Search results for: comprehensive model

Authors: Junyou Shi, Weiwei Cui

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Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.

Keywords: fault detection, fault isolation, testability modeling, BIT

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Authors: Suraj Sharma

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Green infrastructure (GI) offers a contemporary approach for reducing the risk of flooding, improve water quality, and harvesting stormwater for sustainable use. GI promotes landscape planning to enhance sustainable development and urban resilience. However, the existing literature is lacking in ensuring the comprehensive assessment of GI performance in terms of ecosystem function and services for social, ecological, and economical system resilience. We propose a robust indicator set and fuzzy comprehensive evaluation (FCE) for quantitative and qualitative analysis for sustainable water management to assess the capacity of urban resilience. Green infrastructure in urban resilience water management system (GIUR-WMS) supports decision-making for GI planning through scenario comparisons with urban resilience capacity index. To demonstrate the GIUR-WMS, we develop five scenarios for five sectors of Chandigarh (12, 26, 14, 17, and 34) to test common type of GI (rain barrel, rain gardens, detention basins, porous pavements, and open spaces). The result shows the open spaces achieve the highest green infrastructure urban resilience index of 4.22/5. To implement the open space scenario in urban sites, suitable vacant can be converted to green spaces (example: forest, low impact recreation areas, and detention basins) GIUR-WMS is easy to replicate, customize and apply to cities of different sizes to assess environmental, social and ecological dimensions.

Keywords: green infrastructure, assessment, urban resilience, water management system, fuzzy comprehensive evaluation

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.

Keywords: runoff, roughness coefficient, PAR, WRM model

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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Authors: Fatemeh Jannesarvatan, Ghazaal Parastooei, Jimmy frerejan, Saedeh Mokhtari, Peter Van Rosmalen

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Medical and dental education increasingly emphasizes the acquisition, integration, and coordination of complex knowledge, skills, and attitudes that can be applied in practical situations. Instructional design approaches have focused on using real-life tasks in order to facilitate complex learning in both real and simulated environments. The Four component instructional design (4C/ID) model has become a useful guideline for designing instructional materials that improve learning transfer, especially in health profession education. The objective of this study was to apply the 4C/ID model in the creation of virtual patients (VPs) that dental students can use to practice their clinical management and clinical reasoning skills. The study first explored the context and concept of complication factors and common errors for novices and how they can affect the design of a virtual patient program. The study then selected key dental information and considered the content needs of dental students. The design of virtual patients was based on the 4C/ID model's fundamental principles, which included: Designing learning tasks that reflect real patient scenarios and applying different levels of task complexity to challenge students to apply their knowledge and skills in different contexts. Creating varied learning materials that support students during the VP program and are closely integrated with the learning tasks and students' curricula. Cognitive feedback was provided at different levels of the program. Providing procedural information where students followed a step-by-step process from history taking to writing a comprehensive treatment plan. Four virtual patients were designed using the 4C/ID model's principles, and an experimental design was used to test the effectiveness of the principles in achieving the intended educational outcomes. The 4C/ID model provides an effective framework for designing engaging and successful virtual patients that support the transfer of knowledge and skills for dental students. However, there are some challenges and pitfalls that instructional designers should take into account when developing these educational tools.

Keywords: 4C/ID model, virtual patients, education, dental, instructional design

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Authors: Adji Achmad Rinaldo Fernandes

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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

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Authors: Antero J. S. Kivinen, Suvi-Sadetta Kaarakainen

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Digitalization touches every aspect of contemporary society, changing the way we live our everyday life. Contemporary society is sometimes described as knowledge society including unprecedented amount of information people face daily. The tools to manage this information flow are ICT-skills which are both technical skills and reflective skills needed to manage incoming information. Therefore schools are under constant pressure of revision. In the latest Programme for International Student Assessment (PISA) girls have been outperforming boys in all Organization for Economic Co-operation and Development (OECD) member countries and the gender gap between girls and boys is widest in Finland. This paper presents results of the Comprehensive Schools in the Digital Age project of RUSE, University of Turku. The project is in connection with Finnish Government Analysis, Assessment and Research Activities. First of all, this paper examines gender differences in ICT-skills of Finnish upper comprehensive school students. Secondly, it explores in which way differences are changing when students proceed to upper secondary and vocational education. ICT skills are measured using a performance-based ICT-skill test. Data is collected in 3 phases, January-March 2017 (upper comprehensive schools, n=5455), September-December 2017 (upper secondary and vocational schools, n~3500) and January-March 2018 (Upper comprehensive schools). The age of upper comprehensive school student’s is 15-16 and upper secondary and vocational school 16-18. The test is divided into 6 categories: basic operations, productivity software, social networking and communication, content creation and publishing, applications and requirements for the ICT study programs. Students have filled a survey about their ICT-usage and study materials they use in school and home. Cronbach's alpha was used to estimate the reliability of the ICT skill test. Statistical differences between genders were examined using two-tailed independent samples t-test. Results of first data from upper comprehensive schools show that there is no statistically significant difference in ICT-skill tests total scores between genders (boys 10.24 and girls 10.64, maximum being 36). Although, there were no gender difference in total test scores, there are differences in above mentioned six categories. Girls get better scores on school related and social networking test subjects while boys perform better on more technical oriented subjects. Test scores on basic operations are quite low for both groups. Perhaps these can partly be explained by the fact that the test was made on computers and majority of students ICT-usage consist of smartphones and tablets. Against this background it is important to analyze further the reasons for these differences. In a context of ongoing digitalization of everyday life and especially working life, the significant purpose of this analyses is to find answers how to guarantee the adequate ICT skills for all students.

Keywords: basic education, digitalization, gender differences, ICT-skills, upper comprehensive education, upper secondary education, vocational education

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Authors: Shreyas Jayasimha, Suneel Anand Sundharesan, Rohan Tigadi

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In the recent past, the United States of America and Russia were the only two dominant players in the field of space exploration and had a virtual monopoly in the field of space and technology. However, this has changed over the past few years. Many other nation states such as India, China, and the UK have made significant progress in this field. Amongst these nations, the growth and development of the Indian space program have been nothing short of a miracle. Starting recently, India has successfully launched a series of satellites including its much acclaimed Mangalyaan mission, which placed a satellite in Mars’ orbit. The fact that India was able to attain this feat in its attempt demonstrates the enormous growth potential and promise that the Indian space program holds for the coming years. However, unlike other space-faring nations, India does not have a comprehensive and consolidated space insurance policy. In this regard, it is pertinent to note that, the costs and risks involved in a administering a space program are enormous. Therefore, in the absence of a comprehensive space insurance policy, any losses from an unsuccessful will have to be borne by the state exchequer. Thus, in order to ensure that Indian space program continues on its upward trajectory, the Indian establishment should seriously consider formulating a comprehensive insurance policy. This paper intends to analyze the international best practices followed by other space-faring nations in relation to space insurance policy. Thereafter, the authors seek to examine the current regime in India relating to space insurance policy. Finally, the authors will conclude by providing a series of recommendations regarding the essential elements that should be part of any Indian space insurance policy regime.

Keywords: India, space insurance policy, space law, Indian space research organization

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Authors: Abd Alati Ali Abushnaq, Malek Essnni, Abduraouf Eteer

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The present study proposes a comprehensive approach to effectively utilize associated gas from the KK remote station, eliminating the practice of flaring and mitigating greenhouse gas (GHG) emissions. The proposed integrated system involves diverting the associated gas via a newly designed pipeline, seamlessly connecting to the existing 12-inch pipeline at the tie-in point. The proposed destination is the low-pressure system at A-100 or 3rd stage, where the associated gas will be channeled towards the NGL (natural gas liquid) plant for processing. To ensure the system's efficacy under varying gas production scenarios, the study employs two industry-standard simulation software packages, Aspen HYSYS and PIPSIM. The simulated results demonstrate the system's ability to handle the projected increase in gas production, reaching up to 38 MMSCFD. This comprehensive analysis ensures the system's robustness and adaptability to future production demands.

Keywords: associated gas, flaring mitigation, GHG emissions, pipeline diversion, NGL plant, KK remote station, production forecasting, Aspen HYSYS, PIPSIM

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Authors: Peter Shi

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Algorithmic trading is a rapidly expanding domain within quantitative finance, constituting a substantial portion of trading volumes in the US financial market. The demand for rigorous and robust mathematical theories underpinning these trading algorithms is ever-growing. In this study, the author establishes a new stock market model that integrates the Efficient Market Hypothesis and the statistical arbitrage. The model, for the first time, finds probabilistic relations between the rational price and the market price in terms of the conditional expectation. The theory consequently leads to a mathematical justification of the old market adage: buy-low and sell-high. The thresholds for “low” and “high” are precisely derived using a max-min operation on Bayes’s error. This explicit connection harmonizes the Efficient Market Hypothesis and Statistical Arbitrage, demonstrating their compatibility in explaining market dynamics. The amalgamation represents a pioneering contribution to quantitative finance. The study culminates in comprehensive numerical tests using historical market data, affirming that the “buy-low” and “sell-high” algorithm derived from this theory significantly outperforms the general market over the long term in four out of six distinct market environments.

Keywords: efficient market hypothesis, behavioral finance, Bayes' decision, algorithmic trading, risk control, stock market

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Dina Tamazin, Nicoleta Tipi, Sahar Validi

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The oil refining industry plays vital role in the world economy. Oil refining companies operate in a more complex and dynamic environment than ever before. In addition, oil refining companies and the public are becoming more conscious of crude oil scarcity and climate changes. Hence, sustainability in the oil refining industry is becoming increasingly critical to the industry's long-term viability and to the environmental sustainability. Mainly, it is relevant to the measurement and evaluation of the company's sustainable performance to support the company in understanding their performance and its implication more objectively and establishing sustainability development plans. Consequently, the oil refining companies attempt to re-engineer their supply chain to meet the sustainable goals and standards. On the other hand, this research realized that previous research in oil refining sustainable supply chain performance measurements reveals that there is a lack of studies that consider the integration of sustainability in the supply chain performance measurement practices in the oil refining industry. Therefore, there is a need for research that provides performance guidance, which can be used to measure sustainability and assist in setting sustainable goals for oil refining supply chains. Accordingly, this paper aims to present a comprehensive oil refining sustainable supply chain performance measurement theoretical framework. In development of this theoretical framework, the main characteristics of oil refining industry have been identified. For this purpose, a thorough review of relevant literature on performance measurement models and sustainable supply chain performance measurement models has been conducted. The comprehensive oil refining sustainable supply chain performance measurement theoretical framework introduced in this paper aims to assist oil refining companies in measuring and evaluating their performance from a sustainability aspect to achieve sustainable operational excellence.

Keywords: oil refining industry, oil refining sustainable supply chain, performance measurement, sustainability

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Sanja Šurdonja, Aleksandra Deluka-Tibljaš, Mirna Klobučar, Irena Ištoka Otković

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Roundabouts are a common choice in the case of reconstruction of an intersection, whether it is to improve the capacity of the intersection or traffic safety, especially in urban conditions. The regulation for the design of roundabouts is often related to driving culture, the tradition of using this type of intersection, etc. Individual values in the regulation are usually recommended in a wide range (this is the case in Croatian regulation), and the final design of a roundabout largely depends on the designer's experience and his/her choice of design elements. Therefore, before-after analyses are a good way to monitor the performance of roundabouts and possibly improve the recommendations of the regulation. This paper presents a comprehensive before-after analysis of a roundabout on the country road network near Rijeka, Croatia. The analysis is based on a thorough collection of traffic data (operating speeds and traffic load) and design elements data, both before and after the reconstruction into a roundabout. At the chosen location, the roundabout solution aimed to improve capacity and traffic safety. Therefore, the paper analyzed the collected data to see if the roundabout achieved the expected effect. A traffic microsimulation model (VISSIM) of the roundabout was created based on the real collected data, and the influence of the increase of traffic load and different traffic structures, as well as of the selected design elements on the capacity of the roundabout, were analyzed. Also, through the analysis of operating speeds and potential conflicts by application of the Surrogate Safety Assessment Model (SSAM), the traffic safety effect of the roundabout was analyzed. The results of this research show the practical value of before-after analysis as an indicator of roundabout effectiveness at a specific location. The application of a microsimulation model provides a practical method for analyzing intersection functionality from a capacity and safety perspective in present and changed traffic and design conditions.

Keywords: before-after analysis, operating speed, capacity, design.

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Authors: Daniel Osorio, Janneth Gonzalez, Andres Pinzon

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In this work, proteins and metabolic pathways associated with the neuroprotective response mediated by the synthetic neurosteroid tibolone under a palmitate-induced inflammatory model were identified by flux balance analysis (FBA). Three different metabolic scenarios (‘healthy’, ‘inflamed’ and ‘medicated’) were modeled over a gene expression data-driven constructed tissue-specific metabolic reconstruction of mature astrocytes. Astrocyte reconstruction was built, validated and constrained using three open source software packages (‘minval’, ‘g2f’ and ‘exp2flux’) released through the Comprehensive R Archive Network repositories during the development of this work. From our analysis, we predict that tibolone executes their neuroprotective effects through a reduction of neurotoxicity mediated by L-glutamate in astrocytes, inducing the activation several metabolic pathways with neuroprotective actions associated such as taurine metabolism, gluconeogenesis, calcium and the Peroxisome Proliferator Activated Receptor signaling pathways. Also, we found a tibolone associated increase in growth rate probably in concordance with previously reported side effects of steroid compounds in other human cell types.

Keywords: astrocytes, flux balance analysis, genome scale metabolic reconstruction, inflammation, neuroprotection, tibolone

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Authors: Christian Louis Kühner, Florian Pfeffel, Valentin Nickolai

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Taking care of children, dependents, or pets can be a difficult and time-consuming task. Especially for part- and full-time employees, it can feel exhausting and overwhelming to meet these obligations besides working a job. Thus, working mostly at home and not having to drive to the company can save valuable time and stress. This study aims to show the influence that the working model has on the job satisfaction of employees with care responsibilities in comparison to employees who do not have such obligations. Using structural equation modeling (SEM), the three work models, “work from home”, “working remotely”, and a hybrid model, have been analyzed based on 13 influencing constructs on job satisfaction. These 13 factors have been further summarized into three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, an online survey was conducted with n = 684 employees from the service sector. Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. In addition, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that among the employees with care responsibilities, the higher the proportion of working from home in comparison to working from the office, the more satisfied the employees are with their job. Since the work models that meet the requirements of comprehensive care led to higher job satisfaction amongst employees with such obligations, adapting as a company to such private obligations by employees can be crucial to sustained success. Conversely, the satisfaction level of the working model where employees work at the office is higher for workers without caregiving responsibilities.

Keywords: care responsibilities, home office, job satisfaction, structural equation modeling

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: Rohit Sane, Pravin Ghadigaonkar, Purvi Ahuja, Suvarna Tirmare, Archana Kelhe, Kranti Shinde, Rahul Mandole

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To evaluate the efficacy of Comprehensive Diabetic Care Program with the reduction of HbA1c in overweight Diabetes Mellitus Type II patients retrospectively. Methods: Retrospective study was carried out on 34 overweight type II diabetic patients (Mean Age = 54.58 ±11.38 yrs). A total of 34 patients were enrolled after screening of 68 patients (HbA1c 7-10%). The patients were on concomitant drugs namely insulin (11.76%), DPP-4 inhibitor (17.64%), Biguanide (55.88%), Sulfonylurea (52.94%), thiazolidinedione (11.76%), other medications (20.58%) and no allopathic medications (14.70%). The patients were given Comprehensive Diabetic Care Program consisting of panchkarma procedures namely snehana (external oleation), swedana (passive heat therapy) and basti (enema), which was completed in 15 sittings. During the therapy and next 90 days, the patients followed low carbohydrate and moderate protein & fat diet. The primary endpoint of this study was the evaluation of reduction in HbA1c at the end of the follow-up after 90 days. Results: Thirty-four overweight type II diabetic patients (mean age: 54.58[±11.38], HbA1c[7-10%], 67.64% male and 32.35% female) were enrolled in the study. A significant reduction was observed in HbA1c levels (14.30%, p<0.05) at the end of the 90 days follow-up as compared to baseline. Also, BMI was reduced by 5.87%. There was reduction in the usage of the concomitant drugs namely insulin (2.94%), DPP-4 inhibitor (2.94%), Biguanide (32.35%), Sulfonylurea (35.29%), thiazolidinedione (5.88%), other medications(17.64%) and no allopathic medications (32.35%). Conclusion: The results of the study highlight not only in the reduction of HbA1c, but also in BMI and drug tapering of the CDC program in the overweight type II diabetic patients with HbA1c (7-10%).

Keywords: HbA1c, low carb diet, Panchakarma therapy, Type II Diabetes

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Authors: Adam Y. Sulaiman, Donal F. Cotter, Ming J. Huang, Neil J. Hewitt

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Suitable low global warming potential (GWP) refrigerants that conform to F-gas regulations are required to extend the operational envelope of high-temperature heat pumps (HTHPs) used for industrial waste heat recovery processes. The thermophysical properties and characteristics of these working fluids need to be assessed to provide a comprehensive understanding of operational effectiveness in HTHP applications. This paper presents the results of a theoretical simulation to investigate a range of low-GWP refrigerants and their suitability to supersede refrigerants HFC-245fa and HFC-365mfc. A steady-state thermodynamic model of a single-stage HTHP with an internal heat exchanger (IHX) was developed to assess system cycle characteristics at temperature ranges between 50 to 80 °C heat source and 90 to 150 °C heat sink. A practical approach to maximize the operational efficiency was examined to determine the effects of regulating minimum superheat within the process and subsequent influence on energetic and exergetic efficiencies. A comprehensive map of minimum superheat across the HTHP operating variables were used to assess specific tipping points in performance at 30 and 70 K temperature lifts. Based on initial results, the refrigerants HCFO-1233zd(E) and HFO-1336mzz(Z) were found to be closely aligned matches for refrigerants HFC-245fa and HFC-365mfc. The overall results show effective performance for HCFO-1233zd(E) occurs between 5-7 K minimum superheat, and HFO-1336mzz(Z) between 18-21 K dependant on temperature lift. This work provides a method to optimize refrigerant selection based on operational indicators to maximize overall HTHPs system performance.

Keywords: high-temperature heat pump, minimum superheat, energy & exergy efficiency, low GWP refrigerants

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Authors: Young-Kwang Lee, Eun-Gu Ji, Min-Joo Kim, Seung-Jae Oh

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The purpose of this study is to develop a social participation activity scale for the elderly. As a result of exploratory factor analysis, confirmatory factor analysis was conducted using maximum likelihood method using bundled items. In conclusion, thirteen items of social participation activity scale seemed appropriate. Finally, convergent validity and discriminant validity were verified on the scale with the fit. The convergent validity was based on the variance extracted value. In other words, the hypothesis that the variables are the same is rejected and the validity is confirmed. This study extensively considered the measurement items of the social participation activity scale used to measure social participation activities of the elderly. In the future, it will be meaningful that it can be used as a tool to verify the effectiveness of services in organizations that provide social welfare services to elderly people such as comprehensive social welfare centers and the elderly comprehensive social welfare centers.

Keywords: elderly, social participation, scale development, validity

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Authors: Arezoo Fallahi

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Background and purpose: Non-alcoholic fatty liver is one of the most common liver disorders, which, as the most important cause of death from liver disease, has unpleasant consequences and complications. The aim of this study was to investigate the effect of an educational intervention based on a health belief model to prevent non-alcoholic fatty liver among women. Materials and Methods: This experimental study was performed among 110 women referring to comprehensive health service centers in Malayer City, west of Iran, in 2023. Using the available sampling method, 110 Participants were divided into experimental and control groups. The data collection tool included demographic characteristics and a questionnaire based on the health belief model. In The experimental group, three one-hour training sessions were conducted in the form of pamphlets, lectures and group discussions. Data were analyzed using SPSS software version 21, by correlation tests, paired t-tests independent t-tests. Results: The mean age of participants was 38.07±6.28 years, and Most of the participants were middle-aged, married, housewives with academic education, middle-income and overweight. After the educational intervention, the mean scores of the constructs include perceived sensitivity (p=0.01), perceived severity (p=0.01), perceived benefits (p=0.01), guidance for internal (p=0.01) and external action (p=0.01), and perceived self-efficacy (p=0.01) in the experimental group were significantly higher than the control group. The score of perceived barriers in the experimental group decreased after training. The perceived obstacles score in the test group decreased after the training (15.2 ± 3.9 v.s 11.2 ± 3.3, (p<0.01). Conclusion: The findings of the study showed that the design and implementation of educational programs based on the constructs of the health belief model can be effective in preventing women from developing higher levels of non-alcoholic fatty liver.

Keywords: health, education, believe, behaviour

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Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

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In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

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Authors: J. Rhodes, V. Cheng, P. Lok

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The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

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Authors: Ahmad Sarfaraz, Raiyad Herwies

Abstract:

In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

Abstract:

The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

Abstract:

In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Givi Kupatadze

Abstract:

Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.

Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities

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Authors: Maria Komal, Zaineb Khalil, Mehreen Sirshar

Abstract:

Due to the recent technological advancements, Games have become one of the most demanding applications. Gaming industry is rapidly growing and the key to success in this industry is the development of good quality games, which is a highly competitive issue. The ultimate goal of game developers is to provide player’s satisfaction by developing high-quality games. This research is the comprehensive survey of techniques followed by game industries to ensure games quality. After analysis of various techniques, it has been found that quality simulation according to ISO standards and play test methods are used to ensure games quality. Because game development requires cross-disciplined team, an increasing trend towards distributed game development has been observed. This paper evaluates the strengths and weaknesses of current methodologies used in game industry and draws a conclusion. We have also proposed quality parameters which can be used as a heuristic framework to identify those attributes which have high testing priorities.

Keywords: game development, computer games, video games, gaming industry, quality assurance, playability, user experience

Procedia PDF Downloads 528