Search results for: independent RBF model

Authors: Emad A. S. Abu-Ayyash

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Cohesive devices, the linguistic tools that are usually employed to hold the different parts of the text together, have been the focus of a significant number of discourse analysis studies. These linguistic tools have grabbed the attention of researchers since the inception of the first and most comprehensive model of cohesion in 1976. However, it was noticed that some cohesive devices (e.g., endophoric reference, conjunctions, ellipsis, substitution, and lexical ties) – being thought of as more popular than others (e.g., exophoric reference) – were over-researched. The present paper explores the usage of two cohesive devices that have been evidently almost absent from discourse analysis studies. These cohesive devices are exophoric and homophoric references, the linguistic items that can be interpreted in terms of the physical and cultural contexts of discourse. The significance of the current paper, therefore, stems from the fact that it attempts to fill a gap in the research conducted so far on cohesive devices. This study provides an explanation of the concepts of the cohesive devices that have been employed in a plethora of research on cohesion and elucidates the relevant context-related concepts. The paper also identifies the gap in cohesive devices research. Exophora and homophora, the least visited cohesive devices in previous studies, were qualitatively and quantitatively explored in six opinion articles, four produced by eight postgraduate English as a Foreign Language (EFL) students in a university in the United Arab Emirates and two by professional NS writers in the Independent and the Guardian. The six pieces were about the United Kingdom Independent Party (UKIP) leader’s call to ban the burqa in the UK and were analysed vis-a-vis the employment and function of homophora and exophora. The study found that both EFL students and native speakers employed exophora and homophora considerably in their writing to serve a variety of functions, including building assumptions, supporting main ideas, and involving the readers among others.

Keywords: cohesive devices, context, culture, exophoric reference, homophoric reference

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Authors: Hui Liu, Xiaozan Wang, Jiarong Zhong, Ziming Shao

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Introduction: Related research shows that students don’t concentrate on teacher’s speaking in the classroom. The d2 attention test is a time-limited test about selective attention. The d2 attention test can be used to evaluate individual selective attention. Purpose: To use the d2 attention test tool to measure the difference between the attention level of the experimental class and the control class before and after Brain-Break and to explore the effect of Brain-Break in the classroom on students' selective attention. Methods: According to the principle of no difference in pre-test data, two classes in the fourth- grade of Shenzhen Longhua Central Primary School were selected. After 20 minutes of class in the third class in the morning and the third class in the afternoon, about 3-minute Brain-Break intervention was performed in the experimental class for 10 weeks. The normal class in the control class did not intervene. Before and after the experiment, the d2 attention test tool was used to test the attention level of the two-class students. The paired sample t-test and independent sample t-test in SPSS 23.0 was used to test the change in the attention level of the two-class classes around 10 weeks. This article only presents results with significant differences. Results: The independent sample t-test results showed that after ten-week of Brain-Break, the missed errors (E1 t = -2.165 p = 0.042), concentration performance (CP t = 1.866 p = 0.05), and the degree of omissions (Epercent t = -2.375 p = 0.029) in experimental class showed significant differences compared with control class. The students’ error level decreased and the concentration increased. Conclusions: Adding Brain-Break interventions in the classroom can effectively improve the attention level of fourth-grade primary school students to a certain extent, especially can improve the concentration of attention and decrease the error rate in the tasks. The new sport's learning model is worth promoting

Keywords: cultural class, micromotor, attention, D2 test

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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: Ilyasu G., Ogoina D., Otu AA, Muhammed FD, Ebenso B., Otokpa D., Rotifa S., Tuduo-Wisdom O., Habib AG

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Background: The 2014 Ebola Virus Disease (EVD) outbreak was characterized by fear, misconceptions and irrational behaviors. We conducted a knowledge attitude and practice survey of EVD in Nigeria to inform the institution of effective control measures. Methods: Between July 30th and September 30th 2014, a cross-sectional study on knowledge, attitude and practice (KAP) of Ebola Virus Disease (EVD) was undertaken among adults of the general population and healthcare workers (HCW) in three states of Nigeria, including Kano, Cross River and Bayelsa states. Demographic information and data on KAP were obtained using a self-administered standardized questionnaire. The percentage KAP scores were categorized as good and poor. Independent predictors of good knowledge of EVD were ascertained using a binary logistic regression model. Results: Out of 1035 study participants with a median age of 32 years, 648 (62.6%) were males, 846 (81.7%) had tertiary education and 441 (42.6%) were HCW. There were 218, 239 and 578 respondents from Bayelsa, Cross Rivers, and Kano states, respectively. The overall median percentage KAP scores and interquartile ranges (IQR) were 79.46% (15.07%), 95.0% (33.33%), and 49.95% (37.50%), respectively. Out of the 1035 respondents, 470 (45.4%), 544(52.56%), and 252 (24.35%) had good KAP of EVD defined using 80%, 90%, and 70% score cut-offs, respectively. Independent predictors of good knowledge of EVD were a HCW (Odds Ratio-OR-2.89, 95% Confidence interval-CI of 1.41-5.90), reporting ‘moderate to high fear of EVD’ (OR-2.15, 95% CI-1.47-3.13) and ‘willingness to modify habit’ (OR-1.68, 95% CI-1.23-2.30). Conclusion: Our results reveal suboptimal EVD-related knowledge, attitude and practice among adults in Nigeria. To effectively control future outbreaks of EVD in Nigeria, there is a need to institute public sensitization programs that improve understanding of EVD and address EVD-related myths and misconceptions, especially among the general population.

Keywords: Ebola, health care worker, knowledge, attitude

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate is questioned as a risk factor for weight gain. The relations between basal metabolic rate and body composition have not been cleared yet. The impact of fat mass on basal metabolic rate is also uncertain. Within this context, indices based upon total body mass as well as total body fat mass are available. In this study, the aim is to investigate the potential clinical utility of these indices in the adult population. 287 individuals, aged from 18 to 79 years, were included into the scope of the study. Based upon body mass index values, 10 underweight, 88 normal, 88 overweight, 81 obese, and 20 morbid obese individuals participated. Anthropometric measurements including height (m), and weight (kg) were performed. Body mass index, diagnostic obesity notation model assessment index I, diagnostic obesity notation model assessment index II, basal metabolic rate-to-weight ratio were calculated. Total body fat mass (kg), fat percent (%), basal metabolic rate, metabolic age, visceral adiposity, fat mass of upper as well as lower extremities and trunk, obesity degree were measured by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical evaluations were performed by statistical package (SPSS) for Windows Version 16.0. Scatterplots of individual measurements for the parameters concerning correlations were drawn. Linear regression lines were displayed. The statistical significance degree was accepted as p < 0.05. The strong correlations between body mass index and diagnostic obesity notation model assessment index I as well as diagnostic obesity notation model assessment index II were obtained (p < 0.001). A much stronger correlation was detected between basal metabolic rate and diagnostic obesity notation model assessment index I in comparison with that calculated for basal metabolic rate and body mass index (p < 0.001). Upon consideration of the associations between basal metabolic rate-to-weight ratio and these three indices, the best association was observed between basal metabolic rate-to-weight and diagnostic obesity notation model assessment index II. In a similar manner, this index was highly correlated with fat percent (p < 0.001). Being independent of the indices, a strong correlation was found between fat percent and basal metabolic rate-to-weight ratio (p < 0.001). Visceral adiposity was much strongly correlated with metabolic age when compared to that with chronological age (p < 0.001). In conclusion, all three indices were associated with metabolic age, but not with chronological age. Diagnostic obesity notation model assessment index II values were highly correlated with body mass index values throughout all ranges starting with underweight going towards morbid obesity. This index is the best in terms of its association with basal metabolic rate-to-weight ratio, which can be interpreted as basal metabolic rate unit.

Keywords: basal metabolic rate, body mass index, children, diagnostic obesity notation model assessment index, obesity

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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: 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: Alon Cohen, Jeffrey Kantor, Shalom Levy

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The use of the audit risk model in auditing has faced limitations and difficulties, leading auditors to rely on a conceptual level of its application. The qualitative approach to assessing risks has resulted in different risk assessments, affecting the quality of audits and decision-making on the adoption of CAATTs. This study aims to investigate risk factors impacting the implementation of the audit risk model and propose a complementary risk-based instrument (KRIs) to form substance risk judgments and mitigate against heightened risk of material misstatement (RMM). The study addresses the question of how risk factors impact the implementation of the audit risk model, improve risk judgments, and aid in the adoption of CAATTs. The study uses a three-stage scale development procedure involving a pretest and subsequent study with two independent samples. The pretest involves an exploratory factor analysis, while the subsequent study employs confirmatory factor analysis for construct validation. Additionally, the authors test the ability of the KRIs to predict audit efforts needed to mitigate against heightened RMM. Data was collected through two independent samples involving 767 participants. The collected data was analyzed using exploratory factor analysis and confirmatory factor analysis to assess scale validity and construct validation. The suggested KRIs, comprising two risk components and seventeen risk items, are found to have high predictive power in determining audit efforts needed to reduce RMM. The study validates the suggested KRIs as an effective instrument for risk assessment and decision-making on the adoption of CAATTs. This study contributes to the existing literature by implementing a holistic approach to risk assessment and providing a quantitative expression of assessed risks. It bridges the gap between intuitive risk evaluation and the theoretical domain, clarifying the mechanism of risk assessments. It also helps improve the uniformity and quality of risk assessments, aiding audit standard-setters in issuing updated guidelines on CAATT adoption. A few limitations and recommendations for future research should be mentioned. First, the process of developing the scale was conducted in the Israeli auditing market, which follows the International Standards on Auditing (ISAs). Although ISAs are adopted in European countries, for greater generalization, future studies could focus on other countries that adopt additional or local auditing standards. Second, this study revealed risk factors that have a material impact on the assessed risk. However, there could be additional risk factors that influence the assessment of the RMM. Therefore, future research could investigate other risk segments, such as operational and financial risks, to bring a broader generalizability to our results. Third, although the sample size in this study fits acceptable scale development procedures and enables drawing conclusions from the body of research, future research may develop standardized measures based on larger samples to reduce the generation of equivocal results and suggest an extended risk model.

Keywords: audit risk model, audit efforts, CAATTs adoption, key risk indicators, sustainability

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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: Saad Bin Nasir

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The research will examine the role of corporate governance (CG) practices on firm’s financial performance. Population of this research will be manufacture sector of Pakistan. For the purposes of measurement of impact of corporate governance practices such as board size, board independence, ceo/chairman duality, will take as independent variables and for the measurement of firm’s performance return on assets and return on equity will take as dependent variables. Panel data regression model will be used to estimate the impact of CG on firm performance.

Keywords: corporate governance, board size, board independence, leadership

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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: Cassandra Springate, Alexandra Furber, Jack E. Hines

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Objectives: To create an evidence map of the cost-utility studies available with non-small cell lung cancer patients, and identify the geographical settings and interventions used. Methods: Using the Disease, Study Type, and Model Type filters in heoro.com we identified all cost-utility studies published between 1960 and 2017 with patients with non-small cell lung cancer. These papers were then indexed according to pre-specified categories. Results: Heoro.com identified 89 independent publications, published between 1995 and 2017. Of the 89 papers, 74 were published since 2010, 28 were from the USA, and 35 were from Europe, 16 of which were from the UK. Other publications were from China and Japan (13), Canada (9), Australia and New Zealand (4), and other countries (8). Fifty-nine studies included a chemotherapy intervention, of which 23 included erlotinib or gefitinib, 21 included pemetrexed or docetaxel, others included nivolumab (3), pembrolizumab (2), crizotinib (2), denosumab (2), necitumumab (1), and bevacizumab (1). Also, 19 studies modeled screening, staging, or surveillance strategies. Conclusions: The cost-utility studies found for NSCLC most commonly looked at the effectiveness of different chemotherapy treatments, with some also evaluating the addition of screening strategies. Most were also conducted with patient data from the USA and Europe.

Keywords: cancer, cost-utility, economic model, non-small cell lung cancer

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Authors: S. Benchelha, H. Chennaoui, M. Hakdaoui, L. Baidder, H. Mansouri, H. Ejjaaouani, T. Benchelha

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Northern Morocco is characterized by relatively young mountains experiencing a very important dynamic compared to other areas of Morocco. The dynamics associated with the formation of the Rif chain (Alpine tectonics), is accompanied by instabilities essentially related to tectonic movements. The realization of important infrastructures (Roads, Highways,...) represents a triggering factor and favoring landslides. This paper is part of the establishment of landslides susceptibility map and concerns the mapping of unstable areas in the province of Taounate. The landslide was identified using the components of the false color (FCC) of images Landsat OLI: i) the first independent component (IC1), ii) The main component (PC), iii) Normalized difference index (NDI). This mapping for landslides class is validated by in-situ surveys.

Keywords: landslides, False Color Composite (FCC), Independent Component Analysis (ICA), Principal Component Analysis (PCA), Normalized Difference Index (NDI), Normalized Difference Mid Red Index (NDMIDR)

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Authors: Zhan Zheng-Qun, Li Min, Xie Yan

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Technology plays a key role in determining productivity and economy development in a country. The process of enterprises’ innovation can be seen as a process of knowledge management including the process of knowledge attainment; acquisition and converting and integrating into new knowledge. This research analyzes the influence factors and mechanism of the independent innovation of high-tech enterprises in the year 1995-2013. The result shows that the technology import has a significant positive effect on the innovation capacity of enterprises. And the absorptive capacity, represented by the research outlay input and research staff input, has a significant positive effect on the innovation capacity of enterprises. Furthermore, the effect of technology import on the independent research capacity of high-tech enterprises is significantly positively affected by their absorptive capacity.

Keywords: technology import, innovation capacity, absorptive capacity, high-tech industry

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Authors: SeungKu Ahn, Sewon Lee

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This study examines the effects of regulatory policies on corporate R&D activities and innovation and suggests regulatory directions for the enhancement of corporate performance. This study employs a regression model with R&D activities as dependent variables and the regulatory index as an independent variable. The results of this study are as follows: The regulation is negatively associated with the input and output of R&D activities. The regulation encourages small and medium-sized firms to invest in R&D. The regulation has a positive effect on patent applications for small and medium-sized firms.

Keywords: governmental regulation, research and development performance, small and medium-sized firms, technological innovation

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Authors: Fazli Rahim Shinwari, Ulrich Dittmer

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Like many megacities around the world, Kabul is facing severe problems due to the rising frequency of urban flooding. Since 2001, Kabul is experiencing rapid population growth because of the repatriation of refugees and internal migration. Due to unplanned development, green areas inside city and hilly areas within and around the city are converted into new housing towns that had increased runoff. Trenches along the roadside comprise the unplanned drainage network of the city that drains the combined sewer flow. In rainy season overflow occurs, and after streets become dry, the dust particles contaminate the air which is a major cause of air pollution in Kabul city. In this study, a stormwater management model is introduced as a basis for a systematic approach to urban drainage planning in Kabul. For this purpose, Kabul city is delineated into 8 watersheds with the help of one-meter resolution LIDAR DEM. Storm, water management model, is developed for Wazirabad catchment by using available data and literature values. Due to lack of long term metrological data, the model is only run for hourly rainfall data of a rain event that occurred in April 2016. The rain event from 1st to 3rd April with maximum intensity of 3mm/hr caused huge flooding in Wazirabad Catchment of Kabul City. Model-estimated flooding at some points of the catchment as an actual measurement of flooding was not possible; results were compared with information obtained from local people, Kabul Municipality and Capital Region Independent Development Authority. The model helped to identify areas where flooding occurred because of less capacity of drainage system and areas where the main reason for flooding is due to blockage in the drainage canals. The model was used for further analysis to find a sustainable solution to the problem. The option to construct new canals was analyzed, and two new canals were proposed that will reduce the flooding frequency in Wazirabad catchment of Kabul city. By developing the methodology to develop a stormwater management model from digital data and information, the study had fulfilled the primary objective, and similar methodology can be used for other catchments of Kabul city to prepare an emergency and long-term plan for drainage system of Kabul city.

Keywords: urban hydrology, storm water management, modeling, SWMM, GEO-SWMM, GIS, identification of flood vulnerable areas, urban flooding analysis, sustainable urban drainage

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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

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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: Syafinatul Fitri

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Cakrawala Baca is one of social organization in Indonesia that realize to transform its organization into social enterprise to create more sustainable organization that result more sustainable social impact. Cakrawala Baca implements voluntary system for its organization and it has passive social target. It funds its program by several fund rising activities that depend on donors or sponsor. Therefore social activity that held does not create sustainable social impact. It is different with social enterprise that usually more independent in funding its activity through social business and implement active social target and professional work for organization member. Therefore social enterprise can sustain its organization and then able to create sustainable social impact. Developing transformation model from social movement into social enterprise is the focus of this study. To achieve the aim of study, benchmark approach from successful social enterprise in Indonesia that has previously formed as social movement is employed. The benchmark is conducted through internal and external scanning that result the understanding of how they transformed into social enterprise. After understanding SAM and Agritektur transformation, transformation pattern is formulated based on their transformation similarities. This transformation pattern will be implemented to formulate the transformation plan for Cakrawala Baca to be a social enterprise.

Keywords: social movement/social organization, non-profit organization (NPO), social enterprise, transformation, Benchmarks approach

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

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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: R. Reshma srilakshmi, S. Shalini, P. Yogeeswari, D. Sriram

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Lysine aminotransferase is a crucial enzyme for dormancy in M. tuberculosis. It is involved in persistence and antibiotic resistance. In present work, we attempted to develop benzthiazole derivatives as lysine aminotransferase inhibitors. In our attempts, we also unexpectedly arrived at an interesting compound 21 (E)-4-(5-(2-(benzo[d]thiazol-2-yl)-2-cyanovinyl)thiophen-2-yl)benzoic acid which even though has moderate activity against persistent phase of mycobacterium, it has significant potency against active phase. In the entire series compound 22 (E)-4-(5-(2-(benzo[d]thiazol-2-yl)-2-cyanovinyl)thiophen-2-yl)isophthalic acid emerged as potent molecule with LAT IC50 of 2.62 µM. It has a significant log reduction of 2.9 and 2.3 fold against nutrient starved and biofilm forming mycobacteria. It was found to be inactive in MABA assay and M.marinum induced zebra fish model. It is also devoid of cytotoxicity. Compound 22 was also found to possess bactericidal effect which is independent of concentration and time. It was found to be effective in combination with Rifampicin in 3D granuloma model. The results are very encouraging as the hit molecule shows activity against active as well as persistent forms of tuberculosis. The identified hit needs further more pharmacokinetic and dynamic screening for development as new drug candidate.

Keywords: benzothiazole, latent tuberculosis, LAT, nutrient starvation

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Authors: Rylle Evan Gabriel Zamora, Micah Dennise Malia, Abygail Deniese Villabona

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The primary motivators of altruism are usually viewed as mutually exclusive. In this study, we wanted to know if the two primary motivators, reciprocity and empathy, can work together in motivating altruism. Therefore, we wanted to find out if there is a significant interaction of effects between reciprocity and empathy. To show how this may occur, we devised the combined altruism model, which is based on Batson’s empathy altruism hypothesis. A sample of 120, 6th-grade students were randomly selected and then randomly assigned to four treatment groups. A 2x2 between subjects’ design was used, which had empathy and reciprocity as independent variables, and altruism as the dependent variable. The study made use of materials that were effort based, where subjects were required to complete a task or a puzzle to help a person in a given scenario, two videos, one to prime empathy were also used. This along with Witt & Boleman’s adapted Self-Reported Altruism Scale was used to determine an individual’s altruism. It was found that both variables were significant in motivating altruism, with empathy being the greater of the two. However, there was no significant interaction of effects between the two variables. To explain why this occurred, we turned to the combined altruism model, where it was found that when empathically primed, we tend to not think of ourselves when helping others. Future studies could focus on other variables, especially age which is said to be one of the greatest factors that influenced the results of the experiment.

Keywords: reciprocity, empathy, altruism, experimental psychology, social psychology

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Michael Naderhirn, Marco Pavone

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Problem statement, motivation, and aim of work: So far, the development of control algorithms was done by control engineers in a way that the controller would fit a specification by testing. When it comes to the certification of an autonomous car in highly complex scenarios, the challenge is much higher since such a controller must mathematically guarantee to implement the rules of the road while on the other side guarantee aspects like safety and real time executability. What if it becomes reality to solve this demanding problem by combining Formal Verification and System Theory? The aim of this work is to present a workflow to solve the above mentioned problem. Summary of the presented results / main outcomes: We show the usage of an English like language to transform the rules of the road into system specification for an autonomous car. The language based specifications are used to define system functions and interfaces. Based on that a formal model is developed which formally correctly models the specifications. On the other side, a mathematical model describing the systems dynamics is used to calculate the systems reachability set which is further used to determine the system input boundaries. Then a motion planning algorithm is applied inside the system boundaries to find an optimized trajectory in combination with the formal specification model while satisfying the specifications. The result is a control strategy which can be applied in real time independent of the scenario with a mathematical guarantee to satisfy a predefined specification. We demonstrate the applicability of the method in simulation driving scenarios and a potential certification. Originality, significance, and benefit: To the authors’ best knowledge, it is the first time that it is possible to show an automated workflow which combines a specification in an English like language and a mathematical model in a mathematical formal verified way to synthesizes a controller for potential real time applications like autonomous driving.

Keywords: formal system verification, reachability, real time controller, hybrid system

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Authors: Xingyu Gao, Qiang Wu

Abstract:

Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

Procedia PDF Downloads 33

Authors: Yen Chia-Ju, Cheng Ding-Ruei

Abstract:

This study took case office building as subject and explored the responsive work order repair request of facilities and equipment in offices and public areas by gray theory, with the purpose of providing for future related office building owners, executive managers, property management companies, mechanical and electrical companies as reference for deciding and assessing forecast model. Important conclusions of this study are summarized as follows according to the study findings: 1. Grey Relational Analysis discusses the importance of facilities repair number of six categories, namely, power systems, building systems, water systems, air conditioning systems, fire systems and manpower dispatch in order. In terms of facilities maintenance importance are power systems, building systems, water systems, air conditioning systems, manpower dispatch and fire systems in order. 2. GM (1,N) and regression method took maintenance hours as dependent variables and repair number, leased area and tenants number as independent variables and conducted single month forecast based on 12 data from January to December 2011. The mean absolute error and average accuracy of GM (1,N) from verification results were 6.41% and 93.59%; the mean absolute error and average accuracy of regression model were 4.66% and 95.34%, indicating that they have highly accurate forecast capability.

Keywords: rey theory, forecast model, Taipei 101, office buildings, property management, facilities, equipment

Procedia PDF Downloads 428

Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

Abstract:

Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

Procedia PDF Downloads 626

Authors: M. Bodner, M. Scampicchio

Abstract:

Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm^–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R² = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R² = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA

Procedia PDF Downloads 132