A 1.9-GHz CMOS power amplifier for polar transmitters was implemented with a 0.25-m radio frequency CMOS process. All the matching components, including the input and output transformers, were fully integrated. The concepts of mode locking and adaptive load were applied in order to increase the efficiency and dynamic range of the amplifier. The amplifier achieved a drain efficiency of 33% at a maximum output power of 28 dBm. The measured dynamic range was 34 dB for a supply voltage that ranged from 0.7 to 3.3 V. The measured improvement of the low power efficiency was 140% at an output power of 16 dBm.
SummaryObjectives: The aims of this study were to develop detailed clinical models (DCMs) for nursing problems related to perinatal care and to test the applicability of these detailed clinical models. Methods: First, we extracted entities of nursing problems by analyzing nursing-problem statements from nursing records, reviewing the literature, and interviewing nurse experts. Second, we extracted attributes and possible values needed to describe the entities in more detail by again analyzing nursing statements, reviewing the literature, and consulting nurse experts. Third, DCMs were modeled by linking each entity with possible attributes with value sets and optionalities. Fourth, entities, attributes and value sets in the DCMs were mapped to the International Classification for Nursing Practice (ICNP) version 2. Finally, DCMs were validated by consulting a group of experts and by applying them to real clinical data and nursing care scenarios published in the literature. The adequacy of the entities, attributes, value sets, and optionalities of the attributes were validated. Results: Fifty-eight entities were identified, 41 entities from nursing records, 12 entities from literature review and 5 entities from nurse experts. Sixty-five attributes with values were identified, 25 attributes from nursing records, 34 attributes from literature review, and 6 attributes from nurse experts. In total 58 DCMs were developed and validated. Conclusions: The DCMs developed in this study can ensure that electronic health records contain meaningful and valid information, and support the semantic interoperability of nursing information.
The purpose of Blind Source Separation (BSS) is to obtain separated sources from convolutive mixture inputs. Among the various available BSS methods, Independent Component Analysis (ICA) is one of the representative methods. Its key idea is to repetitively update and calculate the measures. However, dealing with the measures obtained from multi-array sensors causes obstacles for real-time use. In order to solve this problem, it is necessary to convert the software implementation of BSS algorithm into the hardware architecture. Through the use of hardware architecture, the BSS algorithm can efficiently work within a relatively short time. In this study, we investigate a practical method using a parallel algorithm and architecture for hardware use in a blind source separation. We design a feedback network for real-time speech signal processing. The network is composed of forward and updates algorithms. The architecture of the network is systolic and therefore it is suitable for parallel processing. We only have to add and connect modules for scaling. This paper covers the process from the systolic design of BSS to the hardware implementation using Xilinx FPGAs. The simulation results of our proposed implementation are also represented in the experimental section. In that section, our architecture returns satisfying results with robust qualities.
This paper proposes a parallel annealing algorithm, called step‐wise‐overlapped parallel annealing, that can provide a massive speed‐up utilizing a multiprocessor system with a large number of processors. We improve the parallel annealing scheme of the systolic algorithm that was proposed by Aart et al. Instead of the temperature decrement at each subchain, it decides the decrement ratio at the start of each Markov chain using the standard deviation of the cost distribution in the previous Markov chain of the full length. Thus the improved annealing schedule keeps a good temperature profile even with a large number of processors. We also enhance the communication pattern.
The new parallel annealing algorithm has a simple communication pattern and thus less communication overheads. The decomposition strategy of this parallel annealing algorithm is independent of application problems. Experimental results of the step‐wise‐overlapped parallel annealing algorthm for the travelling salesman problems show high efficiencies even when a large number of processors are used; it produces near optimal solutions with a speedup of 70.8 by using 128 processors. It can be implemented efficiently on a message‐passing multiprocessor system with a large number of processors, such as a hypercube computer.
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