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Strategic feasibility outlook for blue energy investments using an integrated decision-making approach
(2025) Eti, Serkan; Yüksel, Serhat; Dinçer, Hasan
Conducting feasibility analysis in blue energy investments is very critical to provide performance analysis of the projects. However, a significant portion of the studies in the literature focus on general energy projects. Nevertheless, there are not enough studies for a more specific area such as blue energy. This situation significantly increases the need for this type of priority analysis. Accordingly, the purpose of this study is to identify the most appropriate strategies to increase the effectiveness of the feasibility analysis of blue energy investments via a novel decision-making model. In the first stage of the model, the importance levels of experts are computed using machine learning technique. The second stage includes weighting the feasibility criteria set for blue energy project investment by Fermatean fuzzy entropy. After that, the strategic alternatives for increasing the capacity of blue energy projects are ranked with Fermatean fuzzy CoCoSo. The main contribution of this study to the literature is making a detailed evaluation to generate appropriate strategies for the feasibility analysis of the blue energy investments via a novel decision-making model. The integration of AI system provides some advantages to the proposed model. In this way, the decision matrix is obtained by calculating the importance weights of each expert. This situation allows to have more accurate analysis results. It is defined that the technological infrastructure of the company plays the most critical role (weight: 0.173) when conducting feasibility analysis for blue energy investments. Similarly, it is also identified that the financial performance of the business (weight: 0.172) is also important to conduct a more successful feasibility analysis for blue energy investments. On the other side, the ranking results demonstrate that collaborating with the investment-ready companies for increasing the innovative technologies is the most appropriate strategy to increase the capacity of blue energy projects.
Innovative approaches to green digital twin technologies of sustainable smart cities using a novel hybrid decision-making system
(2025) Cao, Jifeng; Spulbar, Cristi; Eti, Serkan; Horobet, Alexandra; Yüksel, Serhat; Dinçer, Hasan
Digital twin technologies play a very important role in the provision of smart cities. However, it is not clear which innovative strategies should be implemented first on how to optimize digital twin technologies for sustainable smart cities. The main performance indicators should be identified to use the limited resources more efficiently and to generate more effective investment strategies. Accordingly, the purpose of this study is to generate innovative approaches to green digital twin technologies of sustainable smart cities. To achieve this issue, first, important criteria of digital twin technologies for assessing sustainable smart cities are weighted via spherical fuzzy simple weight calculation (SIWEC). The second part includes ranking innovative alternatives for green digital twin technologies by considering spherical fuzzy simple additive weighting (SAW). The main contribution of this manuscript is to identify the most effective investment strategies for the improvements of digital twin technologies to reach smart cities by establishing a novel model. The preference of the SIWEC method in the criteria weighting process provides some advantages to the model. The most important feature of this method is that the direct importance of the criterion is taken into consideration in the questions asked to the experts. In this way, it is possible for the experts to give more sensitive answers. The findings indicate that smart grid integration (weight: 0.231) is determined as the most important criterion in the development of digital twin technologies for the provision of smart cities. Circular economy (weight: 0.230) is another variable that plays an important role in the provision of smart cities. On the other hand, decentralized energy system with microgrids is found as the most important alternative for this situation. Some critical actions should be taken to improve the smart grid effectiveness. In this scope, providing renewable energy incentives has a strong influence on the improvements of these projects.
Innovative financial solutions for sustainable investments using artificial intelligence-based hybrid fuzzy decision-making approach in carbon capture technologies
(2025) Yüksel, Serhat; Eti, Serkan; Dinçer, Hasan; Gökalp, Yaşar; Olaru, Gabriela Oana; Kalaycı Oflaz, Nihal
High costs, technical difficulties, and policy uncertainties are the main challenges in carbon capture technology investments. Therefore, innovative financial products are required to develop projects that overcome these difficulties. Some issues must be considered when developing innovative financial products. An important problem in this process is that these features cannot possibly exist together in the new financial product, because each of these features incurs some costs. Therefore, identifying the most important features of innovative financial products is necessary. Accordingly, this study develops a new and innovative financial product to increase the effectiveness of investments in carbon capture technologies. For this purpose, a novel artificial intelligence (AI)-based fuzzy decision-making model is constructed. First, the weights of the experts were calculated by considering AI methodology. Second, the factors affecting investment in carbon capture technologies were weighted using a spherical fuzzy DEMATEL. Finally, the financial features required for investments were ranked using the spherical fuzzy ARAS method. This study’s main contribution is its creation of a novel fuzzy decision-making model by integrating AI methodology with fuzzy decision-making theory. In this process, the weights of the experts are calculated using an AI approach. It is concluded that cost-effectiveness must be prioritized in the development of new financial products. Technological competence is another aspect that should be considered in this process. However, innovative financial products should include risk management and flexible financing.
A novel fuzzy decision-making approach to pension fund investments in renewable energy
(2025) Yüksel, Serhat; Eti, Serkan; Dinçer, Hasan; Meral, Hasan; Umar, Muhammad; Gökalp, Yaşar
Pension fund must consider some significant issues when making renewable energy project investment decisions. It is necessary to determine the most important factors and prioritize the indicators. Accordingly, the purpose of this study is to conduct a priority analysis of the determinants of investment in renewable energy projects by pension funds. This study constructs a novel fuzzy decision-making model. First, five indicators for this process are weighted using an entropy methodology based on sine trigonometric Pythagorean fuzzy sets. The CRITIC methodology is also considered to make a comparative evaluation. Second, five different clean energy investment alternatives for pension funds are ranked using the RATGOS methodology. Similarly, this ranking analysis is also made by considering TOPSIS technique to check the reliability of the results. The main contribution of this study is the creation of a new and comprehensive fuzzy decision-making model to identify the most important factors in renewable energy project investments for pension funds. The proposed model uses the RATGOS technique to rank clean energy investment alternatives for pension funds. By considering the geometrical mean in the RATGOS calculation process, criticisms related to existing ranking techniques can be overcome. The use of sine trigonometric Pythagorean fuzzy numbers provides significant benefits to the quality of the proposed decision-making model. The defuzzification process can be implemented appropriately using these sets. Therefore, this study’s findings pave the way for investors to make investment decisions under these circumstances. It is concluded that the most important criterion is risk minimization. Effective regulations are another critical issue. Furthermore, the ranking results indicate that the most suitable renewable energy alternative is green bonds. The comparative results with STPFY-TOPSIS show that the proposed model generates coherent and reliable findings.
A novel approach to prioritizing health technology investments using integrated ai-based ranking model
(2025) Gökalp, Yaşar; Eti, Serkan; Dinçer, Hasan; Yüksel, Serhat
Purpose – Health technologies are an issue that directly affectsthe sustainability and quality of health services. Due to budget constraints, it is not financially possible for businesses to apply comprehensive improvement strategies to all these criteria. In this case, it is possible for businesses to implement more priority strategies. Accordingly, the main purpose of this study is to evaluate the important performance indicators of health technology investments. Design/methodology/approach – Firstly, with the help of the artificial intelligence system, a decision matrix is established. Secondly, spherical fuzzy total order of preference decision-making trial and evaluation laboratory methodology istaken into consideration for weighting the criteria. Thirdly, emerging seven countries are ranked by using spherical fuzzy MultiAtributive Ideal-Real Comparative Analysis (MAIRCA). Findings – The findings demonstrate that the criteria of health policies and research and development are defined as the most significant factor in this regard. China and Turkey are also found to be the most successful emerging countries with respect to the performance of health technology investments. Originality/value – The main contribution of this study is that a novel decision-making model is generated by integrating artificial methodology into the spherical fuzzy sets.
On weakly s-ρ-ideals in noncommutative rings
(2024) Abouhalaka, Alaa; Çay, Hatice; Groenewald, Nico
Let R be a noncommutative ring, and φ ≠ S ⊆ R be an m-system of R. In this paper, we extend the concept of weakly prime ideals in noncommutative rings by introducing weakly S-ρ-ideals. This generalization builds on the notions of right S-prime, weakly S-n-ideals and S-ρ-ideals. We present equivalent definitions and key properties of weakly S-ρ-ideals. We also explore with the method of idealization how the weakly S-ρ-ideal property transfers to related rings and construct such ideals. On the other hand we give a generalization of S-J-ideals which were introduced in [12].
S-j-ideals: a study in commutative and noncommutative rings
(2024) Abouhalaka, Alaa; Çay, Hatice; Ersoy, Bayram Ali
In this paper, we introduce the concept of S- (Formula presented.) -ideals in both commutative and noncommutative rings. For a commutative ring R and a multiplicatively closed subset S, we show that many properties of (Formula presented.) -ideals apply to S- (Formula presented.) -ideals and examine their characteristics in various ring constructions, such as homomorphic image rings, quotient rings, cartesian product rings, polynomial rings, power series rings, idealization rings, and amalgamation rings. In noncommutative rings, where S is an m-system, we define right S- (Formula presented.) -ideals. We demonstrate the equivalence of S- (Formula presented.) -ideals and right S- (Formula presented.) -ideals in commutative rings with identity and provide examples to illustrate the connections between right S-prime ideals and (Formula presented.) -ideals.
Generalization of ρ-ideals associated with an m-system and a special radical class
(2025) Çay, Hatice; Abouhalaka, Alaa; Ersoy, Bayram Ali
Let phi not equal S subset of R be an m-system of a ring R, and let. be a special radical. This study introduces the concept of S-rho-ideals in noncommutative rings. This notion extends the previously studied rho-ideals and can also be seen as a generalization of the right S-prime ideals. We show how some properties associated with rho-ideals have evolved into results within these generalizations. Relationships between S-rho-ideals and other types of ideals like rho-ideals, right S-prime ideals, and S-finite ideals are shown. We show the behaviour of this notion in related rings. The construction of (S boxed plus M)-rho-ideals in idealization rings is presented for an R- R-bimodule M. Additionally, we introduce S-P-ideals using Baer-McCoy radical P and examine their properties.
A machine learning and fuzzy logic model for optimizing digital transformation in renewable energy: insights into industrial information integration
(2024) Eti, Serkan; Yüksel, Serhat; Dinçer, Hasan; Pamucar, Dragan; Deveci, Muhammet; Olaru, Gabriela Oana
The most essential criteria to improve digital transformation in renewable energy projects should be identified. This situation helps the companies to use limited financial budgets and human resources in the most efficient way. Therefore, a new study is needed to analyze the performance indicators of the digital transformation process in renewable energy projects. Accordingly, this study aims to identify the most significant performance indicators of digital transformation for these projects. A three-stage machine learning and fuzzy logic-based decision-making model has been constructed in this process. The first stage includes the weight calculation of the experts by dimension reduction methodology. Secondly, essential factors of digital transformation in renewable energy projects are examined via Fermatean fuzzy criteria importance through intercriteria correlation (CRITIC). The final part consists of the ranking of emerging seven countries with Fermatean fuzzy weighted aggregated sum product assessment (WASPAS). On the other side, combined compromise solution (CoCoSo) method is also taken into consideration in this process to make a comparative evaluation. The main contribution of this study is the generation of novel machine learning and fuzzy logic integrated decision-making model to make evaluation related to the digital transformation of renewable energy projects. In this model, machine learning technique is used to determine the importance weights of the experts. Similarly, integrating Fermatean fuzzy numbers with CRITIC and WASPAS techniques also contributes to the literature by minimizing the uncertainty and identifying the relationship between the items. The findings demonstrate that employing qualified personnel plays the most critical role in increasing digital transformation in renewable energy projects. Additionally, government support is very critical in the successful implementation of digital transformation processes in renewable energy projects.
Assessment of water electrolysis projects for green hydrogen production with a novel hybrid q-learning algorithm and molecular fuzzy-based modelling
(2024) Dinçer, Hasan; Eti, Serkan; Acar, Merve; Yüksel, Serhat
Determining the most important criteria for increasing the efficiency of water electrolysis investments provides businesses with a competitive advantage. Although there are many studies in the literature on this importance, there are very few studies determining the most important of these performance indicators. To satisfy this gap, the purpose of this study is to make assessment of water electrolysis projects for green hydrogen production via a novel model. First, the balanced expert evaluation matrices are obtained by q-learning algorithm. Secondly, the criteria for water electrolysis investments are prioritized using molecular fuzzy Bayesian network (BANEW). Thirdly, green hydrogen strategies for water electrolysis investments are ranked with molecular fuzzy multi-objective particle swarm optimization (MOPSO). The most important contribution of this study to the literature is the determination of the criteria that should be applied primarily for the performance increase of water electrolysis investments by creating a new model. The use of molecular fuzzy numbers is a very important contribution of the model to the literature. In this process, the use of three-dimensional geometric figures allows the reduction of uncertainties in decision-making processes. The findings indicate that lifespan of electrolysers and production capacity are the most essential criteria. Additionally, proton exchange membrane electrolysers and alkaline water electrolysis are found as the most critical green hydrogen strategies. Extending the life of electrolysers is crucial to increase sustainability in hydrogen production and reduce long-term costs. In this context, research incentives should be provided for the development of materials and technologies to increase the durability of electrolysers. Similarly, establishing quality standards to extend the life of electrolysers also contributes to achieving this goal.
Innovative solution suggestions for financing electric vehicle charging infrastructure investments with a novel artificial intelligence-based fuzzy decision-making modelling
(2024) Kou, Gang; Eti, Serkan; Yüksel, Serhat; Dinçer, Hasan; Ergün, Edanur; Gökalp, Yaşar
The right methods for effective financing of electric vehicle charging infrastructure investments should be identified. However, in the literature, there is no consensus on which funding source would be right for these projects. There is a need for a new study to recommend the most appropriate financing strategy for these projects. Accordingly, the purpose of this study is to identify innovative solutions for financing electric vehicle charging infrastructure investments. A novel fuzzy decision-making model is introduced to reach this objective. Firstly, the weights of experts are calculated using dimension reduction. Secondly, Spherical fuzzy decision matrix is obtained. Thirdly, the criteria in charging infrastructure for electric vehicles are weighted using Spherical fuzzy criteria importance through intercriteria correlation (CRITIC). Fourthly, innovative solutions for financing electric vehicles charging infrastructure are ranked via Spherical fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS). The main contribution of this study is that effective strategies can be identified for financing electric vehicle charging infrastructure investments by establishing a novel decision-making model. Most of the existing models in the literature could not consider the weights of the experts. This condition is criticized by different scholar because these experts can have different qualifications. To satisfy this problem, in this study, dimension reduction algorithm with machine learning is taken into consideration to compute thee weights of the experts. The findings demonstrate that the most effective criterion in the innovative financial solution for the charging infrastructure of electric vehicles is determined as “potential income”. According to the ranking results, it is also defined that the most sustainable solution among the innovative strategies for financing the charging infrastructure of electric vehicles is “blockchain technology”.
Technical assessment of solar energy storage investments with recommender system-enhanced quantum picture fuzzy rough sets
(2024) Kou, Gang; Dinçer, Hasan; Yüksel, Serhat; Eti, Serkan; Acar, Merve
The performance of solar energy storage projects should be improved by taking appropriate actions. However, there are very different criteria that affect the performance of these investments. Therefore, businesses need to focus on more important criteria to use the budget effectively and efficiently. This situation increases the need for a priority analysis for performance indicators of solar energy storage investments. Accordingly, the purpose of this study is to make evaluation for the technical assessment of solar energy storage investments. In this scope, a new four-stage model is introduced by considering different decision-making techniques and fuzzy sets. The first stage is related to the prioritizing the experts with artificial intelligence (AI)-based decision-making method. Secondly, the missing evaluations of solar energy storage investments are estimated with expert recommender system. In the following part, the criteria for the technical assessment of solar energy storage investments are weighted by quantum picture fuzzy rough sets (QPFRS) adopted M−SWARA. The final stage consists of ranking the solar energy storage alternatives with QPFR-VIKOR. The main contribution of this study is the generation of the decision matrix by the help of AI. This situation gives an opportunity to calculate the significance weights of the experts. Therefore, the analysis results can be more reliable and coherent. It is concluded that battery capacity is the most critical factor for the technical assessment of solar energy storage investments. On the other hand, pumped hydro for mechanic energy is found as the most significant solar energy storage alternative. Governments should provide the necessary incentives for the development of high-capacity battery technologies. In this context, tax reductions can be provided to companies that invest in production technologies. This contributes to the cost efficiency of businesses.
Holistic evaluation of energy transition technology investments using an integrated recommender system and artificial intelligence-based fuzzy decision-making approach
(2024) Dinçer, Hasan; Pamucar, Dragan; Yüksel, Serhat; Deveci, Muhammet; Eti, Serkan; Hacıoğlu, Ümit
The most essential criteria should be determined in the selection of the suitable energy transition technologies due to budget deficit problem. Therefore, it is necessary to identify the most important criteria in energy transition technology selection. Therefore, a new study is needed to determine the most prominent issues in the correct selection of energy transition technologies. The purpose of this study is to identify the most appropriate energy transition technology alternative. Within this framework, a novel artificial intelligence (AI)-based fuzzy decision-making model has been presented. In the first part, the experts are prioritized by the help of AI methodology. In the next section, missing evaluations of energy transition technology investments are estimated via expert recommender system. Thirdly, the weights of the criteria for energy transition technology selection are computed by quantum picture fuzzy rough sets (QPFR) M-Stepwise Weight Assessment Ratio Analysis (SWARA). At the final stage, selected energy transition technology alternatives are ranked via QPFR-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The main contribution of this study is the integration of AI technique to the proposed model. Similar to this issue, using M-SWARA methodology in the process of criteria weighting increases the quality of the findings. This methodology helps to consider the impact relation map of the criteria. The findings demonstrate that the most important factor is cost-effectiveness of energy transition. Similarly, it is also found that the local ecosystem is the second most significant issue. On the other side, the ranking results denote that compact renewable systems for small scale production is the most optimal solution of energy transition technology alternatives.
The relationship between perceived stress and emotional eating in bus drivers: the effect of shift work
(2024) Bayraktaroğlu, Emre; Hızlı Güldemir, Hilal; Eti, Serkan; Kayalı Sevim, Merve; Saleki, Neda
This study discusses the relationship between perceived stress and emotional eating based on shiftwork in city bus drivers. It was conducted with 1403 male city bus drivers working in Istanbul. Questions about the drivers’ physical activity and dietary habits, the Healthy Diet Index (HDI), Emotional Appetite Questionnaire and Perceived Stress Scale-10 data were collected and evaluated in two groups: shift and non-shift employees. It was found that the shift workers (SWs) have lower perceived stress, physical activity, HDI and positive emotional appetite averages. In addition, for SWs, a positive correlation was found between negative emotional appetite scores and physical activity and HDI scores. In conclusion, the drivers working in shifts were found to be slightly overweight and had lower physical activity levels, had lower HDI scores, and their nutritional status was more negatively impacted than their counterparts.
Financial multidimensional assessment of a green hydrogen generation process via an integrated artificial intelligence-based four-stage fuzzy decision-making model
(2024) Yüksel, Serhat; Dinçer, Hasan; Acar, Merve; Ergün, Edanur; Eti, Serkan; Gökalp, Yaşar
It is widely accepted that there is an urgent need to make green hydrogen (GH2) projects financially viable to reduce global warming. However, any form of improvements to these GH2 projects lead to substantial cost increase. Due to this cost increase, making many improvements negatively affects the financial profitability of hydrogen projects. This is why there is a need for new advanced financial priority analysis tools so that it is easier to develop GH2 projects globally. Accordingly, the aim of this study is to identify and then define the most important factors affecting GH2 generation projects. To achieve this aim, this work proposes a new fuzzy multi-criteria decision-making model based on artificial intelligence (AI). First, experts are weighted with AI technique. Second, the missing evaluations are filled via a recommender system. Third, criteria weights are calculated by the M-SWARA technique integrated with quantum picture fuzzy rough (QPFR) sets. Finally, GH2 energy generation processes are listed by the QPFR-VIKOR approach. Overall, the main contribution of this study is the generation of a comprehensive AI oriented fuzzy decision-making model to make a detailed evaluation with respect to the financial potential improvements of the GH2 generation projects. The main originality of this model is the consideration of AI to calculate the weights of the criteria. Similarly, another benefit of the proposed model, that increases its superiority against other models, is the completion of missing evaluations by experts thanks to the recommender system. It is concluded that the most important criterion affecting green hydrogen investments is organizational effectiveness.
Analyzing energy transition for industry 4.0-driven hybrid energy system selection with advanced neural network-used multi-criteria decision-making technique
(2024) Liu, Peide; Eti, Serkan; Yüksel, Serhat; Dinçer, Hasan; Gökalp, Yaşar; Ergün, Edanur; Aysan, Ahmet Faruk
This study aims to select the appropriate renewable energy alternatives for the efficiency of hybrid energy systems to increase energy transition performance. For this purpose, a novel neural network (NN)-based fuzzy decision-making model is constructed that has three different stages. In the first stage, NN-based fuzzy decision matrix is created. Secondly, 6 different variables based on industry 4.0 are weighted with the sine trigonometric Pythagorean fuzzy entropy technique. Additionally, another calculation has been implemented with criteria importance through intercriteria correlation (CRITIC) to identify the consistency of the results. Furthermore, in the third stage, considering 5 different renewable energy alternatives, 10 different combinations are identified for hybrid energy systems. The most effective alternatives are defined by the sine trigonometric Pythagorean fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS) method. Moreover, to test the validity of these results, another analysis is conducted using the additive ratio assessment (ARAS) technique. The main contribution of the study is that the optimal renewable energy combination required for an efficient hybrid energy system is determined by performing a priority analysis between the variables. This situation has a significant guiding feature for investors. Similarly, the development of the RATGOS technique both increases the methodological originality of the study and enables more accurate alternative ranking. It is identified that the results of all methods are similar. Therefore, this situation gives information about the coherency and validity of the findings. It is concluded that the most important criterion is real-time capability. It is also denoted that the best combination for hybrid energy systems is Solar-Wind.
Evaluation of psychosocial risks affecting academician using the sine trigonometric pythagorean fuzzy (st-pfn) dematel method
(2024) Tepe, Serap; Çabuk, Ahmet; Eti, Serkan; Mertoğlu, Bülent
BACKGROUND:In the realm of academia, psychosocial risk factors play a pivotal role, exerting considerable influence on the well-being and performance of scholars. Factors such as excessive workloads, unrelenting performance expectations, time constraints, and competitive atmospheres can detrimentally affect their health and overall quality of life. Moreover, issues like social isolation, work-life imbalance, and academic anxiety further compound these challenges, impeding academic progress and success. OBJECTIVE:Thus, it is imperative to identify, mitigate, and manage psychosocial risk factors effectively to foster a conducive academic environment conducive to productivity and achievement. METHODS:This study employs a novel approach, integrating expert opinions and utilizing sine trigonometry Pythagorean fuzzy numbers to ascertain the degrees of importance and rank psychosocial risk factors through the DEMATEL method. This methodology presents a unique contribution to existing literature, offering fresh insights into this critical area of study. RESULTS:Evaluation of 25 factors reveals burnout, job dissatisfaction, precarious working conditions, lack of trust, unfair treatment, job insecurity, and limited developmental opportunities as primary concerns, underscoring the multifaceted nature of these challenges. CONCLUSIONS:In the occupational sphere, active participation from all stakeholders in addressing psychosocial risks is paramount for effective problem resolution. It is incumbent upon parties involved to discharge their duties, foster collaboration, enhance working conditions, ensure equity, and facilitate avenues for professional growth. Each identified risk factor addressed and preempted translates into a tangible reduction in workplace accidents and occupational ailments, underscoring the tangible benefits of proactive risk management.
Information received and usefulness of the sources of information to cancer patients at an oncology hospital in Turkey
(2024) İnce, Büşra; Atak Çakır, Pınar; Eti, Serkan; Mutluay, Fatma
Aim: Cancer treatment typically involves a combination of approaches like surgery, chemotherapy, and radiation therapy. Offering accurate and valuable information about cancer plays a crucial role in helping patients prepare for their treatment and improves their adherence to it. To assess the information received by cancer patients, the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life (QL) Group has developed the EORTC INFO module. The objective of this study is to examine the reliability and validity of the Turkish version of the EORTC QLQ-INFO25 system. Specifically, it aims to evaluate how patients perceive the benefits of the information they receive and the duration for which the information remains useful to them. Material and Methods: We administered the Turkish versions of three questionnaires to 197 patients at various stages of their illness: the EORTC QLQINFO25, the EORTC Quality of Life Questionnaire -Core 30 (QLQ-C30), and the EORTC Cancer In -Patient Satisfaction with Care Questionnaire (IN-PATSAT32). These stages included chemotherapy, radiotherapy, and surgery. To ensure the questionnaire's reliability and validity, we utilized Cronbach's alpha, inter -scale correlation, and factor analysis. Results: The validity analysis revealed that the scale had a sufficient level of explained variance, with 66.68% accounted for by the factor analysis findings. Furthermore, the reliability analysis indicated a high level of reliability for the entire questionnaire, with a Cronbach's alpha coefficient of 0.92. The selected questions from the EORTC IN-PATSAT32 and their correlation with the 4 identified areas and 2 items of the EORTC QLQ-INFO25 demonstrated strong convergent validity. On the other hand, there was a low correlation between the EORTC-QLQ-C30 questionnaire and the different areas of the EORTC QLQINFO25 questionnaire, suggesting that these two questionnaires measured distinct concepts. Discussion: The study found that the Turkish version of the EORTC QLQ-INFO25 scale is a valid and reliable instrument for assessing the knowledge level of cancer patients. These findings suggest that the scale can be effectively utilized within the Turkish society to evaluate the information and understanding of cancer patients.
Preliminary study: The test technique for the evaluation on spatial navigation in the absence of visual data in healthy individuals
(Tehran University of Medical Sciences, 2024) Yılmaz, Oğuz; Kurtuluş, Ceren; Ersin, Kerem; Gündoğdu, Oğulcan; Eti, Serkan; Şerbetçioğlu, Mustafa Bülent
Background and Aim: Path integration refers to the capability of utilizing self-motion information produced by one’s own bodily movements to accurately determine and maintain one’s position in space. Typically, path integration mechanisms come into play when visual information is limited or absent. The objective of this study was to develop a path integration test that relies solely on self-motion cues derived from body movements, without the involvement of visual cues. Methods: The study involved 157 volunteers (86 females and 71 males) aged between 18 and 70 years. Participants were asked to walk on a coordinated ground with their closed eyes and follow the six different commands. They were, after that, requested to return their initial position. Movement time was manually measured by the stopwatch. The distance between the original reference point and estimated starting point was recorded. Results: The second command that showed the lowest standard deviation out of the six commands given to the participants was observed as the more reliable test among the other commands (47.51±33.75). In addition, the completion time of the second command increased with increasing age (p[removed]
Prioritizing the indicators of energy performance management: a novel fuzzy decision-making approach for G7 service industries
(IOP Publishing Ltd, 2024) Yüksel, Serhat; Eti, Serkan; Dinçer, Hasan; Gökalp, Yaşar; Yavuz, Duygu; Mikhaylov, Alexey; Pinter, Gabor
Ensuring energy performance management is important in many ways, such improvement of energy efficiency and decrease of energy costs are reduced. There are various indicators of the effectiveness of energy performance management of buildings. Due to this situation, businesses need to make the necessary improvements for the development of these factors. Nonetheless, these actions cause an increase in the costs of the companies. Hence, among these actions, the more important ones need to be identified. Owing to this issue, businesses can use their limited budgets for more priority indicators. The purpose of this study is to evaluate the main indicators of energy performance management systems. In this way, a new model is proposed to make a priority analysis for the hospitals. Firstly, five indicators of energy performance management systems are selected by considering ISO 50006 standards. Furthermore, these indicators are weighted by using Spherical fuzzy CRITIC. Secondly, G7 countries are examined with fuzzy RATGOS technique. Identification of the most significant indicators of the energy performance systems is an important novelty of this study. The most significant methodological novelty of this study is proposing a new technique to the literature named RATGOS. It is understood that energy efficiency is the most crucial indicator of energy performance management. Furthermore, it is also identified that France is the most successful G7 economy with respect to the energy performance management. Japan and United States have also high performance in this respect. It is recommended that necessary actions should be taken to increase energy efficiency. By conducting an energy audit, energy consumption data is analyzed so that energy losses and inefficiencies can be detected. This assessment provides opportunities for energy efficiency and helps identify improvement strategies.

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