Chip-integrated optical frequency combs are attractive optical sources in comb applications requiring high-repetition-rate, low power consumption, or compact size. Spontaneous soliton formation via Kerr parametric osc...
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This paper presents a novel approach for head tracking in augmented reality (AR) flight simulators using an adaptive fusion of Kalman and particle filters. This fusion dynamically balances the strengths of both algori...
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Wireless train communication network (WLTCN) is a promising technology for intelligent rail vehicles. It is responsible for bearer of train control services (TCS) and passenger information services (PIS), with the lat...
Wireless train communication network (WLTCN) is a promising technology for intelligent rail vehicles. It is responsible for bearer of train control services (TCS) and passenger information services (PIS), with the latter mainly referring to multimedia services. The two services have notably different quality of service (QoS) requirements from traditional telecommunication services. To realize multiple services co-existence bearer with different quality of service (QoS) requirements in a single network, we propose a radio access network (RAN) slicing framework to fully utilize the bandwidth resource within a WLTCN in this paper. Based on the characteristics of TCS and PIS, the communications models for the two services are proposed. Next, the slicing strategy problem is formulated as the system bandwidth minimization problem, and then it is transformed into an equivalent problem as the non-convexity. We proposed a dual-decomposition based bandwidth allocation (DBA) algorithm to derive the closed-form expressions for the optimal resource allocation. Simulation results show that the proposed slicing strategy enables WLTCN to meet the QoS requirements for TCS and PIS with minimal bandwidth consumption.
Most modern high-data-rate optical communication systems require at each end a light source to transmit the data and a detector to receive the data. In order to realize a communication scheme where the transmitter uni...
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Most modern high-data-rate optical communication systems require at each end a light source to transmit the data and a detector to receive the data. In order to realize a communication scheme where the transmitter unites with the receiver, we take advantage of a coupled injection-locked semiconduct. From the theoretical description of two mutually coupled diode lasers using a set of six nonlinear differential-delay equations we outline the stable compound cavity solutions of this system and investigate their dependencies in terms of locking bandwidth, coupling strength and coupling phase. From these modeling results we then design a remarkably simple communication system without any additional detectors that exploits compound laser states of different frequency detunings of the coupled laser system as information carriers with simultaneous upstream information of the first laser and downstream information of the second laser. The data recognition is accomplished by evaluating the compound state utilizing the change in the terminal voltage of both lasers (laser-as-detector principle) with respect to their solitary case (i.e., the terminal voltage of the uncoupled lasers), yielding the message via the agreed decoding scheme. The functionality of the principle had been demonstrated by a table-top experiment with good error-free transmission and potential to improve the transmission speed of this proof-of-principle demonstration. Our concept reduces the complexity compared to conventional transmission systems, thus providing the potential to significantly reduce the costs of the overall transmission setup an,d in particular, transferring the concept to other challenging wavelengths and other semiconductor lasers. Since the optical signal then no longer needs to be detected by an optical detection unit, the amount of optical components required for ordinary data transmission is reduced.
Manufacturer-independent medical device interoperability has been strongly demanded by the clinicians and healthcare delivery organizations (HDOs), however has not been achieved in practice for decades. The ISO/IEEE 1...
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Every society has its own characteristics, shaped from time to time by the various innovative, disruptive, but in any case, dynamically changing mechanisms that affect it most. In today's society, technological in...
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ISBN:
(数字)9798350329520
ISBN:
(纸本)9798350329537
Every society has its own characteristics, shaped from time to time by the various innovative, disruptive, but in any case, dynamically changing mechanisms that affect it most. In today's society, technological innovation plays a major role in the development of individuals and their abilities. Education is the most typical and obvious arena for shaping, developing, and preparing for the challenges of the future. As in the leading sectors, in the world of education, rapid responses and immediate reactions to change significantly increase the ability to achieve and maintain success and thus marketability. As a sector responsible for developing the competences of individuals, building knowledge and training professionals, education should seek to keep pace with trends and break with traditional approaches and methods, so that, in addition to incorporating technological developments, a renewed approach to organizational development and methodology is an important means of achieving the desired success and effectiveness. In the course of our work, we provide a summary insight into the project work of student groups who require up-to-date IT skills, use advanced IT tools, plan, and implement their web development workflows supported by database management, front-end planning and design, and back-end programming with a project management approach according to the latest trends, interpreting the advantages and disadvantages of working methods for success.
Image restoration with regularization models is very popular in the image processing literature. Total variation (TV) is one of the important edge preserving regularization models used, however, to obtain optimal rest...
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We fabricated a sophisticated Si photonic integrated circuit for investigating topological photonics SSH model. In the selective excitation and observation of SSH coupled microrings, we observed the wavefunctions of e...
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We fabricated a sophisticated Si photonic integrated circuit for investigating topological photonics SSH model. In the selective excitation and observation of SSH coupled microrings, we observed the wavefunctions of e...
The solubility of CO2 in polyethylene glycol (PEG) polymer is a critical parameter for optimizing its use in various industrial processes, underscoring the need for precise predictive models. In this research, a Rando...
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The solubility of CO2 in polyethylene glycol (PEG) polymer is a critical parameter for optimizing its use in various industrial processes, underscoring the need for precise predictive models. In this research, a Random Forest (RF) machine learning model is meticulously tuned through four sophisticated optimization algorithms: Batch Bayesian Optimization (BBO), Self-Adaptive Differential Evolution (SADE), Bayesian Probability Improvement (BPI), and Gaussian Processes Optimization (GPO). The model leverages a dataset of 164 experimental samples, incorporating essential input parameters such as pressure, PEG molar mass, and temperature to predict CO2 solubility. To prevent overfitting, K-fold cross-validation is applied throughout model training. The efficacy of each optimization method is evaluated using computational runtime and performance metrics, including R-squared (R2), mean squared error (MSE), and average absolute relative error (AARE%). Correlation analysis indicates that pressure has a moderate positive relationship with CO2 solubility (correlation coefficient: 0.58), while PEG molar mass and temperature exhibit weaker associations (0.2 and 0.05, respectively). Among the optimization techniques, RF-BPI proves to be the most effective, delivering superior predictive performance. The results show RF-BPI achieves an R2 of 0.9625 for the training set and 0.9307 for the test set, surpassing other methods. For benchmarking, a conventional multiple linear regression (LR) model was tested, demonstrating significantly lower accuracy (R2 notably inferior to RF-BPI’s 0.9307 on the test set). In terms of computational efficiency, BPI records the shortest runtime (63.9 seconds), while SADE is the least efficient, requiring 2370.2 seconds. Sensitivity analysis further clarifies the relative impact of each input variable on CO2 solubility, affirming the power of data-driven approaches in modeling complex systems. The created models can be seen as promising predictive tools
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