Search results for: elderly care service model

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

Procedia PDF Downloads 408

Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

Abstract:

Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

Procedia PDF Downloads 139

Authors: Motalleb Byzedi, Seyedeh Chaman Naderi Korvandan

Abstract:

Regarding annual statistics of groundwater level resources about current piezometers at Qorveh plains, both ARMA & PARMA modeling methods were applied in this study by the using of SAMS software. Upon performing required tests, a model was used with minimum amount of Akaike information criteria and suitable model was selected for piezometers. Then it was possible to make necessary estimations by using these models for future fluctuations in each piezometer. According to the results, ARMA model had more facilities for modeling of aquifer. Also it was cleared that eastern parts of aquifer had more failures than other parts. Therefore it is necessary to prohibit critical parts along with more supervision on taking rates of wells.

Keywords: qorveh plain, groundwater level, ARMA, PARMA

Procedia PDF Downloads 272

Authors: Sami Mestiri, Abdeljelil Farhat

Abstract:

The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

Procedia PDF Downloads 530

Authors: Yi Wang, Xun Liang

Abstract:

This paper introduces a model of internet public opinion waves, which describes the message propagation and measures the influence of a detected event. We collect data on public opinion propagation from different platforms on the internet, including micro-blogs and news. Then, we compare the spread of public opinion to the seismic waves and correspondently define the P-wave and S-wave and other essential attributes and characteristics in the process. Further, a model is established to evaluate the magnitude scale of the events. In the end, a practical example is used to analyze the influence of network public opinion and test the reasonability and effectiveness of the proposed model.

Keywords: internet public opinion waves (IPOW), magnitude scale, cross-platform, information propagation

Procedia PDF Downloads 274

Authors: S. Saeed, T. Butt, M. Rehan, S. Khaliq

Abstract:

Objective: To determine the frequency of pre-analytical errors in samples taken from patients for various lab tests at Fauji Foundation Hospital, Rawalpindi. Material and Methods: All the lab specimens for diagnostic purposes received at the lab from Fauji Foundation hospital, Rawalpindi indoor and outdoor patients were included. Total number of samples received in the lab is recorded in the computerized program made for the hospital. All the errors observed for pre-analytical process including patient identification, sampling techniques, test collection procedures, specimen transport/processing and storage were recorded in the log book kept for the purpose. Results: A total of 476616 specimens were received in the lab during the period of study including 237931 and 238685 from outdoor and indoor patients respectively. Forty-one percent of the samples (n=197976) revealed pre-analytical discrepancies. The discrepancies included Hemolyzed samples (34.8%), Clotted blood (27.8%), Incorrect samples (17.4%), Unlabeled samples (8.9%), Insufficient specimens (3.9%), Request forms without authorized signature (2.9%), Empty containers (3.9%) and tube breakage during centrifugation (0.8%). Most of these pre-analytical discrepancies were observed in samples received from the wards revealing that inappropriate sample collection by the medical staff of the ward, as most of the outdoor samples are collected by the lab staff who are properly trained for sample collection. Conclusion: It is mandatory to educate phlebotomists and paramedical staff particularly performing duties in the wards regarding timing and techniques of sampling/appropriate container to use/early delivery of the samples to the lab to reduce pre-analytical errors.

Keywords: pre analytical lab errors, tertiary care hospital, hemolyzed, paramedical staff

Procedia PDF Downloads 198

Authors: Sofia Cramerotti, Angela Cattoni, Laura Biancato, Dario Ianes

Abstract:

The recognition of specific standards for new professionals, within the teaching profile, is a necessary process in order to foster an innovative school vision in accordance with the change that school is experiencing. In line with the reform of the national education and training system and with the National Training Plan for teachers, our Research and Development department developed a training project based on a framework (Syllabus) of skills that each 'Expert Teacher' should master in order to fulfill what the different specific profiles request. The syllabus is a fundamental tool for a training process consistent with the teaching profiles, both to guide the to-become teachers entering in service and to provide the in-service teachers with a system of evaluation and improvement of their skills. According to the national and international literature about professional standards for teachers, we aggregated the skills of the syllabus in three macro areas: (1) Area of professional skills related to the teacher profile and their continuous training; (2) area of teaching skills related to the school innovation; (3) area of organizing skills related to school participation for its improvement. The syllabus is a framework that identifies and describes the skills of the expert teacher in all of their roles. However, the various skills take on different importance in the different profiles involved in the school; some of those skills are determining a role, others could be secondary. Therefore, the characterization of the different profiles is represented by suitably weighted skills sets. In this way, the same skill could differently characterize each profile. In the future, we hope that the skills development and training for the teacher could evolve in a skills development and training for the whole school staff ('Expert Team'). In this perspective, the school will, therefore, benefit from a solid team, in which the skills of the various profiles are all properly developed and well represented.

Keywords: framework, skills, teachers, training

Procedia PDF Downloads 168

Authors: Khitam Ibrahem Shlash Mohammad

Abstract:

Background: Postnatal depression is a focus of considerable research attention, but little is known about the pattern of stress across this period. Objective: to investigate the prevalence of stress after childbirth for Jordanian women and identify associated risk factors. Method: Design: A descriptive cross-sectional study. Participants were recruited six to eight weeks postpartum, provided personal, social and obstetric information, and completed the stress subscale of Depression Anxiety and Stress Scale (DASS-S), the Maternity Social Support Scale (MSSS), and Perceived Self-Efficacy Scale (PSES). Setting: maternal and child health care clinics in four health care centres in Maan city in Southern Jordan. Participants: Arabic speaking women (n = 324) between the ages of 18 and 45 years, six to eight weeks postpartum, primiparous or multiparous at low risk for obstetric complications. Data collection took place between October 2015 and January 2016. Ethical clearance was obtained prior to data collection. Results: The prevalence of postpartum stress among Jordanian women was 39.8 %. A regression analysis revealed that occupation, low social support, financial problems, difficult marital relationships, difficult relationship with family-in-law, giving birth to a female baby, difficult childbirth, and low self-efficacy were associated with postpartum stress. Conclusions and implications for practice: Jordanian women need support during pregnancy, during and after childbirth. Postpartum emotional support and assessment of symptoms of stress need to be incorporated into routine practice. The opportunity for open discussion along with increased awareness and clarification of common misconceptions about postpartum stress is necessary.

Keywords: prevalence, postpartum, stress, Jordanian women

Procedia PDF Downloads 339

Authors: Yiqi Wu, Simon Tait, Andrew Nichols

Abstract:

Management of UK railway drainage assets is challenging due to the large amounts of historical assets with long asset life cycles. A major concern for asset managers is to maintain the required performance economically and efficiently while complying with the relevant regulation and legislation. As the majority of the drainage assets are buried underground and are often difficult or costly to examine, it is important for asset managers to understand and model the degradation process in order to foresee the upcoming reduction in asset performance and conduct proactive maintenance accordingly. In this research, a Markov chain approach is used to model the deterioration process of rail drainage assets. The study is based on historical condition scores and characteristics of drainage assets across the whole railway network in England, Scotland, and Wales. The model is used to examine the effect of various characteristics on the probabilities of degradation, for example, the regional difference in probabilities of degradation, and how material and shape can influence the deterioration process for chambers, channels, and pipes.

Keywords: deterioration, degradation, markov models, probability, railway drainage

Procedia PDF Downloads 205

Authors: Atefeh Salehipoor

Abstract:

Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: 1. Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. 2. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. 3. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. 4. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. 5. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. 6. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension

Procedia PDF Downloads 66

Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

Abstract:

Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

Procedia PDF Downloads 207

Authors: Natalia Ortega

Abstract:

Safety Culture (SCU) involves various perceptual, psychological, behavioral, and managerial factors. It has been shown that creating and maintaining an SCU is one way to reduce and prevent accidents and fatalities. In the construction sector, safety attitude, knowledge, and a supportive environment are predictors of safety behavior. The highest possible proportion of safety behavior among employees can be achieved by improving their safety attitude and knowledge. Accordingly, top management's commitment to safety is vital in shaping employees' safety attitude; therefore, the first step to improving employees' safety attitude is the genuine commitment of top management to safety. One of the factors affecting the successful implementation of health and safety promotion programs is the construction industry's subcontracting model. The contractual model's complexity, combined with the need for coordination among diverse stakeholders, makes it challenging to implement, manage, and follow up on health and well-being initiatives. The Systems theoretic accident model and process (STAMP) concept has expanded global consideration in recent years, increasing research attention. STAMP focuses attention on the role of constraints in safety management. The findings discover a growth of the research field from the definition in 2004 by Leveson and is being used across multiple domains. A systematic literature review of this novel model aims to meet the safety goals for human space exploration with a powerful and different approach to safety management, safety-driven design, and decision-making. Around two hundred studies have been published about applying the model. However, every single model for safety requires time to transform into research and practice, be tested and debated, and grow further and mature.

Keywords: stamp, risk management, accident prevention, safety culture, systems thinking, construction industry, safety

Procedia PDF Downloads 67

Authors: Samar Alkindy

Abstract:

Purpose: The BIM model has been used to support the planning of different construction projects in the industry by showing the different stages of the construction process. The model has been instrumental in identifying some of the common errors in the construction process through the spatial arrangement. The continuous use of the BIM model in the construction industry has resulted in various radical changes such as virtual prototyping. Construction virtual prototyping is a highly advanced technology that incorporates a BIM model with realistic graphical simulations, and facilitates the simulation of the project before a product is built in the factory. The paper presents virtual prototyping in the construction industry by examining its application, challenges and benefits to a construction project. Methodology approach: A case study was conducted for this study in four major construction projects, which incorporate virtual construction prototyping in several stages of the construction project. Furthermore, there was the administration of interviews with the project manager and engineer and the planning manager. Findings: Data collected from the methodological approach shows a positive response for virtual construction prototyping in construction, especially concerning communication and visualization. Furthermore, the use of virtual prototyping has increased collaboration and efficiency between construction experts handling a project. During the planning stage, virtual prototyping has increased accuracy, reduced planning time, and reduced the amount of rework during the implementation stage. Irrespective of virtual prototyping being a new concept in the construction industry, the findings outline that the approach will benefit the management of construction projects.

Keywords: construction operations, construction planning, process simulation, virtual prototyping

Procedia PDF Downloads 218

Authors: Susan D. Toliver

Abstract:

Within the professional research literature on parenting in the United States, there is a paucity of research on parenting within the African American or Black community. Research on parenting focused on African Americans within the upper middle class, who constitute a critical and growing sector within the African American population, is all but non-existent. Research to address this void is needed. Despite the progress that has been made toward eliminating the long-standing racial divides in U.S. society, these divides persist and continue to affect different experiences and opportunity structures for White Americans versus Black Americans, including those in the upper middle class. Achievement of middle and upper middle class status of adult heads of families has generally been seen as the route to greater success and well-being for their children. While higher family class status is positively correlated with these factors, the strength of the relationship between higher social class and success and well-being is weaker for Black American families as compared to White American families. In light of the realities of racial inequality, African American parents, including those who have achieved higher status, have unique concerns for their children. African American parents, on the basis of their own experiences and their sense of the world as being highly racialized, anticipate the kinds of experiences that their children are likely to encounter as they grow and mature from childhood to adulthood and beyond. Racial discrimination and macro and micro racial aggressions are continued sources of concern for these parents. On the basis of in-depth personal interviews with upper middle class African American parents, findings suggest that the parenting goals and strategies of African American parents are influenced by the continuing significance of race as a social divide, including in higher socio-economic strata, in the United States. Black American families' parenting practices differ from those of White American families and are inclusive of the unique factors that threaten the well-being of African American children. Specifically, parenting practices are shaped by parents' fears about the racial experiences that they anticipate that their children will encounter. Parents' perceptions of parental effectiveness are linked to their ability to prepare their children for success in confronting, understanding, and contextualizing racial inequalities and aggressions. Theories of Parental Projective Care are useful in understanding the special considerations and unique parenting goals and behaviors of higher status African Americans.

Keywords: African American parenting, parental projective care, parenting effectiveness, racial socialization, upper middle class parenting

Procedia PDF Downloads 127

Authors: Elisa Bertagna

Abstract:

A frame analysis of the work done by various energy multinational companies concerning diversity issues and gender equality is presented. Documents of four multinational companies - two from Finland and two from Italy - have been studied. The array of companies’ documents includes data from their websites, policies and so on. The Finnish and Italian contexts have been chosen as a sample of North and South Europe, of 'advanced' and 'less advanced'. The aim of the analysis is to understand if and how human resource and diversity management in Finnish and Italian multinational energy companies communicate their activity towards the employees. Attention is given on how employees are reacting in their role and on the consequences of its social positioning. The findings of this essay are crucially important. They show how the companies in object tend to focus on the HR and DM positive actions towards female employees’ struggles since the industry is characterized by multinationals with male-dominated employees. In this way, other categories, which are also depicted as sensitive such as young and elderly people or foreigners, do not receive the same amount of attention. Consequently, power hierarchies can be found: 'women' as a social category are given more importance and space in the companies’ data than others. Consequently, the present work analysis reflects on possible struggles that such companies might be facing concerning gender biases and further diverse issues.

Keywords: energy, diversity, gender, multinationals, power hierarchies

Procedia PDF Downloads 133

Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

Abstract:

The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

Procedia PDF Downloads 420

Authors: H. Mohammadi Majd, M. Jalali Azizpour, V. Tavaf, A. Jaderi

Abstract:

In upsetting processes contact friction significantly influence metal flow, stress-strain state and process parameters. Furthermore, tribological conditions influence workpiece deformation and its dimensional precision. A viscoplastic constitutive law, the Anand model, was applied to represent the inelastic deformation behavior in upsetting process. This paper presents research results of the influence of contact friction coefficient on a workpiece deformation in upsetting process.finite element parameters. This technique was tested for three different specimens simulations of the upsetting and the corresponding material and can be successfully employed to predict the deformation of the upsetting process.

Keywords: friction, upsetting, barreling, Anand model

Procedia PDF Downloads 320

Authors: Grienggrai Rajchakit

Abstract:

As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

Procedia PDF Downloads 145

Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

Abstract:

Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

Procedia PDF Downloads 97

Authors: Kareem Adedokun

Abstract:

Official secrecy is one of the colonial vestiges which upholds non – disclosure of essential information for public consumption. Information, though an indispensable tool in tax administration, is not to be divulged by any person in an official duty of the revenue agency. As a matter o fact, the Federal Inland Revenue Service (Establishment) Act, 2007 emphasizes secrecy and confidentiality in dealing with tax payer’s document, information, returns and assessment in a manner reminiscent of protecting tax payer’s privacy in all situations. It is so serious that any violation attracts criminal sanction. However, Nigeria, being a democratic and egalitarian state recently enacted Freedom of Information Act which heralded in openness in governance and takes away the confidentialities associated with official secrets Laws. Official secrecy no doubts contradicts the philosophy of freedom of information but maintaining a proper balance between protected rights of tax payers and public interest which revenue agency upholds is an uphill task. Adopting the Doctrinal method, therefore, the author of this paper probes into the real nature of the relationship between taxpayers and Revenue Agencies. It also interfaces official secrecy with the doctrine of Freedom of Information and consequently queries the retention of non – disclosure clause under Federal Inland Revenue Service (Establishment) Act (FIRSEA) 2007. The paper finds among others that non – disclosure provision in tax statutes particularly as provided for in FIRSEA is not absolute; so also is the constitutional rights and freedom of information and unless the non – disclosure clause finds justification under any recognized exemption provided under the Freedom of Information Act, its retention is antithesis to democratic ethos and beliefs as it may hinder public interest and public order.

Keywords: confidentiality, information, official secrecy, tax administration

Procedia PDF Downloads 321

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

Abstract:

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

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

Procedia PDF Downloads 131

Authors: Ciwang Teyra, A. H. Y. Lai

Abstract:

Introduction: Indigenous LGBTQ individuals face with significant life stress such as racial and gender discrimination and microaggressions, which may lead to negative impacts of their mental health. Although studies relevant to Taiwanese indigenous LGBTQpeople gradually increase, most of them are primarily conceptual or qualitative in nature. This research aims to fulfill the gap by offering empirical quantitative evidence, especially investigating the impact of racial and gender microaggressions on mental health among Taiwanese indigenous LGBTQindividuals with an intersectional perspective, as well as examine whether social support can help them to cope with microaggressions. Methods: Participants were (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Standardised measurements was used, including Racial Microaggression Scale (10 items), Gender Microaggression Scale (9 items), Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender, and perceived economic hardships. Structural equation modelling (SEM) was employed using Mplus 8.0 with the latent variables of depression and anxiety as outcomes. A main effect SEM model was first established (Model1).To test the moderation effects of perceived social support, an interaction effect model (Model 2) was created with interaction terms entered into Model1. Numerical integration was used with maximum likelihood estimation to estimate the interaction model. Results: Model fit statistics of the Model 1:X2(df)=1308.1 (795), p<.05; CFI/TLI=0.92/0.91; RMSEA=0.06; SRMR=0.06. For Model, the AIC and BIC values of Model 2 improved slightly compared to Model 1(AIC =15631 (Model1) vs. 15629 (Model2); BIC=16098 (Model1) vs. 16103 (Model2)). Model 2 was adopted as the final model. In main effect model 1, racialmicroaggressionand perceived social support were associated with depression and anxiety, but not sexual orientation microaggression(Indigenous microaggression: b = 0.27 for depression; b=0.38 for anxiety; Social support: b=-0.37 for depression; b=-0.34 for anxiety). Thus, an interaction term between social support and indigenous microaggression was added in Model 2. In the final Model 2, indigenous microaggression and perceived social support continues to be statistically significant predictors of both depression and anxiety. Social support moderated the effect of indigenous microaggression of depression (b=-0.22), but not anxiety. All covariates were not statistically significant. Implications: Results indicated that racial microaggressions have a significant impact on indigenous LGBTQ people’s mental health. Social support plays as a crucial role to buffer the negative impact of racial microaggression. To promote indigenous LGBTQ people’s wellbeing, it is important to consider how to support them to develop social support network systems.

Keywords: microaggressions, intersectionality, indigenous population, mental health, social support

Procedia PDF Downloads 134

Authors: L. Torchane

Abstract:

This study is devoted to defining the optimal conditions for the nitriding of pure iron at atmospheric pressure by using NH3-Ar-C3H8 gas mixtures. After studying the mechanisms of phase formation and mass transfer at the gas-solid interface, a mathematical model is developed in order to predict the nitrogen transfer rate in the solid, the ε-carbonitride layer growth rate and the nitrogen and carbon concentration profiles. In order to validate the model and to show its possibilities, it is compared with thermogravimetric experiments, analyses and metallurgical observations (X-ray diffraction, optical microscopy and electron microprobe analysis). Results obtained allow us to demonstrate the sound correlation between the experimental results and the theoretical predictions.

Keywords: gaseous nitrocarburizing, kinetic model, diffusion, layer growth kinetic

Procedia PDF Downloads 521

Authors: Hanlin Liu, Hua Li, Yintan AI

Abstract:

Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

Procedia PDF Downloads 29

Authors: Yuan-Jye Tseng, Ching-Yen Chen

Abstract:

In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

Procedia PDF Downloads 173

Authors: Lazzat M. Zhamaliyeva, Nurgul A. Abenova, Gauhar S. Dilmagambetova, Ziyash Zh. Tanbetova, Moldir B. Ahmetzhanova, Tatyana P. Ostretcova, Aliya A. Yegemberdiyeva

Abstract:

Introduction: There are many reasons for the weak training of family doctors in Kazakhstan: the unified national educational program is not focused on competencies, the role of a general practitioner (GP) is not clear, poor funding for the health care and education system, outdated teaching and assessment methods, inefficient management. We highlight two issues in particular. Firstly, academic teachers of family medicine (FM) in Kazakhstan do not practice as family doctors; most of them are narrow specialists (pediatricians, therapists, surgeons, etc.); they usually hold one-time consultations; clinical mentors from practical healthcare (non-academic teachers) do not have the teaching competences, and the vast majority of them are also narrow specialists. Secondly, clinical sites (polyclinics) are unprepared for general practice and do not follow the principles of family medicine; residents do not like to be in primary health care (PHC) settings due to the chaos that is happening there, as well as due to the lack of the necessary equipment for mastering and consolidating practical skills. Aim: We present the concept of the family physicians’ training office (FPTO), which is being created as a friendly learning environment for young general practitioners and for the involvement of academic teachers of family medicine in the practical work and innovative development of PHC. Methodology: In developing the conceptual framework and identifying practical activities, we drew on literature and expert input, and interviews. Results: The goal of the FPTO is to create a favorable educational and clinical environment for the development of the FM residents’ competencies, in which the residents with academic teachers and clinical mentors could understand and accept the principles of family medicine, improve clinical knowledge and skills, and gain experience in improving the quality of their practice in scientific basis. Three main areas of office activity are providing primary care to the patients, improving educational services for FM residents and other medical workers, and promoting research in PHC and innovations. The office arranges for residents to see outpatients at least 50% of the time, and teachers of FM departments at least 1/4 of their working time conduct general medical appointments next to residents. Taking into account the educational and scientific workload, the number of attached population for one GP does not exceed 500 persons. The equipment of the office allows FPTO workers to perform invasive and other manipulations without being sent to other clinics. In the office, training for residents is focused on their needs and aimed at achieving the required level of competence. International methodologies and assessment tools are adapted to local conditions and evaluated for their effectiveness and acceptability. Residents and their faculty actively conduct research in the field of family medicine. Conclusions: We propose to change the learning environment in order to create teams of like-minded people, to unite residents and teachers even more for the development of family medicine. The offices will also invest resources in developing and maintaining young doctors' interest in family medicine.

Keywords: educational environment, family medicine residents, family physicians’ training office, primary care research

Procedia PDF Downloads 125

Authors: Zhou Hong, Gu Xiao-Qing, Lıu Hong-Jiao, Leng Jing

Abstract:

Seamless learning is becoming a research hotspot in recent years, and the emerging of micro-lectures, flipped classroom has strengthened the development of seamless learning. Based on the characteristics of the seamless learning across time and space and the course structure of the flipped classroom, and the theories of language learning, we put forward the language learning model which can support ‘seamless flipped’ environment (abbreviated as ‘S-F’). Meanwhile, the characteristics of the ‘S-F’ learning environment, the corresponding framework construction and the activity design of diversified corpora were introduced. Moreover, a language learning app named ‘Daily Speaking’ was developed to facilitate the practice of the language learning model in ‘S-F’ environment. In virtue of the learning case of Shanghai language, the rationality and feasibility of this framework were examined, expecting to provide a reference for the design of ‘S-F’ learning in different situations.

Keywords: seamless learning, flipped classroom, seamless-flipped environment, language learning model

Procedia PDF Downloads 174

Authors: Hassnen M. Jafer, Khalid S. Hashim, W. Atherton, Ali W. Alattabi

Abstract:

This study investigates the effect of two important parameters (length of curing period and percentage of the added binder) on the strength of soil treated with OPC. An intermediate plasticity silty clayey soil with medium organic content was used in this study. This soft soil was treated with different percentages of a commercially available cement type 32.5-N. laboratory experiments were carried out on the soil treated with 0, 1.5, 3, 6, 9, and 12% OPC by the dry weight to determine the effect of OPC on the compaction parameters, consistency limits, and the compressive strength. Unconfined compressive strength (UCS) test was carried out on cement-treated specimens after exposing them to different curing periods (1, 3, 7, 14, 28, and 90 days). The results of UCS test were used to develop a non-linear multi-regression model to find the relationship between the predicted and the measured maximum compressive strength of the treated soil (qu). The results indicated that there was a significant improvement in the index of plasticity (IP) by treating with OPC; IP was decreased from 20.2 to 14.1 by using 12% of OPC; this percentage was enough to increase the UCS of the treated soil up to 1362 kPa after 90 days of curing. With respect to the statistical model of the predicted qu, the results showed that the regression coefficients (R2) was equal to 0.8534 which indicates a good reproducibility for the constructed model.

Keywords: cement admixtures, soft soil stabilisation, geotechnical parameters, multi-regression model

Procedia PDF Downloads 352

Authors: Lotfi O. Gargab, Ruichong R. Zhang

Abstract:

A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

Procedia PDF Downloads 364

Authors: Sonia Besbes, Mahmoud El Hajem, Habib Ben Aissia, Jean Yves Champagne, Jacques Jay

Abstract:

In this work, we present a computational study for the characterization of the flow in a rectangular bubble column. To simulate the dynamic characteristics of the flow, a three-dimensional transient numerical simulations based on a coupled discrete phase model (DPM) and Volume of Fluid (VOF) model are performed. Modeling of bubble column reactor is often carried out under the assumption of a flat liquid surface with a degassing boundary condition. However, the dynamic behavior of the top surface surmounting the liquid phase will to some extent influence the meandering oscillations of the bubble plume. Therefore it is important to capture the surface behavior, and the assumption of a flat surface may not be applicable. So, the modeling approach needs to account for a dynamic liquid surface induced by the rising bubble plume. The volume of fluid (VOF) model was applied for the liquid and top gas which both interacts with bubbles implemented with a discrete phase model. This model treats the bubbles as Lagrangian particles and the liquid and the top gas as Eulerian phases with a sharp interface. Two-way coupling between Eulerian phases and Lagrangian bubbles are accounted for in a single set continuous phase momentum equation for the mixture of the two Eulerian phases. The effect of gas flow rate on the dynamic and time-averaged flow properties was studied. The time averaged liquid velocity field predicted from simulations and from our previous PIV measurements shows that the liquid is entrained up flow in the wake of the bubbles and down flow near the walls. The simulated and measured vertical velocity profiles exhibit a reasonable agreement looking at the minimum velocity values near the walls and the maximum values at the column center.

Keywords: bubble column, computational fluid dynamics (CFD), coupled DPM and VOF model, hydrodynamics

Procedia PDF Downloads 375