-w A (s, t) Operators Associated with Generalized Aluthge Transformations

Authors: Mohammed Husein Mohammed Rashid

Abstract:

Let Τ = U |Τ| be a polar decomposition of a bounded linear operator T on a complex Hilbert space with ker U = ker |T|. T is said to be class p-w A(s,t) if (|T*|ᵗ|T|²ˢ|T*|ᵗ )ᵗᵖ/ˢ⁺ᵗ ≥|T*|²ᵗᵖ and |T|²ˢᵖ ≥ (|T|ˢ|T*|²ᵗ|T|ˢ)ˢᵖ/ˢ⁺ᵗ with 0Keywords: class p-w A (s, t), normaloid, isoloid, finite, orthogonality

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2579 Thermal Radiation and Chemical Reaction Effects on MHD Casson Fluid Past a Permeable Stretching Sheet in a Porous Medium

Authors: Y. Sunita Rani, Y. Hari Krishna, M. V. Ramana Murthy, K. Sudhaker Reddy

Abstract:

This article studied effects of radiation and chemical reaction on MHD casson fluoid flow past a Permeable Stretching Sheet in a Porous Medium. Suitable transformations are considered to transform the governing partial differential equations as ordinary ones and then solved by the numerical procedures like Runge- Kutta – Fehlberg shooting technique method. The effects of various governing parameters, on the velocity, temperature and concentration are displayed through graphs and discussed numerically.

Keywords: MHD, Casson fluid, porous medium, permeable stretching sheet

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2578 Location Quotient Analysis: Case Study

Authors: Seyed Habib A. Rahmati, Mohamad Hasan Sadeghpour, Parsa Fallah Sheikhlari

Abstract:

Location quotient (LQ) is a comparison technique that represents emphasized economic structure of single zone versus the standard area to identify specialty for every zone. In another words, the exact calculation of this metric can show the main core competencies and critical capabilities of an area to the decision makers. This research focus on the exact calculation of the LQ for an Iranian Province called Qazvin and within a case study introduces LQ of the capable industries of Qazvin. Finally, through different graphs and tables, it creates an opportunity to compare the recognized capabilities.

Keywords: location quotient, case study, province analysis, core competency

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2577 Infrastructural Investment and Economic Growth in Indian States: A Panel Data Analysis

Authors: Jonardan Koner, Basabi Bhattacharya, Avinash Purandare

Abstract:

The study is focused to find out the impact of infrastructural investment on economic development in Indian states. The study uses panel data analysis to measure the impact of infrastructural investment on Real Gross Domestic Product in Indian States. Panel data analysis incorporates Unit Root Test, Cointegration Teat, Pooled Ordinary Least Squares, Fixed Effect Approach, Random Effect Approach, Hausman Test. The study analyzes panel data (annual in frequency) ranging from 1991 to 2012 and concludes that infrastructural investment has a desirable impact on economic development in Indian. Finally, the study reveals that the infrastructural investment significantly explains the variation of economic indicator.

Keywords: infrastructural investment, real GDP, unit root test, cointegration teat, pooled ordinary least squares, fixed effect approach, random effect approach, Hausman test

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2576 The Impact of Covid-19 on Anxiety Levels in the General Population of the United States: An Exploratory Survey

Authors: Amro Matyori, Fatimah Sherbeny, Askal Ali, Olayiwola Popoola

Abstract:

Objectives: The study evaluated the impact of COVID-19 on anxiety levels in the general population in the United States. Methods: The study used an online questionnaire. It adopted the Generalized Anxiety Disorder Assessment (GAD-7) instrument. It is a self-administered scale with seven items used as a screening tool and severity measure for generalized anxiety disorder. The participants rated the frequency of anxiety symptoms in the last two weeks on a Likert scale, which ranges from 0-3. Then the item points are summed to provide the total score. Results: Thirty-two participants completed the questionnaire. Among them, 24 (83%) females and 5 (17%) males. The age range of 18-24-year-old represented the most respondents. Only one of the participants tested positive for the COVID-19, and 39% of them, one of their family members, friends, or colleagues, tested positive for the coronavirus. Moreover, 10% have lost a family member, a close friend, or a colleague because of COVID-19. Among the respondents, there were ten who scored approximately five points on the GAD-7 scale, which indicates mild anxiety. Furthermore, eight participants scored 10 to 14 points, which put them under the category of moderate anxiety, and one individual who was categorized under severe anxiety scored 15 points. Conclusions: It is identified that most of the respondents scored the points that put them under the mild anxiety category during the COVID-19 pandemic. It is also noticed that severe anxiety was the lowest among the participants, and people who tested positive and/or their family members, close friends, and colleagues were more likely to experience anxiety. Additionally, participants who lost friends or family members were also at high risk of anxiety. It is obvious the COVID-19 outcomes and too much thinking about the pandemic put people under stress which led to anxiety. Therefore, continuous assessment and monitoring of psychological outcomes during pandemics will help to establish early well-informed interventions.

Keywords: anxiety and covid-19, covid-19 and mental health outcomes, influence of covid-19 on anxiety, population and covid-19 impact on mental health

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2575 Acoustic Induced Vibration Response Analysis of Honeycomb Panel

Authors: Po-Yuan Tung, Jen-Chueh Kuo, Chia-Ray Chen, Chien-Hsing Li, Kuo-Liang Pan

Abstract:

The main-body structure of satellite is mainly constructed by lightweight material, it should be able to withstand certain vibration load during launches. Since various kinds of change possibility in the space, it is an extremely important work to study the random vibration response of satellite structure. This paper based on the reciprocity relationship between sound and structure response and it will try to evaluate the dynamic response of satellite main body under random acoustic load excitation. This paper will study the technical process and verify the feasibility of sonic-borne vibration analysis. One simple plate exposed to the uniform acoustic field is utilized to take some important parameters and to validate the acoustics field model of the reverberation chamber. Then import both structure and acoustic field chamber models into the vibro-acoustic coupling analysis software to predict the structure response. During the modeling process, experiment verification is performed to make sure the quality of numerical models. Finally, the surface vibration level can be calculated through the modal participation factor, and the analysis results are presented in PSD spectrum.

Keywords: vibration, acoustic, modal, honeycomb panel

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2574 A Multigrid Approach for Three-Dimensional Inverse Heat Conduction Problems

Authors: Jianhua Zhou, Yuwen Zhang

Abstract:

A two-step multigrid approach is proposed to solve the inverse heat conduction problem in a 3-D object under laser irradiation. In the first step, the location of the laser center is estimated using a coarse and uniform grid system. In the second step, the front-surface temperature is recovered in good accuracy using a multiple grid system in which fine mesh is used at laser spot center to capture the drastic temperature rise in this region but coarse mesh is employed in the peripheral region to reduce the total number of sensors required. The effectiveness of the two-step approach and the multiple grid system are demonstrated by the illustrative inverse solutions. If the measurement data for the temperature and heat flux on the back surface do not contain random error, the proposed multigrid approach can yield more accurate inverse solutions. When the back-surface measurement data contain random noise, accurate inverse solutions cannot be obtained if both temperature and heat flux are measured on the back surface.

Keywords: conduction, inverse problems, conjugated gradient method, laser

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2573 The Effect of Institutions on Economic Growth: An Analysis Based on Bayesian Panel Data Estimation

Authors: Mohammad Anwar, Shah Waliullah

Abstract:

This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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2572 Extension of Positive Linear Operator

Authors: Manal Azzidani

Abstract:

This research consideres the extension of special functions called Positive Linear Operators. the bounded linear operator which defined from normed space to Banach space will extend to the closure of the its domain, And extend identified linear functional on a vector subspace by Hana-Banach theorem which could be generalized to the positive linear operators.

Keywords: extension, positive operator, Riesz space, sublinear function

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2571 From Convexity in Graphs to Polynomial Rings

Authors: Ladznar S. Laja, Rosalio G. Artes, Jr.

Abstract:

This paper introduced a graph polynomial relating convexity concepts. A graph polynomial is a polynomial representing a graph given some parameters. On the other hand, a subgraph H of a graph G is said to be convex in G if for every pair of vertices in H, every shortest path with these end-vertices lies entirely in H. We define the convex subgraph polynomial of a graph G to be the generating function of the sequence of the numbers of convex subgraphs of G of cardinalities ranging from zero to the order of G. This graph polynomial is monic since G itself is convex. The convex index which counts the number of convex subgraphs of G of all orders is just the evaluation of this polynomial at 1. Relationships relating algebraic properties of convex subgraphs polynomial with graph theoretic concepts are established.

Keywords: convex subgraph, convex index, generating function, polynomial ring

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2570 The Impact of Board Characteristics on Firm Performance: Evidence from Banking Industry in India

Authors: Manmeet Kaur, Madhu Vij

Abstract:

The Board of Directors in a firm performs the primary role of an internal control mechanism. This Study seeks to understand the relationship between internal governance and performance of banks in India. The research paper investigates the effect of board structure (proportion of nonexecutive directors, gender diversity, board size and meetings per year) on the firm performance. This paper evaluates the impact of corporate governance mechanisms on bank’s financial performance using panel data for 28 listed banks in National Stock Exchange of India for the period of 2008-2014. Returns on Asset, Return on Equity, Tobin’s Q and Net Interest Margin were used as the financial performance indicators. To estimate the relationship among governance and bank performance initially the Study uses Pooled Ordinary Least Square (OLS) Estimation and Generalized Least Square (GLS) Estimation. Then a well-developed panel Generalized Method of Moments (GMM) Estimator is developed to investigate the dynamic nature of performance and governance relationship. The Study empirically confirms that two-step system GMM approach controls the problem of unobserved heterogeneity and endogeneity as compared to the OLS and GLS approach. The result suggests that banks with small board, boards with female members, and boards that meet more frequently tend to be more efficient and subsequently have a positive impact on performance of banks. The study offers insights to policy makers interested in enhancing the quality of governance of banks in India. Also, the findings suggest that board structure plays a vital role in the improvement of corporate governance mechanism for financial institutions. There is a need to have efficient boards in banks to improve the overall health of the financial institutions and the economic development of the country.

Keywords: board of directors, corporate governance, GMM estimation, Indian banking

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2569 A Machine Learning Approach for Intelligent Transportation System Management on Urban Roads

Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

Abstract:

Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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2568 Application of GeoGebra into Teaching and Learning of Linear and Quadratic Equations amongst Senior Secondary School Students in Fagge Local Government Area of Kano State, Nigeria

Authors: Musa Auwal Mamman, S. G. Isa

Abstract:

This study was carried out in order to investigate the effectiveness of GeoGebra software in teaching and learning of linear and quadratic equations amongst senior secondary school students in Fagge Local Government Area, Kano State–Nigeria. Five research items were raised in objectives, research questions and hypotheses respectively. A random sampling method was used in selecting 398 students from a population of 2098 of SS2 students. The experimental group was taught using the GeoGebra software while the control group was taught using the conventional teaching method. The instrument used for the study was the mathematics performance test (MPT) which was administered at the beginning and at the end of the study. The results of the study revealed that students taught with GeoGebra software (experimental group) performed better than students taught with traditional teaching method. The t- test was used to analyze the data obtained from the study.

Keywords: GeoGebra Software, mathematics performance, random sampling, mathematics teaching

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2567 Geometric Nonlinear Dynamic Analysis of Cylindrical Composite Sandwich Shells Subjected to Underwater Blast Load

Authors: Mustafa Taskin, Ozgur Demir, M. Mert Serveren

Abstract:

The precise study of the impact of underwater explosions on structures is of great importance in the design and engineering calculations of floating structures, especially those used for military purposes, as well as power generation facilities such as offshore platforms that can become a target in case of war. Considering that ship and submarine structures are mostly curved surfaces, it is extremely important and interesting to examine the destructive effects of underwater explosions on curvilinear surfaces. In this study, geometric nonlinear dynamic analysis of cylindrical composite sandwich shells subjected to instantaneous pressure load is performed. The instantaneous pressure load is defined as an underwater explosion and the effects of the liquid medium are taken into account. There are equations in the literature for pressure due to underwater explosions, but these equations have been obtained for flat plates. For this reason, the instantaneous pressure load equations are arranged to be suitable for curvilinear structures before proceeding with the analyses. Fluid-solid interaction is defined by using Taylor's Plate Theory. The lower and upper layers of the cylindrical composite sandwich shell are modeled as composite laminate and the middle layer consists of soft core. The geometric nonlinear dynamic equations of the shell are obtained by Hamilton's principle, taken into account the von Kàrmàn theory of large displacements. Then, time dependent geometric nonlinear equations of motion are solved with the help of generalized differential quadrature method (GDQM) and dynamic behavior of cylindrical composite sandwich shells exposed to underwater explosion is investigated. An algorithm that can work parametrically for the solution has been developed within the scope of the study.

Keywords: cylindrical composite sandwich shells, generalized differential quadrature method, geometric nonlinear dynamic analysis, underwater explosion

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2566 Progressive Type-I Interval Censoring with Binomial Removal-Estimation and Its Properties

Authors: Sonal Budhiraja, Biswabrata Pradhan

Abstract:

This work considers statistical inference based on progressive Type-I interval censored data with random removal. The scheme of progressive Type-I interval censoring with random removal can be described as follows. Suppose n identical items are placed on a test at time T0 = 0 under k pre-fixed inspection times at pre-specified times T1 < T2 < . . . < Tk, where Tk is the scheduled termination time of the experiment. At inspection time Ti, Ri of the remaining surviving units Si, are randomly removed from the experiment. The removal follows a binomial distribution with parameters Si and pi for i = 1, . . . , k, with pk = 1. In this censoring scheme, the number of failures in different inspection intervals and the number of randomly removed items at pre-specified inspection times are observed. Asymptotic properties of the maximum likelihood estimators (MLEs) are established under some regularity conditions. A β-content γ-level tolerance interval (TI) is determined for two parameters Weibull lifetime model using the asymptotic properties of MLEs. The minimum sample size required to achieve the desired β-content γ-level TI is determined. The performance of the MLEs and TI is studied via simulation.

Keywords: asymptotic normality, consistency, regularity conditions, simulation study, tolerance interval

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2565 Random Variation of Treated Volumes in Fractionated 2D Image Based HDR Brachytherapy for Cervical Cancer

Authors: R. Tudugala, B. M. A. I. Balasooriya, W. M. Ediri Arachchi, R. W. M. W. K. Rathnayake, T. D. Premaratna

Abstract:

Brachytherapy involves placing a source of radiation near the cancer site which gives promising prognosis for cervical cancer treatments. The purpose of this study was to evaluate the effect of random variation of treated volumes in between fractions in the 2D image based fractionated high dose rate brachytherapy for cervical cancer at National Cancer Institute Maharagama, Sri Lanka. Dose plans were analyzed for 150 cervical cancer patients with orthogonal radiographs (2D) based brachytherapy. ICRU treated volumes was modeled by translating the applicators with the help of “Multisource HDR plus software”. The difference of treated volumes with respect to the applicator geometry was analyzed by using SPSS 18 software; to derived patient population based estimates of delivered treated volumes relative to ideally treated volumes. Packing was evaluated according to bladder dose, rectum dose and geometry of the dose distribution by three consultant radiation oncologist. The difference of treated volumes depends on types of the applicators, which was used in fractionated brachytherapy. The means of the “Difference of Treated Volume” (DTV) for “Evenly activated tandem (ET)” length” group was ((X_1)) -0.48 cm3 and ((X_2)) 11.85 cm3 for “Unevenly activated tandem length (UET) group. The range of the DTV for ET group was 35.80 cm3 whereas UET group 104.80 cm3. One sample T test was performed to compare the DTV with “Ideal treatment volume difference (0.00cm3)”. It is evident that P value was 0.732 for ET group and for UET it was 0.00 moreover independent two sample T test was performed to compare ET and UET groups and calculated P value was 0.005. Packing was evaluated under three categories 59.38% used “Convenient Packing Technique”, 33.33% used “Fairly Packing Technique” and 7.29% used “Not Convenient Packing” in their fractionated brachytherapy treatments. Random variation of treated volume in ET group is much lower than UET group and there is a significant difference (p<0.05) in between ET and UET groups which affects the dose distribution of the treatment. Furthermore, it can be concluded nearly 92.71% patient’s packing were used acceptable packing technique at NCIM, Sri Lanka.

Keywords: brachytherapy, cervical cancer, high dose rate, tandem, treated volumes

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2564 Inference for Compound Truncated Poisson Lognormal Model with Application to Maximum Precipitation Data

Authors: M. Z. Raqab, Debasis Kundu, M. A. Meraou

Abstract:

In this paper, we have analyzed maximum precipitation data during a particular period of time obtained from different stations in the Global Historical Climatological Network of the USA. One important point to mention is that some stations are shut down on certain days for some reason or the other. Hence, the maximum values are recorded by excluding those readings. It is assumed that the number of stations that operate follows zero-truncated Poisson random variables, and the daily precipitation follows a lognormal random variable. We call this model a compound truncated Poisson lognormal model. The proposed model has three unknown parameters, and it can take a variety of shapes. The maximum likelihood estimators can be obtained quite conveniently using Expectation-Maximization (EM) algorithm. Approximate maximum likelihood estimators are also derived. The associated confidence intervals also can be obtained from the observed Fisher information matrix. Simulation results have been performed to check the performance of the EM algorithm, and it is observed that the EM algorithm works quite well in this case. When we analyze the precipitation data set using the proposed model, it is observed that the proposed model provides a better fit than some of the existing models.

Keywords: compound Poisson lognormal distribution, EM algorithm, maximum likelihood estimation, approximate maximum likelihood estimation, Fisher information, skew distribution

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2563 A Reduced Distributed Sate Space for Modular Petri Nets

Authors: Sawsen Khlifa, Chiheb AMeur Abid, Belhassan Zouari

Abstract:

Modular verification approaches have been widely attempted to cope with the well known state explosion problem. This paper deals with the modular verification of modular Petri nets. We propose a reduced version for the modular state space of a given modular Petri net. The new structure allows the creation of smaller modular graphs. Each one draws the behavior of the corresponding module and outlines some global information. Hence, this version helps to overcome the explosion problem and to use less memory space. In this condensed structure, the verification of some generic properties concerning one module is limited to the exploration of its associated graph.

Keywords: distributed systems, modular verification, petri nets, state space explosition

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2562 Churn Prediction for Savings Bank Customers: A Machine Learning Approach

Authors: Prashant Verma

Abstract:

Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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2561 The Effects of SMS on the Formal Writings of the Students: A Comparative Study among the Students of Different Departments of IUB

Authors: Sumaira Saleem

Abstract:

This study reveals that the use of SMS effect the formal writing of the students. SMS is in vogue sine the last decade but its detrimental effects are effecting not only to the set norms but also deviant forms of expressions have come into the community to which all are not acquainted and it creates a hurdle in effective communication. It also determines the reasons behind the usage of SMS practices in the formal writings like in assignments and examinations. For this study a questionnaire was designed for faculty and students the data was collected from The Islamia University Bahawalpur and the formal work of the students was also collected to check the manifestation of SMS practices in writings. Data was analysed on excel sheet and the tables and graphs are used to explain the ratios and percentages of SMS usage. The results show that the usage of SMS has very strong effect upon the students writing.

Keywords: technology, writing, effects, SMS

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2560 Understanding the Thermal Transformation of Random Access Memory Cards: A Pathway to Their Efficient Recycling

Authors: Khushalini N. Ulman, Samane Maroufi, Veena H. Sahajwalla

Abstract:

Globally, electronic waste (e-waste) continues to grow at an alarming rate. Several technologies have been developed to recover valuable materials from e-waste, however, their efficiency can be increased with a better knowledge of the e-waste components. Random access memory cards (RAMs) are considered as high value scrap for the e-waste recyclers. Despite their high precious metal content, RAMs are still recycled in a conventional manner resulting in huge loss of resources. Our research work highlights the precious metal rich components of a RAM. Inductively coupled plasma (ICP) analysis of RAMs of six different generations have been carried out and the trends in their metal content have been investigated. Over the past decade, the copper content of RAMs has halved and their tin content has increased by 70 %. The stricter environmental laws have facilitated ~96 % drop in the lead content of RAMs. To comprehend the fundamentals of thermal transformation of RAMs, our research provides their detailed kinetic study. This can assist the e-waste recyclers in optimising their metal recovery processes. Thus, understanding the chemical and thermal behaviour of RAMs can open new avenues for efficient e-waste recycling.

Keywords: electronic waste, kinetic study, recycling, thermal transformation

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2559 Robust Electrical Segmentation for Zone Coherency Delimitation Base on Multiplex Graph Community Detection

Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

Abstract:

The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

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2558 The Determinants of Corporate Social Responsibility Disclosure Extent and Quality: The Case of Jordan

Authors: Hani Alkayed, Belal Omar, Eileen Roddy

Abstract:

This study focuses on investigating the determinants of Corporate Social Responsibility Disclosure (CSRD) extent and quality in Jordan. The study examines factors that influence CSR disclosure extent and quality, such as corporate characteristics (size, gearing, firm’s age, and industry type), corporate governance (board size, number of meetings, non-executive directors, female directors in the board, family directors in the board, foreign members, audit committee, type of external auditors, and CEO duality) and ownership structure (government ownership, institutional ownership, and ownership concentration). Legitimacy theory is utilised as the main theory for our theoretical framework. A quantitative approach is adopted for this research and content analysis technique is used to gather CSR disclosure extent and quality from the annual reports. The sample is withdrawn from the annual reports of 118 Jordanian companies over the period of 2010-2015. A CSRD index is constructed, and includes the disclosures of the following categories; environmental, human resources, product and consumers, and community involvement. A 7 point-scale measurement was developed to examine the quality of disclosure, were 0= No Disclosures, 1= General disclosures, (Non-monetary), 2= General disclosures, (Non-monetary) with pictures, charts, and graphs 3= Descriptive/ qualitative disclosures, specific details (Non-monetary), 4= Descriptive/ qualitative disclosures, specific details with pictures, charts, and graphs, 5= Numeric disclosures, full descriptions with supporting numbers, 6= Numeric disclosures, full descriptions with supporting numbers, pictures, and Charts. This study fills the gap in the literature regarding CSRD in Jordan, and the fact that all the previous studies have ignored a clear categorisation as a measurement of quality. The result shows that the extent of CSRD is higher than the quality in Jordan. Regarding the determinants of CSR disclosures, the followings were found to have a significant relationship with both extent and quality of CSRD except non-executives, were the significant relationship was found just with the extent of CSRD: board size, non-executive directors, firm’s age, foreign members on the board, number of boards meetings, the presence of audit committees, big 4, government ownership, firm’s size, industry type.

Keywords: content analysis, corporate governance, corporate social responsibility disclosure, Jordan, quality of disclosure

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2557 Designing Stochastic Non-Invasively Applied DC Pulses to Suppress Tremors in Multiple Sclerosis by Computational Modeling

Authors: Aamna Lawrence, Ashutosh Mishra

Abstract:

Tremors occur in 60% of the patients who have Multiple Sclerosis (MS), the most common demyelinating disease that affects the central and peripheral nervous system, and are the primary cause of disability in young adults. While pharmacological agents provide minimal benefits, surgical interventions like Deep Brain Stimulation and Thalamotomy are riddled with dangerous complications which make non-invasive electrical stimulation an appealing treatment of choice for dealing with tremors. Hence, we hypothesized that if the non-invasive electrical stimulation parameters (mainly frequency) can be computed by mathematically modeling the nerve fibre to take into consideration the minutest details of the axon morphologies, tremors due to demyelination can be optimally alleviated. In this computational study, we have modeled the random demyelination pattern in a nerve fibre that typically manifests in MS using the High-Density Hodgkin-Huxley model with suitable modifications to account for the myelin. The internode of the nerve fibre in our model could have up to ten demyelinated regions each having random length and myelin thickness. The arrival time of action potentials traveling the demyelinated and the normally myelinated nerve fibre between two fixed points in space was noted, and its relationship with the nerve fibre radius ranging from 5µm to 12µm was analyzed. It was interesting to note that there were no overlaps between the arrival time for action potentials traversing the demyelinated and normally myelinated nerve fibres even when a single internode of the nerve fibre was demyelinated. The study gave us an opportunity to design DC pulses whose frequency of application would be a function of the random demyelination pattern to block only the delayed tremor-causing action potentials. The DC pulses could be delivered to the peripheral nervous system non-invasively by an electrode bracelet that would suppress any shakiness beyond it thus paving the way for wearable neuro-rehabilitative technologies.

Keywords: demyelination, Hodgkin-Huxley model, non-invasive electrical stimulation, tremor

Procedia PDF Downloads 128
2556 Generator Subgraphs of the Wheel

Authors: Neil M. Mame

Abstract:

We consider only finite graphs without loops nor multiple edges. Let G be a graph with E(G) = {e1, e2, …., em}. The edge space of G, denoted by ε(G), is a vector space over the field Z2. The elements of ε(G) are all the subsets of E(G). Vector addition is defined as X+Y = X Δ Y, the symmetric difference of sets X and Y, for X, Y ∈ ε(G). Scalar multiplication is defined as 1.X =X and 0.X = Ø for X ∈ ε(G). The set S ⊆ ε(G) is called a generating set if every element ε(G) is a linear combination of the elements of S. For a non-empty set X ∈ ε(G), the smallest subgraph with edge set X is called edge-induced subgraph of G, denoted by G[X]. The set EH(G) = { A ∈ ε(G) : G[A] ≅ H } denotes the uniform set of H with respect to G and εH(G) denotes the subspace of ε(G) generated by EH(G). If εH(G) is generating set, then we call H a generator subgraph of G. This paper gives the characterization for the generator subgraphs of the wheel that contain cycles and gives the necessary conditions for the acyclic generator subgraphs of the wheel.

Keywords: edge space, edge-induced subgraph, generator subgraph, wheel

Procedia PDF Downloads 464
2555 Application of Directed Acyclic Graphs for Threat Identification Based on Ontologies

Authors: Arun Prabhakar

Abstract:

Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

Procedia PDF Downloads 139