The increasingly massive use of e-Learning illustrates the speed and need for innovation in learning. According to the National Higher Education Standards (SN-Dikti), constructive alignment is required between learnin...
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A future networking design called "software-defined networking"combines network programmability with centralized administration (SDN). Network administration is currently handled by SDN, which, at the regula...
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Quasi-isotropic antennas have gained attention due to the emergence of the Internet of Things (IoT) and Wireless Sensing Networks (WSNs), for their orientation-insensitive communication ability. For those applications...
Quasi-isotropic antennas have gained attention due to the emergence of the Internet of Things (IoT) and Wireless Sensing Networks (WSNs), for their orientation-insensitive communication ability. For those applications, electrically small (ES) antennas are usually preferred, which can save space for the IoT or sensing nodes, while reducing the material cost. Several compact isotropic antennas have been reported recently. However, only very few of them have shown dual-band operation ability. A novel design method to design a dual-band quasi-isotropic ES antenna is presented in this conference proceeding. The utilization of a band stop filter (BSF) enables the conventional single-band quasi-isotropic split ring resonator (SRR) antenna to behave in a dual-band operation, while maintaining the quasi-isotropic radiation for both bands. The proposed antenna is designed, fabricated, and measured, which shows a dual-band operation (both bands in ka<1 region) while maintaining decent performance.
In this work, we present a novel algorithm design methodology that finds the optimal algorithm as a function of inequalities. Specifically, we restrict convergence analyses of algorithms to use a prespecified subset o...
In this work, we present a novel algorithm design methodology that finds the optimal algorithm as a function of inequalities. Specifically, we restrict convergence analyses of algorithms to use a prespecified subset of inequalities, rather than utilizing all true inequalities, and find the optimal algorithm subject to this restriction. This methodology allows us to design algorithms with certain desired characteristics. As concrete demonstrations of this methodology, we find new state-of-the-art accelerated first-order gradient methods using randomized coordinate updates and backtracking line searches.
As data shift or new data become available, updating clinical machine learning models may be necessary to maintain or improve performance over time. However, updating a model can introduce compatibility issues when th...
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Every patient has health record, it was written as statement of patient's conditions, treatments, and medications, and nowadays it is become digitalized, it can be copied and shared easily, but the nature of EHR i...
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A substantial number of people are presently making use of decentralised cryptocurrencies that are built on blockchain technology. These crypto currencies have garnered a lot of interest over the course of the last fe...
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This paper proposes a low-cost interface and refined digital twin for the Raven-II surgical robot. Previous simulations of the Raven-II, e.g. via the Asynchronous Multibody Framework (AMBF), presented salient drawback...
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ISBN:
(数字)9798350377118
ISBN:
(纸本)9798350377125
This paper proposes a low-cost interface and refined digital twin for the Raven-II surgical robot. Previous simulations of the Raven-II, e.g. via the Asynchronous Multibody Framework (AMBF), presented salient drawbacks, including control inputs inconsistent with Raven-II software, and lack of stable, high-fidelity physical contact simulations. This work bridges both of these gaps, both (1) enabling robust, simulated contact mechanics for dynamic physical interactions with the Raven-II, and (2) developing a universal input format for both simulated and physical platforms. The method furthermore proposes a low cost, commodity game-controller interface for controlling both virtual and real realizations of Raven-II, thus greatly reducing the barrier to access for Raven-II research and collaboration. Overall, this work aims to eliminate the inconsistencies between simulated and real representations of the Raven-II. Such a development can expand the reach of surgical robotics research. Namely, providing end-to-end transparency between the simulated AMBF and physical Raven-II platforms enables a software testbed previously unavailable, e.g. for training real surgeons, for creating digital synthetic datasets, or for prototyping novel architectures like shared control strategies. Experiments validate this transparency by comparing joint trajectories between digital twin and physical testbed given identical inputs. This work may be extended and incorporated into recent efforts in developing modular or common software infrastructures for both simulation and control of real robotic devices, such as the Collaborative Robotics Toolkit (CRTK).
Background: The study aimed to develop and validate a deep learning-based computer Aided Triage (CADt) algorithm for detecting pleural effusion in chest radiographs using an active learning (AL) framework. This is aim...
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Hypertension is a noncommunicable disease (NCD) that causes global concern, high costs and a high number of deaths. Internet of Things, Ubiquitous Computing, and Cloud Computing enable the development of systems for r...
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