Domain Name Systems (DNS) provide critical performance in directing Internet traffic. It is a significant duty of DNS service providers to protect DNS servers from bandwidth attacks. Data mining techniques may identify different trends in detecting anomalies, but these approaches are insufficient to provide adequate methods for querying traffic data in significant network environments. The patterns can enable the providers of DNS services to find anomalies. Accordingly, this research has used a new approach to find the anomalies using the Neural Network (NN) because intrusion detection techniques or conventional rule-based anomaly are insufficient to detect general DNS anomalies using multi-enterprise network traffic data obtained from network traffic data (from different organizations). NN was developed, and its results were measured to determine the best performance in anomaly detection using DNS query data. Going through the R² results, it was found that NN could satisfactorily perform the DNS anomaly detection process. Based on the results, the security weaknesses and problems related to unpredictable matters could be practically distinguished, and many could be avoided in advance. Based on the R² results, the NN could perform remarkably well in general DNS anomaly detection processing in this study.

This paper examines the wave velocity of protein microtubules using a elasticity model that incorporates body forces, based on the structure of these hollow cylinder-like structures., the governing equations are analytically solved to determine how the body forces effect the wave velocity. To analyze the microtubule waves velocity, use microtubules with simply supported ends. The electric field of a dipole vibrating at the same frequency as microtubule vibrations approximates the electric field generated by the rhythmic motion of every charge. The numerical findings for the three modes of frequencies in the longitudinal, radial, and torsional directions for the current conditions are compared with the results of previous calculations.

High Strength steel reinforced Reactive Powder Concrete (RPC) Beam is a new type of beams which has evident advantages than the conventional concrete beams. However, there is limited research on the shear bearing capacity of high-strength steel reinforced RPC structures, and there is a lack of theoretical support for structural design. In order to promote the application of high-strength steel reinforced RPC structures in engineering, it is necessary to select a shear model and derive applicable calculation methods. By considering the shear span ratio, steel fiber volume ratio, longitudinal reinforcement ratio, stirrup ratio, section shape, horizontal web reinforcement ratio, stirrup configuration angle and other variables in the shear test of 32 high-strength steel reinforced RPC beams, the applicability of three theoretical methods to the shear bearing capacity of high-strength steel reinforced RPC beams was explored. The plasticity theory adopts the RPC200 biaxial failure criterion, establishes an equilibrium equation based on the principle of virtual work, and derives the calculation formula for the shear bearing capacity of high-strength steel reinforced RPC beams; Based on the Strut and Tie Theory, considering the softening phenomenon of RPC, a failure criterion is established, and the balance equation and deformation coordination condition of the combined force are combined to derive the calculation formula for the shear bearing capacity of high-strength reinforced RPC beams; Based on the Rankine theory and Rankine failure criterion, taking into account the influence of size effects, a calculation formula for the shear bearing capacity of high-strength reinforced RPC beams is derived. Experimental data is used for verification, and the results are in good agreement with a small coefficient of variation.

The process of concrete production consumes an immense volume of water, with approximately one billion metric tons of freshwater being utilized for tasks such as aggregate washing, fresh concrete production, and concrete curing. The accessibility of clean water for the public is hindered by the limited availability of water resources, primarily due to the rapid expansion of industries such as tanneries, stone quarries, and concrete manufacturing. These industries not only consume substantial amounts of freshwater but also generate significant volumes of various types of waste. Therefore, the use of fresh water in concrete production should be minimized. Few studies have reviewed the production of concrete using wastewater to derive practical and applicable findings for the industry. Thus, this study thoroughly explores the physical and chemical effects of wastewater on concrete, examining aspects like durability, hardened properties, and rheological characteristics. It identifies key factors that can compromise concrete properties when exposed to wastewater. The scarcity of research on integrating wastewater into concrete production underscores the urgent necessity for innovative approaches and methodologies in this field. While the inclusion of wash water typically reduces the workability of fresh concrete, it often enhances its compressive strength. Notably, significant improvements have been observed when using tertiary processed wastewater, wash water, polyvinyl alcohol-based wash water (PVAW), and reclaimed water in the concrete mixing process. The application of tertiary treatment to wastewater resulted in a notable enhancement of compressive strength, showing increases of up to 7%. In contrast, wastewater treated through secondary methods experienced a decline in strength ranging from 9% to 18% over a period of six months. However, the use of reclaimed wastewater demonstrated an improvement in strength by 8% to 17%, depending on the concentration level ranging from 25% to 100%. In contrast, the utilization of secondary processed wastewater and industrial water has a minimal impact on the concrete's strength.

During the clinkering stages of cement production, the chemical composition of fine raw materials such as limestone and clay, which include iron oxide (Fe₂O₃), silicon dioxide (SiO₂) and aluminum oxide (Al₂O₃), significantly influences the quality of the final product. Specifically, the chemical interaction of Fe₂O₃ with CaO, SiO₂ and Al₂O₃ during clinkerisation plays a key role in determining the chemical reactivity and overall quality of the final cement, shaping the properties of the concrete produced. As an extension, this study aims to investigate the physical effects of incorporating nanosized Fe₂O₃ particles as fillers in concrete matrices, and their impact on concrete structures, namely slabs. To accurately model the reinforced concrete (RC) slabs, a refined trigonometric shear deformation theory (RTSDT) is used. Additionally, the stochastic Eshelby's homogenization approach is employed to determine the thermoelastic properties of nano-Fe₂O₃ infused concrete slabs. To ensure comprehensive coverage in the study, the RC slabs undergo various mechanical loads and are exposed to temperature fields to assess their thermo-mechanical performance. Furthermore, the slabs are assumed to rest on a three-parameter viscoelastic foundation, comprising the Winkler elastic springs, Pasternak shear layer and a damping parameter. The equilibrium governing equations of the system are derived using the principle of virtual work and subsequently solved using Navier's technique. The findings indicate that while ferric oxide nanoparticles enhance the mechanical properties of concrete against mechanical loading, they have less favorable effects on its performance against thermal exposure. However, the viscoelastic foundation contributes to mitigating these effects, improving the concrete's overall performance in both scenarios. These results highlight the trade-offs between mechanical and thermal performance when using Fe₂O₃ nanoparticles in concrete and underscore the importance of optimizing nanoparticle content and loading conditions to improve the structural performance of concrete structures.