Journal articles on the topic 'Variable data-reuse factor'

The development of e-Research infrastructure has enabled data to be shared and accessed more openly. Policy mandates for data sharing have contributed to the increasing availability of research data through data repositories, which create favourable conditions for the re-use of data for purposes not always anticipated by original collectors. Despite the current efforts to promote transparency and reproducibility in science, data re-use cannot be assumed, nor merely considered a ‘thrifting’ activity where scientists shop around in data repositories considering only the ease of access to data. The lack of an integrated view of individual, social and technological influential factors to intentional and actual data re-use behaviour was the key motivator for this study. Interviews with 13 social scientists produced 25 factors that were found to influence their perceptions and experiences, including both their unsuccessful and successful attempts to re-use data. These factors were grouped into six theoretical variables: perceived benefits, perceived risks, perceived effort, social influence, facilitating conditions, and perceived re-usability. These research findings provide an in-depth understanding about the re-use of research data in the context of open science, which can be valuable in terms of theory and practice to help leverage data re-use and make publicly available data more actionable.

This study intends to analyze how service quality of online order delivery food affects perceived value, reuse intention, and word-of-mouth intention. To achieve the goal, the study was conducted for 31 days, from March 1, 2022 to March 31, 2022, targeting restaurant consumers who have experience in online food order delivery in Seoul and the metropolitan area. A total of 300 copies of the questionnaire was distributed. Among those, 283 copies were collected, and a total of 259 copies was used, excluding 24 copies with insincere answers. The results of analysis of data collected from the sample are summarized as follows. First, as a result of multiple regression analysis for the test of <H1>, all three variables-food quality, environmental factors, health factors-were found to have a significant effect on perceived value. Second, as a result of simple regression analysis for the test of <H2>, one variable-perceived value-was found to have a significant effect on reuse intention. Third, as a result of simple regression analysis for the test of <H3>, one variable-perceived value-was found to have a significant effect on word-of-mouth intention.

Abstract In the application software development process with complex data content and constantly changing structure, it is difficult to cope with rapid changes in requirements only by relying on object inheritance and component technology, resulting in low software development efficiency. In order to improve the efficiency of software development, the paper proposes a software reuse technology based on the common factor method. In the process of writing code, first, use common factors to express the relationship between changes and unchanging parts; then; integrate component member variables, file UI component data initialization, data acquisition, addition, modification and verification, achieve more efficient code reuse. Taking the application practice of the research and development of the hospital nutrition department consultation software as a case, the research results show that the technology can quickly reuse the existing code, generate the code required for new requirements, ensure the quality of the software, and improve the efficiency of the development of the software.

Purpose – The purpose of this paper is to analyze the impact of chatbot characteristics on customer satisfaction and reuse intention. Design/Methodology/Approach – The study collected data from 259 customers with experience using chatbots on online shopping malls. Statistical programs SPSS 27.0 and AMOS 26.0 were used for data analysis in this study. The empirical analysis consisted of frequency analysis, reliability analysis, confirmatory factor analysis, and hypothesis testing, in that respective order. Findings – The results showed that chatbot characteristics (empathy, intimacy, accuracy, ease of use, social presence) and the relationship between customer satisfaction had a positive effect, and customer satisfaction had a positive effect on chatbot reuse intention. In addition, hedonic motivation showed a moderating effect on the relationship between accuracy, ease of use, and customer satisfaction, and utilitarian motivation showed a moderating effect on the relationship between accuracy and customer satisfaction. Research Implications – This paper divided the characteristics of chatbots into empathy, intimacy, accuracy, ease of use, and social presence, which provides a theoretical framework for future research on chatbots, and has certain reference value. The importance of consumer psychological variables is confirmed by analyzing hedonic motivation and utilitarian motivation as moderating variables. In addition, the results of this study are of great significance to the application and improvement of chatbots utilized by online shopping mall companies. In the online shopping mall environment, retailers can use chatbots as a communication supplementary strategy to participate in customer service and improve the efficiency of the customer shopping experience.

The goal of this research was to assess factors influencing participation of households in solid waste management in Muhanga city of southern province, Rwanda; more specifically, the research had the following specific objectives were to analyze factors influencing household participation in solid waste management in Muhanga City, to examine the solid waste management at household level in Muhanga city and to establish whether there is a significant effect of household participation in solid waste management in Muhanga city. The ANOVA tables proved better understandings of how the regression equation predicts the behaviors of the dependent against independent variables, and the model equation proved that the data are fit in the equation. The regression models predicted that the dependent variable was strongly significant as the data sample we have is fit. In the "sig." column, we find that the value of P is less than 0.005 that is P<0.005 (note that the value less than 0.005 is interpreted as 000 in the SPSS outputs). From that point, regression analysis revealed a positive relationship (R = 975). The R coefficient of 0.975 indicates that the predictors of the model which family size and cost, have a correlation of 97.5% with the dependent variable (solid waste management) The study also revealed that a combination of family size and cost together contributed to 95.2% (R2= 0.952) of the solid waste management. Therefore, we concluded that the regression model was statistically significant and predict the results from our variables. The side of the Model summary exemplified that the R-value indicated some simple correlations between our variables. This demonstrated a higher degree of correlation between the dependent and independent variables from the study. Similarly, the R square proved how the total variation between all the dependent variables and solid waste management was in relation. This lead us to conclude that there was a strong relationship between family size, cost and solid waste management in Muhanga district. From the shortcomings of the research, the following recommendations have been provided; there is need to create awareness and sensitize households on integrated solid waste management especially on how households can reduce, reuse and recycle the generated solid wastes at household level by the County Government.Segregation of solid wastes at the household should be encouraged as this makes it easy to deal with the different types of solid wastes in Muhanga City.

ABSTRACT This study aimed to analyze the influence of variable factors in the UTAUT2 (Unified Theory of Acceptance and Use of Technology) model on behavioral intention to use CWM (Crowdfunding-Waqf Model) in the Kitabisa.com application. The population used in this study were active users of the Kitabisa.com application, which are spread throughout Indonesia. Data collection techniques in this study used survey techniques by distributing questionnaires online to 174 respondents. The sampling technique used in this study was purposive sampling, which is a sampling technique with certain criteria. This study used the SEM-PLS analysis technique. The results of this study indicate that the Effort Expectancy (EE) and Habit (HB) variables have a significant positive effect on behavioral intention to use CWM (Crowdfunding-Waqf Model) in the Kitabisa.com application, thus wakif really considers the ease of use of technology and habits as a determining factor in the adoption of a technology, while 5 other variables, namely Performance Expectancy (PE), Price Value (PV), Social Influence (SI), Hedonic Motivation (HM), and Facilitating Condition (FC) variables have no significant positive effect on behavioral intention to use CWM (Crowdfunding-Waqf Model). The reason of these 5 variables are not significant is because the test results from the Hypothesis Test showed a number that was greater than the significance level of 5% or 0.05. Thus, the dependent variable in the form of Behavioral Intention to Use is only influenced by the Effort Expectancy (EE) and Habit (HB) variables. The contribution of this research is to encourage the policy makers to make policies or laws and regulations that can optimize the benefits of developing the waqf crowdfunding model (CWM) and protect all processes related to the use of productive waqf assets whose funds are collected from the Kitabisa.com application. Keywords: Crowdfunding Waqf Model, Kitabisa.com Application, Unified Theory of Acceptance and Use of Technology, Productive Waqf ABSTRAK Peneltian ini bertujuan untuk menganalisis pengaruh faktor variabel di dalam model UTAUT2 (Unified Theory of Acceptance and Use of Technology) terhadap behvioral intention to use CWM (Crowdfunding-Waqf Model) pada aplikasi Kitabisa.com. Populasi yang digunakan dalam penelitian ini adalah pengguna aktif aplikasi KitaBisa.com yang tersebar di seluruh Indonesia. Teknik pengumpulan data pada penelitian ini menggunakan Teknik survey dengan membagikan kuesioner secara online kepada 174 responden. Jenis pengambilan sampel yang digunakan Purposive sampling yaitu teknik penentuan sampel dengan kriteria tertentu. Penelitian ini menggunakan Teknik analisis SEM-PLS. Hasil penelitian ini menunjukkan bahwa variabel Effort Expectancy (EE) dan variabel Habit (HB) berpengaruh positif signifikan terhadap behvioral intention to use CWM (Crowdfunding-Waqf Model) dalam aplikasi Kitabisa.com, dengan demikian wakif sangat mempertimbangkan kemudahan dalam penggunaan suatu teknologi dan kebiasaan merupakan faktor penentu dalam adopsi suatu teknologi, sementara 5 variabel lainnya yaitu variabel Performace Expectancy (PE), Price Value (PV), Social Influence (SI), Hedonic Motivation (HM), dan variabel Facilitating Condition (FC) tidak berpengaruh positif signifikan terhadap behvioral intention to use CWM (Crowdfunding-Waqf Model). Adapun alasan 5 variabel tersebut tidak signifikan adalah karena hasil pengujian dari Uji Hipotesis menunjukkan angka yang lebih besardari tingkat signifikansi 5% atau 0.05. Dengan demikian, variabel dependen berupa Behavioral Intention to Use hanya dipengaruhi oleh variabel Effort Expectancy (EE) dan variabel Habit (HB) di dalam penelitian ini. Kontribusi dari adanya penelitian ini bagi para policy maker adalah dapat membuat kebijakan atau peraturan perundang-undangan yang dapat mengoptimalkan manfaat dari pengembangan Crowdfunding wakaf model (CWM) dan melindungi segala proses terkait pemanfaatan asset-aset wakaf produktif dan dana yang dikumpulkan dari aplikasi Kitabisa.com. Kata Kunci: Crowdfunding Wakaf Model, Aplikasi Kitabisa.com, Unified Theory of Acceptance and Use of Technology, Wakaf Produktif REFERENCES Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. 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This study aims to identify factors that influence patients' decisions to reuse health services at the Griya Medika Dompet Dhuafa Lampung Hospital. The research method used was an analytical survey with a cross-sectional design. Data was collected through questionnaires, medical records, and valid references. The research results show that factors such as the quality of doctor/nurse service, facilities, speed of service, and distance have a significant influence on patient decisions. Facilities are the most dominant variable in influencing a patient's decision to return for treatment. Managerial implications and suggestions are presented to improve the quality of care and improve certain aspects that influence patient decisions.

Despite hundreds of studies, we know very little about the causes and fitness-related consequences of nest-site selection. For example, it is not typically known whether the rarely reported fitness consequences of site selection are the result of nest, individual, or nest-site variables or combinations of these factors. Reuse of previously constructed nest sites is a prevalent behavior in many animals and offers the opportunity to experimentally tease apart whether seasonal reproductive success is a function of nest, individual, or nest-site characteristics. I used observational and experimental data to test three hypotheses related to these factors in association with barn swallow ( Hirundo rustica L., 1758) nest reuse. While both nest and individual characteristics explain variation in seasonal reproductive success, nest location per se is not an important factor defining the outcome of nest-site selection. Whereas traits related to habitat and individual characteristics are likely confounded in correlational studies, my experiments demonstrate a causal relationship between seasonal reproductive success and aspects of the nest and individual, the latter explaining more variation in the model than nest characteristics. Knowledge of the relative roles of individual, nest, and nest-site attributes are important for understanding the causes and consequences of habitat selection behavior.

The accelerated advancement in technology resulted to the appearance of Self Service Technology. One form of self-service technology in the banking sector is the presence of mobile banking. This study aims to examine the influence of five factors toward the reusing of Mobile Bank Central Asia (BCA) in Bandung. Those factors used in this study were the extension of Technology Acceptance Model (TAM) constructs, i.e perceived usefulness, perceived ease of use, perceived credibility, customer awareness and social influence. Data was collected through distributed questionnaire to 100 respondents who used Mobile BCA by using judgment sampling. Multiple linear regression technique was employed to investigate the influence among variables. This study empirically concluded that consumer intention to reuse BCA mobile services was positively influenced by social influence, customer awareness and perceived ease of use. On the other hand, perceived usefulness and perceived credibility did not influence the intention of reusing Mobile BCA in Bandung. Further study is suggested to use probability sampling technique to cover the real voice of mobile banking user in Bandung and to explore the lack influence of perceived usefulness and perceived credibility toward reusing of Mobile BCA.

The transport sector, and especially the increase in individual vehicle ownership, contribute significantly to air pollution. The transition to electric vehicles (EVs) is seen as a sustainable alternative to reduce emissions of polluting gases. However, in Brazil, the EV market has not yet reached a significant size. Given this scenario, this study aims to analyze the factors that influence the decision to buy EVs in Brazil, highlighting personal, psychological, economic, performance, and environmental variables and barriers. The aim is also to develop a model with guidelines that can help stakeholders. The quantitative stage of the study involved a survey of 514 respondents. The data were analyzed using statistical methods, including structural equation modeling (SEM), which allowed for a deeper investigation of the proposed hypotheses. The survey findings reveal that, in the Brazilian context, performance factors—such as autonomy, availability of recharging infrastructure, and maintenance—are the main drivers influencing EV purchase decisions. Environmental factors, including energy reuse, pollution reduction, and minimizing environmental impacts, have also gained significant importance. Economic factors are crucial, particularly concerning cost–benefit perceptions. The differences between Brazil and other regions highlight the importance of accounting for cultural and economic variations when analyzing consumer behavior towards EVs.

Decolorization of Malachite green in aqueous solution by adsorption onto Populus deltoides sawdust (PSD) was optimized through a four-factor, three-level Box–Behnken design in response surface methodology. The influences of four independent variables such as initial pH of solution (3–7), dye concentration (50–300 mg/L), adsorbent dose (0.2–2 g/L), and temperature (23–50 °C) were studied to optimize the condition of dye removal. A natural log transformation was suggested by the Box–Cox plot in order to enhance the model significance. Regression analysis showed good fit of the experimental data to the second-order polynomial model with high coefficient of determination values (R2 = 0.996; Radj.2 = 0.9913; Rpred.2 = 0.9769), F-value of 213.03, and p-value of <0.0001 (α = 0.05). Under optimum values of all the four variables, viz., pH of 6.02, initial dye concentration of 262.6 mg/L, adsorbent dose of 0.23 g/L and temperature of 30.3 °C, the maximum uptake (qe) was noted to be 920.9 mg/g. The experimental equilibrium adsorption data were fitted well to the Langmuir isotherm model (R2 = 0.9949). Kinetic studies revealed that adsorption followed pseudo-second order. It was found that PSD is suitable for reuse four times in successive adsorption-desorption cycles with loss of 25.2% in adsorption capacity.

Background: CKD is a worldwide public health problem. HCV is the most frequent complication of patients on hemodialysis, it is very important to screen patients for HCV seropositivity, asit may lead to severe liver disease, complications in renal transplant and death. Aim: To find the incidence of HCV seropositivity and identify factors associated with hemodialysis patients at the Dialysis Center. Methodology: A Retrospective Cohort study conducted at Hemodialysis Unit, Sheikh Zayed Hospital, Lahore from January 2015 to December 2015. Secondary data was collected from all the record files of all the patients included in the study available at Sheikh Zayed hospital. Data was also collected by a questionnaire from patient to determine different variables. Data for age, gender, HCV seroconversion, number of transfusions, emergency dialysis at any other hemodialysis center, surgeries, previous history of HCV, dialyzer reuse and dental procedure etc. was collected and patients were divided in two groups according to HCV status at the end of study. Data for seroconversion was studied for relation with given risk factors using Chi-square test and odds ratios with 95% confidence interval. Binary logistic regression was used to see the adjusted odds ratio of various risk factors for seroconversion. P-value ≤0.05 was considered significant. Results: The mean age of the patients was 43.40±16.37 years. The frequency of previous transfusions was 120(48%) The frequency of emergency dialysis outside Shaikh Zayed Hospital was 76(30.4%). The frequency of surgeries was 126(50.4%). The frequency of dental procedures was 102(40.8%). The mean duration of dialysis was 17.6±5.73. The incidence of HCV seroconversion in hemodialysis patients was 124(49.6%). Conclusion: We concluded that the incidence of HCV seroconversion in hemodialysis patients was 8.2% per year and over a period of six years nearly 49.6% who were undergoing dialysis in our dialysis center. Keywords: HCV seroconversion, hemodialysis patients

The Open Government Data portals (OGD), thanks to the presence of thousands of geo-referenced datasets, containing spatial information are of extreme interest for any analysis or process relating to the territory. For this to happen, users must be enabled to access these datasets and reuse them. An element often considered as hindering the full dissemination of OGD data is the quality of their metadata. Starting from an experimental investigation conducted on over 160,000 geospatial datasets belonging to six national and international OGD portals, this work has as its first objective to provide an overview of the usage of these portals measured in terms of datasets views and downloads. Furthermore, to assess the possible influence of the quality of the metadata on the use of geospatial datasets, an assessment of the metadata for each dataset was carried out, and the correlation between these two variables was measured. The results obtained showed a significant underutilization of geospatial datasets and a generally poor quality of their metadata. In addition, a weak correlation was found between the use and quality of the metadata, not such as to assert with certainty that the latter is a determining factor of the former.

Background: Poor solid waste management is a major public health and environmental concern in developing countries like Ethiopia. This study aimed to assess the status of household solid waste management and associated factors in Fiche town. Methods: A community-based cross-sectional study was conducted among 236 residents of Fiche town from January to March 2022. Both questionnaire and field observation was used to collect data from households in the town. Data were first checked manually for completeness, then coded and entered into SPSS version 20, then descriptive statistics such as frequency and percentage were done. Multivariate logistic regression analysis was done to assess the potential predictors of the outcome variable ( P < .05). Result: In the present study, 185 (78.4%), of residents uses improper solid waste management practices. Multivariable logistic regression analysis revealed that knowledge of reduce, reuse and recycle (3R) (adjusted odds ratio [AOR] = 6.61; 95% confidence interval [CI] 2.94, 14.87), access to door to door waste collection (AOR = 3.91; 95% CI 2.03, 7.51), treating waste as a resource (AOR = 3.06; 95% CI 1.47, 6.36) and knowledge about the rule and regulations of solid waste management (AOR = 6.49; 95% CI 3.09, 13.61) were found to be significantly associated with waste management practices. Conclusion: Therefore, there is a need to raise awareness about solid waste management at the community level using different pieces of training. In addition, the city municipality needs to strengthen door to door waste collection services.

Satisfying consumer need is the desire of every company. Apart from being an important factor for the survival of the company, satisfying consumer needs can increase its superiority in the competition. Consumers who are satisfied with products and services tend to repurchase the product and reuse the service when the same need reappears in the future. This study aims to determine the effect to aisy drink marketing communication strategy on consumer buying interest in the city of Bima. This study uses a quantitative approach with a survey method. The population in this study are consumers who have seen marketing communication strategies through prmotions, the number of samples taken in this study were 50 respondents with the sampling used in this study was purposive sampling. The research instrument used a questionnaire with a likert scale. Data analysis used simple linear regression, partial test with t test. To test the effect between variables using SPSS (Statistical service product solutions) version 20.00. The results showed that the marketing communication strategy of aisy drink through social media had a positive effect on buying interest at AISY in Bima city.

High-pressure water jet machining is characterized by wide possibilities of cutting diverse materials together with multi-layer materials with dissimilar properties, accurate cutting complex profiles, as well as conducting them in uncommon conditions, especially in cases of thick materials. An additional advantage of water jet technology is its environmental friendliness. This paper presents tests of the cutting performance of tool steel with the use of an abrasive water jet (AWJ). The state-of-the-art has shown insufficient scientific evidence in AWJ tool steels cutting using recycled abrasive materials. Therefore, the main motivation for this paper was to carry out research from an environment aspect. The reuse of abrasives and the use of recycled materials have immense potential to reduce processing costs while remaining environmentally friendly. The RSM method was used for modeling and optimization. A response surface design (RSM) is a package of an advanced design-of-experiment (DOE) approaches that support better understanding and optimize response, exploring the relationships between several explanatory variables and one or more response variables. Based on this research, feed rate is the key factor influencing the depth of cut, while the water nozzle diameter has a secondary effect, and the concentration of abrasive has the least influence on the depth of cut. High level of variance (the percentage of variability in the reaction that is interpreted by the formula) confirms that the models fit well to the investigational data.

Reduce, Reuse, and Recycle (3R) on waste management is one of the key strategies implemented in Indonesian to reduce the negative impact of waste on the environment. This study aims to explore the influence of socio-economic factors on the level of community participation of 3R in Lhoknga District, Aceh Province. The socio-economic factors analyzed include gender, age, educational attainment, income, occupation, housing status, and household size. This study used a descriptive quantitative survey approach involving 30 randomly selected respondents. Data analysis was conducted using Structural Equation Modeling-Partial Least Square (SEM-PLS) to identify the relationship between socio-economic variables and various forms of community participation, including cognitive participation, physical participation, material contributions, skills, and waste management. The analysis results show that socio-economic characteristics do not have a significant influence on the various forms of participation in waste management. The P Values for different types of participation are above 0.05, such as cognitive participation (0.342), physical participation (0.312), material contributions (0.390), skills (0.302), and general waste management participation (0.342). This indicates that there is no statistically significant relationship between socio-economic factors and the level of participation in waste management in Lhoknga. Participation in 3R activities is more influenced by individual awareness rather than socio-economic factors.

Purpose The purpose of this paper is to identify and describe the relationship between the precursors and consequences of customer loyalty (CL) in the Indian financial sector, specially banking and insurance context, taking a sample of individual customers as respondents from the Indian State of Punjab. Design/methodology/approach The collected data have been analyzed using univariate, bivariate and multivariate analysis techniques. Specifically, descriptive statistics have been assessed to examine the basic characteristics of the sample data. Confirmatory factor analysis with maximum likelihood criteria has been adopted for the measurement and validation of various constructs. Independent samples t-test has been used to compare the CL of public and private firms, banks and insurance firms, and for some of the demographic variables like gender, marital status, etc. One-way ANOVA has been used to compare the CL for variables having more than two groups. Structural equation modeling (SEM) has been used to measure the impact of CL on the BP of financial services firms. Findings The result shows that BP is a higher-order construct measured in terms of word-of-mouth, repurchase intention, price premium and share of wallet. Though each of the four measures of CL is special and unique in nature, yet a high level of positive correlation has been seen among these dimensions. The study reveals that CL is not significantly different for the banking firms and insurance firms in Punjab. Research limitations/implications The authors consider this work as one of the foundational elements that will enable further advances toward the governance of multi-layer business impact modeling systems. Extensive usability tests would enable to further confirm the findings of the paper. This study contributes to the customer relationship management and services marketing literature by providing empirical support for CL and BP relationship in the Indian context. Practical implications The approach described here should improve the maintainability, reuse and clarity of business process models and in extension improve data for CL in large banking and insurance organizations. The approaches described here should improve the maintainability, reuse and clarity of loyalty and relationship of the customer with that of organizations. This can improve data for customer relationship and loyalty in banking and insurance sector. Originality/value This paper fulfills an identified gap to enabling SEM enabled models for data regarding customer relationship and loyalty. Loyalty revolves around the concept of relationship. CL is not a new concept, but recent years have demonstrated a developing interest to fabricate CL because of customer-oriented techniques or strategies. Over the previous era, CL has been broadly inspected inside marketing, trades and transactions. It can be concluded that the CL significantly influences BP.

Satisfying consumer needs is the dream of every company. Apart from being an important factor for the survival of the company, meeting consumer needs can increase its superiority in the competition. Consumers who are satisfied with the quality and price of the product tend to repurchase the product and reuse the product when the same need reappears in the future. This study aims to determine the analysis of customer loyalty on skincare wardah in the city of Bima. This research uses a quantitative approach with a survey method, while this type of research includes descriptive research. The population in this study were customers who used Wardah skincare, the number of samples taken in this study were 96 respondents. The sample used in this study was accidental. The research instrument used a questionnaire with a Likert scale. Data analysis used validity test, reliability test, and on sample test. To test the independent variables using SPSS (Statistical Service Product Solutions) version 23.00. Research results Based on the results of the one sample t-test at Skincare Wardah City of Bima it is said to be good because it is more than 70%, which means that Customer Loyalty to Skincare Wardah City of Bima is in accordance with consumer desires.

Satisfying consumer needs is the desire of every company. Apart from being an important factor for the company's survival, satisfying the needs of consumers can increase its advantage over the competition. Consumers who are satisfied with products and services tend to buy back products and reuse services when the same needs reappear at a later date. This study aims to determine the effect of removal of baggage facilities on customer satisfaction on Air Wings Airline. This research uses a quantitative approach with a survey method. This study uses a quantitative approach with a survey method, while this type of research is categorized as a causal research. The population in this study are consumers who have used air flight services using wing air, the number of samples taken in this study were 50 respondents with the sampling used in this study was purposive sampling. The research instrument used a questionnaire with a Likert scale. Data analysis used simple linear regression, partial test with t test. To test the effect between variables using SPSS (Statistical Service Product Solutions) version 23.00. The results showed that the elimination of baggage facilities had a positive and significant effect on customer satisfaction on the Air Wings airline

Satisfying consumer needs is the dream of every company. Apart from being an important factor for the company's survival, meeting consumer needs can increase its superiority in competition. Consumers who are satisfied with product design and product quality tend to buy back the product and reuse the product when the same need arises at a later date. This study aims to determine the effect of product design and product quality on consumer satisfaction at Honda Scoopy on Astra Motor. This study uses a quantitative approach with a survey method, while this type of research includes associative research. The population in this study are consumers who have used Honda Scoopy, the number of samples taken in this study were 100 respondents. The sample used in this study was purposive sampling. The research instrument used a questionnaire with a Likert scale. Data analysis used multiple linear regression, correlation test, determination test, partial test analysis with t test and f test (simultaneous). To test the effect between variables using SPSS (Statistical Service Product Solutions) version 23.00. The results based on the t test (partial) show that product design affects customer satisfaction, product quality affects product satisfaction, while product design and product quality simultaneously affect product satisfaction.

The world usage of raw materials is 70% higher than what the Earth can safely renew. Circular Economy represents a new model of economic development relying on the 7Rs (redesign, reduce, reuse, repair, renovate, recycle, and recover) to provide operational and strategic benefits on the micro, meso, and macro levels. This research aims to determine the impact that circular economy competitiveness and innovation have on economic growth within European countries by evaluating the impact of four independent variables selected from the European Commission Circular Economy monitoring framework on the GNI per capita. This paper analyses the competitiveness through Values Added at Factor Cost (VAFC), Gross Investment in Tangible Goods (GITG), and Number of Employees (EMP) in Circular Economy, innovation through the Number of Patents in climate change mitigation technologies related to wastewater treatment or waste management (PAT), while the economic growth was estimated based on the GNI per capita annual growth rate (GNIpc). Correlation and regression methods were applied to the sample of 25 European countries using the log-transformed data. The results show that the correlation between VAFC and GNIpc is moderate and significant but negative, while the correlation between GITG and EMP and GNIpc is not statistically significant.

Fast covariance calculation is required both for simultaneous localization and mapping (SLAM; e.g., in order to solve data association) and for evaluating the information-theoretic term for different candidate actions in belief space planning (BSP). In this article, we make two primary contributions. First, we develop a novel general-purpose incremental covariance update technique, which efficiently recovers specific covariance entries after any change in probabilistic inference, such as the introduction of new observations/variables or relinearization. Our approach is shown to recover them faster than other state-of-the-art methods. Second, we present a computationally efficient approach for BSP in high-dimensional state spaces, leveraging our incremental covariance update method. State-of-the-art BSP approaches perform belief propagation for each candidate action and then evaluate an objective function that typically includes an information-theoretic term, such as entropy or information gain. Yet, candidate actions often have similar parts (e.g., common trajectory parts), which are however evaluated separately for each candidate. Moreover, calculating the information-theoretic term involves a costly determinant computation of the entire information (covariance) matrix, which is [Formula: see text] with [Formula: see text] being dimension of the state or costly Schur complement operations if only marginal posterior covariance of certain variables is of interest. Our approach, rAMDL-Tree, extends our previous BSP method rAMDL, by exploiting incremental covariance calculation and performing calculation reuse between common parts of non-myopic candidate actions, such that these parts are evaluated only once, in contrast to existing approaches. To that end, we represent all candidate actions together in a single unified graphical model, which we introduce and call a factor-graph propagation (FGP) action tree. Each arrow (edge) of the FGP action tree represents a sub-action of one (or more) candidate action sequence(s) and in order to evaluate its information impact we require specific covariance entries of an intermediate belief represented by the tree’s vertex from which the edge is coming out (e.g., tail of the arrow). Overall, our approach has only a one-time calculation that depends on [Formula: see text], while evaluating action impact does not depend on [Formula: see text]. We perform a careful examination of our approaches in simulation, considering the problem of autonomous navigation in unknown environments, where rAMDL-Tree shows superior performance compared with rAMDL, while determining the same best actions.

Diterima:Revisi:Terbit: Satisfying consumer needs is the dream of every company. Apart from being an important factor for the company's survival, meeting consumer needs can increase its superiority in competition. Consumers who are satisfied with the facility and location tend to buy back the product and reuse the product when the same needs reappear at a later date. This study aims to determine the effect of facilities and location on the interest in visiting the water boom arema raya bima city. This study uses a quantitative approach with a survey method, while this type of research includes associative research. The population in this study were consumers who had visited the Araema Raya water boom, the number of samples taken in this study were 100 respondents. The sample used in this study was purposive sampling. The research instrument used a questionnaire with a Likert scale. Data analysis used multiple linear regression, correlation test, determination test, partial test analysis with t test and f test (simultaneous). To test the effect between variables using SPSS (Statistical Service Product Solutions) version 26.00. The results of the study based on the t test (partial) show that there is no effect of facilities on interest in visiting, location has an effect on interest in visiting, while facilities and location jointly affect interest in visiting.Â

Information technology has made mobile banking easy, convenient and accessible to 178 million unique mobile subscribers base in Indonesia. Out of this 50 million are smartphone users and collectively about 132 million are internet users . This rising trend has been forcing 120 commercial banks in the country to ramp up their mobile-based banking initiatives. However, in contrast to it, only 50 million have bank accounts out of 250 million Indonesian population size . This poses a few challenges to digital adoption using mobile as medium, especially when a limited number of people have bank accounts and the cost of internet is high due to geographical, infrastructural spread and cost barriers. The purpose of this study is to unearth such factors that have - direct or indirect - influence on consumer acceptance for mobile banking applications. This research model examines 205 respondents from online surveys in Jabodetabek, Indonesia. To conduct this study, we have used Unified Theory of Acceptance and Use of Technology (UTAUT2) model that helps in understanding perceived credibility and perceived self-efficacy variables and their roles in influencing the adoption for m-banking. Data was analysed using Partial Least Square (PLS) method. The findings suggest that performance expectancy, effort expectancy, and social influence have a significant effect on behavioral intention. Performance expectancy is the factor that mostly influences behavior intention. It can also be stated that behavioral intention, facilitating condition and habit – all of these have a significant effect on reuse behavior.

Free maternity services is the offering of medical and obstetric care to pregnant women without any financial cost. Complications related to pregnancy were a major reproductive health problem that lead to disability and increased maternal deaths. Free maternity was introduced in Kenya in 2013 with a focus of achieving 100% utilization of the service and reducing high mortality rate. Homa-Bay County had a low percentage of 54% deliveries taking place in health facilities within the county. The main objective of this study was to establish Determinants of Health facilities Influencing Utilization of Free Maternity Services among Women of Reproductive Age 15-49 Years Attending Health Facilities in Homa-Bay County. Descriptive cross-sectional study design was applied to establish the main objective of this study. A probability and non-probability sampling techniques was used to select 420 respondents. The study utilized quantitative and qualitative methods of data collection. Data analysis was conducted with aid of Statistical Package for Social Scientists (SPSS) version 23. Analysis methods used were; factor analysis and regression analyses methods for quantitative data to determine the relationship and associations among the variables. Qualitative data was analyzed through content analysis by conducting thematic analysis. A total of 396 that was 94% response rate established 54% (213/396) mothers were interviewed and were aged between 20 years and 29years. Results showed that; age of the mothers was insignificant in utilization of free maternity services. Further analysis using logistics regression revealed that the respondents who agreed with the need for a well-equipped health facility with good sanitation system were 63% (OR 0.37, p = 0.03) more likely to reuse FMS. Distance was insignificant in utilization as long as the facility was well-equipped and adequately staffed as 57% (228/396).This study concluded that there was significant association between staff respect, and honesty of the staff with utilization of free maternity service. This study recommended that the County Government of Homa-Bay should increase awareness to women of reproductive age at the community level about FMS through Community health promotion officers in order to improve FMS uptake in Homa-Bay County.

The rainfall available in the watershed is key factor for determining the availability of water to fulfill the different demand mainly for agriculture, hydropower water supply, industry, etc. A watershed is that contributes runoff water to a common point Runoff is one of the important hydrologic variables used in most of the water resource applications. Runoff is the total surface flow from a given drainage area. Rainfall duration, intensity and aerial distribution influence the rate and volume of runoff. Watershed characteristics such as slope, shape and size, cover of soil and duration of rainfall have a direct effect on the peak flow and volume of runoff from any area (Chandler and Walker, 1998). Rainfall and runoff are significant constitute the sources of water for recharge of ground water in the watershed. Estimation of runoff in a watershed is very important to manage the water resources efficiently. Most of the part of the Marathwada region is comes under assured rainfall zone. The region receives mean annual rainfall of 880 mm. Rainfall in uncertain and erratic in this region and sometimes suffers from severe droughts. The rainfall data for Aurangabad, Parbhani and Nanded stations were collected from the Agro-meteorological station under VNMKV, Parbhani. Runoff was estimated using SCS curve number method considering the all parameters like soil type, vegetation etc. The rainfall runoff relationship was worked out for further planning of small water harvesting structures like farm ponds. The runoff potential for Aurangabad, Parbhani and Nanded station is found to be 20.07 %, 28.31 % and 31.69 % respectively, indicating a good scope for rainwater harvesting and thereby, many more rainwater harvesting structures can be constructed based on site specific conditions. A relation between rainfall and runoff for Aurangabad, Parbhani and Nanded stations were worked out as Y = 0.301X - 55.711 ( R2 value - 0.75), Y = 0.4043X - 88.882 (R2 value - 0.8687) and Y = 0.6018X - 209.2 (R2 value -0.9575) respectively. The linear rainfall-runoff relation obtained can be used for finding out runoff corresponding to any rainfall occurring in the area. The rainfall runoff relationship will be useful for determination of rainwater harvesting potential and its reuse for enhancing production potential of various rainfed crops.

Objectives:A large-scale freshwater lake is a freshwater lake with a storage of 5,000,000 tons or more among freshwater lakes. It is located at the end of the basin, so complex and various pollutants flow in from a wide basin, and it has a characteristic of longer retention and greater accumulation for a long time in the lake. Since the continuous inflow and accumulation of non-point pollution sources for agricultural purpose occurred due to the repeated reuse of agricultural water near freshwater lakes, and the complex water use and occurred drainage structure, water pollution is aggravating. In this study, the main pollution sources of large-scale freshwater lakes were derived through multivariate statistical analysis using various water quality factors for efficient freshwater lake management. The analysis is performed out to predict the future Chlorophyll-<i>a</i>(Chl-<i>a</i>) and to identify major factors affecting algal growth, and to use them as establish effective countermeasures to improve water quality based on the characteristics of freshwater lakes algal growth the future.Methods:In the case of GanWol(GW), GeumGang(GG), GeumHO(GeH), NamYang(NY), DaeHo(DH), BuNam(BN), SapGyo(SG), ASan(AS), YoungSan(YS), YoungAm(YA) in the water environment information system operated by the Ministry of Environment, water quality data on a monthly basis for 10 years from January, 2011 to December, 2020 were collected from three point measurement located in the lake. In the case of GoHeung(GoH), GunNae(GN), Busa(BS), SeokMoon(SM), and HaeNam(HN), water quality data were collected on a quarterly basis for 5 years from April 2015 to March 2019 from one point measurement located in the lake.Results and Discussion:As a result of Korean trophic state index (TSI<sub>ko</sub>) analysis, most of the large-scale freshwater lakes in the central region of the West Sea were classified as Hypertrophic, and all of the large-scale freshwater lakes in the southern region of the West Sea were classified as Eutrophic. Based on the results from factor analysis and principal component analysis, countermeasures against organic matters, nutrients, and algal bloom in terms of type of large-scale freshwater lake should be prepared. As a result of multiple linear regression analysis for Chl-<i>a</i> prediction, large-scale freshwater lakes in the central region of the West Sea had higher explanatory rates than large-scale freshwater lakes in the southern region of the West Sea, but all were analyzed below 0.8, suggesting that the accuracy was not high.Conclusions:BOD, COD, TOC, T-N, and T-P concentration of freshwater lakes in the central region of the West Sea have more deterioating water quality than freshwater lakes in the southern region of the West Sea, suggesting that organic pollutants and nutrients need to be managed. As a result of the factor analysis, it is judged that organic matter & algae type nutrient type, and complex type classification, and appropriate water quality management measures for each type are required. All regression models used for prediction of Chl-<i>a</i> were analyzed as <i>p</i><0.05, and the independent variables of each prediction formula were meaningful in explaining Chl-<i>a</i>. Chl-<i>a</i> is changed by the complex effects of various water quality factors, and it is also judged that the influence of water quality external products such as precipitation, sunshine time, and flow rate should also be considered. In the future, if the regression is performed by integrating the water quality factors and external factors of a longer period, it is possible to create a model with a slightly higher explanatory rate by increasing the R<sup>2</sup> value.

To date, discrete event stochastic simulations of large scale biological reaction systems are extremely compute-intensive and time-consuming. Besides, it has been widely accepted that spatial factor plays a critical role in the dynamics of most biological reaction systems. The NSM (the Next Sub-Volume Method), a spatial variation of the Gillespie’s stochastic simulation algorithm (SSA), has been proposed for spatially stochastic simulation of those systems. While being able to explore high degree of parallelism in systems, NSM is inherently sequential, which still suffers from the problem of low simulation speed. Fine-grained parallel execution is an elegant way to speed up sequential simulations. Thus, based on the discrete event simulation framework JAMES II, we design and implement a PDES (Parallel Discrete Event Simulation) TW (time warp) simulator to enable the fine-grained parallel execution of spatial stochastic simulations of biological reaction systems using the ANSM (the Abstract NSM), a parallel variation of the NSM. The simulation results of classical Lotka-Volterra biological reaction system show that our time warp simulator obtains remarkable parallel speed-up against sequential execution of the NSM.I.IntroductionThe goal of Systems biology is to obtain system-level investigations of the structure and behavior of biological reaction systems by integrating biology with system theory, mathematics and computer science [1][3], since the isolated knowledge of parts can not explain the dynamics of a whole system. As the complement of “wet-lab” experiments, stochastic simulation, being called the “dry-computational” experiment, plays a more and more important role in computing systems biology [2]. Among many methods explored in systems biology, discrete event stochastic simulation is of greatly importance [4][5][6], since a great number of researches have present that stochasticity or “noise” have a crucial effect on the dynamics of small population biological reaction systems [4][7]. Furthermore, recent research shows that the stochasticity is not only important in biological reaction systems with small population but also in some moderate/large population systems [7].To date, Gillespie’s SSA [8] is widely considered to be the most accurate way to capture the dynamics of biological reaction systems instead of traditional mathematical method [5][9]. However, SSA-based stochastic simulation is confronted with two main challenges: Firstly, this type of simulation is extremely time-consuming, since when the types of species and the number of reactions in the biological system are large, SSA requires a huge amount of steps to sample these reactions; Secondly, the assumption that the systems are spatially homogeneous or well-stirred is hardly met in most real biological systems and spatial factors play a key role in the behaviors of most real biological systems [19][20][21][22][23][24]. The next sub-volume method (NSM) [18], presents us an elegant way to access the special problem via domain partition. To our disappointment, sequential stochastic simulation with the NSM is still very time-consuming, and additionally introduced diffusion among neighbor sub-volumes makes things worse. Whereas, the NSM explores a very high degree of parallelism among sub-volumes, and parallelization has been widely accepted as the most meaningful way to tackle the performance bottleneck of sequential simulations [26][27]. Thus, adapting parallel discrete event simulation (PDES) techniques to discrete event stochastic simulation would be particularly promising. Although there are a few attempts have been conducted [29][30][31], research in this filed is still in its infancy and many issues are in need of further discussion. The next section of the paper presents the background and related work in this domain. In section III, we give the details of design and implementation of model interfaces of LP paradigm and the time warp simulator based on the discrete event simulation framework JAMES II; the benchmark model and experiment results are shown in Section IV; in the last section, we conclude the paper with some future work.II. Background and Related WorkA. Parallel Discrete Event Simulation (PDES)The notion Logical Process (LP) is introduced to PDES as the abstract of the physical process [26], where a system consisting of many physical processes is usually modeled by a set of LP. LP is regarded as the smallest unit that can be executed in PDES and each LP holds a sub-partition of the whole system’s state variables as its private ones. When a LP processes an event, it can only modify the state variables of its own. If one LP needs to modify one of its neighbors’ state variables, it has to schedule an event to the target neighbor. That is to say event message exchanging is the only way that LPs interact with each other. Because of the data dependences or interactions among LPs, synchronization protocols have to be introduced to PDES to guarantee the so-called local causality constraint (LCC) [26]. By now, there are a larger number of synchronization algorithms have been proposed, e.g. the null-message [26], the time warp (TW) [32], breath time warp (BTW) [33] and etc. According to whether can events of LPs be processed optimistically, they are generally divided into two types: conservative algorithms and optimistic algorithms. However, Dematté and Mazza have theoretically pointed out the disadvantages of pure conservative parallel simulation for biochemical reaction systems [31]. B. NSM and ANSM The NSM is a spatial variation of Gillespie’ SSA, which integrates the direct method (DM) [8] with the next reaction method (NRM) [25]. The NSM presents us a pretty good way to tackle the aspect of space in biological systems by partitioning a spatially inhomogeneous system into many much more smaller “homogeneous” ones, which can be simulated by SSA separately. However, the NSM is inherently combined with the sequential semantics, and all sub-volumes share one common data structure for events or messages. Thus, directly parallelization of the NSM may be confronted with the so-called boundary problem and high costs of synchronously accessing the common data structure [29]. In order to obtain higher efficiency of parallel simulation, parallelization of NSM has to firstly free the NSM from the sequential semantics and secondly partition the shared data structure into many “parallel” ones. One of these is the abstract next sub-volume method (ANSM) [30]. In the ANSM, each sub-volume is modeled by a logical process (LP) based on the LP paradigm of PDES, where each LP held its own event queue and state variables (see Fig. 1). In addition, the so-called retraction mechanism was introduced in the ANSM too (see algorithm 1). Besides, based on the ANSM, Wang etc. [30] have experimentally tested the performance of several PDES algorithms in the platform called YH-SUPE [27]. However, their platform is designed for general simulation applications, thus it would sacrifice some performance for being not able to take into account the characteristics of biological reaction systems. Using the similar ideas of the ANSM, Dematté and Mazza have designed and realized an optimistic simulator. However, they processed events in time-stepped manner, which would lose a specific degree of precisions compared with the discrete event manner, and it is very hard to transfer a time-stepped simulation to a discrete event one. In addition, Jeschke etc.[29] have designed and implemented a dynamic time-window simulator to execution the NSM in parallel on the grid computing environment, however, they paid main attention on the analysis of communication costs and determining a better size of the time-window.Fig. 1: the variations from SSA to NSM and from NSM to ANSMC. JAMES II JAMES II is an open source discrete event simulation experiment framework developed by the University of Rostock in Germany. It focuses on high flexibility and scalability [11][13]. Based on the plug-in scheme [12], each function of JAMES II is defined as a specific plug-in type, and all plug-in types and plug-ins are declared in XML-files [13]. Combined with the factory method pattern JAMES II innovatively split up the model and simulator, which makes JAMES II is very flexible to add and reuse both of models and simulators. In addition, JAMES II supports various types of modelling formalisms, e.g. cellular automata, discrete event system specification (DEVS), SpacePi, StochasticPi and etc.[14]. Besides, a well-defined simulator selection mechanism is designed and developed in JAMES II, which can not only automatically choose the proper simulators according to the modeling formalism but also pick out a specific simulator from a serious of simulators supporting the same modeling formalism according to the user settings [15].III. The Model Interface and SimulatorAs we have mentioned in section II (part C), model and simulator are split up into two separate parts. Thus, in this section, we introduce the designation and implementation of model interface of LP paradigm and more importantly the time warp simulator.A. The Mod Interface of LP ParadigmJAMES II provides abstract model interfaces for different modeling formalism, based on which Wang etc. have designed and implemented model interface of LP paradigm[16]. However, this interface is not scalable well for parallel and distributed simulation of larger scale systems. In our implementation, we accommodate the interface to the situation of parallel and distributed situations. Firstly, the neighbor LP’s reference is replaced by its name in LP’s neighbor queue, because it is improper even dangerous that a local LP hold the references of other LPs in remote memory space. In addition, (pseudo-)random number plays a crucial role to obtain valid and meaningful results in stochastic simulations. However, it is still a very challenge work to find a good random number generator (RNG) [34]. Thus, in order to focus on our problems, we introduce one of the uniform RNGs of JAMES II to this model interface, where each LP holds a private RNG so that random number streams of different LPs can be independent stochastically. B. The Time Warp SimulatorBased on the simulator interface provided by JAMES II, we design and implement the time warp simulator, which contains the (master-)simulator, (LP-)simulator. The simulator works strictly as master/worker(s) paradigm for fine-grained parallel and distributed stochastic simulations. Communication costs are crucial to the performance of a fine-grained parallel and distributed simulation. Based on the Java remote method invocation (RMI) mechanism, P2P (peer-to-peer) communication is implemented among all (master-and LP-)simulators, where a simulator holds all the proxies of targeted ones that work on remote workers. One of the advantages of this communication approach is that PDES codes can be transferred to various hardwire environment, such as Clusters, Grids and distributed computing environment, with only a little modification; The other is that RMI mechanism is easy to realized and independent to any other non-Java libraries. Since the straggler event problem, states have to be saved to rollback events that are pre-processed optimistically. Each time being modified, the state is cloned to a queue by Java clone mechanism. Problem of this copy state saving approach is that it would cause loads of memory space. However, the problem can be made up by a condign GVT calculating mechanism. GVT reduction scheme also has a significant impact on the performance of parallel simulators, since it marks the highest time boundary of events that can be committed so that memories of fossils (processed events and states) less than GVT can be reallocated. GVT calculating is a very knotty for the notorious simultaneous reporting problem and transient messages problem. According to our problem, another GVT algorithm, called Twice Notification (TN-GVT) (see algorithm 2), is contributed to this already rich repository instead of implementing one of GVT algorithms in reference [26] and [28].This algorithm looks like the synchronous algorithm described in reference [26] (pp. 114), however, they are essentially different from each other. This algorithm has never stopped the simulators from processing events when GVT reduction, while algorithm in reference [26] blocks all simulators for GVT calculating. As for the transient message problem, it can be neglect in our implementation, because RMI based remote communication approach is synchronized, that means a simulator will not go on its processing until the remote the massage get to its destination. And because of this, the high-costs message acknowledgement, prevalent over many classical asynchronous GVT algorithms, is not needed anymore too, which should be constructive to the whole performance of the time warp simulator.IV. Benchmark Model and Experiment ResultsA. The Lotka-Volterra Predator-prey SystemIn our experiment, the spatial version of Lotka-Volterra predator-prey system is introduced as the benchmark model (see Fig. 2). We choose the system for two considerations: 1) this system is a classical experimental model that has been used in many related researches [8][30][31], so it is credible and the simulation results are comparable; 2) it is simple but helpful enough to test the issues we are interested in. The space of predator-prey System is partitioned into a2D NXNgrid, whereNdenotes the edge size of the grid. Initially the population of the Grass, Preys and Predators are set to 1000 in each single sub-volume (LP). In Fig. 2,r1,r2,r3stand for the reaction constants of the reaction 1, 2 and 3 respectively. We usedGrass,dPreyanddPredatorto stand for the diffusion rate of Grass, Prey and Predator separately. Being similar to reference [8], we also take the assumption that the population of the grass remains stable, and thusdGrassis set to zero.R1:Grass + Prey ->2Prey(1)R2:Predator +Prey -> 2Predator(2)R3:Predator -> NULL(3)r1=0.01; r2=0.01; r3=10(4)dGrass=0.0;dPrey=2.5;dPredato=5.0(5)Fig. 2: predator-prey systemB. Experiment ResultsThe simulation runs have been executed on a Linux Cluster with 40 computing nodes. Each computing node is equipped with two 64bit 2.53 GHz Intel Xeon QuadCore Processors with 24GB RAM, and nodes are interconnected with Gigabit Ethernet connection. The operating system is Kylin Server 3.5, with kernel 2.6.18. Experiments have been conducted on the benchmark model of different size of mode to investigate the execution time and speedup of the time warp simulator. As shown in Fig. 3, the execution time of simulation on single processor with 8 cores is compared. The result shows that it will take more wall clock time to simulate much larger scale systems for the same simulation time. This testifies the fact that larger scale systems will leads to more events in the same time interval. More importantly, the blue line shows that the sequential simulation performance declines very fast when the mode scale becomes large. The bottleneck of sequential simulator is due to the costs of accessing a long event queue to choose the next events. Besides, from the comparison between group 1 and group 2 in this experiment, we could also conclude that high diffusion rate increased the simulation time greatly both in sequential and parallel simulations. This is because LP paradigm has to split diffusion into two processes (diffusion (in) and diffusion (out) event) for two interactive LPs involved in diffusion and high diffusion rate will lead to high proportional of diffusion to reaction. In the second step shown in Fig. 4, the relationship between the speedups from time warp of two different model sizes and the number of work cores involved are demonstrated. The speedup is calculated against the sequential execution of the spatial reaction-diffusion systems model with the same model size and parameters using NSM.Fig. 4 shows the comparison of speedup of time warp on a64X64grid and a100X100grid. In the case of a64X64grid, under the condition that only one node is used, the lowest speedup (a little bigger than 1) is achieved when two cores involved, and the highest speedup (about 6) is achieved when 8 cores involved. The influence of the number of cores used in parallel simulation is investigated. In most cases, large number of cores could bring in considerable improvements in the performance of parallel simulation. Also, compared with the two results in Fig. 4, the simulation of larger model achieves better speedup. Combined with time tests (Fig. 3), we find that sequential simulator’s performance declines sharply when the model scale becomes very large, which makes the time warp simulator get better speed-up correspondingly.Fig. 3: Execution time (wall clock time) of Seq. and time warp with respect to different model sizes (N=32, 64, 100, and 128) and model parameters based on single computing node with 8 cores. Results of the test are grouped by the diffusion rates (Group 1: Sequential 1 and Time Warp 1. dPrey=2.5, dPredator=5.0; Group 2: dPrey=0.25, dPredator=0.5, Sequential 2 and Time Warp 2).Fig. 4: Speedup of time warp with respect to the number of work cores and the model size (N=64 and 100). Work cores are chose from one computing node. Diffusion rates are dPrey=2.5, dPredator=5.0 and dGrass=0.0.V. Conclusion and Future WorkIn this paper, a time warp simulator based on the discrete event simulation framework JAMES II is designed and implemented for fine-grained parallel and distributed discrete event spatial stochastic simulation of biological reaction systems. Several challenges have been overcome, such as state saving, roll back and especially GVT reduction in parallel execution of simulations. The Lotka-Volterra Predator-Prey system is chosen as the benchmark model to test the performance of our time warp simulator and the best experiment results show that it can obtain about 6 times of speed-up against the sequential simulation. The domain this paper concerns with is in the infancy, many interesting issues are worthy of further investigated, e.g. there are many excellent PDES optimistic synchronization algorithms (e.g. the BTW) as well. Next step, we would like to fill some of them into JAMES II. 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This paper suggests a new Affine Projection (AP) algorithm with variable data-reuse factor using the condition number as a decision factor. To reduce computational burden, we adopt a recently reported technique which estimates the condition number of an input data matrix. Several simulations show that the new algorithm has better performance than that of the conventional AP algorithm.

Abstract Context Dedicated model transformation languages are claimed to provide many benefits over the use of general purpose languages for developing model transformations. However, the actual advantages and disadvantages associated with the use of model transformation languages are poorly understood empirically. There is little knowledge and even less empirical assessment about what advantages and disadvantages hold in which cases and where they originate from. In a prior interview study, we elicited expert opinions on what advantages result from what factors surrounding model transformation languages as well as a number of moderating factors that moderate the influence. Objective We aim to quantitatively asses the interview results to confirm or reject the influences and moderation effects posed by different factors. We further intend to gain insights into how valuable different factors are to the discussion so that future studies can draw on these data for designing targeted and relevant studies. Method We gather data on the factors and quality attributes using an online survey. To analyse the data and examine the hypothesised influences and moderations, we use universal structure modelling based on a structural equation model. Universal structure modelling produces significance values and path coefficients for each hypothesised and modelled interdependence between factors and quality attributes that can be used to confirm or reject correlation and to weigh the strength of influence present. Results We analyzed 113 responses. The results show that the MTL capabilities Tracing and Reuse Mechanisms are most important overall. Though the observed effects were generally 10 times lower than anticipated. Furthermore, we found that moderation effects need to be individually assessed for each influence on a quality attribute. The moderation effects of a single moderating variable vary significantly for each influence, with the strongest effects being 1000 times higher than the weakest. Conclusion The empirical assessment of MTLs is a complex topic that cannot be solved by looking at a single stand-alone factor. Our results provide clear indication that evaluation should consider transformations of different sizes and use-cases that go beyond mapping one elements attributes to another. Language development on the other hand should focus on providing practical, transformation specific reuse mechanisms that allow MTLs to excel in areas such as maintainability and productivity compared to GPLs.

AbstractThe increasing rate of global solid waste generation is startling. This is exacerbating the challenge of decreasing solid waste generation to reduce disposal in landfills. U.S. Army installations offer a unique qualitative and quantitative dataset across a span of geographical locations. Modeling prediction capability of dining facility (DFAC) solid waste streams using data from 11 Army installations was investigated to demonstrate aggregate building and material type generation forecasting. Solid waste generation data were collected, quantified, and categorized for diversion potential (e.g., source reduction, reuse, recycling, composting, etc.) of materials currently landfilled. Over one week, samples from one day of DFAC operations were collected for each installation. Materials from the samples were manually separated into 22 categories, weighed, and recorded. Results identified many solid waste stream materials with diversion potential. Five material types were down selected to construct and validate the linear regression model. The material types down selection was based on available data robustness and applicability beyond military contexts. A linear regression model was constructed for five material and building type combinations to avoid multiplication factor errors of coefficients for each independent variable. Results were statistically significant (p-value ≤ 0.05) for four of five modeling combination predictions. These results demonstrate the unique capability of predicting solid waste generation for the four statistically significant model combinations. Each of the four statistically significant model combinations differed in adjusted R2 values, ranging from 0.988 to 0.996. This study provides five linear regression model combinations with predictive power that could reduce the labor- and cost-intensive process of characterizing waste streams while increasing data availability across the continental U.S. to focus targeted source reduction efforts for dining settings.

This study aims to analyze the influence of On-Time Performance, Price, and In-Flight Service Quality on consumer repurchase decisions for Citilink Airlines, specifically for flights operating through Soekarno-Hatta International Airport and Halim Perdanakusuma Airport. Using quantitative methods, data was collected through online questionnaire distribution using Google Form to Citilink airline service users who had utilized services from both airports. Data analysis was conducted using the Structural Equation Modeling Partial Least Square (SEM-PLS) approach to test relationships between research variables. The results proved that all three independent variables - On-Time Performance, Price, and In-Flight Service Quality - have significant influences on consumer repurchase decisions, both partially and simultaneously. Specifically, On-Time Performance proved to have the most dominant influence on affecting repurchase decisions for Citilink Airlines. These findings indicate that flight punctuality is the primary factor, followed by competitive pricing strategies and good in-flight service quality in encouraging consumers to reuse Citilink's flight services.

AbstractPolypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing.Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

The aim of this article was to develop a model for the usage of Open Access Institutional Repositories (OAIR) in university libraries in Ghana. The article adopted the Technology Acceptance Model (TAM), which was then modified to fit the study. The variables were adapted to improve the fit between data and the theoretical model, keeping the characteristics of TAM. Accessibility, availability and visibility were proposed in addition to the conventional variables of TAM. Positivist paradigm, quantitative methods research and survey design were used for the study. Simple random sampling and stratified random sampling were the sampling procedures and methods employed. A total of 998 respondents completed the questionnaires distributed. The questionnaire was used as a research instrument to gather relevant data for the study. Descriptive statistics (frequencies, percentages, means and standard deviation) and inferential statistics (multinomial logistic regression and Confirmatory Factor Analysis [CFA], using structural equation modelling [SEM]) were used as statistical tools to analyse the data. The study developed an OAIR Usage Model, which would be instrumental in the usage of OAIR in university libraries in Ghana. The model will enhance both user satisfaction and intention to reuse the OAIR, and make OAIR research outputs available, accessible and visible. This article adds to the body of literature on OAIR, as it is used in university libraries.

AbstractThis data article presents a high‐resolution map of available water content (AWC) for Senegal, derived from the iSDA Africa dataset and the USDA Rosetta3 model, as well as the method used for its production. The map covers the entire country at a resolution of 30 m and provides a valuable resource for hydrological studies and spatialized crop model simulations in the region where water is a limiting factor for crop production. The dataset is based on existing soil properties data and leverages pedotransfer functions (PTFs) to estimate water retention capabilities from soil properties. This AWC map derived from datasets with enhanced accuracy offers a more precise estimate of soil water retention capacity, which can be instrumental in informing water and agricultural management, policy decisions and investments. The dataset, including intermediate variables, is available in geotiff format at Cirad Dataverse under the DOI 10.18167/DVN1/SGNSII and complies with FAIR data principles, allowing its broad reuse. The code used to produce this dataset is also made available under the DOI 10.5281/zenodo.10078399, so that AWC maps can be produced for any territory covered by the iSDA Africa product.

Technical question and answer Q&A platforms, such as Stack Overflow, provide a platform for users to ask and answer questions about a wide variety of programming topics. These platforms accumulate a large amount of knowledge, including hundreds of thousands of lines of source code. Developers can benefit from the source code that is attached to the questions and answers on Q&A platforms by copying or learning from (parts of) it. By understanding how developers utilize source code from Q&A platforms, we can provide insights for researchers which can be used to improve next-generation Q&A platforms to help developers to reuse source code fast and easily. In this paper, we first conduct an exploratory study on 289 files from 182 open-source projects, which contain source code that contains an explicit reference to a Stack Overflow post. Our goal is to understand how developers utilize code from Q&A platforms and to reveal barriers that may make code reuse more difficult. In 31.5% of the studied files, developers needed to modify source code from Stack Overflow to make it work in their own projects. The degree of required modification varied from simply renaming variables to rewriting the whole algorithm. Developers sometimes chose to implement an algorithm from scratch based on the descriptions from Stack Overflow answers, even if there was an implementation readily available in the post. In 35.5% of the studied files, developers used Stack Overflow posts as an information source for later reference. To further understand the barriers of reusing code and to obtain suggestions for improving the code reuse process on Q&A platforms, we conducted a survey of 453 open-source developers who are also on Stack Overflow. We find that the top 3 barriers that make it difficult for developers to reuse code from Stack Overflow are: (1) too much code modification required to fit in their projects, (2) incomprehensive code, and (3) low code quality. We summarized and analyzed all survey responses and we identified that developers suggest improvements for future Q&A platforms along the following dimensions: code quality, information enhancement & management, data organization, license, and the human factor. For instance, developers suggest to improve the code quality by adding an integrated validator that can test source code online, and an outdated code detection mechanism that can identify code for outdated software versions. Our findings can be used as a roadmap for researchers and developers to improve future Q&A platforms.    

Wastewater recycling has been considered one way of ensuring sustainable water accessibility for domestic purposes through the UN’s Sustainable Development Goals (SDGs). This work investigated the factors that guide the preference for water recycling in Iwo, Osun State, Nigeria, to encourage its practice in homes. A survey was conducted among 205 randomly selected respondents in the study area to generate the data required to achieve the objectives of the study. Both descriptive and inferential statistical analyses were used using SPSS version 16.0. The study revealed that 79.3% of the respondents, mostly women, responded “nay” to wastewater reuse, attributing this to good access to fresh water, among other reasons. The factor analysis (FA) of the 13 variables obtained from the field extracted six variables that gave 76.542% of the variance about the respondents’ preference for wastewater recycling, namely: 1) method of producing wastewater; 2) proportion of the wastewater available for use; 3) volume of wastewater generated; 4) level of support for the practice of wastewater recycling; 5) perception about wastewater; and 6) reasons for wastewater recycling. Further analysis revealed that the six variables could be summarized into two, with the first three factors forming the first and the last three variables forming the second group: issues related to wastewater production and human attitude-related factors. Therefore, we reject the alternative hypothesis (H1) and accept the null hypothesis (H0) that the availability of wastewater does not hinder households’ preference for its use. The work concluded that the preferences for wastewater recycling are associated with issues about its production and human attitude/perceptions about wastewater. Public enlightenment and wastewater treatment technology in the study area and similar communities could probably enhance the preference for wastewater recycling.

Abstract The conservation of historical buildings is essential for safeguarding architectural heritage, facilitating urban development, and promoting sustainable economic growth. This research investigates the adaptive reuse of industrial architectural heritage in Hong Kong, focusing on its sustainable contributions to architectural practice and urban redevelopment. Employing the hedonic pricing model, this study quantitatively analyses the impact of industrial heritage conservation on property prices, revealing its significant contributions to imperatives with economic and developmental goals. Positioning Hong Kong as a paradigmatic example, this study uses a comprehensive analysis of 34,892 property transaction records collected from January 2010 to September 2022 across 23 subdistricts and offers critical insights into the challenges and opportunities of safeguarding industrial heritage within dynamic high-density urban landscapes. The findings indicate that approximately 75% of the variability in industrial property prices can be attributed to significant variables at the 1% confidence level. Key architectural parameters, including gross floor area (GFA), age, and floor level, demonstrate nonlinear relationships with industrial buildings designated for heritage conservation. The data suggest that industrial properties with a GFA of up to 10,989 square feet and an age of up to 41.5 years are considered best for preserving heritage values. Other urban planning parameters, such as the provisions of car parks and proximity to public transportation interchanges, also have significant positive external impacts on industrial property prices. These findings provide empirical evidence regarding the influence of heritage conservation on industrial property prices, serving as a valuable resource for policy-makers aiming to promote sustainable urban development and effective resource allocation. By integrating heritage conservation into urban planning strategies, this research underscores the vital role that preserved industrial heritage can play in fostering vibrant, sustainable urban environments.

Free maternity services is the offering of medical and obstetric care to pregnant women without any financial cost. Complications related to pregnancy were a major reproductive health problem that lead to disability and increased maternal deaths. Free maternity was introduced in Kenya in 2013 with a focus of achieving 100% utilization of the service and reducing high mortality rate. Homa-Bay County had a low percentage of 54% deliveries taking place in health facilities within the county. The main objective of this study was to establish Determinants of Health facilities Influencing Utilization of Free Maternity Services among Women of Reproductive Age 15-49 Years Attending Health Facilities in Homa-Bay County. Descriptive cross-sectional study design was applied to establish the main objective of this study. A probability and non-probability sampling techniques was used to select 420 respondents. The study utilized quantitative and qualitative methods of data collection. Data analysis was conducted with aid of Statistical Package for Social Scientists (SPSS) version 23. Analysis methods used were; factor analysis and regression analyses methods for quantitative data to determine the relationship and associations among the variables. Qualitative data was analyzed through content analysis by conducting thematic analysis. A total of 396 that was 94% response rate established 54% (213/396) mothers were interviewed and were aged between 20 years and 29years. Results showed that; age of the mothers was insignificant in utilization of free maternity services. Further analysis using logistics regression revealed that the respondents who agreed with the need for a well-equipped health facility with good sanitation system were 63% (OR 0.37, p = 0.03) more likely to reuse FMS. Distance was insignificant in utilization as long as the facility was well-equipped and adequately staffed as 57% (228/396).This study concluded that there was significant association between staff respect, and honesty of the staff with utilization of free maternity service. This study recommended that the County Government of Homa-Bay should increase awareness to women of reproductive age at the community level about FMS through Community health promotion officers in order to improve FMS uptake in Homa-Bay County.