Browsing by Author "Öztürk, H"

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    Artificial neural network-based prediction technique for wear loss quantities in Mo coatings
    Çetinel, H; Öztürk, H; Çelik, E; Karlik, B
    Mo coated materials are used in automotive, aerospace, pulp and paper industries in order to protect machine parts against wear and corrosion. In this study, the wear amounts of Mo coatings deposited on ductile iron substrates using an atmospheric plasma-spray system were investigated for different loads and environment conditions. The Mo coatings were subjected to sliding wear against AISI 303 counter bodies under dry and acid environments. In a theoretical study, cross-sectional microhardness from the surface of the coatings, loads, environment and friction test durations were chosen as variable parameters in order to determine the amount of wear loss. The numerical results obtained via a neural network model were compared with the experimental results. Agreement between the experimental and numerical results is reasonably good. (c) 2006 Elsevier B.V. All rights reserved.
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    Nursing students' classroom climate perceptions: A longitudinal study
    Kurt, Y; Özkan, ÇG; Öztürk, H
    Background: As a versatile and dynamic process, classroom climate directly affects the learning levels of students and their quality of life while in school. Objectives: The study was conducted to explore and compare nursing students' perceptions of classroom climate throughout four years of university education and to evaluate the influencing factors. Design and settings: The longitudinal study was conducted between 2017 and 2020 in the nursing department of a university in Turkey. Participants: The study was carried out with 134 nursing students who enrolled in their first year and agreed to participate in the study. Methods: The data were collected at the end of the fall semester of each of the four years using the Student Information Form and the Classroom Climate Inventory. Results: The mean score of students' perceptions of classroom climate was 2.88 +/- 0.83 for all academic years. The classroom climate inventory mean scores of fourth-year students were statistically significantly higher than their scores in the first and third years (p = 0.000). The students' classroom climate levels were statistically significantly affected by the positive classroom communication among students in all academic years in a positive direction. Statistically significant effective factors in students' classroom climate perceptions by year were as follows: the sense of belongingness to the class in the second and third years (although significantly lower in the first year), socio-cultural activities organized at school the second and fourth years (p < 0.05), instructors' attitudes supporting classroom communication in the first year, and opportunities supporting communication in the school environment in the fourth year (p < 0.05). Conclusions: Students' perception of the classroom climate was moderate overall and affected by positive classroom communication among students in all academic years. School administrators and educators can develop strategies and organize activities to increase positive communication in the classroom.
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    Comparison of the effects of face-to-face and electronic peer mentoring on students' care plan preparation and motivation levels
    Kurt, Y; Ozkan, ÇG; Öztürk, H
    Background: It is a basic requirement in professional nursing education that nursing students learn the process of caring as the entity at the center of nursing practice. Peer mentoring programs can be beneficial for the mutual growth of mentors and mentees and improve the care competencies of nursing students. Objective: To compare the effects of face-to-face and electronic peer mentoring on students' nursing process-based patient care plan preparation and motivation levels for the course. Design: The study used an experimental three-group design. Settings and participants: This experimental study was conducted with 83 first-and 6 fourth-year nursing students. Method: The data were collected with the information and opinion form, the Instructional Materials Motivation Survey (IMMS), and the Nursing Care Plan Rubric (NCPR). In the study, conducted with three subgroups of each group, the experimental group received electronic peer mentoring (EPM), and the experimental group 2 received face-to-face peer mentoring (FPM), while the control group did not receive any intervention. Results: It was statistically significant that the students in the EPM group had higher patient care plan preparation scores than the FPM and control groups, and the FPM group had higher patient care plan preparation scores than the control group (p < 0.05). Also, the students in the FPM group had statistically significantly higher confidence -satisfaction sub-dimension scores on the IMMS than those in the EPM and control groups (p < 0.05). Conclusion: While electronic peer mentoring was effective on the patient care plan preparation levels of first-year nursing students, face-to-face peer mentoring was more effective in increasing the students' confidence and attitude levels and thus their motivation levels.
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    Standardised Pressure Injury Prevention Protocol (SPIPP- Adult) Checklist 2.0: Language and Content Validity Study
    Özkan, ÇG; Kurt, Y; Öztürk, H
    IntroductionImplementation of clinical practice guidelines, an important strategy in the prevention of pressure injuries, enables the nurse to interpret evidence-based guideline recommendations, reduce errors, ensure compliance and standardisation of complex processes, manage patient-related risks and systematically regulate all preventable conditions.ObjectiveThis study was conducted to ensure the Turkish language and content validity of the Standardised Pressure Injury Prevention Protocol (SPIPP- Adult) Checklist 2.0.MethodIn this methodological research study, a five-stage technique was used in the translation of the SPIPP- Adult Checklist 2.0, which was created and revised by Joyce Pitmann et al. based on the International 2019 Clinical Practice Guidelines, into Turkish. These stages included initial translation, evaluation of initial translation, back translation, evaluation of back translation and expert opinion. Davis technique was used to determine the content validity of SPIPP- Adult Checklist 2.0.ResultsThe scale was translated into Turkish and back-translated into the original language and the opinions of nine experts were obtained. The content validity scores of the SPIPP- Adult Checklist 2.0 were found to be between 0.88 and 1.0 and the total CGI score was calculated as 0.99. This value shows that content validity is at an acceptable level. After expert evaluations, it was decided that the final version of the scale was appropriate for use.ConclusionThis study demonstrated that the SPIPP- Adult Checklist 2.0 is a valid tool. Interventions using the evidence-based checklist should be integrated into the workflow and provide the best opportunity for successful and sustainable pressure injury prevention.
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    Optimal expansion planning of electrical energy distribution substation considering hydrogen storage
    Basaran, K; Öztürk, H
    Electricity network operators undertake important responsibilities such as balancing electricity demand and supply, minimizing power outages, and making the necessary maintenance, repairs, and investments to provide safe and continuous energy. In this context, the most significant challenge encountered today is the need for a more immediate renewal of distribution grid expansion plans, owing to the rapid increase in energy demand and the grid integration of renewable energy power plants and electric vehicle charging stations. In order to find a solution to this issue, an active distribution network has been analyzed under five scenarios based on load demand forecasting. The artificial neural network method has been employed for the forecast of load demand, and the DigSilent Power Factory (DPF) model of the distribution network has been utilized to analyze the effects of scenarios. Connecting PV plants with capacities of 3 MW and 5 MW to different feeders in the distribution network, along with Hydrogen Energy Storage (HES) with a capacity of 1 MW to one feeder, has resulted in a reduction of the distribution transformer's occupancy rate from 79.8% to 70.6%. The contribution of a 1 MW HES system to the transformer occupancy rate was determined to be 1.3%. The results highlight the importance of considering the annual load demand forecast, as well as the network integration of PV power plants, electric vehicle charging stations, and hydrogen storage in grid expansion planning.
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    The effect of behavior changes caused by the covid-19 pandemic on electricity consumptions and feeder loads: a case study on an electricity distribution feeder
    Öztürk, H; Basaran, K
    The COVID-19 (Sars CoV-2) virus, which emerged in Wuhan city of Hubei province of China in December 2019, affected the whole world in a short time and was declared a global epidemic by the World Health Organization (WHO) as of March 11, 2020. After this date, closure measures have been implemented all over the world to prevent the spread of the virus. Due to the provisions taken, there have been changes in electrical energy consumption compared to previous years. In March, April and May 2020, when the restrictions affected human life the most, dynamic changes occurred in energy demand all over the world. This has affected international energy markets, energy production and grid load planning. Although the total electricity consumption in Turkey increased compared to the previous year, there was a decrease in the consumption in the commercial tariff. In this study, the effects of the COVID-19 pandemic on electricity consumption were analyzed by analyzing the electricity consumption of Turkey and Izmir, depending on the tariffs, based on time. A case study was conducted on an electricity distribution feeder to see the impact of COVID-19 on electricity distribution networks. For the case study, an electricity distribution feeder with 99% of the subscriber density in the residential and commercial tariff group was selected. For the feeder, load forecasting was made using artificial neural networks machine learning method according to 2018, 2019 and 2020 data. In the load forecasting study, 75% of the data was selected for learning and 25% for testing. As a result of the study, the actual and forecasted load data of 2020 were compared. The effects of the COVID-19 pandemic on the lad of an electricity distribution feeder were investigated. In the study, the best performance values of load forecasting were found mse as 0.0024 and R2 as 0.83.