Diabetes is a prevalent chronic health disease affecting millions of people over the world. Early detection and effective management contribute in preventing its complications. This study investigates the use of machi...
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Diabetes is a prevalent chronic health disease affecting millions of people over the world. Early detection and effective management contribute in preventing its complications. This study investigates the use of machi...
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ISBN:
(数字)9798350388282
ISBN:
(纸本)9798350388299
Diabetes is a prevalent chronic health disease affecting millions of people over the world. Early detection and effective management contribute in preventing its complications. This study investigates the use of machine learning algorithms to predict the risk of acquiring diabetes based on multiple clinical parameters (Indian PIMA Dataset). In the study, advanced data preprocessing techniques like missing data handling, outlier rejection, robust scaling and SOMTE oversampling are consolidated with eight traditional machine learning. Effectiveness of those eight models such as Gradient Boosting (GB), XGBoost (EGB), Random Forest (RF), Light GBM (LGBM), Cat Boost (CB), Ada Boost (AB), Decision Tree (DT) and K-Nearest Neighbor (KNN) are analyzed and compared. The prediction outcomes of each model are contrasted using accuracy, roc score and F1 score. After evaluating the model’s performances, GB has provided the highest accuracy of 90.25%, ROC score of 96.38% and F1 score of 86.48%.
As an essential functionality, flexible focusing of surface plasmons (SPs) is of particular interest in nonlinear optics and highly integrated plasmonic circuitry. Here, we developed a versatile plasmonic metalens, a ...
As an essential functionality, flexible focusing of surface plasmons (SPs) is of particular interest in nonlinear optics and highly integrated plasmonic circuitry. Here, we developed a versatile plasmonic metalens, a metasurface comprised of coupled subwavelength resonators, whose optical responses exhibit a remarkable feature of electromagnetically induced transparency (EIT). We demonstrate numerically and experimentally how a proper spatial design of the unit elements steers SPs to arbitrary foci based on the holographic principles. More specifically, we show how to control the interaction between the constituent EIT resonators to efficiently manipulate the focusing intensity of SPs. We also demonstrated that the proposed metalens is capable of achieving frequency division multiplexing. The power and simplicity of the proposed design would offer promising opportunities for practical plasmonic devices.
Isochronal synchronization is a unique phenomenon in which physically distant oscillators wired together relax into zero-lag synchronous behavior over time. Such behavior is observed in natural processes and, recently...
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Isochronal synchronization is a unique phenomenon in which physically distant oscillators wired together relax into zero-lag synchronous behavior over time. Such behavior is observed in natural processes and, recently...
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ISBN:
(纸本)9781467315593
Isochronal synchronization is a unique phenomenon in which physically distant oscillators wired together relax into zero-lag synchronous behavior over time. Such behavior is observed in natural processes and, recently, has been considered for promising applications in communication. Towards technological development of devices that explore isochronal sync, stability issues of the phenomenon need to be considered, both in the context of a pair or a network of coupled oscillators. This study concerns such stability issues by using the Lyapunov-Krasovskii theorem to propose a framework to study synchronization stability by using accessible parameters of the network coupling setup. As a result, relations between stability and network parameters are unveiled and the comprehension of roads leading to stability is enhanced.
In order to improve the global convergent ability of the standard particle swarm optimization (SPSO), the paper develops a new version of particle swarm optimization guided by the acceleration information (AGPSO). Fir...
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ISBN:
(纸本)1424406048
In order to improve the global convergent ability of the standard particle swarm optimization (SPSO), the paper develops a new version of particle swarm optimization guided by the acceleration information (AGPSO). Firstly, the paper introduces the concept of acceleration into the AGPSO version and makes a convergent analysis of the new model. Secondly, the paper studies the parameter choices of the AGPSO model. Thirdly, the paper provides the A GPSO with an oscillating factor to adjust the influence of the acceleration on the velocity, which can guarantee the AGPSO to converge to the global optimization validly. Finally, the proposed AGPSO versions are used to some benchmark optimizations, the experimental results show those AGPSO versions can overcome the premature problem validly, and outperforms the standard PSO in the global search ability with a quicker convergent speed
In a telecommunication management network (TMN), the interworking of manager and agent needs to exchange and process management information which is defined as the shared management knowledge (SMK) in the ITU-T Recomm...
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In a telecommunication management network (TMN), the interworking of manager and agent needs to exchange and process management information which is defined as the shared management knowledge (SMK) in the ITU-T Recommendation M.3010. The SMK includes information on the protocol knowledge, management functions, managed object classes and their instances and authorized capabilities. We examine in detail the design issues in developing an SMK system for supporting management systems. We present a design of a CORBA-based SMK system including the procedures of obtaining the SMK information from the management information base (MIB) and of the SMK context negotiations. Finally, our effort on the prototype implementation of an SMK system using ORBeline and OSIMIS is presented.
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