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Investigation of Effective Factors on Thermal Efficiency of Steam Boiler Used in Power Plants
No full text2nd International Conference on Engineering and Science to Achieve the Sustainable Development Goals, ICASDG 2023 -- 9 July 2023 through 10 July 2023 -- Hybrid, Tabriz -- 197984Boiler is a pressure vessel that provides a heat transfer surface (generally a set of tubes) between the combustion products and the water. A boiler is usually integrated into a system with many components. It used to produce steam. The generation part of a steam system uses a boiler to add energy to a feedwater supply to generate steam. The energy is released from the combustion of fossil fuels or from process waste heat The purpose of this study is to examine and evaluate the positive effects of using cast iron and stainless steel in steam boilers, specifically with regard to improving the boilers' thermal and structural performance, mechanical qualities, and durability. Numerical analysis, 3D mathematical modeling, and simulation were crucial to the success of the investigation. The study found that the maximum Von Mises stress recorded for the cast iron was 2.0499 MPa, and the maximum Von Mises stress of the stainless steel was 2.0406 MPa, both based on simulations and numerical results produced via the ANSYS software package. Cast iron had a maximum elastic strain of 0.0328. In contrast, stainless steel's maximum elastic strain was only 0.0140. Cast iron experienced maximum overall deformations of 82.86 mm. As a point of contrast, the maximum overall deformations of the stainless steel were just 36.66 mm. Stainless steel's mechanical qualities surpass those of cast iron. Stainless steel's superior corrosion resistance, durability, and mechanical performance meant it was the material of choice for the steam boiler. The Von Mises stress, elastic strain, and total deformations were all reduced by 4.53%, 57.32%, and 55.71%, respectively, when stainless steel was used in place of cast iron in the second case study scenario. © 2024 American Institute of Physics Inc.. All rights reserved
A numerical assessment of the efficiency of partial saturation as a countermeasure against lique faction-induced uplift of tunnels
No full textTunnels located in liquefiable soils are prone to flotation following earthquakes. When the shaking-induced pore water pressure buildup continues, saturated soil surrounding the tunnels liquefies, flotation occurs and the soil loses its shear resistance against the uplift force from the buoyancy of the tunnel. Mitigation of liquefaction-induced uplift of tunnels is one of the concerns of geotechnical engineers. This article aims to investigate the efficacy of the available mitigation techniques using a finite element program with an emphasis on the prediction of excess pore water pressures in the surrounding soil and the uplift of the tunnel. In addition to the conventional techniques, a newly developed technique "Partial Saturation" was modeled to examine its effect on the reduction of the tunnel uplift. A parametric study was done to compare the effectiveness of partial saturation with other mitigation techniques. Results showed that the partial saturation technique would effectively dissipate the excess pore water pressure in the soil around the tunnels. It also performs well in the reduction of the uplift of the tunnel. The most appealing advantage of this technique against the other available mitigation techniques is that it can be employed easily without disturbing the soil around the tunnels. A new methodology to numerically simulate the partially saturated sands was described in this paper
Integration of convolutional neural networks and grey wolf optimization for advanced cybersecurity in IoT systems
No full textThe rapid integration and application of the Internet of Things in daily life have significantly improved connectivity and intelligent control to various devices. However, it has exposed such systems to increased susceptibility to cyber challenges, such as infiltration, data sovereignty, and cyberattacks. There is a need for an efficient and secure solution to these apparent security concerns which require complex social structures to adapt to various learning lessons quickly. The purpose of this study is to provide an inventive evolutionary operation to enhance the security of IoT networks and by integrating Convolutional Neural Networks and items of Grey Wolf Optimization algorithms – Standard GWO, Modified GWO and Advanced modified GWO. The GWOs were used to include surveillance accuracy layout, hence boosting detection accuracy. The action Lloyd testing found that smaller OWG intelligence (which achieved initially) unlimited interpretations which increased the percentage and was 97.4 %. This approach was further increased with FGWE, achieving 97.7 percentage, and 97.8 2.02% errors. The performance of both was 98.4 and 97.5 for the two classes, respectively. The current study’s results reveal the effectiveness of computational development to enhancing secure IoT networks and offer a secure prototype for potential study to optimize the security structure. effet for keynote curricular scenarios due to the system cause and trusty security solutions
Beş faktör kişilik modeli ve sürdürülebilir tüketim davranışları arasındaki ilişki ve çevre bilincinin etkisi
Get PDFKüresel sorunlara yönelik farkındalık son zamanlarda oldukça artmış ve insanları
sürdürülebilirlik temelli davranışlara yönlendirmiştir. Dünyada, ortalama sıcaklık giderek
artarken beraberinde iklim krizi, çevre sorunları ve biyoçeşitliliğin azalması gibi
problemlere yol açarak, canlıların yaşamı için tehdit oluşturmaya başlamıştır. Buna çözüm
olarak geliştirilen sürdürülebilir kalkınma anlayışının sağlanabilmesi için tüketicilerin
sürdürülebilirlik temelli davranışlar göstermesi oldukça büyük bir önem arz etmiştir.
Çalışmanın amacı küresel bir soruna çözüm olma niyetindeki tüketicilerin, kişilik
özelliklerine göre sürdürülebilir tüketim davranışlarını incelemek ve çevre bilincinin bu
ilişki üzerindeki etkisini araştırmaktır. Araştırmanın önemi, tüketicilerin kişilik özellikleri
ve çevre bilinci koşuluyla sürdürülebilir tüketim davranışlarını açıklamak ve tüketicilerin,
sürdürülebilir tüketime yönelimini sağlayan faktörlerin incelenmesinde literatüre katkı
sağlamaktır. Bu doğrultuda, alanda gelecek çalışmalara yardımcı bir kaynak olabileceği
planlanmaktadır. Bu araştırma kapsamında veriler kolayda örneklem yöntemi ile çevrim-içi
anket tekniği ile toplanmıştır. 250 katılımcıdan elde edilen verilerin analizi için IBM SPSS
24.0 ve Smart PLS programları kullanılmıştır. Araştırmada kullanılan değişkenlerin birbiri
arasındaki ilişki, Yapısal Eşitlik Modeli (YEM) yöntemi ile test edilmiştir. Elde edilen
bulgulara göre kişilik özellikleri ve çevre bilinci arasında anlamlı bir ilişki bulunmuş olup, sürdürülebilir tüketim davranışlarıyla arasında anlamlı bir ilişki bulgular arasında yer
almamıştır. Çalışma, alanda literatür taraması yapılarak desteklenmiştir.In this study, awareness of global problems has recently increased considerably and has led
people to sustainability-based behaviors. While the average temperature in the world is
gradually increasing, , it has started to pose a threat to the life of living things by causing
problems such as climate crisis, environmental problems and decrease in biodiversity. In
order to ensure the sustainable development approach developed as a solution to this
problem, it has become very important for consumers to show sustainability-based
behaviors. The aim of the study is to examine the sustainable consumption behaviors of
consumers who intend to be a solution to a global problem according to their personality
traits and to investigate the effect of environmental awareness on this relationship. The
importance of the research is to explain the sustainable consumption behaviors of
consumers in terms of personality traits and environmental awareness and to contribute to
the literature in examining the factors that enable consumers' orientation towards
sustainable consumption. In this direction, it is planned to be a helpful source for future
studies in the field. Within the scope of this research, data were collected through online
survey technique with convenience sampling method. IBM SPSS 24.0 and Smart PLS
programs were used to analyze the data obtained from 250 participants. The relationship
between the variables used in the study was tested with the Structural Equation Modeling
(SEM) method. According to the findings, there is a significant relationship between the variables used in the study was tested with the Structural Equation Modeling (SEM)
method. According to the findings, there is a significant relationship between
environmental awareness and personality traits, but there is no significant relationship
between environmental awareness and sustainable consumption behaviors
Improving 5G network security using machine learning with MQTT data analysis
Get PDFWith the rapid proliferation of Internet of Things (IoT) devices and the global shift towards
5G technology, there arises a critical need to address and bolster the security mechanisms of
these systems. This thesis presents a comprehensive study on user security within 5G
networks, specifically focusing on the Message Queuing Telemetry Transport (MQTT)
protocol, a widely adopted lightweight messaging protocol in IoT environments. Utilizing
the MQTT-IoT-IDS2020 dataset, we employed advanced machine learning models to detect
and predict potential intrusions. Our proposed model, based on the Catboost algorithm,
showcases superior performance with an accuracy rate of 99.99%, outpacing previously
established benchmarks. This work not only emphasizes the vulnerabilities present in
modern 5G IoT networks but also demonstrates the efficacy of machine learning as a tool to
counteract these challenges. The results highlight the potential for machine learning
algorithms, when optimized and appropriately applied, to significantly enhance the security
and reliability of 5G-connected IoT devices. Furthermore, the study sets the foundation for
future research endeavors aiming to solidify security in our increasingly connected digital
landscape
A Cyborg's perception of the city
Get PDFWhen the algorithms of reinforcement learning (RL) blend with architecture and urban
design, a ‘cyborg’ construct that entails cybernetic principles of feedback, can be used to
find adaptable and responsive designs that are better suited for users, as user preference, user
habitual behaviours, and social and environmental conditions are continuously changing.
With methodologies motivated by RL algorithms, architects can use them in Unity’s MLAgents toolkit, containing agents that have the capability to learn from their positive and
negative actions in environments, in an alike manner to how human beings would, through
simulation studies that imitate real-world set-ups that may be too intricate to study using
conventional techniques, by examining curiosity-driven behavioural patterns and
preferences in agents to discover design solutions that apply to real-life. Using RL
algorithms in ML-Agents mimics real-world settings where cyborg explorers, agents with a
flâneur attitude on exploration, can use their curiosity about environments to be motivated
in navigating and learning about it, offering architects the opportunity to learn about realworld behavioural patterns through the perceptions of a cyborg explorer. This thesis’
simulation study examines the influence of curiosity as a motivational drive on a cyborg
explorer’s behavioural patterns in one of Istanbul’s urban settings, with a focus on the Sultan
Ahmet Camii neighbourhood.Takviyeli öğrenme (RL) algoritmaları mimari ve kentsel tasarımla harmanlandığında,
sibernetik geri bildirim ilkelerini içeren bir 'cyborg' yapısı, kullanıcı tercihleri, alışkanlık
davranışları, sosyal ve çevresel koşullar sürekli değiştiğinden, kullanıcılar için daha uygun,
uyarlanabilir ve duyarlı tasarımlar bulmak için kullanılabilir. RL algoritmalarıyla motive
edilen metodolojilerle, mimarlar Unity'nin ML-Agents araç setinde, geleneksel tekniklerle
incelenemeyecek kadar karmaşık olabilecek gerçek dünya kurulumlarını taklit eden
simülasyon çalışmaları yapabilirler. Bu çalışmalarla ajanların merak odaklı davranış
kalıplarını ve tercihlerini inceleyerek, insanların yaptığına benzer şekilde ortamlardaki
olumlu ve olumsuz eylemlerden öğrenme yeteneğine sahip ajanlar oluşturabilirler. MLAgents'da RL algoritmalarının kullanılması, keşif konusunda flâneur bir tutuma sahip olan
cyborg kaşiflerin, ortamlar hakkındaki meraklarını gezinme ve öğrenme konusunda motive
olmak için kullanabilecekleri gerçek dünya ortamlarını taklit eder. Bu sayede, mimarlar bir
cyborg kâşifin algıları aracılığıyla gerçek dünyadaki davranış kalıpları hakkında bilgi
edinme fırsatı bulurlar. Bu simülasyon çalışması, Sultan Ahmet Camii mahallesine
odaklanarak, İstanbul'un kentsel ortamlarından birinde bir cyborg kâşifin davranış kalıpları
üzerinde, merakın motivasyon bir dürtü olarak etkisini incelemektedir
Predicting postoperative atrial fibrillation after cardiac surgery using the Naples prognostic score
Get PDFIntroduction The Naples prognostic score (NPS) is a novel indicator of nutritional and inflammatory statuses in cancer patients. Development of atrial fibrillation after cardiac surgery (POAF) is a common complication that increases the incidence of adverse events. Numerous studies have investigated predictors of POAF. Yet, this study is the first to evaluate the prognostic value of NPS in predicting the development of POAF. Materials and methods The population of this retrospective single-center case-control study consisted of all consecutive patients who underwent cardiac surgery between January 2021 and December 2023. The patients included in the study sample were divided into two groups according to whether they had POAF (group POAF) or remained in sinus rhythm (group RSR). Univariate and multivariate analyses were conducted to identify the variables that significantly predicted the development of POAF. Results This study consisted of 860 patients with a mean age of 61.77 ± 9.13 years and 77.5% (n = 667) were male. The incidence of POAF in the sample was 24.8% (n = 214). NPS was significantly higher in group POAF than in group RSR (2.18 ± 0.99 vs. 1.96 ± 1.02, P = 0.008). Multivariate analysis revealed age [odds ratio (OR): 1.242, 95% confidence interval (CI): 1.020-1.304, P < 0.001] and high NPS (OR: 1.698, 95% CI: 1.121-1.930, P < 0.010) as independent predictors of POAF. Conclusion High NPS values, along with advanced age, were found to be strongly associated with an increased risk of developing POAF. Therefore, it is concluded that NPS is a significant and independent predictor of POAF in patients undergoing cardiac surgery
Exploring free amino acid profiles in CCHF patients: Implications for disease progression
No full textThis study investigated the intricate interplay between Crimean-Congo hemorrhagic fever virus (CCHFV) infection and alterations in amino acid metabolism. Our primary aim is to elucidate the impact of Crimean-Congo hemorrhagic fever (CCHF) on specific amino acid concentrations and identify potential metabolic markers associated with viral infection. One hundred ninety individuals participated in this study, comprising 115 CCHF patients, 30 CCHF negative patients, and 45 healthy controls. Liquid chromatography-tandem mass spectrometry techniques were employed to quantify amino acid concentrations. The amino acid metabolic profiles in CCHF patients exhibit substantial distinctions from those in the control group. Patients highlight distinct metabolic reprogramming, notably characterized by arginine, histidine, taurine, glutamic acid, and glutamine metabolism shifts. These changes have been associated with the underlying molecular mechanisms of the disease. Exploring novel therapeutic and diagnostic strategies addressing specific amino acids may offer potential means to mitigate the severity of the disease
The impact of a-tomatine on shear bonding strength in different dentin types and on cariogenic microorganisms: an in vitro and in silico study
Get PDFIntroduction: The objective of this study is to investigate the shear bonding strength of a glycoalkaloid, also a novel matrix metalloproteinase enzyme known as α-tomatine, on two different surfaces of dentin (sound & caries-affected) and its efficacy against cariogenic microorganisms using in vitro and in silico methods.
Methods: The effect of a-tomatine at different concentrations (0.75 / 1 / 1.5 µM) on shear bonding strength in caries-affected and sound dentin was also investigated (n = 10; each per subgroup). The analysis of shear bonding and failure tests was conducted after a 24-hour storage period. Fracture surfaces were examined under a scanning electron microscope. A stock solution 3 mM of a-tomatine was prepared for antimicrobial evaluation. Antimicrobial activities of the agents against Streptococcus mutans ATCC 25175, Lactobacillus casei ATCC 4646, and Candida albicans ATCC 10231 standard strains were investigated by microdilution method. In addition, through the method of molecular docking and dynamic analysis, the affinity of a-tomatine for certain enzymes of these microorganisms was examined.
Results: The pretreatment agent and dentin type significantly influenced shear bonding strength values (p < 0.05). As the molarity of a-tomatine increased, the bonding value decreased in sound dentin, while the opposite was true in caries-affected dentin. According to molecular docking and dynamic analysis, the highest affinity was observed in L. casei's signaling protein. Microdilution assays revealed a-tomatine to exhibit fungicidal activity against C. albicans and bacteriostatic effects against S. mutans. No antimicrobial effect was observed on L. casei.
Conclusion: a-tomatine demonstrates a positive impact by serving as both a pretreatment agent for bonding strength and an inhibitor against certain cariogenic microorganisms
The effect of decolonization-decontamination prophylaxis versus traditional prophylaxis in orthopedic surgery in Kosovo
Get PDFThis study aimed to compare empirical prophylactic treatment with decoloni-zation-decontamination prophylaxis protocol in order to reduce surgical site infections. The study was conducted in Kosovo Ortomedica Orthopedic Hos-pital, the data from all patients admitted to the hospital between June 2018 and June 2019 was collected retrospectively, all the patients admitted to the hospital between November 2021 and January 2022 were followed prospectively. 127 patients were treated empirically, and 93 patients were prospectively treated with decolonization-decontamination prophylaxis protocol. The empirically treated patients were given cefazolin before surgery. However, the prospectively treated patients were first tested for MRSA infections and the observed infections were treated with decolonization-decontamination prophylaxis protocol. The infection status and the postoperative CRP values of the patients were compared and found to be significantly higher in the empirical group (4.7% versus 0, p=0.038 and 7.1% versus 0, p=0.006, for empirical and decolonization-decontamination groups respectively). In conclusion, the implementation of the decolonization-decontamination protocol has been shown to effectively decrease the incidence of infections in orthopedic surgical procedures. Nevertheless, it is imperative to conduct additional research utilizing a more extensive sample size and pharmacoeconomic studies in order to substantiate its viability as a prophylaxis measure