Search Results (53)

Chaos, characterized by a broad spectrum, aperiodic, unpredictable behavior, and sensitivity to initial conditions, has been widely studied as a potential candidate for secure data transmission. Switching voltage converters (SVCs) are well known for their ability to exhibit nonlinear and, more specifically, chaotic behavior. In contrast to conventional approaches that seek to eliminate chaotic behavior in switching voltage converters, this work proposes exploiting such behavior to generate chaotic oscillations for further use in authentication and physical-layer security systems. However, reliable data recovery in a converter-based chaotic communication system requires synchronization between the transmitter and receiver converters operating in the chaotic regime. This work demonstrates the leader–follower synchronization of chaotic buck converters via control-signal injection using both SPICE simulations and laboratory experiments, contributing to the experimental investigation of chaotic power electronics. Simulation and experimental results confirm synchronization of chaotic buck converters using the proposed method, achieving a high correlation (>0.8) between the output waveforms. Furthermore, the analysis of the effect of noise in the synchronization channel demonstrates that converters remain highly correlated for SNR values down to 20 dB, suggesting their potential applicability to chaos-based communication systems. The proposed method achieves synchronization at the expense of the follower converter’s output-voltage regulation capability and requires both converters to share a common clock source, motivating future research on integrated synchronization and control strategies. Full article

This research examines the behavioral shifts within a discrete-time predator–prey framework, constructed by applying the forward Euler discretization to a continuous model. The system incorporates Smith’s growth dynamics for the prey population alongside a Holling type III functional response to characterize predator behavior. Through bifurcation analysis, it is demonstrated that the interior fixed point undergoes stability loss via Neimark–Sacker and period-doubling transitions, leading to the emergence of quasiperiodic oscillations and chaos. Furthermore, the application of normal-form theory verifies the nondegeneracy of these bifurcations and establishes the direction of the resulting orbits. We use phase portraits, Lyapunov exponents, and bifurcation diagrams to confirm the model’s rich dynamics. These numerical tools demonstrate how the system moves from stable equilibria to more intricate behaviors. The application of partial rank correlation coefficients reveals the most influential parameters governing the system’s asymptotic population levels, providing a global perspective on parameter sensitivity. The Ott–Grebogi–Yorke (OGY) chaos control strategy is employed to suppress unwanted bifurcations and stabilize chaotic oscillations within the system. These results underscore the role of nonlinear interactions and discrete-time frameworks in precipitating unpredictable population fluctuations while simultaneously offering a suite of mechanisms for enhancing the stability of ecological networks. Full article

This study presents an adaptive sliding mode control approach for trajectory tracking of a quadrotor unmanned aerial vehicle functioning under external interference and kinematic unpredictability. Linear and rotational motion equations formulated in inactive local coordinate system frames are developed with the aid of a nonlinear six-degrees-of-freedom quadrotor dynamic model. Through mitigating excessive switching activity, reliability is improved. Here, the proposed controller integrates sliding mode control with bounded adaptive switching gain factors and boundary-layer smoothing. The operational design is applied within a sequential outer-loop/inner-loop structure for linear and orientation control. The conventional sliding mode control, alongside the proportional derivative control, which employs MATLAB/Simulink R2024a simulations while being interference-affected with an unknown performance set-up, is deployed in this work to relatively appraise the proposed ASM controller. The assessment involves three-dimensional trajectory, control input characteristics, tracking error analysis, adaptive gain growth, and chattering analysis with quantitative performance metrics. The computational output revealed that the proposed ASMC attained superior tracking performance with limited oscillation and level control action. The controller achieves a total RMSE of approximately 0.38 m and a lower aggregate tracking error when using the conventional SMC and PD controllers under equivalent conditions. Furthermore, the adaptive gain mechanism successfully lowers chattering while maintaining robustness against interferences, a large amount of ambiguity, and inertial imbalance with signal noise. The results validate that the proposed ASMC delivers a functional balance between robustness, control smoothness, and tracking accuracy alongside execution homogeneity for autonomous quadrotor UAV trajectory tracking in unsettled and unstable environments. Full article

In the context of increasingly frequent and highly unpredictable unconventional emergencies and growing supply chain uncertainty, traditional static reward-and-punishment mechanisms often fail to curb enterprises’ speculative stockpiling, leading to strategic oscillations and instability in collaborative emergency supply stockpiling systems. To address the lack of attention to dynamic governance mechanisms, this paper develops a tripartite evolutionary game model involving the government, stockpiling enterprises, and the public under the assumption of bounded rationality. The model examines how a dynamic reward-and-punishment mechanism affects the evolution of collaborative stockpiling strategies and system stability. Results show that under a static mechanism, enterprise strategies are highly sensitive to fluctuations in speculative returns and regulatory costs, making stable equilibrium difficult to achieve. In contrast, a behavioral-state-dependent dynamic mechanism adjusts reward-and-punishment intensities in response to feedback on enterprise behavior, uses changes in the proportion of enterprises choosing responsible stockpiling as the trigger for adaptive adjustment, reshapes enterprises’ payoff structures, and thereby forms an adaptive governance mechanism based on behavioral feedback. This suppresses speculative stockpiling and promotes convergence toward stability. The analysis indicates that increasing reward-and-punishment intensity does not necessarily improve governance effectiveness: excessive penalties may increase volatility, whereas an appropriate range of reward-and-punishment intensities improves system stability and governance efficiency. Public oversight functions primarily as a phased external constraint; as responsible stockpiling behavior gradually stabilizes, the system’s dependence on sustained high-intensity oversight gradually decreases. These findings provide a decision-support framework for policymakers to translate evolutionary game analysis into adaptive administrative regulation. Full article

An important module that must be present in any communication system is a random number generator (RNG). One of the RNGs is the True RNG (TRNG), which is completely random. The output of the TRNG is unpredictable as it extracts its randomness from physical phenomena such as temperature, noise, power supply fluctuations, timing jitter in oscillators, and metastability in digital circuits. It is used in many applications such as cryptography, IoT sensors, and mobile equipment. In this paper, a novel low-power TRNG architecture is proposed: its core novelty is that all the system modules are adaptive to be more efficient and cooperate with system variations. It consists of a morphing gated ring oscillator, a lightweight real-time entropy monitoring, and a dynamic sampling window. Each module is verified before system integration. Our system strikes a favorable trade-off between randomness and power consumption as all the modules are implemented using LOMOS standard cells—a power-efficient topology for CMOS logic gate design. It consumes 0.226 μW from a 0.4 V supply at 1 MHz. The proposed architecture is evaluated using the NIST SP 800-22 statistical test suite, and successfully passes 10 randomness tests. Full article

Large Unmanned Underwater Vehicles (UUVs) are playing an increasingly critical role in complex marine missions due to their enhanced payload and endurance capabilities. However, the safe recovery of these platforms remains a significant challenge, complicated by their high inertia, strong hydrodynamic interactions, and unpredictable environmental disturbances. In particular, the nonlinear coupling effects between the mechanical structure and the hydrodynamic environment exert a considerable influence on the system, accounting for nearly 50% of the tension on the arresting cable. To address these challenges, this paper proposes a variable tension control strategy for a UUV underwater arresting recovery system, utilizing a Well-Shaped Reward Entropy-regularized Proximal Policy Optimization (WSR-E-PPO) algorithm. In this framework, the real-time velocity and displacement of the UUV are utilized to represent the spatiotemporal characteristics of the recovery state, and a hybrid reward function integrating sparse and continuous rewards based on Potential-Based Reward Shaping (PBRS) is designed. Simulation results demonstrate that the proposed method enables the UUV to return to the docking point without oscillation, while effectively limiting the total recovery time to approximately 80 s—a 37.5% reduction compared with existing methods. Furthermore, the strategy ensures smoother tension regulation throughout the process. These findings provide a solid technical foundation and assurance for the stable and safe underwater recovery of large UUVs. Full article

Hydraulic oscillator tools (HOTs) are effective solutions for mitigating excessive drag encountered during sliding drilling in horizontal wells. However, their field performance remains unpredictable due to theoretical limitations in modeling nonlinear friction behavior under axial vibration. To address this gap, a series of friction tests was conducted on sandstone–steel pairs under water-based mud lubrication. Experimental results demonstrate that steady-state sliding friction follows the velocity-dependent Dieterich–Ruina model, while vibration–sliding coupled friction is accurately described by the Dahl model. Integrating these findings, a comprehensive drillstring dynamic model was developed. The model was solved using an explicit central difference method and validated against field hook load data from Well XX-1, with prediction errors below 9%. Parametric studies further quantified HOT performance, revealing that excitation force amplitude and HOT placement significantly impact drag reduction, whereas vibration frequency exerts a relatively modest influence. Meanwhile, the effective propagation distance induced by the hydraulic oscillator is relatively limited, resulting in a drag reduction rate of no more than 30% even under optimal parameter conditions. This work establishes a validated theoretical framework for optimizing hydraulic oscillator parameters in horizontal drilling. Full article

With the growing importance of personal information security, numerous methods have been proposed for data encryption. To ensure system safety, ciphers must be unpredictable and robust. In modern Rivest–Shamir–Adleman (RSA) encryption systems, two prime numbers are required for key generation, and their randomness and unpredictability are essential for security. In this study, we propose a secure system for generating the prime numbers used in RSA encryption. The inherent properties of chaotic systems are employed as a Pseudo Random Number Generator (PRNG), while a Ring Oscillator is utilized as a True Random Number Generator (TRNG). The Miller–Rabin algorithm is further applied to verify the primality of the numbers produced by the PRNG. The entire design is implemented on a Field Programmable Gate Array (FPGA) to achieve a fully hardware system. Full article

Although there is a growing body of literature on the impact of COVID-19 pandemic, limited evidence exists on the impact of the pandemic on informal female-owned enterprises, and especially those that are located in urban informal settlements. Based on a quantitative survey of 448 vendors selected through stratified random sampling, this study employed a descriptive design to examine the dynamics of women-led informal food vending enterprises across four informal settlements in Nairobi, with particular emphasis on the adverse impacts of the COVID-19 pandemic and the vendors’ coping strategies. Our findings show that women food vendors face numerous challenges which intensified during the pandemic, leading to increased business operation costs, spoilage of perishable products, and oscillating daily sales and profits due to unpredictable market forces. The vendors adopted various strategies to cushion their enterprises and households, including price and stock adjustments; the implementation of hygiene measures; increased use of mobile phones for transactions; reliance on credit, loans, savings, and social networks; temporary business closures; and the relocation of household members to rural areas. These results underscore the critical need for context-specific strategies to support and foster the resilience and sustainability of informal economies during future global pandemics. This is particularly urgent given that very few vendors received some form of institutional support, in addition to having limited access to business loans and training opportunities. Full article

The Internet of Things (IoT) has transformed global connectivity by linking people, smart devices, and data. However, as the number of connected devices continues to grow, ensuring secure data transmission and communication has become increasingly challenging. IoT security threats arise at the device level due to limited computing resources, mobility, and the large diversity of devices, as well as at the network level, where the use of varied protocols by different vendors introduces further vulnerabilities. Physical Unclonable Functions (PUFs) provide a lightweight, hardware-based security primitive that exploits inherent device-specific variations to ensure uniqueness, unpredictability, and enhanced protection of data and user privacy. Additionally, modeling attacks against PUF architectures is challenging due to the random and unpredictable physical variations inherent in their design, making it nearly impossible for attackers to accurately replicate their unique responses. This study collected approximately 80,000 Challenge Response Pairs (CRPs) from a Ring Oscillator (RO) PUF design to evaluate its resilience against modeling attacks. The predictive performance of five machine learning algorithms, i.e., Support Vector Machines, Logistic Regression, Artificial Neural Networks with a Multilayer Perceptron, K-Nearest Neighbors, and Gradient Boosting, was analyzed, and the results showed an average accuracy of approximately 60%, demonstrating the strong resistance of the RO PUF to these attacks. The NIST statistical test suite was applied to the CRP data of the RO PUF to evaluate its randomness quality. The p-values from the 15 statistical tests confirm that the CRP data exhibit true randomness, with most values exceeding the 0.01 threshold and supporting the null hypothesis of randomness. Full article

The increase in the number of Unmanned Aerial Vehicles (UAVs) for liquid transport tasks, such as agricultural spraying, results in significant stability challenges. The free movement of the liquid, known as sloshing, generates unpredictable forces that destabilize the vehicle and increase collision risks. This study treats this problem by developing and validating a nonlinear control strategy to ensure precise trajectory tracking while actively suppressing liquid sloshing. The coupled dynamics of the system are modeled using the Euler–Lagrange formalism by representing the UAV as a planar vertical take-off and landing (PVTOL) aircraft and the liquid sloshing dynamics as an equivalent pendulum model. The stability of the entire closed-loop system is proven using Lyapunov’s direct method. The analytical results are validated through numerical simulations in MATLAB/Simulink, which demonstrate excellent tracking of desired altitude and horizontal trajectories. Crucially, the simulations confirm that the controller effectively attenuates the sloshing oscillations, offering a robust solution to enhance the safety and operational performance of UAVs in liquid transport applications. Full article

The rapid growth of Internet of Things (IoT) devices and the emergence of 5G/6G networks have created major challenges in secure and reliable data transmission. Traditional cryptographic algorithms, while robust, often suffer from high computational complexity and latency, making them less suitable for large-scale, real-time applications. This paper proposes a chaos-based encryption framework that uses the Sprott chaotic oscillator to generate secure and unpredictable signals for encryption. To achieve accurate synchronization between the transmitter and the receiver, two bio-inspired metaheuristic algorithms—the Pachycondyla Apicalis Algorithm (API) and the Penguin Search Optimization Algorithm (PeSOA)—are employed to identify the optimal control parameters of the Sprott system. This optimization improves synchronization accuracy and reduces computational overhead. Simulation results show that PeSOA-based synchronization outperforms API in convergence speed and Root Mean Square Error (RMSE). The proposed framework provides robust, scalable, and low-latency encryption for IoT and 5G/6G networks, where massive connectivity and real-time data protection are essential. Full article

This work investigates resilient control for uncertain nonlinear systems subject to unknown and unpredictable sensor delays. Conventional observer-based delay-compensation methods typically require known delay bounds or measurable timing information, which limits their applicability to strongly nonlinear dynamics. To address this issue, a resilient adaptive fuzzy observer-based sliding control (AFOSMC) framework is developed. A generalized nonlinear plant model is considered, and an adaptive fuzzy observer is constructed to estimate unmeasured states while explicitly decomposing the delayed measurement residual into estimation and delay components. A sliding-mode controller integrated with fuzzy approximation ensures robust tracking in the presence of modeling uncertainties and delay-induced distortions. A delay-dependent Lyapunov function with an integral term is derived, yielding explicit conditions that guarantee uniform ultimate boundedness (UUB) of all closed-loop signals. The proposed approach provides a unified and delay-resilient solution for nonlinear observer–controller co-design under unpredictable sensing delays. Simulations on a Duffing oscillator with a $0.15$ s sensing delay show that the proposed AFOSMC model achieves a total tracking RMSE of $3.6\times {10}^{-2}$, whereas a baseline sliding-mode controller without delay compensation becomes unstable after delay activation. Full article

Conservation Tillage Technology (CTT) is vital for mitigating soil degradation, yet its adoption rates remain far below targets. This study develops an evolutionary game model that integrates heterogeneous time preferences and the lemon market effect to explore the dynamic adoption mechanisms among boundedly rational farmers. Results show that farmers with high discount rates (indicating strong time preference) undervalue long-term benefits, creating a significant barrier to CTT adoption. The lemon market effect, where P represents the benefit from information asymmetry for non-adopters and Q is the corresponding loss for adopters, critically shapes the system equilibria: (1) when $P>Q$, a stable coexistence of adoption strategies emerges; (2) when $P<Q$, the system exhibits unpredictable heteroclinic cycles; (3) when $P=Q$, it forms a conservative Hamiltonian system characterized by stable periodic oscillations. These findings provide a dynamic analytical framework for understanding green technology diffusion and offer a theoretical basis for crafting sustainable agricultural policies in developing countries. Full article

The need for unpredictable sequences of bits is common in many important security applications. These sequences can only be generated by true random number generators (TRNGs). Apart from the natural analog domain for TRNGs, this type of generator is also required as a digital-based solution, particularly leveraging field-programmable gate array (FPGA) platforms. Despite the number of existing FPGA-based implementations, new solutions that use different types of entropy sources, utilize fewer FPGA resources, or ensure higher throughput are still being sought. This paper presents an architecture of a simple TRNG targeted for implementation in FPGAs. As a source of entropy, the TRNG exploits jitter in capacitive oscillators and metastability in flip-flops. The capacitive oscillators, in turn, use the input–output cells of an FPGA chip and unconnected external pins and cyclically charge and discharge the parasitic capacitance associated with these pins. The TRNG needs a small number of FPGA resources, namely 13 look-up tables (LUTs), 12 flip-flops, and 3 unused pins. Its throughput is approximately 12.5 Mbit/s for AMD/Xilinx Artix-7 FPGA family chips. The presented TRNG passes all the NIST statistical tests for a wide range of operating conditions. Full article