Search results for: independent cascade model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18028

Search results for: independent cascade model

17818 Using Arellano-Bover/Blundell-Bond Estimator in Dynamic Panel Data Analysis – Case of Finnish Housing Price Dynamics

Authors: Janne Engblom, Elias Oikarinen

Abstract:

A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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17817 Analysis of the Social Problems of the Early Adolescents in Northeast China

Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgianna Duarte

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The social problems of early adolescents in Northeast China were examined with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). In this study, the data consisted of 2532 early adolescents. The relevant variables such as sports activities, hobbies, chores and the number of close friends, as independent variables have been included in this study. The stratified sampling method was used to collect data from 2532 participants. The analysis results indicated that sports activities, hobbies, chores and the number of close friends, as predictors can be used in a predictive model, which significantly predict the social problem T-score.

Keywords: social problems, ASEBA, early adolescents, predictive Model

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17816 Association between Job Satisfaction, Motivation and Five Factors of Organizational Citizenship Behavior

Authors: Khadija Mushtaq, Muhammad Umar

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The research aims to study the association between job satisfaction, motivation and the five factors of organizational citizenship behavior (i.e. Altruism, Conscientiousness, Sportsmanship, Courtesy and Civic virtue) among Public Sector Employees in Pakistan.In this research Structure Equation Modeling with confirmatory factor analysis was used to test the relationship between two independent and five dependent variables. Data was collected through questionnaire survey from 152 Public Servants Working in Gujrat District-Pakistan in different capacities. Stratified Random Sampling Technique was used to conduct this survey. The results of the study indicate that five factors of OCB have positive significant relation with both motivation and job satisfaction except the relationship of Civic Virtue with Motivation.The research findings implicate that factors other than motivation and job satisfaction may also affect OCB. Likewise, all the five factors of OCB may not be present in all populations. Thus, Managers must concentrate on increasing motivation and job satisfaction to increase OCB. Furthermore, the present research gives a direction to future researchers to use more independent variables (e.g. Culture, leadership, workplace environment, various job attitudes, types of motivation, etc.) on different types of populations with larger sample size in order to find the reasons behind insignificant relationship of civic virtue with Motivation in the research in hand and to generalize the tested model.

Keywords: five factors of organizational citizenship behavior (OCB), motivation, job satisfaction, public sector employees in Pakistan

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17815 Study of Age-Dependent Changes of Peripheral Blood Leukocytes Apoptotic Properties

Authors: Anahit Hakobjanyan, Zdenka Navratilova, Gabriela Strakova, Martin Petrek

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Aging has a suppressive influence on human immune cells. Apoptosis may play important role in age-dependent immunosuppression and lymphopenia. Prevention of apoptosis may be promoted by BCL2-dependent and BCL2-independent manner. BCL2 is an antiapoptotic factor that has an antioxidative role by locating the glutathione at mitochondria and repressing oxidative stress. STAT3 may suppress apoptosis in BCL2-independent manner and promote cell survival blocking cytochrome-c release and reducing ROS production. The aim of our study was to estimate the influence of aging on BCL2-dependent and BCL2-independent prevention of apoptosis via measurement of BCL2 and STAT3 mRNAs expressions. The study was done on Armenian population (2 groups: 37 healthy young (mean age±SE; min/max age, male/female: 37.6±1.1; 20/54, 15/22), 28 healthy aged (66.7±1.5; 57/85, 12/16)). mRNA expression in peripheral blood leukocytes (PBL) was determined by RT-PCR using PSMB2 as the reference gene. Statistical analysis was done with Graph-Pad Prism 5; P < 0.05 considered as significant. The expression of BCL2 mRNA was lower in aged group (0.199) compared with young ones (0.643)(p < 0.01). Decrease expression was also recorded for female and male subgroups (p < 0.01). The expression level of STAT3 mRNA was increased (young, 0.228; aged, 0.428) (p < 0.05) during aging (in the whole age group and male/female subgroups). Decreased level of BCL2 mRNA may indicate about the suppression of BCL2-dependent prevention of apoptosis during aging in peripheral blood leukocytes. At the same time increased the level of STAT3 may suggest about activation of BCL2-independent prevention of apoptosis during aging.

Keywords: BCL2, STAT3, aging, apoptosis

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17814 Effect of Education Based-on the Health Belief Model on Preventive Behaviors of Exposure to ‎Secondhand Smoke among Women

Authors: Arezoo Fallahi

Abstract:

Introduction: Exposure to second-hand smoke is an important global health problem and threatens the health of people, especially children and women. The aim of this study was to determine the effect of education based on the Health Belief Model on preventive behaviors of exposure to second-hand smoke in women. Materials and Methods: This experimental study was performed in 2022 in Sanandaj, west of Iran. Seventy-four people were selected by simple random sampling and divided into an intervention group (37 people) and a control group (37 people). Data collection tools included demographic characteristics and a second-hand smoke exposure questionnaire based on the Health Beliefs Model. The training in the intervention group was conducted in three one-hour sessions in the comprehensive health service centers in the form of lectures, pamphlets, and group discussions. Data were analyzed using SPSS software version 21 and statistical tests such as correlation, paired t-test, and independent t-test. Results: The intervention and control groups were homogeneous before education. They were similar in terms of mean scores of the Health Belief Model. However, after an educational intervention, some of the scores increased, including the mean perceived sensitivity score (from 17.62±2.86 to 19.75±1.23), perceived severity score (28.40±4.45 to 31.64±2), perceived benefits score (27.27±4.89 to 31.94±2.17), practice score (32.64±4.68 to 36.91±2.32) perceived barriers from 26.62±5.16 to 31.29±3.34, guide for external action (from 17.70±3.99 to 22/89 ±1.67), guide for internal action from (16.59±2.95 to 1.03±18.75), and self-efficacy (from 19.83 ±3.99 to 23.37±1.43) (P <0.05). Conclusion: The educational intervention designed based on the Health Belief Model in women was effective in performing preventive behaviors against exposure to second-hand smoke.

Keywords: education, women, exposure to secondhand smoke, health belief model

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17813 An Intelligent Prediction Method for Annular Pressure Driven by Mechanism and Data

Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

Abstract:

Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

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17812 A Development of Holonomic Mobile Robot Using Fuzzy Multi-Layered Controller

Authors: Seungwoo Kim, Yeongcheol Cho

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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.

Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.

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17811 Use of Socially Assistive Robots in Early Rehabilitation to Promote Mobility for Infants with Motor Delays

Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

Abstract:

Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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17810 Model Averaging for Poisson Regression

Authors: Zhou Jianhong

Abstract:

Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again.

Keywords: model averaging, poission regression, Kullback-Leibler distance, statistics

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17809 A Model for Academic Coaching for Success and Inclusive Excellence in Science, Technology, Engineering, and Mathematics Education

Authors: Sylvanus N. Wosu

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Research shows that factors, such as low motivation, preparation, resources, emotional and social integration, and fears of risk-taking, are the most common barriers to access, matriculation, and retention into science, technology, engineering, and mathematics (STEM) disciplines for underrepresented (URM) students. These factors have been shown to impact students’ attraction and success in STEM fields. Standardized tests such as the SAT and ACT often used as predictor of success, are not always true predictors of success for African and Hispanic American students. Without an adequate academic support environment, even a high SAT score does not guarantee academic success in science and engineering. This paper proposes a model for Academic Coaching for building success and inclusive excellence in STEM education. Academic coaching is framed as a process of motivating students to be independent learners through relational mentorship, facilitating learning supports inside and outside of the classroom or school environment, and developing problem-solving skills and success attitudes that lead to higher performance in the specific subjects. The model is formulated based on best strategies and practices for enriching Academic Performance Impact skills and motivating students’ interests in STEM. A scaled model for measuring the Academic Performance Impact (API) index and STEM is discussed. The study correlates API with state standardized test and shows that the average impact of those skills can be predicted by the Academic Performance Impact (API) index or Academic Preparedness Index.

Keywords: diversity, equity, graduate education, inclusion, inclusive excellence, model

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17808 Flow Transformation: An Investigation on Theoretical Aspects and Numerical Computation

Authors: Abhisek Sarkar, Abhimanyu Gaur

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In this report we have discussed the theoretical aspects of the flow transformation, occurring through a series of bifurcations. The parameters and their continuous diversion, the intermittent bursts in the transition zone, variation of velocity and pressure with time, effect of roughness in turbulent zone, and changes in friction factor and head loss coefficient as a function of Reynolds number for a transverse flow across a cylinder have been discussed. An analysis of the variation in the wake length with Reynolds number was done in FORTRAN.

Keywords: bifurcation, attractor, intermittence, energy cascade, energy spectra, vortex stretching

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17807 Factors Impacting Technology Integration in EFL Classrooms: A Study of Qatari Independent Schools

Authors: Youmen Chaaban, Maha Ellili-Cherif

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The purpose of this study was to examine the effects of teachers’ individual characteristics and perceptions of environmental factors that impact their technology integration into their EFL (English as a Foreign Language) classrooms. To this end, a national survey examining EFL teachers’ perceptions was conducted at Qatari Independent schools. 263 EFL teachers responded to the survey which investigated several factors known to impact technology integration. These factors included technology availability and support, EFL teachers’ perceptions of importance, obstacles facing technology integration, competency with technology use, and formal technology preparation. The impact of these factors on teachers’ and students’ educational technology use was further measured. The analysis of the data included descriptive statistics and a chi-square analysis test in order to examine the relationship between these factors. The results revealed important cultural factors that impact teachers’ practices and attitudes towards technology in the Qatari context. EFL teachers were found to integrate technology most prominently for instructional delivery and preparation. The use of technology as a learning tool received less emphasis. Teachers further revealed consistent perceptions about obstacles to integration, high levels of confidence in using technology, and consistent beliefs about the importance of using technology as a learning tool. Further analyses of the factors impacting technology integration can assist with Qatar’s technology advancement and development efforts by indicating the areas of strength and areas where additional efforts are needed. The results will lay the foundation for conducting context-specific professional development suitable for the needs of EFL teachers in Qatari Independent Schools.

Keywords: educational technology integration, Qatar, EFL, independent schools, ICT

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17806 Independent Encryption Technique for Mobile Voice Calls

Authors: Nael Hirzalla

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The legality of some countries or agencies’ acts to spy on personal phone calls of the public became a hot topic to many social groups’ talks. It is believed that this act is considered an invasion to someone’s privacy. Such act may be justified if it is singling out specific cases but to spy without limits is very unacceptable. This paper discusses the needs for not only a simple and light weight technique to secure mobile voice calls but also a technique that is independent from any encryption standard or library. It then presents and tests one encrypting algorithm that is based of frequency scrambling technique to show fair and delay-free process that can be used to protect phone calls from such spying acts.

Keywords: frequency scrambling, mobile applications, real-time voice encryption, spying on calls

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17805 Estimation of Missing Values in Aggregate Level Spatial Data

Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

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17804 Assessing Level of Pregnancy Rate and Milk Yield in Indian Murrah Buffaloes

Authors: V. Jamuna, A. K. Chakravarty, C. S. Patil, Vijay Kumar, M. A. Mir, Rakesh Kumar

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Intense selection of buffaloes for milk production at organized herds of the country without giving due attention to fertility traits viz. pregnancy rate has lead to deterioration in their performances. Aim of study is to develop an optimum model for predicting pregnancy rate and to assess the level of pregnancy rate with respect to milk production Murrah buffaloes. Data pertaining to 1224 lactation records of Murrah buffaloes spread over a period 21 years were analyzed and it was observed that pregnancy rate depicted negative phenotypic association with lactation milk yield (-0.08 ± 0.04). For developing optimum model for pregnancy rate in Murrah buffaloes seven simple and multiple regression models were developed. Among the seven models, model II having only Service period as an independent reproduction variable, was found to be the best prediction model, based on the four statistical criterions (high coefficient of determination (R 2), low mean sum of squares due to error (MSSe), conceptual predictive (CP) value, and Bayesian information criterion (BIC). For standardizing the level of fertility with milk production, pregnancy rate was classified into seven classes with the increment of 10% in all parities, life time and their corresponding average pregnancy rate in relation to the average lactation milk yield (MY).It was observed that to achieve around 2000 kg MY which can be considered optimum for Indian Murrah buffaloes, level of pregnancy rate should be in between 30-50%.

Keywords: life time, pregnancy rate, production, service period, standardization

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17803 Independence of the Judiciary in South Africa: An Assessment After Twenty Years of Democracy

Authors: Serges Djoyou Kamga, Gerard Emmanuel Kamdem Kamga

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Any serious constitutionalism entails a system of government characterised by the separation of powers between the executive, the legislature, and the judiciary. The latter is generally in charge of upholding the rule of law and the respect for human rights which are vital for the functioning of any democracy. Therefore, for the judiciary to play its role as a watchdog, it should be independent from other branches of government. The aim of this paper is to examine the independence of the judiciary in South Africa after 20 of democracy. Defining judicial independence as the courts’ ability ‘to decide cases on the basis of established law and the merits of the case, without interference from other political or governmental agents’, the paper examines the extent to which the South African judiciary is independent after twenty years of democracy. As part of assessing the independence of the judiciary, the paper begins by looking at the situation during apartheid, then proceeds with an examination of the post-apartheid legal order. It also examines the institutional independence of the judiciary by looking into its day to day activities which revolve around its self-governance, or administrative and financial independence. In addition, the paper assesses the judges’ individual independence by examining whether judicial appointment, security of tenure, judges’ remuneration and disciplinary actions and the removal of judges from office do not contain loopholes that can hinder judicial independence. Ultimately, the chapter argues that although the South African model of judicial independence is yet to be perfect, it is a good practice that can be emulated by other African countries.

Keywords: judical independence, South Africa, democracy, separation of powers

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17802 Implementation and Validation of a Damage-Friction Constitutive Model for Concrete

Authors: L. Madouni, M. Ould Ouali, N. E. Hannachi

Abstract:

Two constitutive models for concrete are available in ABAQUS/Explicit, the Brittle Cracking Model and the Concrete Damaged Plasticity Model, and their suitability and limitations are well known. The aim of the present paper is to implement a damage-friction concrete constitutive model and to evaluate the performance of this model by comparing the predicted response with experimental data. The constitutive formulation of this material model is reviewed. In order to have consistent results, the parameter identification and calibration for the model have been performed. Several numerical simulations are presented in this paper, whose results allow for validating the capability of the proposed model for reproducing the typical nonlinear performances of concrete structures under different monotonic and cyclic load conditions. The results of the evaluation will be used for recommendations concerning the application and further improvements of the investigated model.

Keywords: Abaqus, concrete, constitutive model, numerical simulation

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17801 Investigating the Behavior of Water Shortage Indices for Performance Evaluation of a Water Resources System

Authors: Frederick N. F. Chou, Nguyen Thi Thuy Linh

Abstract:

The impact of water shortages has been increasingly severe as a consequence of population growth, urbanization, economic development, and climate change. The need for improvements in reliable water supply systems is urgent with the increasing living standards of regions. In this study, a suitable shortage index capable of multi-aspect description - frequency, magnitude, and duration - is adopted to more accurately describe the characteristics of a shortage situation. The values of the index were determined to cope with the increasing need for reliability. There are four reservoirs in series located on the Be River of the Dong Nai River Basin in Southern Vietnam. The primary purpose of the three upstream reservoirs is hydropower generation while the primary purpose of the fourth is water supply. A compromise between hydropower generation and water supply can be negotiated for these four reservoirs to reduce the severity of water shortages. A generalized water allocation model was applied to simulate the water supply, and hydropower generation of various management alternatives and the system’s reliability was evaluated using the adopted multiple shortage indices. Modifying management policies of water resources using data-based indexes can improve the reliability of water supply.

Keywords: cascade reservoirs, hydropower, shortage index, water supply

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17800 Widely Diversified Macroeconomies in the Super-Long Run Casts a Doubt on Path-Independent Equilibrium Growth Model

Authors: Ichiro Takahashi

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One of the major assumptions of mainstream macroeconomics is the path independence of capital stock. This paper challenges this assumption by employing an agent-based approach. The simulation results showed the existence of multiple "quasi-steady state" equilibria of the capital stock, which may cast serious doubt on the validity of the assumption. The finding would give a better understanding of many phenomena that involve hysteresis, including the causes of poverty. The "market-clearing view" has been widely shared among major schools of macroeconomics. They understand that the capital stock, the labor force, and technology, determine the "full-employment" equilibrium growth path and demand/supply shocks can move the economy away from the path only temporarily: the dichotomy between the short-run business cycles and the long-run equilibrium path. The view then implicitly assumes the long-run capital stock to be independent of how the economy has evolved. In contrast, "Old Keynesians" have recognized fluctuations in output as arising largely from fluctuations in real aggregate demand. It will then be an interesting question to ask if an agent-based macroeconomic model, which is known to have path dependence, can generate multiple full-employment equilibrium trajectories of the capital stock in the super-long run. If the answer is yes, the equilibrium level of capital stock, an important supply-side factor, would no longer be independent of the business cycle phenomenon. This paper attempts to answer the above question by using the agent-based macroeconomic model developed by Takahashi and Okada (2010). The model would serve this purpose well because it has neither population growth nor technology progress. The objective of the paper is twofold: (1) to explore the causes of long-term business cycle, and (2) to examine the super-long behaviors of the capital stock of full-employment economies. (1) The simulated behaviors of the key macroeconomic variables such as output, employment, real wages showed widely diversified macro-economies. They were often remarkably stable but exhibited both short-term and long-term fluctuations. The long-term fluctuations occur through the following two adjustments: the quantity and relative cost adjustments of capital stock. The first one is obvious and assumed by many business cycle theorists. The reduced aggregate demand lowers prices, which raises real wages, thereby decreasing the relative cost of capital stock with respect to labor. (2) The long-term business cycles/fluctuations were synthesized with the hysteresis of real wages, interest rates, and investments. In particular, a sequence of the simulation runs with a super-long simulation period generated a wide range of perfectly stable paths, many of which achieved full employment: all the macroeconomic trajectories, including capital stock, output, and employment, were perfectly horizontal over 100,000 periods. Moreover, the full-employment level of capital stock was influenced by the history of unemployment, which was itself path-dependent. Thus, an experience of severe unemployment in the past kept the real wage low, which discouraged a relatively costly investment in capital stock. Meanwhile, a history of good performance sometimes brought about a low capital stock due to a high-interest rate that was consistent with a strong investment.

Keywords: agent-based macroeconomic model, business cycle, hysteresis, stability

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17799 Multicollinearity and MRA in Sustainability: Application of the Raise Regression

Authors: Claudia García-García, Catalina B. García-García, Román Salmerón-Gómez

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Much economic-environmental research includes the analysis of possible interactions by using Moderated Regression Analysis (MRA), which is a specific application of multiple linear regression analysis. This methodology allows analyzing how the effect of one of the independent variables is moderated by a second independent variable by adding a cross-product term between them as an additional explanatory variable. Due to the very specification of the methodology, the moderated factor is often highly correlated with the constitutive terms. Thus, great multicollinearity problems arise. The appearance of strong multicollinearity in a model has important consequences. Inflated variances of the estimators may appear, there is a tendency to consider non-significant regressors that they probably are together with a very high coefficient of determination, incorrect signs of our coefficients may appear and also the high sensibility of the results to small changes in the dataset. Finally, the high relationship among explanatory variables implies difficulties in fixing the individual effects of each one on the model under study. These consequences shifted to the moderated analysis may imply that it is not worth including an interaction term that may be distorting the model. Thus, it is important to manage the problem with some methodology that allows for obtaining reliable results. After a review of those works that applied the MRA among the ten top journals of the field, it is clear that multicollinearity is mostly disregarded. Less than 15% of the reviewed works take into account potential multicollinearity problems. To overcome the issue, this work studies the possible application of recent methodologies to MRA. Particularly, the raised regression is analyzed. This methodology mitigates collinearity from a geometrical point of view: the collinearity problem arises because the variables under study are very close geometrically, so by separating both variables, the problem can be mitigated. Raise regression maintains the available information and modifies the problematic variables instead of deleting variables, for example. Furthermore, the global characteristics of the initial model are also maintained (sum of squared residuals, estimated variance, coefficient of determination, global significance test and prediction). The proposal is implemented to data from countries of the European Union during the last year available regarding greenhouse gas emissions, per capita GDP and a dummy variable that represents the topography of the country. The use of a dummy variable as the moderator is a special variant of MRA, sometimes called “subgroup regression analysis.” The main conclusion of this work is that applying new techniques to the field can improve in a substantial way the results of the analysis. Particularly, the use of raised regression mitigates great multicollinearity problems, so the researcher is able to rely on the interaction term when interpreting the results of a particular study.

Keywords: multicollinearity, MRA, interaction, raise

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17798 Innovative Approaches to Formal Education: Effect of Online Cooperative Learning Embedded Blended Learning on Student's Academic Achievement and Attitude

Authors: Mohsin Javed

Abstract:

School Education department is usually criticized for utilizing quite low or fewer academic days due to many reasons like extreme weather conditions, sudden holidays, summer vocations, pandemics and, terrorism etc. The purpose of the experimental study was to determine the efficacy of online cooperative learning (OCL) integrated in the rotation model of blended learning. The effects on academic achievement of students and students' attitude about OCL embedded learning were assessed. By using a posttest only control group design, sixty-two first-year students were randomly allocated to either the experimental (30) or control (32) group. The control group received face to face classes for six sessions per week, while the experimental group had three OCL and three formal sessions per week under rotation model. Students' perceptions of OCL were evaluated using a survey questionnaire. Data was analyzed by independent sample t test and one sample t test. According to findings, the intervention greatly improved the state of the dependent variables. The results demonstrate that OCL can be successfully implemented in formal education using a blended learning rotation approach. Higher secondary institutions are advised to use this model in situations like Covid 19, smog, unexpected holidays, instructor absence from class due to increased responsibilities, and summer vacations.

Keywords: blended learning, online cooperative learning, rotation model of blended learning, supplementing

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17797 The Impact of Kids Science Labs Intervention Program on Independent Thinking and Academic Achievement in Young Children

Authors: Aliya Kamilyevna Salahova

Abstract:

This study examines the effectiveness of the Kids Science Labs intervention program, based on STEM, in fostering independent thinking among preschool and elementary school children and its influence on their academic achievement. Through a comprehensive methodology involving interviews, surveys, observations, case studies, and statistical tests, data were collected from various sources to accurately analyze the program's effects. The findings indicate a significant positive impact on children's independent thinking abilities, leading to improved academic performance in mathematics and science, enhanced learning motivation, and a propensity to critically evaluate problem-solving approaches. This research contributes to the theoretical understanding of how STEM activities can foster independent thinking and academic success in young children, providing valuable insights for the development of educational programs. Introduction: The goal of this study is to investigate the influence of the Kids Science Labs intervention program, grounded in STEM, on the development of independent thinking skills among preschool and elementary school children. By addressing this objective, we aim to explore the program's potential to enhance academic performance in mathematics and science. The study's findings have theoretical significance as they shed light on the ways in which STEM activities can foster independent thinking in young children, thus enabling educators to design effective learning programs that promote academic success. Methodology: This study employs a robust methodology that includes interviews, surveys, observations, case studies, and statistical tests. These methods were carefully selected to collect comprehensive data from multiple sources, such as documents and records, ensuring a thorough analysis of the program's effects. The use of diverse data collection and analysis procedures facilitated an in-depth exploration of the research questions and yielded reliable results. Results: The results indicate that children participating in the Kids Science Labs program experienced a sustained positive impact on their independent thinking abilities. Moreover, these children demonstrated improved academic performance in mathematics and science, displaying higher learning motivation and the capacity to critically evaluate problem-solving methods and seek optimal solutions. Theoretical Importance: This study contributes significantly to the existing theoretical knowledge by elucidating how STEM activities can foster independent thinking and enhance academic success in preschool and elementary school children. The findings have practical implications for educators, empowering them to develop learning programs that stimulate independent thinking, leading to improved academic performance in young children. Discussion: The findings of this research affirm that the Kids Science Labs intervention program is highly effective in fostering independent thinking among preschool and elementary school children. The program's positive impact extends to improved academic performance in mathematics and science, highlighting its potential to enhance learning outcomes. Educators can leverage these findings to develop educational programs that promote independent thinking and elevate academic achievement in young children. Conclusion: In conclusion, the Kids Science Labs intervention program has been found to be highly effective in fostering independent thinking among preschool and elementary school children. Furthermore, participation in the program correlates with improved academic performance in mathematics and science. The study's outcomes underscore the importance of developing educational initiatives that stimulate independent thinking in young children, thereby enhancing their academic success.

Keywords: STEM in preschool, STEM in elementary school, kids science labs, independent thinking, STEM activities in early childhood education

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17796 Literature Review of Empirical Studies on the Psychological Processes of End-of-Life Cancer Patients

Authors: Kimiyo Shimomai, Mihoko Harada

Abstract:

This study is a literature review of the psychological reactions that occur in end-of-life cancer patients who are nearing death. It searched electronic databases and selected literature related to psychological studies of end-of-life patients. There was no limit on the search period, and the search was conducted until the second week of December 2021. The keywords were specified as “death and dying”, “terminal illness”, “end-of-life”, “palliative care”, “psycho-oncology” and “research”. These literatures referred to Holly (2017): Comprehensive Systematic Review for Advanced Practice Nursing, P268 Figure 10.3 to ensure quality. These literatures were selected with a dissertation score of 4 or 5. The review was conducted in two stages with reference to the procedure of George (2002). First, these references were searched for keywords in the database, and then relevant references were selected from the psychology and nursing studies of end-of-life patients. The number of literatures analyzed was 76 for overseas and 17 for domestic. As for the independent variables, "physical variable" was the most common in 36 literatures (66.7%), followed by "psychological variable" in 35 literatures (64.8%), "spiritual variable" in 21 literatures (38%), and "social variable" in 17 literatures. (31.5%), "Variables related to medical care / treatment" were 16 literatures (29.6%). To summarize the relationship between these independent variables and the dependent variable, when the dependent variable is "psychological variable", the independent variables are "psychological variable", "social variable", and "physical variable". Among the independent variables, the physical variables were the most common. The psychological responses that occur in end-stage cancer patients who are nearing death are mutually influenced by psychological, social, and physical variables. Therefore, it supported the "total pain" advocated by Cicely Saunders.

Keywords: cancer patient, end-of-life, literature review, psychological process

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17795 Internet Purchases in European Union Countries: Multiple Linear Regression Approach

Authors: Ksenija Dumičić, Anita Čeh Časni, Irena Palić

Abstract:

This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analysed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analysed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis.

Keywords: European union, Internet purchases, multiple linear regression model, outlier

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17794 Numerical Model to Study Calcium and Inositol 1,4,5-Trisphosphate Dynamics in a Myocyte Cell

Authors: Nisha Singh, Neeru Adlakha

Abstract:

Calcium signalling is one of the most important intracellular signalling mechanisms. A lot of approaches and investigators have been made in the study of calcium signalling in various cells to understand its mechanisms over recent decades. However, most of existing investigators have mainly focussed on the study of calcium signalling in various cells without paying attention to the dependence of calcium signalling on other chemical ions like inositol-1; 4; 5 triphosphate ions, etc. Some models for the independent study of calcium signalling and inositol-1; 4; 5 triphosphate signalling in various cells are present but very little attention has been paid by the researchers to study the interdependence of these two signalling processes in a cell. In this paper, we propose a coupled mathematical model to understand the interdependence of inositol-1; 4; 5 triphosphate dynamics and calcium dynamics in a myocyte cell. Such studies will provide the deeper understanding of various factors involved in calcium signalling in myocytes, which may be of great use to biomedical scientists for various medical applications.

Keywords: calcium signalling, coupling, finite difference method, inositol 1, 4, 5-triphosphate

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17793 A Unification and Relativistic Correction for Boltzmann’s Law

Authors: Lloyd G. Allred

Abstract:

The distribution of velocities of particles in plasma is a well understood discipline of plasma physics. Boltzmann’s law and the Maxwell-Boltzmann distribution describe the distribution of velocity of a particle in plasma as a function of mass and temperature. Particles with the same mass tend to have the same velocity. By expressing the same law in terms of energy alone, the author obtains a distribution independent of mass. In summary, for particles in plasma, the energies tend to equalize, independent of the masses of the individual particles. For high-energy plasma, the original law predicts velocities greater than the speed of light. If one uses Einstein’s formula for energy (E=mc2), then a relativistic correction is not required.

Keywords: cosmology, EMP, plasma physics, relativity

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17792 Board Composition and Performance of Listed Deposit Money Banks in Nigeria

Authors: Mary David, Denis Basila

Abstract:

This study assessed the Impact of Board Composition on the Performance of Listed Deposit Money Banks in Nigeria. A sample of ten (10) deposit money banks formed the sample of this study. Board size, gender diversity, and board independence were used as the independent variables, and firm size as a control variable, whiles the bank performance was proxy with Tobin’s Q (TQ) as the dependent variable. Secondary data was collected from secondary source through the annual report and account of the banks and was analyzed through the support of STATA 14 versions. Descriptive statistics, correlation matrix, and OLS multiple regression model were adopted for the study. Breusch and pagan lagrangian multiplier test for random effect was conducted. The findings of the study reveal that board size has positive and significant impact on Tobin’s Q, gender diversity has positive and significant impact on Tobin’s Q, while board independent had a negative and nonsignificant influence on the Tobin’s Q, Similarly, firm size was found to have a negative and nonsignificant impact on Tobin’s Q of the study banks. This study recommended that policy makers, stakeholders, and corporate managers of deposit money banks of Nigeria and related industries are encouraged to adopt board sizes and gender diversity that impact positively on bank performance.

Keywords: board composition, performance, deposit money banks, nigeria

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17791 Delay-Independent Closed-Loop Stabilization of Neutral System with Infinite Delays

Authors: Iyai Davies, Olivier L. C. Haas

Abstract:

In this paper, the problem of stability and stabilization for neutral delay-differential systems with infinite delay is investigated. Using Lyapunov method, new delay-independent sufficient condition for the stability of neutral systems with infinite delay is obtained in terms of linear matrix inequality (LMI). Memory-less state feedback controllers are then designed for the stabilization of the system using the feasible solution of the resulting LMI, which are easily solved using any optimization algorithms. Numerical examples are given to illustrate the results of the proposed methods.

Keywords: infinite delays, Lyapunov method, linear matrix inequality, neutral systems, stability

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17790 Factors Influencing the Use of Mobile Phone by Smallholder Farmers in Vegetable Marketing in Fogera District

Authors: Molla Tadesse Lakew

Abstract:

This study was intended to identify the factors influencing the use of mobile phones in vegetable marketing in Fogera district. The use of mobile phones in vegetable marketing and factors influencing mobile phone use were specific objectives of the study. Three kebeles from the Fogera district were selected purposively based on their vegetable production potential. A simple random sampling technique (lottery method) was used to select 153 vegetable producer farmers. Interview schedule and key informants interviews were used to collect primary data. For analyzing the data, descriptive statistics like frequency and percentage, two independent t-tests, and chi-square were used. Furthermore, econometric analysis (binary logistic model) was used to assess the factors influencing mobile phone use for vegetable market information. Contingency coefficient and variance inflation factor were used to check multicollinearity problems between the independent variables. Of 153 respondents, 82 (61.72%) were mobile phone users, while 71 (38.28 %) were mobile phone nonusers. Moreover, the main use of mobile phones in vegetable marketing includes communicating at a distance to save time and minimizing transport costs, getting vegetable marketing price information, identifying markets and buyers to sell the vegetable, deciding when to sell the vegetable, negotiating with buyers for better vegetable prices and for searching of the fast market to avoid from losing of product through perishing. The model result indicated that the level of education, size of land, income, access to credit, and age were significant variables affecting the use of mobile phones in vegetable marketing. It could be recommended to encourage adult education or give training for farmers on how to operate mobile phones and create awareness for the elderly rural farmers as they are able to use the mobile phone for their vegetable marketing. Moreover, farmers should be aware that mobile phones are very important for those who own very small land to get maximum returns from their production. Lastly, providing access to credit and improving and diversifying income sources for the farmers to have mobile phones were recommended to improve the livelihood of farmers.

Keywords: mobile phone, farmers, vegetable marketing, Fogera District

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17789 Reconstructability Analysis for Landslide Prediction

Authors: David Percy

Abstract:

Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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