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Intelligent resource allocation for knowledge-driven semantic communication networks
No full textThe future communication system is undergoing a paradigm shift from "transmitting bits" to "conveying meaning," with semantic communication (SemCom) emerging as its core technology. SemCom’s ultra-high efficiency relies on a shared knowledge base (KB) between sender and receiver. However, in dynamic environments, the KB inevitably becomes outdated, causing a sharp decline in semantic efficiency. To restore system performance, the KB must be updated and synchronize. The core insight of this thesis is that the maintenance process of the KB and the transmission of semantic data itself compete for the same limited wireless resources. This creates a novel and fundamental dynamic trade-off between the immediate utility of transmission and the long-term benefits of KB updates. Existing literature often overlooks this coupling effect, failing to balance the immediate utility of data transmission against the long-term reliability of KB maintenance.
First, to address the KB staleness trade-off, this thesis models knowledge obsolescence as a quantifiable state variable. Based on this, we formulate the dynamic tradeoff between semantic transfer utility and knowledge consensus cost as a 0-1 Mixed-Integer Non-Linear Programming (MINLP) problem. We propose an online scheduling algorithm based on model predictive control (MPC) and iterative marginal cost allocation (IMCA) to efficiently solve this tradeoff. Second, the aforementioned resource allocation problem, along with other wireless networking applications, mathematically manifests as an NP-hard 0-1 MINLP. Traditional optimization solvers struggle to scale due to exponential complexity, while pure reinforcement learning (RL) methods suffer from inefficient search due to blind exploration. Thus, we aim to address the aforementioned challenges by constructing a unified resource optimization framework. Specifically, the main research contribution is proposing a unified 0-1 mixed optimization framework, which models discrete decision processes as Markov Decision Processes (MDPs). Its core innovation lies in solving the continuous relaxation of the original problem as guidance and theoretically proving that the neighborhood of this relaxed solution defines a high potential zone (HPZ), thereby transforming the RL agent’s exploration from blind trial-and-error to efficient guided search. Third, regarding the KB synchronization mechanism itself, existing consensus protocols are designed for wired networks with deterministic fault models, making them overly conservative and inefficient for probabilistic wireless environments. To bridge this gap, this thesis builds an availability-robustness analysis framework for consensus protocols, for consensus protocols used in tasks like KB maintenance, this paper introduces an innovative dual-metric reliability model. This model quantifies the inherent tradeoff between availability and robustness, guiding the optimal design of the quorum through solving a constrained optimization problem. Finally, this thesis designs and builds a multi-user SemCom physical platform based on non-orthogonal multiple access (NOMA). We define semantic throughput (STU) as the optimization objective and propose an improved watering algorithm to address the non-convex semantic-aware power allocation problem. Experimental results validate the significant performance gains of the proposed approach at the semantic level
Experiments of the Richtmyer-Meshkov Instability in a cylindrical and rough surface geometry
No full textAbstract not currently available
Control of hybrid superconducting quantum circuits based on advanced nanomaterials
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Measurement of the t¯tH(b¯b) process using the ATLAS detector with an effective field theory interpretation
Get PDFThe associated production of a Higgs boson with a top-quark pair (t¯tH) provides a direct probe of the top–Higgs Yukawa coupling, the largest coupling in the standard model. Constraining this process is essential for testing the standard model and for probing possible contributions from physics beyond the standard model. This thesis presents a measurement of t¯tH production in the H → b¯b decay channel, using the full Run 2 dataset, 140 fb−1 of proton-proton collision data at a centreof-mass energy of √ s = 13 TeV, collected by the ATLAS detector at the LHC. Included in this analysis are: novel machine learning methods, improved modelling and reconstruction techniques, dedicated high pT uncertainty extrapolation and more. An excess of events over the non-t¯tH background is found with an observed (expected) significance of 4.6 (5.4) standard deviations. The t¯tH cross-section is measured to be σttH¯ = 411+101 −92 fb = 411 ± 54 (stat.) +85 −75 (syst.) fb, for a Higgs boson mass of 125.09 GeV, consistent with the standard model prediction of 507+35 −50 fb. The cross-section is also measured differentially in bins of the Higgs boson transverse momentum within the Simplified Template Cross-Section framework. This analysis is then re-interpreted in the Standard Model Effective Field Theory framework. The three main operators governing the ttH production in this framework, OtG, Otϕ, OϕG, are investigated and constraints are applied to their respective Wilson coefficients ctG, ctϕ, cϕG. Improvements in precision of the Wilson coefficients were seen in individual quadratic fits compared to early Run-2 (2016) studies, particularly with ctϕ = 2.55+2.22 −2.15, whose contributions are unique to the t¯tH production mode, sees improvements in precision by a factor of 2
Social-aware autonomous vehicle-pedestrian coupled decision-making and behavior planning
Get PDFRapid advancements in vehicle automation technology have enabled autonomous vehicles (AVs) to move beyond simple, structured highway settings and operate increasingly within more complex urban environments. As AVs become more prevalent, they will inevitably share the road with diverse traffic participants, particularly pedestrians. The high uncertainty and dynamic nature inherent in human behavior significantly complicate the AV’s decision-making process. To ensure both safety and efficiency while exhibiting socially acceptable behavior, AVs must make real-time decisions and continuously adapt their strategies in response to surrounding pedestrian behaviors. This poses a major challenge to existing AV decision-making systems. Therefore, this study focuses on developing the decision-making strategies for AVs in urban pedestrian-involved environments, spanning scenarios from simple interactions with a single pedestrian to complex cases involving multiple pedestrians. The core objective is to uncover the underlying interaction dynamics and to improve the AV’s capability to make decisions that are safe, efficient and socially acceptable in dynamic, human-centric contexts.
Initially, this study investigates the critical factors influencing the decision making processes of human drivers and pedestrians during vehicle–pedestrian interactions. A series of controlled experiments were conducted using a virtual reality platform designed to collect realistic behavioral data. The data analysis mainly focused on kinematic variables that are easily measurable in real-world deployments. AdaBoost classification and Partial Dependence Plots were employed to identify and visualize the most influential factors affecting pedestrian crossing intentions and driver approaching behaviors. The results indicate that longitudinal distance and vehicle acceleration are the most influential factors in pedestrian decision-making, while pedestrian speed and longitudinal distance also play a crucial role in determining whether the vehicle yields or not. Based on these insights, a simplified mathematical model was developed to relate observable kinematic parameters to pedestrian crossing intentions, providing a practical tool for dynamically inferring crossing intentions during interactions. Additionally, the study explored driver yielding patterns under varying degrees of pedestrian intention clarity. These findings support the development of interpretable and implementable models for real-time decision-making in vehicle–pedestrian interaction scenarios.
In addition, this study examines the decision-making strategies of the AVs when interacting with a single pedestrian in unsignalized intersections. A novel framework was proposed that integrates the Partially Observable Markov Decision Process with behavioral game theory to dynamically model interactive behaviors between the AVs and the pedestrian. Both agents were modeled as dynamic-belief-induced quantal cognitive hierarchy models, considering human reasoning limitations and bounded rationality in the decision-making process. Moreover, a dynamic belief updating mechanism allowed the AV to update its understanding of the opponent’s rationality degree in real-time based on observed behaviors and adapt its strategies accordingly. The analysis results indicate that proposed models effectively simulate vehicle-pedestrian interactions and the AV decision-making approach performs well in safety, efficiency, and smoothness. It captures key patterns of the driving behavior operated by real human drivers in virtual reality experiments and even achieves more comfortable navigation compared to our previous virtual reality experimental data.
Finally, this study investigates the decision-making strategies of the AVs operating in pedestrian-rich shared spaces. A novel framework was proposed for modeling interactions between the AV and multiple pedestrians. In this framework, a cognitive process modeling approach inspired by the Free Energy Principle was integrated into both the AV and pedestrian models to simulate more realistic interaction dynamics. Specifically, the proposed pedestrian Cognitive-Risk Social Force Model adjusts goal-directed and repulsive forces using a fused measure of cognitive uncertainty and physical risk to produce human-like trajectories. Meanwhile, the AV leverages this fused risk to construct a dynamic, riskaware adjacency matrix for a Graph Convolutional Network within a Soft Actor-Critic architecture, allowing it to make more reasonable and informed decisions. The qualitative and quantitative results indicate that the proposed strategy effectively improves safety, efficiency, and smoothness of AV navigation compared to the state-of-the-art method.
In conclusion, this study addresses key challenges in AV decision-making within human-centric urban environments, providing valuable insights as well as practical solutions to support safe, efficient, and socially aware autonomous navigation
Let’s do the twist: chiral information transfer in self-assembled supramolecular functionalised coiled-coils
Get PDFChirality is an inherent feature of life and can be found across many natural systems, from DNA to snail shells. This concept spans from the molecular level, up to visible phenomena at the macroscale, with each step in this increasing scale influencing the next as a result of chiral information transfer. Despite the prevalence of chirality across the scientific field, the exact mechanisms and controls of chiral information transfer are poorly understood.
To aid in the understanding of these mechanisms, a model system taking advantage of the innate chiral information transfer in the self-assembly of peptide sequences, known as coiled coils, has been developed and investigated in this work. By modifying these sequences to feature an aromatic chelating unit at the N-terminus, this work demonstrates a cooperative relationship in which the aromatic chelating units (2,2′-bipyridine and 8-hydroxyquinoline) enhance the α-helical character of the peptide assembly, while the chiral information from the peptide is simultaneously transmitted to the complex, resulting in a chiral bias for onehandedness of the resulting complex.
After discussion of the relevant literature in Chapter 1, Chapter 2 of this work introduces the chiral information transfer exhibited by the coiled coils onto the coordination complex. This chapter focuses on the stabilisation of a homotrimeric coiled coil peptide sequence by the introduction of an aromatic chelating unit (bipyridine/phenanthroline) to the N-terminus of the peptide sequence. It was found that the sequences resulted in the preferential formation of the Δ-[tris-bpy]-peptide and Δ-[tris-phen]-peptide complexes in response to coordination with first row transition metals, Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺. Furthermore, a cooperative relationship between the degree of coiled coil helicity and the degree of chiral bias in the resulting complex has been uncovered, with sequences with more helical character exhibiting more chiral preference as a result. Through comparison to non-helical sequences, it was shown that the chirality of the complex occurs as a result of the helicity of the peptide and not the inherent chirality of the amino acid subunits.
In Chapter 3, the structural tolerances of this cooperative relationship have been investigated. By variation of sequence length, helical content, register position and the distance of the 2,2′-bipyridine from a chiral centre on the peptide, 17 coiled coil forming peptides were synthesised and investigated. By altering these aspects of the structure, it was found that preference for the Δ- and Λ-isomers of the complex can be controlled by altering the register position of the chelating unit, with the d-position being found to favour the Δ-isomer and the e-position favouring the Λ-isomer. Furthermore, the strength of this preference can be controlled by altering the proximity of the chelate to a chiral centre. The identity of the achiral spacers, however, have been found to be an important factor, their ability to H-bond in an i-i+4 pattern being crucial for continuation of the α-helical turns.
In Chapter 4 an alternate chelating unit, 8-hydroxyquinoline, is investigated. The coordination of this ligand to transition metal ion Co²⁺, and p-block metal ions Ga³⁺ and Al³⁺ has been investigated and analysed by circular dichroism and UV-absorbance spectroscopy. The preferential formation of Δ-tris-(8HQ-peptide) and Λ-tris-(8HQ-peptide) complexes were found to be controlled by alteration of the 8-HQ register position, with 8-HQ in the dposition favouring the Λ-isomer and 8-HQ in the e-position favouring the Δ-isomer. The behaviour of these systems in response to pH was also investigated in this chapter and aims to show that the differences between the 2,2′-bipyridine and the 8-HQ chiral preferences are as a result of H-bonding interactions between the 8-HQ chelating units and the peptides.
Graphical Abstract – Cartoon representation of the transfer of chiral information in the systems investigated in this thesis. The information is transferred from the point chirality in the amino acid structures (L-AAs), to helical chirality in the secondary structure (P-Helices), to folding of the super-secondary structure into the opposite handedness helical chirality (M-Supercoiling) and finally, controlling the directionality of an 6-coordinate complex at the N-terminus of the sequence (Λ/Δ)
Performance measurement and management in Kazakhstani higher education: implications for employee wellbeing
No full textAbstract not currently available
Catch me if I fail: unpacking the anti-failure bias in entrepreneurial ecosystem research
No full textAbstract not currently available
Transducer design for ultrasensitive biomagnetic sensors
No full textAbstract not currently available
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