Applications of thermodynamics to study the physical phenomenon of heat conduction

Thermodynamics can be understood as the discipline of the physical sciences, that studies theoretically and practically the different manifestations of energy. The study of thermodynamics is important in relation to the understanding of thermal systems in industry, as well as, supporting energetic processes in living organisms. In relation to the study of energy processes in the context of heat transfer, concepts from thermodynamics are relevant. In the present investigation, the process of heat conduction in a metal bar is analyzed by applying the heat equation and the concept of entropy variation. The first part of the research proposes a numerical method to solve the heat equation in addition to a set of finite difference equations describing the energetic behavior of the system. The numerical solution of the heat equation and the thermodynamic behavior of the system are studied by programming to demonstrate the fit of the results with the theoretical models. Finally, applications of the achieved results in engineering contexts are discussed.

Hub clearance effect in the design space of the cantilevered stator embedded in a 4-stage low-speed research compressor

This paper focuses on the effect of hub clearance in the design space of the highly loaded cantilevered stator. The embedded 1.5 stages of a low-speed research compressor (LSRC) were conducted with Unsteady Reynolds Average Navier-Stokes (URANS) numerical investigation, and the cantilevered stator adopts positive bowed and fore-sweep three-dimensional design. The research details that with the hub clearance increasing from 1.1% to 4.5% span, the loss coefficient and the total leakage momentum of the cantilevered stator correspond to the change of the blade loading near the hub. When designing the inlet metal angle of the rotor downstream the cantilevered stator, emphasis should be given to considering the inter-stage matching below 15% span. The mixing of leakage flow in 1.1% span clearance and 2.5% span clearance is basically completed in the S3 passage, but the mixing of leakage flow in 3.5% span clearance and 4.5% span clearance is still relatively strong downstream of S3. When calculating the relative entropy variation based on Denton’s mixing model, attention should be paid to the relationship between the leakage flow velocity affected by the hub gap and the mainstream velocity, as well as whether the mixing has been completed in the blade passage.

Early detection and mitigation of DDos Attacks in software defined networks

Software Defined networking (SDN) is a new approach for the design and management of computer networks. The main concept behind SDN is the separation of the network’s control and forwarding planes with the control plane moved to the centralized controller. In SDN networks with the centralized controller structure DDoS attacks can easily exhaust the controller's or the switches' computing and communication resources, thus, breakdown the network within a short time. In this thesis, the scheme, running at the controller, can detect DDoS attacks at the early stage. The method not only can detect the attacks but also identify the attacking paths and start a mitigation process to provide some degree of protection of the network devices the moment an attack is detected. The Proposed method is based on the Entropy variation of destination IP address, Flow initiation rate and study of the Flow specifications.

Early detection and mitigation of DDos Attacks in software defined networks

Software Defined networking (SDN) is a new approach for the design and management of computer networks. The main concept behind SDN is the separation of the network’s control and forwarding planes with the control plane moved to the centralized controller. In SDN networks with the centralized controller structure DDoS attacks can easily exhaust the controller's or the switches' computing and communication resources, thus, breakdown the network within a short time. In this thesis, the scheme, running at the controller, can detect DDoS attacks at the early stage. The method not only can detect the attacks but also identify the attacking paths and start a mitigation process to provide some degree of protection of the network devices the moment an attack is detected. The Proposed method is based on the Entropy variation of destination IP address, Flow initiation rate and study of the Flow specifications.

Hematopoietic differentiation is characterized by a transient peak of cell-to-cell gene expression variability in normal and pathological conditions

Hematopoietic differentiation has been considered as a multistep process which is metaphorically represented as linear trajectories with discrete steps from hematopoietic stem cells to mature cells. While the transcriptional state of cells at the beginning or at the end of these trajectories are relatively well described from bulk analysis, what happens in the intermediate states has remained elusive until the use of single cell approaches allowed to capture the dynamic changes of transcriptomic states.Applying Shannon entropy to measure cell-to-cell variability among cells at the same stage of differentiation, we observed a transient peak of gene expression variability in all the hematopoietic differentiation pathways. Strikingly, genes with the highest entropy variation in a given differentiation pathway matched genes known as pathway-specific, whereas genes with the highest expression variation were common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes.These data suggest that differentiation may not be as deterministic and linear as previously thought, but could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination.

Permutation entropy variation for 2007 effusive dome-forming eruption period of Kelud Volcano, Indonesia

The complexity of a system recorded in time series data can be measured statistically using permutation entropy (PE). The state of a system (e.g. regular, chaotic, random, etc.) that underlies the appearance of variations in time series can be determined with PE. Since volcanoes are considered as the complex dynamical system controlled by interactions of many processes. Permutation entropy can be applied to study the system mechanism of volcano. We utilized PE to study system mechanism of Kelud volcano in 2007 dome-forming eruption period, from 3 (KWH; KLD; UMBK) seismic stations with different distances from the crater lake. Then, we want to compare the results. The result of study shows that the PE pattern for each station is different. The unique PE pattern that can be used as an eruption precursor is only shown at KWH and KLD stations. This pattern began to appear 2.7 days before the eruption on 3 November 2007. Data from UMBK station doesn’t show unique PE pattern. The factors such as sensor distance from magmatic activity center, size, and type of eruption probably influenced the final PE result. Using PE as the addition to volcano monitoring can maximize efforts in mitigation activities.