Born This Way: A Self-Organizing Evolution Scheme With Motif for Internet of Things Robustness

Qiu, Tie; Zhang, Lidi; Chen, Ning; Zhang, Songwei; Liu, Wenyuan; Wu, Dapeng

doi:10.1109/tnet.2022.3178408

Cited by 15 publications

(4 citation statements)

References 36 publications

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“…Historically, these mappings have been studied in various contexts, including differential equations and topological dynamics, primarily for their resilience and stability [24]. In essence, a system described as structurally stable is one whose behavior remains qualitatively unchanged against small perturbations [25]. This quality is particularly salient in space environments, characterized by their unpredictability and potential for unforeseen disturbances.…”

Section: Related Workmentioning

confidence: 99%

Self-Organizing Control Systems for Nonlinear Spacecraft in the Class of Structurally Stable Mappings

Abdiramanov,

Taiman,

Beisenbi

et al. 2023

IJACSA

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In recent developments within the domain of aerospace engineering, there is a burgeoning interest in the autonomous control of nonlinear spacecraft using advanced methodologies. The present research delves deep into the realm of self-organizing control systems tailored for such nonlinear spacecraft, emphasizing its application within the framework of structurally stable mappings. By harnessing the inherent characteristics of structurally stable mappingsoften renowned for their resilience to minor perturbations and local modificationsthis research endeavors to design a control mechanism that mitigates the challenges presented by the intrinsic nonlinearity of spacecraft dynamics. Initial findings suggest a commendable enhancement in spacecraft maneuverability and robustness against unforeseen disturbances. Furthermore, the employment of self-organization principles leads to an adaptive and resilient system that can reconfigure its control strategies in real-time, basing decisions on immediate environmental feedback. This adaptability, in essence, mimics biological systems that evolve and adapt in the face of challenges. Such a breakthrough in nonlinear spacecraft control not only widens the horizons for space exploration by making missions safer and more efficient but also contributes foundational knowledge to the broader field of nonlinear dynamic system controls. Researchers and practitioners are encouraged to explore this synergistic combination of self-organization and structurally stable mappings to further harness its potential in diverse arenas beyond aerospace.

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Section: Related Workmentioning

confidence: 99%

Self-Organizing Control Systems for Nonlinear Spacecraft in the Class of Structurally Stable Mappings

Abdiramanov,

Taiman,

Beisenbi

et al. 2023

IJACSA

View full text Add to dashboard Cite

show abstract

“…With the introduction and development of the IoT, large-scale applications and interconnections between devices form the IoT sensing network. It can provide a robust operating environment for localization systems [25,26]. With the surging of smartphone sensing and wireless networking techniques, crowdsensing has become a promising paradigm for cross-space and large-scale sensing [27][28][29][30][31][32][33].…”

Section: Related Workmentioning

confidence: 99%

A Practice-Distributed Thunder-Localization System with Crowd-Sourced Smart IoT Devices

Wang

Qin

et al. 2023

Sensors

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Lightning localization is of great significance to weather forecasting, forest fire prevention, aviation, military, and other aspects. Traditional lightning localization requires the deployment of base stations and expensive measurement equipment. With the development of IoT technology and the continuous expansion of application scenarios, IoT devices can be interconnected through sensors and other technical means to ultimately achieve the goal of automatic intelligent computing. Therefore, this paper proposes a low-cost distributed thunder-localization system based on IoT smart devices, namely ThunderLoc. The main idea of ThunderLoc is to collect dual-microphone data from IoT smart devices, such as smartphones or smart speakers, through crowdsourcing, turning the localization problem into a search problem in Hamming space. We studied the dual microphones integrated with smartphones and used the sign of Time Difference Of Arrival (TDOA) as measurement information. Through a simple generalized cross-correlation method, the TDOA of thunderclaps on the same smartphone can be estimated. After quantifying the TDOA measurement from the smartphone node, thunder localization was performed by minimizing the Hamming distance between the binary sequence and the binary vector measured in a database. The ThunderLoc system was evaluated through extensive simulations and experiments (a testbed with 30 smartphone nodes). The extensive experimental results demonstrate that ThunderLoc outperforms the main existing schemes in terms of effectively locating position and good robustness.

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“…With the construction of the national digital detection network, the observation methods and technologies of the new Internet of things are gradually applied [1][2][3][4], which basically realizes the digitization, networking and integration of seismic monitoring and exploration, and the ability of seismic monitoring and exploration has been greatly improved. The application of digital technology provides rich first-hand data for seismic scientific research and lays a good foundation for explanations and predictions of seismic exploration.…”

Section: Introductionmentioning

confidence: 99%

SeisDeNet: an intelligent seismic data Denoising network for the internet of things

et al. 2023

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Deep learning (DL) has attracted tremendous interest in various fields in last few years. Convolutional neural networks (CNNs) based DL architectures have been successfully applied in computer vision, medical image processing, remote sensing, and many other fields. A recent work has proved that CNNs based models can also be used to handle geophysical problems. Due to noises in seismic signals acquired by geophone equipment this kind of important multimedia resources cannot be effectively utilized in practice. To this end, from the perspective of seismic exploration informatization, this paper takes informatization data in seismic signal acquisition and energy exploration field using cutting-edge technologies such as Internet of things and cloud computing as the research object, presenting a novel CNNs based seismic data denoising (SeisDeNet) architecture is suggested. Firstly, a multi-scale residual dense (MSRD) block is built to leverage the characteristics of seismic data. Then, a deep MSRD network (MSRDN) is proposed to restore the noisy seismic data in a coarse-to-fine manner by using cascading MSRDs. Additionally, the denoising problem is formulated into predicting transform-domain coefficients, by which noises can be further removed by MSRDNs while richer structure details are preserved comparing with the results in spatial domain. By using synthetic seismic records, public SEG and EAGE salt and overthrust seismic model and real field seismic data, the proposed method is qualitatively and quantitatively compared with other leading edge schemes to evaluate it performance, and some results shows that the proposed scheme can produce data with higher quality evaluation while maintaining far more useful data comparing with other schemes. The feasibility of this approach is confirmed by the denoising results, and this approach is shown to be promising in suppressing the seismic noise automatically.

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Born This Way: A Self-Organizing Evolution Scheme With Motif for Internet of Things Robustness

Cited by 15 publications

References 36 publications

Self-Organizing Control Systems for Nonlinear Spacecraft in the Class of Structurally Stable Mappings

Self-Organizing Control Systems for Nonlinear Spacecraft in the Class of Structurally Stable Mappings

A Practice-Distributed Thunder-Localization System with Crowd-Sourced Smart IoT Devices

SeisDeNet: an intelligent seismic data Denoising network for the internet of things

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