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1 – 3 of 3Selman Turkes, Hakan Güney, Serin Mezarciöz, Bülent Sari and Selami Seçkin Tetik
The widespread use of washing machines in textile dyeing and finishing boosts product quality while leading to significant wastewater production. This wastewater poses…
Abstract
Purpose
The widespread use of washing machines in textile dyeing and finishing boosts product quality while leading to significant wastewater production. This wastewater poses environmental risks due to the textile industry's high pollution levels and water consumption. Sustainability hinges on minimizing water usage and treating wastewater for reuse. This study employs Matlab R2020a and Python 2023 to model experimental designs for treating textile production wastewater using the Fenton oxidation method, aiming to address sustainability concerns in the industry.
Design/methodology/approach
The Fenton oxidation process's efficacy and optimal operating conditions were determined through experimental sets employing the Box–Behnken design. Assessing machine learning algorithms on the data, Matlab R2020a utilized an artificial neural network (ANN), while Python 2023 employed support vector regression (SVR), decision trees (DT), and random forest (RF) models. Evaluation of model performance relied on regression coefficient (R2) and mean square error (MSE) outcomes. This methodology aimed to refine the Fenton oxidation process and identify the most efficient parameters, leveraging a combination of experimental design and advanced computational techniques across different programming platforms.
Findings
The study identified optimal conditions: pH 3, Fe+2 concentration of 0.75 g/L, and H2O2 concentration of 5 mM, yielding 87% COD removal. The Box–Behnken design achieved a high R2 of 0.9372, indicating precise predictions. Artificial neural networks (ANN) and support vector regression (SVR) exhibited successful applications, notably achieving an R2 of 0.99936 and low MSE of 0.00416 in the ANN (LOGSIG) model. However, decision trees (DT) and random forests (RF) proved less effective with limited datasets. The findings underscore technology integration in treatment modeling and the environmental imperative of wastewater purification and reuse.
Originality/value
This study, in which water use and wastewater treatment are evaluated with technological integration such as machine learning and data management, reveals how to contribute to targets 6, 9, 12, and 14 within the scope of UNEP 2030 sustainable development goals.
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Gullu Gencer, Hakan Atay, Arzu Gurdogan and Ulker Colakoglu
This study aims to measure the effect of organizational culture perceptions of hotel employees on their organizational silence behavior and job performance, as well as the effect…
Abstract
Purpose
This study aims to measure the effect of organizational culture perceptions of hotel employees on their organizational silence behavior and job performance, as well as the effect of their organizational silence behavior on their job performance.
Design/methodology/approach
A correlational survey model was used in this research and a questionnaire was distributed to collect the data from 389 sampled employees working in four- and five-star hotels in the Kusadasi region in Turkey.
Findings
It was found that organizational culture was not significantly related to organizational silence but that organizational culture and its dimensions were significantly related to job performance. It was also revealed that while organizational silence was not significantly related to job performance, its dimensions were significantly related to job performance.
Practical implications
The results of this study provide insight into organizational culture as an important factor in increasing job performance. The study also revealed how organizational silence behavior and its dimensions affect job performance. In this sense, accommodation establishments will be able to acquire new perspectives in terms of improving job performance.
Originality/value
This paper is deemed important, as it examined these three terms in one model in the field of tourism management. It is thought that it will contribute to the literature by closing the gap in the tourism literature while leading the way for future studies.
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Murat Özdemir, Barış Eriçok, Hakan Topaloğlu and Gamze Tuti
In recent decades, researchers have increasingly begun to study the effects of transformational leadership on various teachers’ attitudes in K-12 settings. However, studies on the…
Abstract
Purpose
In recent decades, researchers have increasingly begun to study the effects of transformational leadership on various teachers’ attitudes in K-12 settings. However, studies on the effect of transformational leadership on the job satisfaction of vocational high school teachers are not sufficient. Therefore, in this study, the nature of the relationship between transformational leadership and job satisfaction in Turkish vocational high schools was examined.
Design/methodology/approach
The study data came from 847 teachers working at 82 state vocational high schools located in 12 regions in Türkiye. To test the research model, we conducted multilevel structural equation modeling to explore the structural relationships between transformational leadership, teacher professional learning, teacher’ self-efficacy and job satisfaction.
Findings
The analysis confirms that teacher professional learning and self-efficacy are prominent mediators in the relationship between transformational leadership and job satisfaction in Turkish vocational high schools.
Originality/value
The present study is expected to contribute to the body of research focusing on the effects of transformational leadership on job satisfaction in vocational high schools. Implications for theory, practice and policy are discussed.
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