1,249 research outputs found
THE SLICER MAP: MOMENTS, CORRELATIONS AND UNIVERSALITY
No full textThis thesis concerns the relation of different models of anomalous transport, and
the possibility of identifying a corresponding universality class. Investigation of
transport of matter in highly confining media is a very active field of research with
numerous applications to bio- and nano-technology. We proceed from a model,
called Slicer Map (SM), developed by Salari et al. CHAOS 25, 073113 (2015), that
captures some features of anomalous transport, while being analytically tractable.
The SM is a one-parameter family of non-chaotic, one-dimensional dynamical
systems. Different trajectories neither converge nor separate in time, except at
discrete instants, when the distance between trajectories jumps discontinuously, because
they are separated by a slicer. This is reminiscent to the role of corners in
polygonal billiards. The SM shows sub-, super-, and normal diffusion as a function of
its control parameter α, that characterises the power-law distribution of the length
of ballistic flights. Salari and co-authors analytically expressed the time dependence
of the moments of positions as a function of α, and compared it with the meansquare
displacement of the Lévy-Lorentz gas (LLg), that also depends on a single
parameter β. The LLg is a stochastic process, that is much more complex than
the SM. Surprisingly it was found that the moments of the positions distributions
of the SM and the LLg have the same asymptotic behaviour when the parameters
α and β are chosen in order to match the exponent of the second moment. However,
moments only partially characterise transport processes. Hence in this thesis
we derive analytic expressions for the position auto-correlations of the SM, and
we compare them with the numerically estimated position auto-correlations of the
LLg. Remarkably, the same relation that produces the agreement of the moments leads to the agreement of the position auto-correlation functions, at least for the
low scatterers density of LLg. In the search of a universality class for these phenomena,
we introduce an exactly solvable model called Fly-and-Die (FnD) dynamics
that generates anomalous diffusion, and we derive analytical expressions for all moments
of the displacements, for the position auto-correlation function, and for the
velocity auto-correlation functions. The parameters of the model can be mapped
to other anomalous transport processes by matching the exponents for the meansquare
displacement and the prefactor of the corresponding power law. Indeed, this
simplification of the SM, generates the same transport regimes as the SM.
It is conjectured that the FnD provides the asymptotic behaviour of all the
position moments and the auto-correlation functions, for the universality class of
systems whose positions statistics are dominated by the ballistic events. The conjecture
is motivated by the fact that the sub-dominant terms in the SM and of the
FnD contribute like the ballistic fights to the asymptotic behaviour, i.e., they contribute
the maximum allowed for a system to belong to such a universality class.
Different models in the class may be distinguished considering other variables. This
is demonstrated here for the velocity auto-correlation function. Numerical results
on the Lévy-Lorentz gas support our conjecture
History and Normativity in Traditional Indian Muslim Thought: Reading Shari`a in the Hermeneutics of Qari Muhammad Tayyab (d.1983)
No full textTraditional forms of Islamic thought have a particular understanding as to how norms and values stand in relation to time and change. This article explores the view of a prominent thinker Qari Muhammad Tayyab, affiliated to the Deobandi school, a prominent traditionalist franchise of seminaries (madrasas) in South Asia
Thermal-aware scheduling in green data centers / Muhammad Tayyab Chaudhry
No full textData centers can go green by saving electricity in two major areas: computing and cooling. Servers in data centers require a constant supply of cold air from on-site cooling mechanism for reliability. Increased computational load makes servers to dissipate more power as heat and eventually amplifies the cooling load. In thermal-aware scheduling, computations are scheduled with the objective of reducing data center wide thermal gradient, hotspots and cooling magnitude. Complemented by heat modeling, thermal-benchmarking, thermal-aware server arrangement; and thermal-aware monitoring and profiling, this scheduling is energy efficient and economical.
This research work proposes multiple techniques for thermal-benchmarking of data center servers such as: Thermal-benchmarking for Standalone Servers (TBSS), Thermal-benchmarking for Server Comparison (TBSC), Multi-intensity TBSS (MiTBSS) and Thermal-benchmarking for Virtualized Clusters (TBVC). These techniques are useful for thermal evaluation of servers, emulating various types of workloads and creating the thermal profiles. A thermal-aware server relocation algorithm (ThSRA) for thermal-stress free arrangement of servers is also proposed. The experimental results show that the peak outlet temperatures of the servers can be brought closer to average outlet temperature by over 5 times through ThSRA. This also brings the lowering of average peak outlet temperature by 3.5% and minimizing the thermal-stress.
Thermal profiles are used for outlet temperature prediction modeling of the servers. These models include the worst case prediction model (WCPM), optimistic prediction model (OPM) and enhanced optimistic prediction model (EOPM). The best prediction model can predict the outlet temperature of the servers with an average error of up to 0.3 degree Celsius. WCPM is applied for offline hotspot-resistant virtual machine deployment algorithm (HVMDA) and hotspot-aware server arrangement algorithm (HSLERA). The combination of HVMDA and HSLERA leads to increase in server utilization by up to 50% and lowering the peak outlet temperature by up to 3% on average. The WCPM and OPM are used for the implementation of online thermal-aware VM scheduling. These schedulers have comparatively lower thermal-gradient across all servers, lower outlet temperatures across all servers, effective use of computing capacity and the power consumption. The proposed proactive schedulers comparatively show up to 11% in total energy savings. All these thermal-aware techniques are helpful in the establishment of green data centers
X-band Slotted Waveguide Antenna
No full textA planar slot array antenna of 12x16 elements is designed at X-band with uniform aperture distribution to get maximum aperture efficiency. The antenna is centre fed from iris coupling slot with alternate slot inclinations to feed
the radiating waveguides in phase. A feeding network of nonstandard waveguides is formed to couple the power from feeding network to radiating aperture. A radiating aperture also of non-standard size is selected to give the low profile antenna at 9.65GHz. The longitudinal shunt slots are used with alternate offsets directions to radiate in phase at boresight
Fault Detection and Severity Level Identification of Spiral Bevel Gears under Different Operating Conditions Using Artificial Intelligence Techniques
No full textSpiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and complex vibration signal, their fault detection is really challenging even in the case of serious defects. Therefore, spiral bevel gears have rarely been used as benchmarking for gears’ fault diagnosis. In this research study, Artificial Intelligence (AI) techniques have been used for fault detection and fault severity level identification of spiral bevel gears under different operating conditions. Although AI techniques have gained much success in this field, it is mostly assumed that the operating conditions under which the trained AI model is deployed for fault diagnosis are same compared to those under which the AI model was trained. If they differ, the performance of AI model may degrade significantly. In order to overcome this limitation, in this research study, an effort has been made to find few robust features that show minimal change due to changing operating conditions; however, they are fault discriminating. Artificial neural network (ANN) and K-nearest neighbors (KNN) are used as classifiers and both models are trained and tested by using the selected robust features for fault detection and severity assessment of spiral bevel gears under different operating conditions. A performance comparison between both classifiers is also carried out
Material Flow Analysis of the Wood-Based Value Chains in a Rapidly Changing Bioeconomy: A Literature Review
No full textMaterial Flow Analysis (MFA) is a key tool in the circular bioeconomy, providing insight into the flow of materials within a system. Its use in the wood-based value chain is increasingly recognized and provides valuable information for policy making. However, to the best of our knowledge, this topic has never been systematically reviewed. To fill this gap, this study developed a systematic literature review of MFA research in the wood-based value chain. Peer-reviewed articles published between 2000 and 2024 were identified via databases such as Scopus and Google Scholar and analyzed in detail to identify and deepen different approaches to MFA with reference to its conceptualization, scope, and methodological implementation. Based on our review we categorized various MFA models based on their scale and scope, revealing significant diversity in methodological terms and data requirements. The results emphasize the existing MFA approaches often face limitations due to inconsistent data quality and lack of detailed product-level analyses. This research provides practical insights on improving data collection methods, such as standardizing input datasets and incorporating economic and social indicators, to enhance the reliability of MFA studies. It also provides guidelines for implementing MFA models aligned with circular economy principles, integrating both traditional and emerging wood products streams. These insights offer valuable directions for future research aimed at more accurately capturing the complexities of wood flows, promoting better resource management, and supporting policy formulation in the bioeconomy sector. The findings of this review underscore the importance of adopting holistic and integrated methodologies that incorporate new bio-based materials and circular economy principles, ensuring that MFA continues to be an effective tool for advancing sustainable resource management in the forest sector
Effect of Multiwall Carbon Nanotubes on the Ablative Properties of Carbon Fiber-Reinforced Epoxy Matrix Composites
No full textThe effect of multiwall carbon nanotubes (MWCNTs) on the thermal and ablative properties of carbon fiber epoxy matrix composites was investigated. Thermochemical and oxidation reactions were found to dominate the ablation mechanism. Shear forces and high temperatures were produced using oxy-acetylene torch. Three types of composites were investigated: (a) carbon fiber epoxy matrix composites, (b) carbon fiber epoxy matrix composite containing 0.2wt% MWCNTs and (c) carbon fiber epoxy matrix composite containing 0.4wt% MWCNTs. Composites containing 0.2wt% MWCNTs showed 5.4% increase in erosion resistance, while composites containing 0.4wt% MWCNTs showed 9.6% increase in erosion resistance compared with carbon fiber epoxy matrix composites. Thermal conductivity increased with the addition of MWCNTs, i.e., 15 and 52% in composites containing 0.2 and 0.4wt% MWCNTs, respectively. Due to the addition of MWCNTs, the increased thermal conductivity of MWCNT-loaded epoxy matrix affected the ablation behavior of carbon fibers and resulted in gradual thinning of carbon fibers
Discussion on <i>α</I>-strictly Contractive Nonself Multivalued Maps
No full textAli, Muhammad/0000-0002-1444-7888; KARAPINAR, ERDAL/0000-0002-6798-3254; Kamran, Tayyab/0000-0001-7833-2476In this paper, we introduce the notions of alpha-contractive condition and strict alpha-admissibility for nonself multivalued mappings. By using these notions, we prove fixed point theorems for nonself multivalued mappings. We also construct an example to support our result
Existence of best proximity points for controlled proximal contraction
No full textKiran, Quanita/0000-0002-3442-3488; KARAPINAR, ERDAL/0000-0002-6798-3254; Ali, Muhammad/0000-0002-1444-7888; Kamran, Tayyab/0000-0001-7833-2476In this paper, we investigate the sufficient condition for the existence of best proximity points for non-self-multivalued mappings. Additionally, we discuss the stability theorem for such mappings. Our results improve and generalize some existing results on the topic in the literature, in particular, the results of Lim and of Abkar and Gabeleh
Supplemental Material - Micro CT based stochastic design and flow analysis of dry fiber preforms manufactured by automated fiber placement
No full textSupplemental Material for Micro CT based stochastic design and flow analysis of dry fiber preforms manufactured by automated fiber placement by Rehan Umer, Muhammad A Ali, Tayyab Khan and Kamran A Khan in Journal of Composite Materials</p
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