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Süt azı dişlerine uygulanan bioflex ve zirkonyum kuronların fiziksel özelliklerinin in vitro olarak karşılaştırılması
Daha sonra doldurulacaktır.
Low cost photovoltaic monitoring system based on lorawan network
Renewable energy, especially solar energy, is increasingly popular in both home and industrial sectors due to globalization. This thesis investigates the design and implementation of a low-cost photovoltaic (PV) monitoring system using the LoRaWAN network. Because it offers a virtual environment for modelling, evaluating, and experimenting with complex systems, the simulation of monitoring a PV system is essential for comprehending system behaviour. The system seeks to provide a low-cost solution for monitoring energy and environmental parameters in PV systems by using the features of LoRaWAN technology for long-range, low-power communication. This thesis offers a thorough analysis of the application of Internet of Things technology for the real-time monitoring of PV system performance. In order to improve the overall efficiency of PV systems, the goal is to offer a dependable and scalable system that facilitates ongoing monitoring, data collecting, and analysis. The system addresses the issues of cost-effectiveness, scalability, and remote monitoring in PV systems by including sensors to capture vital data, such as solar panel output, battery condition, and ambient variables. A LoRaWAN network, which offers long-range and low-power communication and supports data transfer, is perfect for off-grid and remote photovoltaic systems. By adding LoRaWAN technology, systems become more efficient and scalable, opening the door for widespread use of sustainable energy solutions. PV systems are now affordable enough for a broad spectrum of customers, including those who live in remote or underdeveloped areas. The system offers real-time data on PV system performance, facilitating preventive maintenance and well-informed decision-making, according to the findings of the field testing. The data from the DC voltage sensor and PZEM-004T V3 module provide crucial insights into the dynamic behavior of the electrical system under observation. The system's need for electrical power is implied by the continuous increase in active power consumption (Pac), which went from 933 to 2107 Watts. In the MATLAB/Simulink system, the measurement results are concurrently entered into the PV model enabling theoretical simulation and graphically shown as a dashboard. On the same software platform, the assessment and defect detection functionalities for PV modules within real-world operating circumstances are carried out and presented. The capabilities of visual monitoring, assessment, and defect detection of the suggested system have been shown with adequate confidence and accuracy. The suggested system has several benefits over the well-developed ones, including the ability to combine all visualisation monitoring, assessment, and fault detection inside the MATLAB/Simulink environment and to decrease both wire and hardware configuration.
Optimizing network performance rough image processing techniques in omputer science it
A fundamental apparatus for exploring digital protection risks in Internet of Things (IoT) networks is the Botnet of Things (BoT-IoT) dataset. This examination proposes an original way to deal with order BoT-IoT information by changing over the crude information into RGB images and afterward applying calculations, for example, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Irregular Woodland to a helpful classification model. The BoT-IoT dataset is at first changed over into RGB images, where each component vector addresses a pixel in the image. To protect the spatial data of the first information, these photographs are in this manner saved in the.png design. We might take benefit of the strong capacities of example acknowledgment and image regulation procedures for IoT information examination with this change interaction. The RGB images delivered from the BoT-IoT dataset were then sorted utilizing an aggregate classification method. The ensemble includes the most striking Irregular Woodland classifiers, KNN, and SVM, every one of which contributes unmistakable qualities to the general classification issue. To show up at the last classification choice, the estimates of discrete classifiers are shared utilizing a weighted democratic system. The recommended strategy is compelling, as proven by trial discoveries on the BoT-IoT dataset, where the ensemble model accomplishes a great exactness of generally 99.36%. What's more, the model performs well with regards to precision, review, and F1-score, exhibiting its adequacy in isolating noxious action from harmless movement in Internet of Things networks. Inside and out review was likewise finished to explain every classifier's commitment inside the ensemble setting. This examination uncovers the fitting properties of the classifiers: Arbitrary Timberland consolidates the limit of ensemble learning for upgraded speculation, KNN makes utilization of nearby neighbourhood data, and SVM succeeds at dealing with testing choice limits. In any case, this work offers a new way to deal with BoT-IoT information recording using ensemble learning strategies and RGB image models. The extraordinary exactness achieved features this strategy's capability to improve digital protection in Internet of Things networks. Through effective distinguishing proof and alleviation of pernicious activities, the proposed approach adds to the advancement of IoT security exploration and safeguards networked frameworks from arising digital threats.
Yapay zekânın tıpografıye etkisi ve reklam kampanyalarında kullanımı
Bu tez, yapay zekanın tipografi üzerindeki etkisini ve reklam kampanyalarındaki kullanımını ele almakta ve bu alandaki değişimleri ortaya koymaktadır. YZ teknolojilerinin gelişmesiyle birlikte, tipografi çalışmaları yeni bir dönüşüm sürecine girmiştir. Çalışmanın amacı, YZ destekli tipografi çalışmalarının avantajlarını ve dezavantajlarını inceleyerek, bu teknolojinin reklam sektörüne sağladığı katkıları ve potansiyel zorlukları belirlemektir. Yöntem olarak, çeşitli sanatçılar tarafından YZ kullanılarak oluşturulan tipografik eserler detaylı bir şekilde incelenmiş ve bu sayede yapay zekanın bu alandaki etkinliği somut örneklerle değerlendirilmiştir. Tezde sunulan analize göre, YZ tipografi çalışmalarında zaman ve maliyet verimliliği sağlamakta, hızlı prototipleme ve büyük veri setlerinden desen tanıma gibi yeni kapasiteler sunmaktadır. Ancak, bu yeni teknolojinin insan tasarımcının yaratıcılığını ve eleştirel düşünce kabiliyetini tamamen taklit edebilmesindeki sınırlılıklar da göz önünde bulundurulmuştur. Reklam kampanyalarındaki kullanımına yönelik olarak ise YZ tarafından üretilen tipografilerin, hedef kitlelere özelleştirilebilir ve dikkat çekici içerikler sunma konusunda önemli fırsatlar barındırdığı sonucuna ulaşılmıştır.
Numerical assessment of ground vibrations i̇nduced by piles i̇nstallations on surrounding buildings
In this thesis, a comprehensive understanding of impact pile driving on nearby building is presented. The theoretical concept is sufficiently covered. Also, reliable calculation methods that can be used to estimate Peak Particle Velocity as a function of distance from the driven pile are reviewed. Different types of piling-induced vibrations are discussed. The properties of dynamic hammer, pile geometry and soil parameters that govern piling-induced vibrations are highlighted. As well as impedance of hammer, pile and soil are explained. In This thesis, the finite element model was utilized to investigate the effect of both horizontal distance and penetration depths during dynamic pile driving on nearby building. A series of seventy-seven PLAXIS 3D models were established for five-story concrete framed structures to examinate how its different floors and foundations are affected by piling-induced vibrations. Furthermore, one of the novel aspects of this paper is to investigate how piling-induced vibrations affect resident's comfort besides building safety. Another novel aspect, that ratio of vibrations on the building to vibrations on the soil at symmetric distances is computed. Moreover, a comprehensive two-ways sensitivity analysis was performed to illustrate how the structure's floors are affected by variation of hammer, pile and soil properties, in terms of both horizontal distance and pile penetration depths. Keywords: Plie Driving-induce vibrations, Resident's Comfort, Structural damage, Finite Element Modeling, Buildings to Soil Vibration-Induced Ratio, Sensitivity Analysis
İdari yargıda miktar artırımı
İdari yargıda kural olarak dava açma süresi geçtikten sonra dava konusu istemin genişletilmesi ya da değiştirilmesi yasaktır. Ancak bu yasağın hiçbir istisna barındırmamasından dolayı yaşanan mağduriyetler nedeniyle Avrupa İnsan Hakları Mahkemesi tarafından Türkiye aleyhine ihlal kararları verilmiştir. Hak ihlallerini önlemek için 2577 sayılı İdari Yargılama Usulü Kanunu'nda yapılan değişiklikle idari yargıya miktar artırımı kurumu getirilmiştir. Miktar artırımı, Medeni Usul Hukukundaki ıslahtan oldukça farklıdır. Islah, davanın tamamen değiştirilmesine dahi imkan vermektedir. Oysa 2577 sayılı Kanun'da miktar artırımının çerçevesi çok daha dar çizilmiştir. Kanun'a göre miktar artırımı ile yalnızca tam yargı davalarında talep edilen miktar artırılabilmektedir. Ayrıca bu imkanın tek seferlik olduğu ve nihai karar verilinceye kadar kullanılabileceği de kurala bağlanmıştır. Ancak bazen davacının ikinci kez miktar artırımı yapması gerekebilir. Aynı şekilde istinaf kanun yolunda da bu hakkın kullanılması söz konusu olabilir. Kanun maddesi bu tür sorunlara cevap vermekten uzak olduğundan miktar artırımı hakkında mahkemelerin farklı uygulamalarına tanık olunmaktadır. Bu çalışmanın amacı, miktar artırımında karşılaşılan sorunlar hakkında yargı makamlarının verdiği kararları aktarmak ve bu konuları bir ölçüde de olsa aydınlatmaktır.
Innovative approaches to kinematic optimization and material design in robotic prosthetic arm
This thesis provides a thorough study of designing, modelling, and analyzing a 7-degree-of-freedom prosthetic arm. The research illustrates the use of suitable materials to enhance its mechanical efficiency. The research evaluates three distinct materials, that is, Alloy 6061 T6 made of Aluminum, (230 GPa) Epoxy Carbon UD (Uncured), and (65% long glass fibre) of Composite, epoxy, selected for their distinctive mechanical qualities and prospective applicability in prosthetics. The prosthetic arm's design was created with SolidWorks', and its structural performance was evaluated using ANSYS's Workbench under different loading situations. The research depends on tackling the important problem of balancing durability, weight, and strength in a 7-degree-of-freedom prosthetic arm modelling, a balance necessary for human convenience and efficiency. The key mechanical properties, including maximum von-mises stress, total deformation, strain energy equivalent elastic strain, and factor of safety of prosthetic arm, and comprehensive simulations evaluated each material. The findings indicated that although all three advanced materials display satisfactory performance, the Epoxy Carbon UD proved to be the optimal selection. This material displayed the optimal stiffness-to-weight ratio, which is also minimal deformation, and a greater safety factor, making it the most effective choice for the prosthetic arm. This study enhances prosthetic arm advancement by providing insights into choosing materials and optimizing designing. The research highlights the significance of employing sophisticated materials and modeling methodologies to develop prosthetic arm that perform structural requirements while improving the comprehensive experience for users. The thesis concludes with a recommendation for further research, encompassing the investigation of novel materials for composites, the incorporation of intelligent technologies, and the verification of the simulations outputs by physical form modelling
Streamlining life certificate authentication: Biometric integration with fingerprint and vein recognition
With the rapid advancement of technology worldwide, there is an increasing demand for innovative solutions to address challenges in managing and delivering public services, particularly for pensioners. One key challenge faced by institutions responsible for disbursing financial entitlements to pensioners is the "proof of life" verification process, which is often time-consuming and prone to errors. This thesis proposes a digital solution that enhances security and accuracy by combining two biometric authentication methods—fingerprint and vein recognition. By integrating these complementary biometric techniques, the system significantly improves the accuracy of the "proof of life" process. Experimental results demonstrated that the dual-authentication system achieved higher accuracy compared to using a single method, providing over 87.07% accuracy in verifying pensioners' identity, with verification times under 4 seconds. This efficient and secure approach ensures that eligible pensioners can continue receiving their pensions without delays, benefiting both pensioners and service providers.
Sudan's revolution 2018 and impact on foreign relations
This study examines the impact of the 2018 Sudanese Revolution on Sudan's international relations and foreign policy. Utilizing a neoclassical realism framework, it highlights national interests and power dynamics as key factors. A mixed-methods approach combines primary data, documentary analyses, and expert insights to assess historical context and changes in foreign policy. The findings reveal two main outcomes. First, Sudan's removal from the U.S. list of state sponsors of terrorism in 2020 significantly improved its international standing, creating opportunities for foreign investment and economic collaboration with Western nations. Second, the revolution transformed Sudan's relationships with neighboring countries, Western powers, and Arab allies, enhancing its image in the international community. However, these gains are fragile. The initial improvements were short-lived due to a return to civil war, driven by various domestic and international interests. This regression highlights the complex interplay between internal political dynamics and external factors in shaping foreign policy. The research enhances understanding of how revolutionary movements can influence a nation's foreign policy and global standing, stressing the need to consider both internal changes and external pressures. Additionally, it addresses the challenges faced by transitioning states in maintaining diplomatic gains amid instability.
Advanced data analytics for network security: Detecting and mitigating threats through real-time data processing
This research aims to investigate the enhancement of real-time threat identification and mitigation through the application of advanced data analytics in network security. The findings of this literature review and qualitative interviews with field specialists indicate that real-time data processing significantly improves the precision of threat detection and the velocity of response. We highlight advanced machine learning techniques such as decision trees and neural networks due to their ability to identify patterns overlooked by traditional methods. The research underscores the essential requirement for a workforce skilled in data analytics and cybersecurity, as well as the significance of a systematic implementation approach. Recommendations for organizations encompass employee training, utilization of real-time data, and the establishment of systematic deployment strategies. This study has certain limitations, such as the exclusive use of qualitative data. Nonetheless, it demonstrates that data analytics can enhance network security management. It recommends that subsequent research examine ethical issues, such as data protection and privacy within advanced analytics, and do empirical assessments of the proposed methodologies. Businesses must modify their security protocols to leverage data analytics capacity to mitigate the effects of emerging cyber threats.