Search results for: models of organization of the state

Authors: Yumei Wang, Xiaoyu Xu, Li Lu

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Solid-state battery adopts solid-state electrolyte such as oxide- and composite-based solid electrolytes. With the adaption of nonflammable or less flammable solid electrolytes, the safety of solid-state batteries can be largely increased. NASICON (Na₃Zr₂Si₂PO₁₂, NZSP) is one of the sodium ion conductors that possess relatively high ionic conductivity, wide electrochemical stable range and good chemical stability. Therefore, it has received increased attention. We report the development of high-density NZSP through liquid phase sintering and its organic-inorganic composite electrolyte. Through reactive liquid phase sintering, the grain boundary conductivity can be largely enhanced while using an organic-inorganic composite electrolyte, interfacial wetting and impedance can be largely reduced hence being possible to fabricate scalable solid-state batteries.

Keywords: solid-state electrolyte, composite electrolyte, electrochemical performance, conductivity

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Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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Authors: Mehdi Asgarkhani

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Today, investment on Information Technology (IT) solutions in most organizations is the largest component of capital expenditure. As capital investment on IT continues to grow, IT managers and strategists are expected to develop and put in practice effective decision making models (frameworks) that improve decision-making processes for the use of IT in organizations and optimize the investment on IT solutions. To be exact, there is an expectation that organizations not only maximize the benefits of adopting IT solutions but also avoid the many pitfalls that are associated with rapid introduction of technological change. Different organizations depending on size, complexity of solutions required and processes used for financial management and budgeting may use different techniques for managing strategic investment on IT solutions. Decision making processes for strategic use of IT within organizations are often referred to as IT Governance (or Corporate IT Governance). This paper examines IT governance - as a tool for best practice in decision making about IT strategies. Discussions in this paper represent phase I of a project which was initiated to investigate trends in strategic decision making on IT strategies. Phase I is concerned mainly with review of literature and a number of case studies, establishing that the practice of IT governance, depending on the complexity of IT solutions, organization's size and organization's stage of maturity, varies significantly – from informal approaches to sophisticated formal frameworks.

Keywords: IT governance, corporate governance, IT governance frameworks, IT governance components, aligning IT with business strategies

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Authors: Robson da C. Santos, Carlos Henrique de A. S. P. Coutinho, Lucas Moreira Dias, Gerson Gomes Cunha

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The article refers to the development of an augmented reality 3D display, through the control of servo motors and projection of image with aid of video projector on the model. Augmented Reality is a branch that explores multiple approaches to increase real-world view by viewing additional information along with the real scene. The article presents the broad use of electrical, electronic, mechanical and industrial automation for geospatial visualizations, applications in mathematical models with the visualization of functions and 3D surface graphics and volumetric rendering that are currently seen in 2D layers. Application as a 3D display for representation and visualization of Digital Terrain Model (DTM) and Digital Surface Models (DSM), where it can be applied in the identification of canyons in the marine area of the Campos Basin, Rio de Janeiro, Brazil. The same can execute visualization of regions subject to landslides, as in Serra do Mar - Agra dos Reis and Serranas cities both in the State of Rio de Janeiro. From the foregoing, loss of human life and leakage of oil from pipelines buried in these regions may be anticipated in advance. The physical design consists of a table consisting of a 9 x 16 matrix of servo motors, totalizing 144 servos, a mesh is used on the servo motors for visualization of the models projected by a retro projector. Each model for by an image pre-processing, is sent to a server to be converted and viewed from a software developed in C # Programming Language.

Keywords: visualization, 3D models, servo motors, C# programming language

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

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This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: Diana Serbezeanu, Ionela-Daniela Carja, Tachita Vlad-Bubulac, Sergiu Sova

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New phosphorus-containing monomers having methoxy end functional groups were prepared from methyl 4-hydroxybenzoate and two different dichlorides with phosphorus, namely phenyl phosphonic dichloride and phenyl dichlorophosphate. The structures of the monomers were confirmed by FTIR and NMR spectroscopy. The assignments for the 1H, 13C and 31P chemical shifts are based on 1D and 2D NMR homo- and heteronuclear correlations (H,H-COSY (Correlation Spectroscopy), H,C-HMQC (Heteronuclear Multiple Quantum Correlation and H,C-HMBC (Heteronuclear Multiple Bond Correlation)) and 31P-13C couplings. The monomers exhibited good solubility in common organic solvents. Dimethyl sulfoxide was to be a good solvent to grow crystals of considerable size which were investigated by X-ray analysis. One of these two new monomers presented thermotropic liquid crystalline behaviour, as revealed by differential scanning calorimetry (DSC), polarized light microscopy (PLM) and X-ray diffraction (XRD). The transition temperature from crystal to liquid crystalline state (K→LC) was 143°C and from the LC to isotropic state (LC→I) was 167°C. Upon heating, bis(4-(methoxycarbonyl)phenyl formed fine textures, difficult to be ascribed to smectic or nematic phases. Upon cooling from the isotropic state, bis(4-(methoxycarbonyl)phenyl exhibited a mosaic-type texture. X-ray diffraction measurements at small angles (SAXS) of bis(4-(methoxycarbonyl)phenyl showed two peaks at 1.8 Å and 3.5 Å, respectively suggesting organization at supramolecular level.

Keywords: phosphorus-containing monomers, polarized light microscopy, structure investigation, thermotropic liquid crystalline properties

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Authors: Stephen Pembi, Samuel K. Msheliza, Helen A. Andow

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Organizational culture is very important in the organization because it enhances organizational performance and serves as a sense of making and control mechanism that guides and shapes the attitude and behaviour of employees. However, organizational culture issues are frequently disregarded in lieu of activities that may or may not have a good impact on performance. This study examines the relationship between organizational culture and organizational performance of Adama Beverages Ltd, Adamawa State. The study employed an explanatory survey research design with a questionnaire as a source of data collection. One hundred and thirty-five copies of the questionnaire were administered using the convenience method of sampling, out of which one hundred and twenty were retrieved and well answered. The data collected were subjected to the Pearson product-moment correlation technique to test the hypotheses of the study using SPSS. The overall results signify that organizational culture has a significant positive relationship with organizational performance. The multiple regression results show that mission, adaptability, and involvement have a significant positive influence on organizational performance, while consistency has a significant negative influence on organizational performance. Therefore, this study concluded that organizational culture is a strong determinant of organizational performance in Adama Beverages Ltd, Adamawa State. The study recommends that the level of employee input into decision-making, flexibility in responding to changes in the business environment, consistency with values and traditions, and organizational performance should all be maintained by Adama Beverages Ltd.

Keywords: adaptability, consistency, involvement, mission, organizational performance

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Tai-Yue Wang, Yi-Ho Chen

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In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Mohammad Anwar, Shah Waliullah

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

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

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Authors: Jordan Daud, Satriya Wibawa, Wahyu Wardhana

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In the summer of 2014, the leaders of the Islamic State of Iraq and Syria proclaimed the founding of religious-political system known as the caliphate which titled Islamic State (IS). As Caliph, Abu Bakr Baghdadi advocated Jihad from the Ummah (the Muslim community) to defend the Islamic state from unbelievers. This call for Jihad by IS had encouraged some radical organization in Southeast Asia pledge allegiance to IS and established bases for IS operation in Southeast Asia. This development had increased security concern for possible terrorism action in Southeast Asia, which currently not very active due to counterterrorism efforts from ASEAN member states and its cooperation with the world. This paper firstly tries to draw understanding from Ulema (Muslim cleric) about the conception of caliphate and Jihad based on Quran and Hadith. Secondly, this paper will elaborate counterterrorism efforts from ASEAN countries to prevent radicalization and terrorism act in addressing the call for jihad to establish IS in Southeast Asia. The third, this paper will recommend the role of the social community, especially Ulema, in Southeast Asia to prevent the misunderstanding of Jihad which usually used by terrorist to justify their action. Hopefully, this social community role will decrease the radicalization of Muslim community in Southeast Asia alongside with the counterterrorism efforts to create secure and stable ASEAN community based on shared norm and values.

Keywords: caliphate, jihad, ASEAN, counterterrorism, social community

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Authors: Sylvia Acquah

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The assumption that social enterprises are empowering has strong theoretical support, but empirical verification is anecdotal at best. Social enterprises blend social goal with an enterprising idea and therefore in theory these enterprises should provide meaningful jobs that are empowering. Whether jobs created are meaningful, or whether these organizations are practicing social entrepreneurship remains unexplored key questions. This paper addresses these key questions through a comprehensive literature review and an ethnographical study of a Domiciliary Home Care Social Enterprise in the UK. The social entrepreneurs, management and 9 staff members were observed, interviewed and achieves were reviewed and analyzed. In this study, the social entrepreneur’s vision was lost in transition during management change and the organization was only identified as a social enterprise by name. The organization that was set up to tackle lack of continuity in care and create a family of independent carers, was eventually closed down overnight and subjected to investigation by social services and the local council. Also, the ineffectiveness of the organization led to staff being stressed and without the support of the management to help rectify the issues; staff started displaying symptoms of burnout. Social enterprise managers should not only focus on profit maximization or generation, but should equally live up to the core tenets of the enterprise and effectively communicate and gain buy-in of all employees for any changes. Further, there ought to be an independent organization that regulates social enterprises to ensure that they are adhering to their social goals.

Keywords: ethnography, carer, social, enterprise

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Authors: Ana-Marija Stjepić, Luka Sušac, Dalia Suša Vugec

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In the last few years, examples from scientific literature and business practices show that the adoption of technological innovations increases enterprises' performance. Recently, when it comes to the field of information technology innovation, business intelligence systems (BISs) have drawn a significant amount of attention of the scientific circles. BISs can be understood as a form of technological innovation which can bring certain benefits to the organizations that are adopting it. Therefore, the aim of this paper is twofold: (1) to define determinants of successful BISs adoption in small and medium enterprises and thus contribute to this neglected research area and (2) to present the current state of BISs adoption in small and medium-sized companies. In order to do so, determinants are defined and classified into three dimensions, according to the Technology – Organization – Environment (TOE) theoretical framework that describes the impact of each dimension on technological innovations adoption. Moreover, paper brings a case study presenting the adoption of BISs in practice within an organization from tertiary (service) industry sector. Based on the results of the study, guidelines for more efficient, faster and easier BISs adoption are presented.

Keywords: adoption, business intelligence, business intelligence systems, case study, TOE framework

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the direct and indirect effects of variables in path models. One or more structural regression equations are used to estimate a series of parameters in path models to find the better fit of data. However, sometimes the assumptions of classical regression models, such as ordinary least squares (OLS), are violated by the nature of the data, resulting in insignificant direct and indirect effects of exogenous variables. This article aims to explore the effectiveness of a copula-based regression approach as an alternative to classical regression, specifically when variables are linked through an elliptical copula.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Nynke de Jong, Inge G. P. Duimel-Peeters

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The flipped classroom as an instructional strategy and a type of blended learning that reverses the traditional learning environment by delivering instructional content, off- and online, in- and outside the classroom, has been implemented in a 4-weeks module focusing on ageing in Europe at the Maastricht University. The main aim regarding the organization of this module was implementing flipped classroom-principles in order to create meaningful learning opportunities, while educational technologies are used to deliver content outside of the classroom. Technologies used in this module were an online interactive real time lecture from England, two interactive face-to-face lectures with visual supports, one group session including role plays and team-based learning meetings. The cohort of 2015-2016, using educational technologies, was compared with the cohort of 2014-2015 on module evaluation such as organization and instructiveness of the module, who studied the same content, although conforming the problem-based educational strategy, i.e. educational base of the Maastricht University. The cohort of 2015-2016 with its specific organization, was also more profound evaluated on outcomes as (1) experienced duration of the lecture by students, (2) experienced content of the lecture, (3) experienced the extent of the interaction and (4) format of lecturing. It was important to know how students reflected on duration and content taken into account their background knowledge so far, in order to distinguish between sufficient enough regarding prior knowledge and therefore challenging or not fitting into the course. For the evaluation, a structured online questionnaire was used, whereby above mentioned topics were asked for to evaluate by scoring them on a 4-point Likert scale. At the end, there was room for narrative feedback so that interviewees could express more in detail, if they wanted, what they experienced as good or not regarding the content of the module and its organization parts. Eventually, the response rate of the evaluation was lower than expected (54%), however, due to written feedback and exam scores, we dare to state that it gives a good and reliable overview that encourages to work further on it. Probably, the response rate may be explained by the fact that resit students were included as well, and that there maybe is too much evaluation as some time points in the program. However, overall students were excited about the organization and content of the module, but the level of self-directed behavior, necessary for this kind of educational strategy, was too low. They need to be more trained in self-directness, therefore the module will be simplified in 2016-2017 with more clear and fewer topics and extra guidance (step by step procedure). More specific information regarding the used technologies will be explained at the congress, as well as the outcomes (min and max rankings, mean and standard deviation).

Keywords: blended learning, flipped classroom, public health, self-directness

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Mohood A. Bamidele, Fadairo O. Olokesunsi, Muhammed A. Yunus

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This research work focuses on tourism and poverty alleviation in Osun State, it delves in the tourism resources of the state and strategic framework that has been put in place to manage the cultural base tourism that is most prominent in the state. The major instrument used for data collection was questionnaire which was designed for the area and data collected were analyzed using statistical table and chi-square analysis. The result revealed that tourism is under development in Osun State and the tourism potential of the state is yet to be exploited, this is due to lack of appropriate policy to master the development and management of tourism resources, poor publicity, awareness, and lack of adequate basic infrastructure. The research work, therefore, recommended, that, there should be proper and appropriate policy, and that the government should take a leading step to develop tourism in Osun State by creating a workable environment to the private sector and given a substantial budgetary allocation to the tourism in the state.

Keywords: appropriate policy, poor publicity, poverty alleviation, substantial budgetary allocation

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Authors: Malgorzata Kurleto

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This study is trying to analyse the organization of the anti-doping system globally (particularly in Poland). The analysis is going to show the concept of doping, indicating the types of doping, and list of banned substances and methods. The paper discusses ethical aspects of the global anti-doping system. The analysis is focusing on organization of global Anti-Doping Agency. The paper will try to describe the basic assumptions of regulations adopted by WADA, called "standards” as well organization and functioning of the Polish Anti-Doping Agency (including the legal basis: POLADA). The base for this discuss will be the Polish 2018 annual report, which shows the most important assumptions, implementation and the number of anti-doping proceedings conducted in Poland. The aim of this paper is to show ethical arguments on anti-doping management strategies.

Keywords: anti-doping, ethical dilemmas, sports doping, WADA, POLADA

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Authors: Routsukol Sunalai

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This research was to study the relationship between the organizational culture like bureaucratic system, and patronage system in government hospitals with hospital accreditation and its impact on the quality of service in the government hospital accredited. Qualitative research was applied in this study by in-depth interviews with samples containing 20 public welfare service providers, i.e. doctors, nurses and practical nurses and 20 service recipients in the units of study. It was found that the bureaucracy still existed and was evidenced by the structure of the line of command; work systems, clear cut duty divisions, procedures and plans, and the patronage system hindered the quality of service in the government hospitals under the process of development and accreditation. The administrators should encourage and support the creation of a learning process in the organization for self-improvement and work development.

Keywords: hospital in Dusit Area, organization culture, the quality of service, economics and financial engineering

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Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

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Authors: Sunday Sedodo Nupo, Clara Berstien Oguntona, Babatunde Oguntona, Oluseyi Akinloye, P. A. Olunusi Adeboye

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Cardiovascular diseases are now becoming dominant sources of morbidity and mortality worldwide. This study investigated the lipid profile of civil servants. A cross-sectional study was carried out among randomly selected 202 male and 298 female civil servants in Abeokuta Ogun state. A pretested structured questionnaire was used to elicit information on history of non-communicable diseases and physical activity pattern of the respondents. The blood pressures of the subjects were measured and classified using World Health Organization criteria. The total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL). Ethical approval was obtained from Ogun State Ministry of Health. Data collected were analysed using Statistical package for social science version 17.1. Results showed that majority (76%) of the subjects were within the age range of 20 - 40 years, 75% earned between N58,500 - N98,000 monthly and 68% were sedentary. The mean energy intake of men and women were 3942±38 kcal and 2791±3 kcal respectively, while the protein intake for men was 65±49 g/day and 54.28±40 g/day for women. Desirable TC level (<200 mg/dl) was found in 80% of the selected subjects while the normal TG (<150 mg/dl) and LDL (<129 mg/dl) was found in 95% and 90% subjects respectively. The mean TC was 78.91±11 mg/dl and 62.69±9 mg/dl in men and women respectively. The study showed that most of the subjects had normal lipid in terms of serum triglycerides, total cholesterol, HDL cholesterol and LDL cholesterol.

Keywords: high density lipoprotein, morbidity, mortality, triglycerides

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Authors: Charita B. Lasala, Lakambini G. Reluya

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The human factor composing the organization is an asset that needs to be managed conscientiously and to be in tuned with the organization’s need. Thus, the human resources add value to the organization by using their talents, skills and knowledge in transforming the other resources of the organization to either produce or to deliver products and services that generate profits or other valued forms for return. Keeping these kinds of employees has always been the main goal of each Human Resources Department in every company worldwide; regardless of the work being done. They are the most important resource a company can have and treating them well will make them priceless assets that can help make a business a success. Larmen de Guia Memorial College (LGMC) and Royal Oaks International School (ROIS) is one of the many organizations that seek ways to keep the human factor and are in the process of formalization and that people management is on the top of the list thus, this study was made since there was a need for the creation of the Human Resources Department due to its absence in the organization and to help the organization in keeping these valued employees. The study was anchored on the concept that human resources consist of people who perform its activities and that all decisions that affect the workforce concern the organization’s human resources functions. In conducting this study, it made use of the mixed method using both the qualitative and quantitative approaches with focus group discussions. The design has three stages namely: problem conceptualization, case analysis, and output. The output from the survey and interviews tells the abstracted ideas on the proposed HR program for the said institution. Based on the findings of the study, it can be concluded that the personnel in the institution is not in the correct perspective, much more that the personnel has no specific job descriptions. The hiring procedure is not extensive, nor the personnel was given the chance to be exposed to training that would aid them in job development and enhancement of their skills and talents. The compensation package offered by the institution does not commensurate to their services rendered. Lastly, it is concluded that in the opinion/decision rendered by the grievance committee is not fair and that the institution failed to give good motivation/initiative for the employees to be more productive.

Keywords: employee benefits, employee relations, human resources and management, people management, recruitment, trainings

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Authors: Saiakhil Chilaka

Abstract:

Understanding the demographic factors that influence mortality from respiratory diseases like COVID-19, pneumonia, and influenza is crucial for informing public health policy. This study utilizes multivariable regression models to assess the relationship between state, sex, and age group on deaths from these diseases using U.S. data from 2020 to 2023. The analysis reveals that age and sex play significant roles in mortality, while state-level variations are minimal. Although the model’s low R-squared values indicate that additional factors are at play, this paper discusses how these findings, in light of recent research, can inform future public health policy, resource allocation, and intervention strategies.

Keywords: COVID-19, multivariable regression, public policy, data science

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Authors: Julian David Rios Acuna

Abstract:

This paper seeks to argue that the phenomenon of ‘paramilitarism’ in Colombia exhibits the role of violence as constitutive of the political process of state formation in the country. In order to do this, it takes as its point of departure a landmark moment in the long history of private armies known as the ‘paramilitary’ in Colombia. In 2001, paramilitary commanders, politicians, and members of the military and other branches of state power singed what is known as the ‘Pact of Ralito.’ In this pact, the paramilitary appropriated constitutional and legal language. The paper argues that this appropriation shows that the paramilitary and the state express the same claim to sovereign power and therefore have the same foundation. More precisely, paramilitary power shows itself to base its power on the same foundation as the legal order, namely, extreme forms of violence where death is generative of power. In this sense, the paper shows how, by sharing its foundation, Colombian paramilitarism exhibits that state power in Colombia can be characterized as necro-power as Achille Mbembe understands it. The paper argues that paramilitarism shows state power as necro-power by constituting itself as a symptom understood, following Zizek, as that which both shows and overthrows its own foundation. In this way, paramilitarism shows the foundation of the state, thereby reconfiguring this very state. This reconfiguration, explicitly based on necro-power, the paper concludes, transforms the state into a form more appropriate to the political demands of neo-liberalism. By exhibiting its foundation in necro-power through paramilitarism, the Colombian State turns from a liberal into a (neo)liberal democracy.

Keywords: necro-power, necropolitics, paramilitarism in Colombia, state formation, state power, sovereign power

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Authors: Giriraj Achari, Malay Bhattacharyya

Abstract:

In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

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