Search results for: independent RBF model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18498

Search results for: independent RBF model

18348 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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18347 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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18346 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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18345 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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18344 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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18343 Independence of the Judiciary in South Africa: An Assessment After Twenty Years of Democracy

Authors: Serges Djoyou Kamga, Gerard Emmanuel Kamdem Kamga

Abstract:

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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18342 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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18341 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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18340 Mathematical Model to Quantify the Phenomenon of Democracy

Authors: Mechlouch Ridha Fethi

Abstract:

This paper presents a recent mathematical model in political sciences concerning democracy. The model is represented by a logarithmic equation linking the Relative Index of Democracy (RID) to Participation Ratio (PR). Firstly the meanings of the different parameters of the model were presented; and the variation curve of the RID according to PR with different critical areas was discussed. Secondly, the model was applied to a virtual group where we show that the model can be applied depending on the gender. Thirdly, it was observed that the model can be extended to different language models of democracy and that little use to assess the state of democracy for some International organizations like UNO.

Keywords: democracy, mathematic, modelization, quantification

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18339 Cross Matching: An Improved Method to Obtain Comprehensive and Consolidated Evidence

Authors: Tuula Heinonen, Wilhelm Gaus

Abstract:

At present safety, assessment starts with animal tests although their predictivity is often poor. Even after extended human use experimental data are often judged as the core information for risk assessment. However, the best opportunity to generate true evidence is to match all available information. Cross matching methodology combines the different fields of knowledge and types of data (e.g. in-vitro and in-vivo experiments, clinical observations, clinical and epidemiological studies, and daily life observations) and gives adequate weight to individual findings. To achieve a consolidated outcome, the information from all available sources is analysed and compared with each other. If single pieces of information fit together a clear picture becomes visible. If pieces of information are inconsistent or contradictory careful consideration is necessary. 'Cross' can be understood as 'orthographic' in geometry or as 'independent' in mathematics. Results coming from different sources bring independent and; therefore, they result in new information. Independent information gives a larger contribution to evidence than results coming repeatedly from the same source. A successful example of cross matching is the assessment of Ginkgo biloba where we were able to come to the conclusive result: Ginkgo biloba leave extract is well tolerated and safe for humans.

Keywords: cross-matching, human use, safety assessment, Ginkgo biloba leave extract

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18338 A Model for Academic Coaching for Success and Inclusive Excellence in Science, Technology, Engineering, and Mathematics Education

Authors: Sylvanus N. Wosu

Abstract:

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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18337 The Achievement Model of University Social Responsibility

Authors: Le Kang

Abstract:

On the research question of 'how to achieve USR', this contribution reflects the concept of university social responsibility, identify three achievement models of USR as the society - diversified model, the university-cooperation model, the government - compound model, also conduct a case study to explore characteristics of Chinese achievement model of USR. The contribution concludes with discussion of how the university, government and society balance demands and roles, make necessarily strategic adjustment and innovative approach to repair the shortcomings of each achievement model.

Keywords: modern university, USR, achievement model, compound model

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18336 Widely Diversified Macroeconomies in the Super-Long Run Casts a Doubt on Path-Independent Equilibrium Growth Model

Authors: Ichiro Takahashi

Abstract:

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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18335 Estimation of Missing Values in Aggregate Level Spatial Data

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

Abstract:

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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18334 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

Abstract:

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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18333 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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18332 Multicollinearity and MRA in Sustainability: Application of the Raise Regression

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

Abstract:

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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18331 Provision Electronic Management Requirements in Libyan Oil Companies

Authors: Hitham Yami

Abstract:

This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

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18330 Factors Influencing the Use of Mobile Phone by Smallholder Farmers in Vegetable Marketing in Fogera District

Authors: Molla Tadesse Lakew

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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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18329 Internet Purchases in European Union Countries: Multiple Linear Regression Approach

Authors: Ksenija Dumičić, Anita Čeh Časni, Irena Palić

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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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18328 Innovative Approaches to Formal Education: Effect of Online Cooperative Learning Embedded Blended Learning on Student's Academic Achievement and Attitude

Authors: Mohsin Javed

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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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18327 On Cold Roll Bonding of Polymeric Films

Authors: Nikhil Padhye

Abstract:

Recently a new phenomenon for bonding of polymeric films in solid-state, at ambient temperatures well below the glass transition temperature of the polymer, has been reported. This is achieved by bulk plastic compression of polymeric films held in contact. Here we analyze the process of cold-rolling of polymeric films via finite element simulations and illustrate a flexible and modular experimental rolling-apparatus that can achieve bonding of polymeric films through cold-rolling. Firstly, the classical theory of rolling a rigid-plastic thin-strip is utilized to estimate various deformation fields such as strain-rates, velocities, loads etc. in rolling the polymeric films at the specified feed-rates and desired levels of thickness-reduction(s). Predicted magnitudes of slow strain-rates, particularly at ambient temperatures during rolling, and moderate levels of plastic deformation (at which Bauschinger effect can be neglected for the particular class of polymeric materials studied here), greatly simplifies the task of material modeling and allows us to deploy a computationally efficient, yet accurate, finite deformation rate-independent elastic-plastic material behavior model (with inclusion of isotropic-hardening) for analyzing the rolling of these polymeric films. The interfacial behavior between the roller and polymer surfaces is modeled using Coulombic friction; consistent with the rate-independent behavior. The finite deformation elastic-plastic material behavior based on (i) the additive decomposition of stretching tensor (D = De + Dp, i.e. a hypoelastic formulation) with incrementally objective time integration and, (ii) multiplicative decomposition of deformation gradient (F = FeFp) into elastic and plastic parts, are programmed and carried out for cold-rolling within ABAQUS Explicit. Predictions from both the formulations, i.e., hypoelastic and multiplicative decomposition, exhibit a close match. We find that no specialized hyperlastic/visco-plastic model is required to describe the behavior of the blend of polymeric films, under the conditions described here, thereby speeding up the computation process .

Keywords: Polymer Plasticity, Bonding, Deformation Induced Mobility, Rolling

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18326 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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18325 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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18324 Coding and Decoding versus Space Diversity for ‎Rayleigh Fading Radio Frequency Channels ‎

Authors: Ahmed Mahmoud Ahmed Abouelmagd

Abstract:

The diversity is the usual remedy of the transmitted signal level variations (Fading phenomena) in radio frequency channels. Diversity techniques utilize two or more copies of a signal and combine those signals to combat fading. The basic concept of diversity is to transmit the signal via several independent diversity branches to get independent signal replicas via time – frequency - space - and polarization diversity domains. Coding and decoding processes can be an alternative remedy for fading phenomena, it cannot increase the channel capacity, but it can improve the error performance. In this paper we propose the use of replication decoding with BCH code class, and Viterbi decoding algorithm with convolution coding; as examples of coding and decoding processes. The results are compared to those obtained from two optimized selection space diversity techniques. The performance of Rayleigh fading channel, as the model considered for radio frequency channels, is evaluated for each case. The evaluation results show that the coding and decoding approaches, especially the BCH coding approach with replication decoding scheme, give better performance compared to that of selection space diversity optimization approaches. Also, an approach for combining the coding and decoding diversity as well as the space diversity is considered, the main disadvantage of this approach is its complexity but it yields good performance results.

Keywords: Rayleigh fading, diversity, BCH codes, Replication decoding, ‎convolution coding, viterbi decoding, space diversity

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18323 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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18322 Preventive Behaviors of Exposure to ‎Secondhand Smoke among Women: A Study Based on the Health Belief Model

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 secondhand smoke in women. Materials and Methods: This experimental study was performed in 2023in 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 secondhand smoke.

Keywords: women, health behaviour, smoke, belive

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18321 Design of Collaborative Web System: Based on Case Study of PBL Support Systems

Authors: Kawai Nobuaki

Abstract:

This paper describes the design and implementation of web system for continuable and viable collaboration. This study proposes the improvement of the system based on a result of a certain practice. As contemporary higher education information environments transform, this study highlights the significance of university identity and college identity that are formed continuously through independent activities of the students. Based on these discussions, the present study proposes a practical media environment design which facilitates the processes of organizational identity formation based on a continuous and cyclical model. Even if users change by this system, the communication system continues operation and cooperation. The activity becomes the archive and produces new activity. Based on the result, this study elaborates a plan with a re-design by a system from the viewpoint of second-order cybernetics. Systems theory is a theoretical foundation for our study.

Keywords: collaborative work, learning management system, second-order cybernetics, systems theory, user generated contents, viable system model

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18320 Generalized Uncertainty Principle Modified Hawking Radiation in Bumblebee Gravity

Authors: Sara Kanzi, Izzet Sakalli

Abstract:

The effect of Lorentz symmetry breaking (LSB) on the Hawking radiation of Schwarzschild-like black hole found in the bumblebee gravity model (SBHBGM) is studied in the framework of quantum gravity. To this end, we consider Hawking radiation spin-0 (bosons) and spin-12particles (fermions), which go in and out through the event horizon of the SBHBGM. We use the modified Klein-Gordon and Dirac equations, which are obtained from the generalized uncertainty principle (GUP) to show how Hawking radiation is affected by the GUP and LSB. In particular, we reveal that independent of the spin of the emitted particles, GUP causes a change in the Hawking temperature of the SBHBGM. Furthermore, we compute the semi-analytic greybody factors (for both bosons and fermions) of the SBHBGM. Thus, we reveal that LSB is effective on the greybody factor of the SBHBGM such that its redundancy decreases the value of the greybody factor. Our findings are graphically depicted.

Keywords: bumblebee gravity model, Hawking radiation, generalized uncertainty principle, Lorentz symmetry breaking

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18319 A Study on Game Theory Approaches for Wireless Sensor Networks

Authors: M. Shoukath Ali, Rajendra Prasad Singh

Abstract:

Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

Procedia PDF Downloads 432