With the popularity of Social Network Service (SNS) and the increasing of users, individuals' social roles in a social network have become more and more important in recommendation of the personalized services, an...
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ISBN:
(纸本)9781479962402
With the popularity of Social Network Service (SNS) and the increasing of users, individuals' social roles in a social network have become more and more important in recommendation of the personalized services, and in a collective decision-making process as well. In an SNS system, active users may not represent the major opinions among the whole users, and most of the users' opinions may be multifarious. In this study, we consider users' social roles as an important element to support the collective decision-making process. After introducing the social choice theories and collective decision-making model, we present a three-layer model to analyze users' social roles in a hierarchical way, and utilize it to support the collective decision-making process. A case study for COD (Course-Offering Determination) with an application scenario is demonstrated to show the process of how users' social roles are utilized to support the collective decision-making.
A novel Virus-like-particle (VLP) bioreceptor layer has been integrated with an optical microdisk resonator platform for biosensing applications. This bioreceptor layer can be genetically programmed for selective bind...
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This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremen...
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In the majority of cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities in the Pap test. Nowadays, there are ancillary molecular biology techniques providing important information related...
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In the majority of cases, cervical cancer (CxCa) develops as a result of underestimated abnormalities in the Pap test. Nowadays, there are ancillary molecular biology techniques providing important information related to CxCa and the Human Papillomavirus (HPV) natural history, including HPV DNA test, HPV mRNA tests and immunocytochemistry tests. However, these techniques have their own performance, advantages and limitations, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this paper we present a risk assessment model based on a Bayesian Network which, by combining the results of Pap test and ancillary tests, may identify women at true risk of developing cervical cancer and support the management of patients with ASCUS or LSIL cytology. The model, following the paradigm of other implemented systems, can be integrated into existing platforms and be available on mobile terminals for anytime/anyplace medical consultation.
This paper considers the problem of positive stabilization of uncertain linear time-delay systems by state feedback such that the resulting closed-loop system attains maximum stability radius with positivity constrain...
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ISBN:
(纸本)9781467360890
This paper considers the problem of positive stabilization of uncertain linear time-delay systems by state feedback such that the resulting closed-loop system attains maximum stability radius with positivity constraint. First, we focus on the class of linear continuous-time positive delay systems (Metzlerian delay systems) and outline its interesting properties. Using the stability properties associated with this class, we formulate a constrained stabilization problem for the linear time delay system and provide conditions for the existence of controllers satisfying the stability and Metzlerian constraints. The Metzlerian stabilization is solved using Linear Matrix Inequality (LMI) or Linear Programming (LP). Next, we characterize the uncertainties associated with the positive delay systems and define the stability radius associated with this class which can be expressed in a closed form. Finally, we combine Metzlerian stabilization with maximum stability radius with the aid of bounded real lemma (BRL) and provide a complete solution using LMI. Examples are included for the purpose of illustration.
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring sensor saturations is investigated. A practical phenomeno...
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In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring sensor saturations is investigated. A practical phenomenon of nonsynchronous jumps between RNNs modes and desired mode-dependent filters is considered and a nonstationary mode transition among the filters is used to model the non-synchronous jumps to different degrees that are also mode-dependent. The sensor saturation occurs in a probabilistic way according to a Bernoulli sequence. Sufficient conditions on the existence of the nonsynchronous filters are obtained such that the filtering error system is stochastically stable and achieves a prescribed energy-to-peak performance index. A numerical example is presented to verify the theoretical findings.
The auto-correlation based coarse symbol timing scheme yields good correlation timing-metric for wireless orthogonal frequency division multiplexing (OFDM) systems under independent Rayleigh fading channels. However, ...
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The auto-correlation based coarse symbol timing scheme yields good correlation timing-metric for wireless orthogonal frequency division multiplexing (OFDM) systems under independent Rayleigh fading channels. However, it generates a plateau in its timing-metric due to the structure of the preamble added with cyclic prefix (CP). Inherently, the mean square error (MSE) performance of a coarse symbol timing scheme is closely related to the sharpness of its main-lobe timing-metric. Some of the literatures focus on polishing the auto-correlation timing-metrics to find the frame start point. One of the well-known methods uses arithmetic mean of the auto-correlation timing-metrics to generate a peak after post-processing. We propose a post-processing scheme using weighted arithmetic mean of the auto-correlation timing-metrics, and provide a different viewpoint of analyzing the performance of post-processing schemes in additive white Gaussian noise (AWGN) channels, which may be helpful in timing-metric design. By using the knowledge of root mean square (rms) delay spread, we get a general coarse symbol timing scheme for both AWGN and Rayleigh fading channels. The obtained simulation results indicate that the MSE performance of the post-processing scheme is a function of the main-lobe sharpness.
High-Level Synthesis (HLS) has been a hot research topic for more than 30 years. During this long period, HLS has found many enthusiasts and also critics as well. Both of them have presented a lot of arguments for and...
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High-Level Synthesis (HLS) has been a hot research topic for more than 30 years. During this long period, HLS has found many enthusiasts and also critics as well. Both of them have presented a lot of arguments for and against, which have helped HLS mature a lot. Modern HLS environments are not restricted to heuristic optimizations of abstract functional blocks (adders and multipliers) as early approaches where, but are supported by rich, technology characterized component libraries, are integrated with other tool flows for simulation, synthesis, verification and prototyping, and their output can be efficiently installed in advanced multicore System-on-Chip (SoC) architectures. As a consequence, the optimization objectives are no longer only the number of abstract components, but technology dependent real implementation measurements, taken in a fast and accurate manner. In this paper, a modern HLS environment is used to investigate different architecture alternatives for the design of Digital Signal Processing (DSP) hardware accelerators, taking into account both memory and datapath component utilization, as well as SoC connectivity opportunities. The whole investigation is performed at the algorithmic level, using algorithmic constructs and directives to describe different architectural options in an abstract yet precise and high productive way. Experimental results show that correct architectural option selections can lead to more than 100X speedup, with little (practical negligible) resource utilization overhead.
We report the fabrication and characterization of a vertical pn power diode which is realized using two separate epitaxial-growth mechanisms: (a) p-GaN over p-(4H)SiC, and (b) p-GaN over n-(4H)SiC with A1N as...
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We report the fabrication and characterization of a vertical pn power diode which is realized using two separate epitaxial-growth mechanisms: (a) p-GaN over p-(4H)SiC, and (b) p-GaN over n-(4H)SiC with A1N as the interface layer. In all of the cases, n+-doped (4H)SiC serves as the cathode substrate. Pd(200 A)/Au(10000 A) is used for the anode contact while Ni(1000A) is used for the bottom cathode contact. The measured forward drop of the pn diode with A1N as the interface material is found to be around 5.1 V; whereas, it is 3 V for the other sample structure. The measured reverse-blocking voltage is found to be greater than 200 V.
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