Conventional methods for diagnosing bridge damage have centred on tracking changes in modal-based Damage Sensitive Features (DSFs), which are strongly related to structural stiffness. Environmental and operational var...
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ISBN:
(数字)9798350374957
ISBN:
(纸本)9798350374964
Conventional methods for diagnosing bridge damage have centred on tracking changes in modal-based Damage Sensitive Features (DSFs), which are strongly related to structural stiffness. Environmental and operational variations, inefficient use of machine learning approaches for damage detection, and an overall reliance on modal-based DSFs are some of the limits and hurdles that the system still faces, despite substantial progress towards practical deployment. According to the proposed method, the initial three steps are data preparation, feature extraction, and model training. In order to identify damage during the preprocessing step, the suggested approach utilises anomaly scores. Features in the timefrequency domain allow for parallel processing of signals in the signal-to-feature extraction pipeline. After the features have been extracted, the data is used to train GBDT-BiLSTM models. The proposed approach achieves better results than the wellknown alternatives, GBDT and BiLSTM.
This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects f...
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This paper is concerned with model predictive control (MPC) of discrete-time linear systems subject to bounded additive disturbance and mixed constraints on the state and input, whereas the true disturbance set is unk...
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As a part of road networks, sidewalks are critical in urban development and people’s lives. This study introduces the Road Evaluation by Desire Path Simulation System (RED-PaSS), an agent-based modelling (ABM) framew...
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This paper attempts to take a comprehensive look at the challenges of representing the spatio-temporal structures and dynamic processes that define a city’s overall characteristics. For the task of urban planning and...
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The task of long-term action anticipation demands solutions that can effectively model temporal dynamics over extended periods while deeply understanding the inherent semantics of actions. Traditional approaches, whic...
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Understanding and measuring the resilience of food supply networks is a global imperative to tackle increasing food insecurity. However, the complexity of these networks, with their multidimensional interactions and d...
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Recent progress in the fabrication of Resistive Random Access Mem-ory (ReRAM) devices has paved the way for large scale crossbar structures. In particular, in-memory computing on ReRAM cross-bars helps in bridging the...
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Recent progress in the fabrication of Resistive Random Access Mem-ory (ReRAM) devices has paved the way for large scale crossbar structures. In particular, in-memory computing on ReRAM cross-bars helps in bridging the processor-memory speed gap for current CMOS technology. To this end, synthesis and mapping of Boolean functions to such crossbars have been investigated by researchers. However the verification of simple designs on crossbar is still done through manual inspection or sometimes complemented by sim-ulation based techniques. Clearly this is an important problem as real world designs are complex and have higher number of inputs. As a result manual inspection and simulation based methods for these designs are not practical. In this paper for the first time as per our knowledge we pro-pose an automated equivalence checking methodology for majority based in-memory designs on ReRAM crossbars. Our contributions are twofold: first, we introduce an intermediate data structure called ReRAM Sequence Graph (ReSG) to represent the logic-in-memory design. This in turn is translated into Boolean Satifiability (SAT) formulas. These SAT formulas are verified against the golden functional specification using Z3 Satifiability Modulo Theory (SMT) solver. We validate the proposed method by running widely avail-able benchmarks.
The utilization of Artificial Intelligence (AI) to improve processes constitutes a main subject for many enterprises. The area of Production Planning and Control (PPC) possesses several functions that could profit fro...
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The utilization of Artificial Intelligence (AI) to improve processes constitutes a main subject for many enterprises. The area of Production Planning and Control (PPC) possesses several functions that could profit from such approaches. However, manufacturing companies find themselves often limited in the application of these approaches. This paper concentrates on three elements to assist enterprises: 1) the clarification of what AI is (in the manufacturing context) and its application to the field of PPC; 2) a review performed together with manufacturing enterprises in Germany and Hungary in order to understand the obstacles for the implementation of AI; and 3) the proposal of a maturity model to help enterprises understand where they are in regards to AI, as a way to help them create a roadmap to achieve their objectives.
The expansion of charging infrastructure and the optimal utilization of existing infrastructure are key influencing factors for the future growth of electric mobility. The main objective of this paper is to present a ...
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