Osmaniye Korkut Ata University Academic Repository
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Investigation of the effect of ascorbic acid and sorbic acid addition on the shelf life of avocado puree
No full textBu çalışmada, avokado pürelerine askorbik asit (200 ppm) ve sorbik asit (300ppm) ilavesinin, 30 günlük depolama süresi boyunca pürelerin raf ömrüne etkisi incelenmiştir. Avokado pürelerine ilave edilen katkı maddelerinin, avokado pürelerinin pH, kül miktarı, L*, a* ve b* değerleri üzerindeki etkisi önemli bulunmuştur. Öte yandan, katkı maddelerinin yağ, nem, toplam fenol bileşikleri ve antioksidan aktivite değerleri üzerindeki etkisinin önemsiz olduğu tespit edilmiştir. Katkı maddesi ilave edilen avokado püre örneklerine kıyasla, en düşük pH kontrol örneğinde belirlenmiştir. En yüksek L*, a* ve b* değerleri askorbik asit ve sorbik asit ilave edilen örneklerde belirlenmiş, ancak en düşük değer de kontrol örneğinde tespit edilmiştir. Depolama süresinin püre örneklerinin yağ, nem, pH, kül, toplam fenol bileşikleri, antioksidan aktivite, L*, a* ve b* değerleri üzerindeki etkisi önemli bulunmuştur. Depolama süresi boyunca nem miktarı azalmış iken, pH değeri yükselmiştir. Avaokado püresinin maya ve küf sayısı ve toplam mezofil aerobik bakteri sayısı üzerinde katkı maddesi ve depolama süresinin etkisi önemli bulunmuştur. En yüksek maya ve küf sayısı kontrol ve askorbik asit içeren püre örneklerinde belirlenmiş iken, sorbik asit ilave edilen püre örneğinde maya ve küf tespit edilememiştir. Toplam mezofil bakteri sayısı bakımından en yüksek değerler kontrol ve askorbik asit ilave edilen örnekte belirlenmiş iken, en düşük değer sorbik asit ilave edilen avokado püre örneğinde bulunmuştur. Depolama süresi arttıkça maya ve küf ve toplam aerob mezofil bakteri sayısı artış göstermiştir.In this study, the effect of the addition of ascorbic acid (200 ppm) and sorbic acid (300 ppm) to avocado purees on the shelf life of the purees during a 30-day storage period was investigated. The effects of the additives on the pH, ash content, L*, a* and b* values of avocado purees were found to be significant. On the other hand, the effect of additives on fat, moisture, total phenol compounds and antioxidant activity values were found to be insignificant. The lowest pH was determined in the control sample compared to the additive added avocado puree samples. The highest L*, a* and b* values were determined in ascorbic acid and sorbic acid added samples, but the lowest value was determined in the control sample. The effect of storage time on fat, moisture, pH, ash, total phenol compounds, antioxidant activity, L*, a* and b* values of purees samples was found to be significant. While the moisture content decreased during the storage period, the pH value increased. The effect of additive and storage time on yeast and mould counts and total mesophyll aerobic bacteria counts were found to be significant. The highest yeast and mould counts were determined in the control and ascorbic acid containing puree samples, while no yeast and mould were detected in the sorbic acid added puree sample. In terms of total mesophyll bacteria count, the highest values were determined in the control and ascorbic acid added sample, while the lowest value was found in the sorbic acid added avocado puree sample. Yeast and mould and total aerobic mesophilic bacteria counts increased as the storage time increased
Cognitive Patterns in Learner Texts: Exploring Semantic and Semiotic Dimensions Through Topic Modeling
No full textTraditional SLA research often contrasts learner writing with native-speaker norms, perpetuating linguistic inequality and negatively affecting learners’ self-perception and engagement. This chapter examines learner essays without such norms, valuing linguistic diversity and cognitive perspectives. Scrutinizing ICLE corpus, computational topic modeling with BERTopic, and semantic network analysis identified prominent topics across various linguistic backgrounds. The most prevalent topic centered on higher education, particularly the theoretical and practical aspects of university degrees. Key terms like “theoretical,” “degree,” “university,” “practical,” and “real world” formed interconnected semantic networks, reflecting learners’ conceptualizations of academic education. Cross-linguistic examination revealed that conceptual frames such as the University-Society and the Theory-Practice relation were prominent across different first-language groups. Findings highlight the interplay of topic, culture, and instructional practices, advocating a more inclusive approach in SLA research. © 2025 by IGI Global Scientific Publishing
Analysis of copd disease stages using clinical and demographic data
No full textBu çalışma, Kronik Obstrüktif Akciğer Hastalığının (KOAH) evrelerini klinik ve demografik verilerle analiz ederek, makine öğrenimi yöntemleriyle tahmin etmeyi amaçlamaktadır. Hastalığın ilerleyişinin yalnızca solunum sistemiyle sınırlı kalmayıp, sistemik faktörler (örneğin kardiyovasküler parametreler, metabolik göstergeler ve çevresel maruziyetler) ile de ilişkili olduğunu ortaya koymak üzere, Barcelona'daki bir hasta kohortundan elde edilen 230 bireye ait veri seti kullanılmıştır. Veri seti, yaş, cinsiyet, vücut kitle indeksi(VKİ), sigara kullanımı, solunum hızı, oksijen satürasyonu, FEV1/FVC oranı, kan basıncı, kalp hızı, balgam, depresyon ve mesleki maruziyet gibi değişkenleri içermektedir. Analizde, KOAH evreleri (GOLD 1-4) ikili sınıflandırma gruplarına ayrılmış ve çeşitli makine öğrenimi algoritmaları (Karar Ağacı, Rastgele Orman, K-En Yakın Komşu, Gradient Boosting, Yapay Sinir Ağları) test edilmiştir. En yüksek performans, GOLD 2-3 evre geçişinde K-En Yakın Komşu (KNN) algoritması ile elde edilmiş olup, AUC değeri %94,9'a ulaşmıştır. Diğer geçişlerde (GOLD 1-2 ve 3-4) performans düşüşü gözlemlenmiş, bu da hastalığın erken ve ileri evrelerindeki heterojeniteyi yansıtmaktadır. SHAP (SHapley Additive exPlanations) analizi, solunum hızı, kan basıncı, balgam ve VKİ gibi parametrelerin evre tahmininde kritik rol oynadığını; FEV1 gibi geleneksel göstergelerin ise daha az belirleyici olduğunu ortaya koymuştur. Bulgular, KOAH'ın bireyselleştirilmiş yönetimini vurgulamakta; erken müdahale için sistemik parametrelerin izlenmesini ve kişiye özgü tedavi stratejilerini önermektedir. Bu yaklaşım, hastalığın tanı ve prognozunda makine öğreniminin potansiyelini artırmakta, klinik uygulamalara katkı sağlamaktadır.This study aims to predict the stages of Chronic Obstructive Pulmonary Disease (COPD) using machine learning methods, highlighting that disease progression is associated not only with the respiratory system but also with systemic factors such as cardiovascular parameters, metabolic indicators, and environmental exposures. The analysis utilized a dataset of 230 patients from a Barcelona cohort, sourced from the "COPD Analysis" collection on Kaggle, encompassing variables like age, gender, body mass index (BMI), smoking history, respiratory rate, oxygen saturation, FEV1/FVC ratio, blood pressure, heart rate, sputum, depression, and occupational exposures. The COPD stages (GOLD 1-4) were divided into binary classification groups, and various machine learning algorithms (Decision Tree, Random Forest, K-Nearest Neighbor, Gradient Boosting, Artificial Neural Networks) were tested. The highest classification performance was achieved with the K-Nearest Neighbor (KNN) algorithm for the GOLD 2-3 stage transition, yielding an AUC value of 94.9%. Performance declined in other transitions (GOLD 1-2 and 3-4), reflecting the heterogeneity in early and advanced stages. SHAP (SHapley Additive exPlanations) analysis revealed that parameters such as respiratory rate, blood pressure, sputum, and BMI play critical roles in stage prediction, while traditional metrics like FEV1 were less determinant. The findings underscore the need for individualized COPD management, advocating for the monitoring of systemic parameters and tailored treatment strategies for early intervention. This approach enhances the potential of machine learning in COPD diagnosis and prognosis, contributing to clinical practice
Comparative effects of the probiotic bacteria and carob powder on the quality properties of peanut butter
No full textThe present study examined the effect of carob powder and probiotic culture addition on the quality characteristics of peanut butter during a three-month storage period. Carob powder enhanced the growth of Lacticaseibacillus rhamnosus in MRS broth. It also demonstrated technofunctional properties such as oil retention capacity (2.48 g/g), water retention capacity (2.42 g/g), emulsion activity (47.67%), and emulsification index (45.35%). Furthermore, the addition of carob powder to peanut butter promoted a prebiotic effect on the growth of probiotic culture and reduced oil loss in the peanut butter samples. Overall, the effect of storage on the quality properties of peanut butter was negligible (p>0.05), whereas the impact of probiotic culture on carob powder was significant (p<0.05). Probiotic viability in peanut butter without carob powder and with carob powder ranged from 5.95 to 6.45 log CFU/g and from 6.15 to 6.82 log CFU/g, respectively. Specifically, oil loss in probiotic peanut butter with carob powder was lower compared to other peanut butter samples, owing to the oil retention capacity of carob powder. Additionally, all peanut butter samples maintained desirable sensory quality properties throughout storage
Application of machine learning algorithms in predicting deformation energy and loads acting on the rolls in hot rolling processes
No full textIn the profile rolling process, the trial and error approach is still widely applied, which makes design and optimisation efforts time-consuming. This study aims to predict essential process outputs such as forming energy, turning moment, and radial force by using machine learning techniques, based on the dimensions of the workpiece and the pass. Random Forest, XGBoost, Polynomial, and k Nearest Neighbors regression models were trained and validated using ten-fold cross-validation, along with parameter tuning. Model performance was evaluated using the coefficient of determination, mean absolute error, and root mean square error. The XGBoost algorithm provided the highest accuracy with R squared values of 0.939 for turning moment, 0.966 for radial force, and 0.915 for deformation energy. These findings show that machine learning methods can accurately predict process outputs, leading to improved process design, reduced energy consumption and cost, and enhanced product quality. Dans le proc & eacute;d & eacute; de laminage de profil & eacute;s, la m & eacute;thode des approximations successives est encore largement utilis & eacute;e. R & eacute;aliser physiquement de nombreux essais, sans parler des simulations par & eacute;l & eacute;ments finis, prend beaucoup de temps. Par cons & eacute;quent, on consid & egrave;re que la pr & eacute;diction de certains r & eacute;sultats du proc & eacute;d & eacute; de laminage & agrave; l'aide de m & eacute;thodes d'apprentissage automatique peut fournir des avantages significatifs dans la conception et l'optimisation. Dans cette & eacute;tude, on a mod & eacute;lis & eacute; la variation de l'& eacute;nergie de formation utilis & eacute;e lors du laminage grossier, du moment de rotation et des forces radiales agissant sur les cylindres en fonction des dimensions de la pi & egrave;ce entrant dans la passe, ainsi que de la largeur et de la hauteur de la passe, en utilisant des m & eacute;thodes d'apprentissage automatique. L'& eacute;tude a utilis & eacute; des m & eacute;thodes de r & eacute;gression de for & ecirc;t al & eacute;atoire, d'amplification de gradient extr & ecirc;me (XGBoost), polynomiale et des plus proches voisins k (k-NN). Les mod & egrave;les propos & eacute;s ont subi une formation et des essais de validation crois & eacute;e 10 fois et l'on a r & eacute;alis & eacute; des optimisations de param & egrave;tres pour am & eacute;liorer leurs performances. On a & eacute;valu & eacute; les performances des mod & egrave;les construits en utilisant les mesures de coefficient de d & eacute;termination (R2), d'erreur moyenne absolue et d'erreur moyenne quadratique. On a constat & eacute; que le R2 des pr & eacute;dictions obtenues avec l'algorithme XGBoost & eacute;tait de 0.939 pour le moment de rotation, de 0.966 pour la force radiale et de 0.915 pour l'& eacute;nergie de d & eacute;formation, ce qui indique des performances r & eacute;ussies. Les mod & egrave;les propos & eacute;s fournissent des pr & eacute;dictions pr & eacute;cises qui peuvent contribuer significativement & agrave; l'optimisation des param & egrave;tres du proc & eacute;d & eacute;. En identifiant les dimensions de passe optimales pour minimiser l'& eacute;nergie de d & eacute;formation, on peut obtenir une efficacit & eacute; & eacute;nerg & eacute;tique importante, des co & ucirc;ts op & eacute;rationnels r & eacute;duits et une am & eacute;lioration de la qualit & eacute; du produit
An examination of perceived stress situations in sports high schools students
Get PDFBu çalışma lise düzeyindeki öğrencilerin algılanan stres düzeylerini çeşitli demografik değişkenlerle incelemek amacıyla tasarlanmıştır. Çalışmaya Osmaniye Samet Aybaba Spor Lisesi'nde 2024–2025 eğitim-öğretim yılında öğrenim gören 300 öğrenci gönüllü olarak katılmıştır. Örneklem grubunun yeterliliğini belirlemek amacıyla G-power analizi yapılmış ve yeterli sayıda olduğu tespit edilmiştir. Veriler Eskin, Harlak, Demirkıran ve Dereboy (2013) tarafından Türkçe'ye uyarlanan ''Algılanan Stres Ölçeği'' ve araştırmacı tarafından hazırlanan "Kişisel Bilgi Formu" kullanılarak yüz yüze toplanmıştır. Elde edilen veriler SPSS 26.0 paket programı kullanılarak analiz edilmiştir ve normal dağılım göstermediğinden parametrik olmayan testler tercih edilmiştir. Araştırma bulgularına göre cinsiyet değişkeni, spor dalı, spor başarısı ve gelir düzeyi açısından stres düzeylerinde anlamlılık tespit edilmiştir (p<0,05). Ayrıca stres puanları alt boyutları arasındaki ilişki anlamlı bulunmuştur (p<0,05). Bu sonuçlar, spor lisesi öğrencilerinde stresin çok boyutlu bir yapıya sahip olduğunu göstermektedir. Elde edilen bulgulara göre öğrencilerin stres düzeylerini düşürmeye, psikolojik sağlamlıklarını güçlendirmeye ve öğrenme ortamını geliştirmeye odaklanan, seminer temelli eğitim programlarının uygulamaya konulması önerilmektedir. Bu programlar aracılığıyla, yalnızca öğrencilerin değil, aynı zamanda aile üyelerinin de bilinçlendirilmesi hedeflenmelidir. Ayrıca, öğrencilerin iyi oluş hallerini desteklemek amacıyla, boş zaman etkinlikleri ve benzeri eğlenceli faaliyetlere teşvik edici öneriler olarak sunulabilir.This study was designed to investigate the perceived stress levels of high school students with various demographic variables. 300 students studying at Osmaniye Samet Aybaba Sports High School during the 2024–2025 academic year voluntarily participated in the study. A G-power analysis was conducted to determine the adequacy of the sample group, and it was found to be sufficient. Data were collected face-to-face using the "Perceived Stress Scale," which was adapted into Turkish by Eskin, Harlak, Demirkıran, and Dereboy (2013), and the "Personal Information Form" prepared by the researcher. The collected data were analyzed using the SPSS 26.0 statistical package program, and non-parametric tests were preferred since the data did not show a normal distribution. According to the research findings, a significant difference in stress levels was found across the variables of gender, sports branch, sporting success, and income level (p<0.05). Furthermore, the relationship between the sub-dimensions of the stress scores was found to be significant (p<0.05). These results indicate that stress has a multidimensional structure in sports high school students. Based on the findings, it is recommended to implement seminar-based training programs focused on reducing students' stress levels, strengthening their psychological resilience, and improving the learning environment. Through these programs, the aim should be to raise awareness not only among students but also among their family members. Additionally, suggestions encouraging leisure activities and similar enjoyable activities can be offered to support the students' well-being
Performance assessments of cascade refrigeration system with expander boosted subcooling
No full textThis study involves the application of an expander-boosted subcooling refrigeration system to improve the performance of the cascade refrigeration cycles. While previous research has focused on the role of internal heat exchangers, economizers, and ejectors, this work delves deeper into the potential of subcooling to significantly boost system efficiency. In recent years, mechanical subcooling has gained attention as a key strategy in the refrigeration and air conditioning sectors. The study proposes three system configurations: a booster in both the high-and low-temperature stages (2SB), a booster in the high-temperature stage only (HSB), and a booster in the low-temperature stage only (LSB).Performance comparisons were made between R290/R170, R717/R170, and R161/R41 refrigerant pairs, targeting both low-and ultra-low-temperature refrigeration applications. Optimum intermediate and dimensionless temperature values were identified for each refrigerant pair across varying evaporator conditions. Detailed analyses revealed that natural R290/R170 and R161/R41 offers superior COP at evaporator temperatures below-35 degrees C, while the performance gains were significant across all temperatures. Among the configurations, 2SB outperformed the others, with performance enhancement rates increasing as evaporator temperatures decreased. Among the refrigerant pairs analyzed in this study, R161/ R41, R161/R170, and R290/R170 have demonstrated the highest performance for low-temperature and ultra-low-temperature cooling applications, respectively. The study demonstrated performance improvements of up to 20 % at low evaporator temperatures, underscoring the potential of this approach to revolutionize refrigeration efficiency
The impact of consumer perception towards smart retail technology on perceived shopping value attitude and usage intention
No full textGünümüzde sürekli değişen ve gelişen teknolojiyle birlikte ortaya çıkan akıllı perakende teknolojileri perakende sektöründe hizmet sunumunu ve değer yaratımını hızla dönüştürmeye devam etmektedir. Endüstri Devrimi 4.0'ın sonuçlarından birisi olarak ortaya çıkan akıllı perakende teknolojileri, fiziksel ve dijital özellikler arasındaki entegrasyonu derinleştirerek fiziksel mağazalarda olağanüstü alışveriş deneyimleri sunabilmektedir. Bu doğrultuda müşterilerine üstün ve kişiselleştirilmiş perakende hizmetleri sunarak rekabet avantajı kazanmak isteyen perakendeciler fiziksel perakende mağazalarını birer akıllı perakende mağazasına dönüştürmektedir. Akıllı perakende teknolojileri, akıllı aynalar, akıllı giyinme odaları, self-check-out kioskları (self-servis ödeme kioskları), akıllı fiyat etiketleri, akıllı raflar, akıllı alışveriş arabaları, insansız mağazalar gibi diğer birçok teknolojiyi veya temas noktalarını içermektedir. Fiziksel perakende mağazalarında akıllı perakende teknolojilerinin kullanımının hızla yaygınlaşması ve bu teknolojilerin perakendecilere ve müşterilere sunduğu faydalar göz önüne alındığında, bu teknolojilere yönelik tüketici davranışlarının anlaşılmasının kritik öneme sahip olduğu düşünülmektedir. Bu bağlamda çalışmanın birinci amacı, tüketicilerin akıllı perakende teknolojisi özelliklerine yönelik algılarının, akıllı perakende teknolojisine yönelik algıladıkları faydacı, hedonik ve sosyal alışveriş değerine; algılanan faydacı, hedonik ve sosyal alışveriş değerinin tutuma; tutumunda akıllı perakende teknolojisini kullanma niyetine etkilerinin incelenmesidir. Çalışmanın ikinci amacı tüketicilerin sahip oldukları teknolojik yenilikçiliğin, akıllı perakende teknolojisine yönelik algıladıkları faydacı, hedonik ve sosyal değer ile tutum ve tutum ile akıllı perakende teknolojisini kullanma niyetleri arasındaki ilişkiler üzerindeki düzenleyici etkilerinin tespit edilmesidir. Bu amaç kapsamında İstanbul'da ikamet eden 18 yaş ve üzerindeki bir yaşta bulunan ve alışverişlerinde akıllı perakende teknolojisini kullanma bilgisine veya potansiyeline sahip olan toplam 405 katılımcıdan yüz yüze anket yoluyla veri toplanmıştır. Çalışmada verilerin analizini gerçekleştirmek için; keşfedici ve doğrulayıcı faktör analizi, aracı (mediate) ve koşullu süreç analizleri ile yapısal eşitlik modeli analizi tanımlayıcı istatistiki testlerle birlikte uygulanmıştır. Yapısal eşitlik modeli analizi sonucunda, algılanan yenilik, algılanan avantaj ve algılanan zorluğun, algılanan faydacı, hedonik ve sosyal değer üzerinde istatistiksel olarak anlamlı etkilere sahip olduğu tespit edilmiştir. Bununla birlikte analiz sonucunda algılanan güvenin hedonik ve sosyal değer üzerinde istatistiksel olarak anlamlı bir etkiye sahip olduğu fakat faydacı değer üzerinde istatistiksel olarak anlamlı bir etkiye sahip olmadığı tespit edilmiştir. Analiz sonucunda algılanan kontrol, uyumluluk, risk ve gizlilik endişeleri değişkenlerinin algılanan faydacı, hedonik ve sosyal değer üzerinde anlamlı bir etkisinin olmadığı tespit edilmiştir. Bununla birlikte algılanan faydacı, hedonik ve sosyal değer değişkenlerinin tutum; tutumun da kullanma niyeti üzerinde istatistiksel olarak anlamlı etkilere sahip olduğu tespit edilmiştir. Aracılık analizleri, algılanan yenilik, avantaj, uyumluluk, kontrol ve zorluk gibi değişkenlerin; algılanan faydacı, hedonik ve sosyal değer aracılığıyla akıllı perakende teknolojilerine yönelik tutumu anlamlı biçimde etkilediğini ortaya koymuştur. Ayrıca, algılanan güven, risk ve gizlilik endişelerinin hiçbir değer boyutu üzerinden tutumu anlamlı şekilde etkilemediği, dolayısıyla dolaylı etkilerin istatistiksel olarak anlamlı olmadığı belirlenmiştir. Bununla birlikte, algılanan faydacı, hedonik ve sosyal değerlerin tutum aracılığıyla kullanım niyeti üzerinde anlamlı dolaylı etkiler oluşturduğu görülmüştür. Elde edilen bulgular, değer temelli bir yapı içerisinde tutumun, kullanım niyeti üzerindeki belirleyici rolünü ve algılanan faydacı, hedonik ve sosyal değerin bu süreci nasıl şekillendirdiğini göstermektedir. Koşullu süreç analizi sonuçları genel olarak değerlendirildiğinde, teknolojik yenilikçilik değişkeni, algılanan faydacı, hedonik ve sosyal değerlerin tutum ve kullanma niyeti üzerindeki etkilerinde anlamlı bir düzenleyici rol oynamaktadır. Özellikle teknolojik yenilikçiliğin orta ve yüksek düzeylerinde, algılanan faydacı, hedonik ve sosyal değerin tutum ve niyet üzerindeki etkileri güçlenmiş; bu bulgular, modelde anlamlı bir koşullu dolaylı etki (moderated mediation) yapısının varlığını ortaya koymuştur.Today, smart retail technologies that have emerged with the ever-changing and evolving technology continue to rapidly transform service delivery and value creation in the retail sector. Smart retail technologies, which emerged as one of the results of Industrial Revolution 4.0, can offer extraordinary shopping experiences in physical stores by deepening the integration between physical and digital features. In this context, retailers who want to gain a competitive advantage by offering superior and personalized retail services to their customers are transforming their physical retail stores into smart retail stores. Smart retail technologies include many other technologies or touchpoints such as smart mirrors, smart dressing rooms, self-checkout kiosks (self-service payment kiosks), smart price tags, smart shelves, smart shopping carts, unmanned stores, etc. Given the rapid adoption of these technologies in physical retail settings and the benefits they offer to both retailers and consumers, understanding consumer behavior toward smart retail technologies is of critical importance. In this context, the first aim of the study is to examine how consumers' perceptions of the characteristics of smart retail technologies affect their perceived utilitarian, hedonic, and social shopping value; how these perceived values influence attitudes; and how attitudes in turn affect the intention to use smart retail technologies. The second aim is to determine the moderating role of consumers' technological innovativeness in the relationships between perceived utilitarian, hedonic, and social value and attitude, as well as between attitude and behavioral intention. For this purpose, data was collected through a face-to-face survey from a total of 405 participants who are 18 years of age or older and reside in Istanbul and have the knowledge or potential to use smart retail technology in their shopping. The data were analyzed using exploratory and confirmatory factor analyses, mediation and conditional process analyses, and structural equation modeling, along with descriptive statistical tests. As a result of the structural equation modeling analysis, it was found that perceived novelty, perceived advantage, and perceived complexity have statistically significant effects on perceived utilitarian, hedonic, and social value. Additionally, the analysis revealed that perceived trust has a statistically significant effect on hedonic and social value, but not on utilitarian value. The results also indicated that perceived control, compatibility, risk, and privacy concerns do not have significant effects on perceived utilitarian, hedonic, or social value. However, perceived utilitarian, hedonic, and social value were found to have statistically significant effects on attitude, and attitude was found to have a statistically significant effect on the intention to use. Mediation analyses showed that perceived innovation, advantage, compatibility, control, and ease of use significantly affect attitude through perceived values. However, perceived trust, risk, and privacy concerns did not significantly influence attitude through any value dimension, indicating the absence of statistically significant indirect effects. Nevertheless, perceived utilitarian, hedonic, and social values were found to have significant indirect effects on behavioral intention through attitude. The findings demonstrate the determining role of attitude on usage intention within a value-based structure and how perceived utilitarian; hedonic and social value shape this process. The conditional process analysis further revealed that technological innovativeness plays a significant moderating role in the effects of perceived utilitarian, hedonic, and social value on attitude and behavioral intention. Particularly at moderate and high levels of technological innovativeness, the effects of perceived values on both attitude and intention were amplified, indicating the presence of a significant moderated mediation structure in the model
Experimental and numerical examination of RT35 HC thermal energy storage performance with honeycomb fins of different cell sizes
No full textConsidering the lack of sustainability of organic fossil fuels, which serve as the fundamental energy source for people, it is imperative to increase the usage of renewable air conditioning applications. The experimental configuration used in this work was specifically engineered to replicate the consistent temperature of the wall present behind solar panels. Several studies in the literature have documented that the efficiency of energy generation from solar panels diminishes as they increase in temperature. Thus, this work aimed to examine the thermal energy storage characteristics of RT35 HC at a constant wall temperature in trials conducted both with and without fins. Furthermore, to facilitate the comparison of the acquired experimental data, the rectangular enclosure of the experimental setup was scaled in a one-to-one ratio and simulated in three dimensions using the COMSOL Multiphysics software. This paper will establish the experimental parameters and thermo-physical characteristics of RT35 HC for the developed model, and thereafter conduct a numerical analysis. The use of a 3.2 mm honeycomb fin increased the melting area from 2233.11 mm2 to 2706.5 mm2. The utilization of the 3.2 honeycomb fin resulted in a 21.2 % enhancement in both melting and thermal energy storage (TES). The COMSOL Multiphysics 3D simulation of the testing apparatus performed effectively, yielding a regression value of 0.9810 for the phase change area and energy storage.OKUBAP [OKBAP-2022-PT2-010]The authors would like to acknowledge OKUBAP for the financial support of this study (project no: OKUEBAP-2022-PT2-010)
Optimization of drilling parameters for glass fiber-reinforced nanocomposite materials using Taguchi-based CRITIC-VIKOR method
No full textIn this study, custom-fabricated multiwalled carbon nanotube (MWCNT)-reinforced and unreinforced glass fiber-reinforced polymer (GFRP) composites were used. These composites were manufactured via the vacuum-assisted resin transfer molding technique to ensure high-quality, consistent material properties. The study investigates the effects of MWCNT reinforcement ratios, cutting speeds, and feed rates on the drilling performance of GFRP composites. Key processing indicators such as surface roughness (SR), delamination, and thrust force were evaluated. A full factorial design comprising 27 experimental runs was employed. Variance analysis (ANOVA) and the Taguchi method were used for single-response optimization, revealing that the MWCNT reinforcement ratio had the greatest effect on delamination, while feed rate predominantly influenced thrust force. Cutting speed and feed rate were both found to significantly affect SR. For multiobjective optimization, the Criteria Importance Through Intercriteria Correlation-based weighting method was integrated with the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approach. The optimal parameters identified through this methodology were further refined using Taguchi signal-to-noise ratio analysis. According to the VIKOR analysis, feed rate emerged as the most influential factor, with a contribution ratio of 28.48%. The optimal drilling parameters correspond to Experiment No. 10, which involved a 0.5% MWCNT reinforcement ratio, a cutting speed of 25 m/min and a feed rate of 0.10 mm/rev (A2B1C1). Under these conditions, the delamination factor (D-0) was 1.234, thrust force (F) was 82.03 N, and SR (Ra) was 1.575 mu m. This integrated methodology provides a robust framework for optimizing drilling parameters in nanocomposite materials