A Fully Integrated 0.13- μm CMOS Digital Low-IF DBS Satellite Tuner Using a Ring Oscillator-Based Frequency Synthesizer

A low-IF fully integrated tuner for DBS satellite TV applications has been realized in 0.13-mum CMOS. A wideband ring oscillator-based frequency synthesizer having a large frequency step was used to downconvert a cluster of channels to a sliding low-IF frequency, while the second downconversion to baseband was performed in the digital domain. Eliminating the inductors and using a small-area oscillator has reduced both the parasitic magnetic and substrate coupling, allowing single-chip integration of the sensitive tuner and the noisy digital demodulator. A significant reduction in die area was achieved by using a single oscillator to cover the entire satellite TV spectrum, while a noise attenuator was cascaded with the PLL passive loop filter to reduce the equivalent VCO tuning gain. This improves PLL noise and spur performance and allows the on-chip integration of the loop filter. The digital low-IF tuner allows the use of a discrete step AGC loop that results in lower noise figure and higher linearity. Automatic signal path gain and bandwidth digital calibration was realized using replica ring oscillators. Tuner specifications include: 90 dB gain range, 10 dB noise figure at max gain, +25dBm IIP3 at min gain, 1.3deg rms integrated phase noise, <-50dBc spurs, 0.5-W power consumption from dual 1.8/3.3-V supplies, and 1.8times1.2 mm² die area     

Adaptive exception monitoring agents for management by exceptions

Management by exceptions (MBE) is an effective management strategy in many domains. It suggests that managers focus on important jobs (e.g., planning and decision-making) without being involved in the tedious monitoring of exceptions (e.g., a critical item whose current status violates some regulations). Once an exception is detected, the managers are notified to respond to the exception promptly. Therefore, exception monitoring is the key to realize the idea of MBE. An exception monitoring system should detect exceptions in a timely manner for the managers. It should also control the extra loading it incurs to related information servers (e.g., database management systems) and the Intranet, which are fundamental backbones for information processing in businesses. In this paper, a multiagent paradigm Adaptive Agents for Management by Exceptions (AAMBE) is proposed for exception monitoring. The agents adapt to the environment by learning to work together to achieve timely detection of exceptions. An experiment to investigate the performance of AAMBE is conducted by simulating real-world operations of financial management in merchandising trades. Empirical and theoretical analyses show that AAMBE may detect more exceptions in a timelier manner by incurring less extra loading to the related information servers and the Intranet.     

Reversible privacy preserving data mining: a combination of difference expansion and privacy preserving

Privacy Preserving Data Mining (PPDM) can prevent private data from disclosure in data mining. However, the current PPDM methods damaged the values of original data where knowledge from the mined data cannot be verified from the original data. In this paper, we combine the concept and technique based on the reversible data hiding to propose the reversible privacy preserving data mining scheme in order to solve the irrecoverable problem of PPDM. In the proposed privacy difference expansion (PDE) method, the original data is perturbed and embedded with a fragile watermark to accomplish privacy preserving and data integrity of mined data and to also recover the original data. Experimental tests are performed on classification accuracy, probabilistic information loss, and privacy disclosure risk used to evaluate the efficiency of PDE for privacy preserving and knowledge verification.     

Exponential stability of impulsive stochastic fuzzy cellular neural networks with mixed delays and reaction–diffusion terms

The problem of mean square exponential stability for a class of impulsive stochastic fuzzy cellular neural networks with distributed delays and reaction–diffusion terms is investigated in this paper. By using the properties of M-cone, eigenspace of the spectral radius of nonnegative matrices, Lyapunov functional, Itô’s formula and inequality techniques, several new sufficient conditions guaranteeing the mean square exponential stability of its equilibrium solution are obtained. The derived results are less conservative than the results recently presented in Wang and Xu (Chaos Solitons Fractals 42:2713–2721, 2009), Zhang and Li (Stability analysis of impulsive stochastic fuzzy cellular neural networks with time varying delays and reaction–diffusion terms. World Academy of Science, Engineering and Technology 2010), Huang (Chaos Solitons Fractals 31:658–664, 2007), and Wang (Chaos Solitons Fractals 38:878–885, 2008). In fact, the systems discussed in Wang and Xu (Chaos Solitons Fractals 42:2713–2721, 2009), Zhang and Li (Stability analysis of impulsive stochastic fuzzy cellular neural networks with time varying delays and reaction–diffusion terms. World Academy of Science, Engineering and Technology 2010), Huang (Chaos Solitons Fractals 31:658–664, 2007), and Wang (Chaos Solitons Fractals 38:878–885, 2008) are special cases of ours. Two examples are presented to illustrate the effectiveness and efficiency of the results.     

A multi-stage learning framework for intelligent system

As information technologies advance and user-friendly interfaces develop, the interaction between humans and computers, information devices, and new consumer electronics is increasingly gaining attention. One example that most people can relate to is Apple’s innovation in human–computer interaction which has been used on many products such as iPod and iPhone. Siri, the intelligent personal assistant, is a typical application of machine-learning human–computer interaction.Algorithms in machine learning have been employed in many disciplines, including gesture recognition, speaker recognition, and product recommendation systems. While the existing learning algorithms compute and learn from a large quantity of data, this study proposes an improved learning to rank algorithm named MultiStageBoost. In addition to ranking data through multiple stages, the MultiStageBoost algorithm significantly improves the existing algorithms in two ways. Firstly, it classifies and filters data to small quantities and applies the Boosting algorithm to achieve faster ranking performance. Secondly, it enhances the original binary classification by using the reciprocal of fuzzily weighted membership as the ranking distance.The importance of data is revealed in their ranked positions. Usually data ranked in the front are given more attention than those ranked in the middle. For example, after ranking 10,000 pieces of data, the top 10, or at most 100, are the most important and relevant. Whether the data after the top ones are ranked precisely does not really matter. Due to this reason, this study has made improvement on the conventional methods of the pair-wise ranking approach. Not only are data classified and ranked binarily, they are also given different weights depending on whether they are concordant or discordant. Incorporating the concept of weighting into the ranking distance allows us to increase the precision of ranking. Results from experiments demonstrate that our proposed algorithm outperforms the conventional methods in three evaluation measures: P@n, MAP, and NDCG. MultiStageBoost was then applied to speech recognition. However, we do not aim to improve the technology of speech recognition, but simply hope to provide evidences that MultiStageBoost can be used in the classification and ranking in speech recognition. Experiments show that the recognition optimization procedures established by this study are able to increase the recognition rate to over 95% in the personal computing device and industrial personal computer. It is expected that in the future this voice management system will accurately and effectively identify speakers answering the voice response questionnaire and will successfully carry out the functions in the choice of answers, paying the way for the formation of a virtual customer service person.     

Analysis of the electron transport properties in dye-sensitized solar cells using highly ordered TiO2 nanotubes and TiO2 nanoparticles

This study uses TiO2 nanoparticles and highly ordered anatase TiO2 nanotubes (AOTnt) as thin film photoanodes for dye-sensitized solar cells (DSSCs). DSSCs are assembled by single-layer and double-layer films of photoanodes and their electron transfer performance is compared. TiO2 nanoparticles were fabricated by the sol-gel method, and AOTnts were grown on titanium foil. This study uses TiO2 nanoparticles or AOTnts to prepare single-layer photoanodes and TiO2 nanoparticles coated on an AOTnt film to fabricate double-layer photoanodes. These three different photoanodes are soaked in dye and assembled into DSSCs, and their open-loop voltage recession, electrochemical impedance, lifetime, life cycle, and effective diffusion coefficient are measured. Electron transfer efficiency of the photoanodes and light harvesting efficiency are further analyzed. The results show that the electron transfer efficiency, open-loop voltage recession, lifetime, life cycle, and effective diffusion coefficient of the DSSCs assembled using double-layer photoanodes (AOTnt-TiO2) are superior to those of single-layer photoanodes (TiO2 or AOTnt).     

Electrochemical passive properties of AlxCoCrFeNi (x = 0, 0.25, 0.50, 1.00) alloys in sulfuric acids

This study investigates the electrochemical passive properties of Al_xCoCrFeNi alloys in H₂SO₄ by potentiodynamic polarization, EIS, and weight loss tests from 20 to 65 °C. Experimental results indicate that Al harms the corrosion resistance in H₂SO₄ at temperatures exceeding 27 °C owing to the porous and inferior nature of the protection oxide film of Al in these alloys. Closely examining the Arrhenius plots of corrosion current density reveals that both pre-exponential factor A and activation energy E_a increase with Al content. However, A affects corrosion current density more significantly than E_a at higher temperatures and, conversely, at lower temperatures.     

Blood and tissue compatibility of modified polyester: thrombosis, inflammation, and healing

OBJECTIVE: The effects of BRL-32872, azimilide and a selective blocker of the delayed rectifier potassium current, E-4031, were measured at two different basic cycle lengths (BCL), 300 and 1000 ms. Calcium channel antagonists of sarcolemmal (verapamil and nitrendipine) and sarcoplasmic reticulum (ryanodine) membranes were used to investigate whether the inhibition of the calcium current or the calcium release from the sarcoplasmic reticulum could alter the reverse-rate dependence of E-4031 on action potential duration (APD). METHODS: Guinea pig isolated papillary muscles were superfused with a Tyrode solution maintained at 37 degrees C and stimulated at a BCL of 300 or 1000 ms. The standard microelectrode technique was used to record action potential parameters and to study the effects of azimilide, BRL-32872 and E-4031. E-4031 was superfused at increasing concentrations (0.01, 0.03, 0.1 and 0.3 microM) in the absence or in the presence of verapamil (0.3 microM), nitrendipine (0.03 microM) or ryanodine (0.1 microM). RESULTS: BRL-32872 and azimilide induced a self-limited concentration-dependent increase in APD. The effect of BRL-32872 was not dependent on the stimulation frequency whereas the effect of azimilide was significantly reduced at the shorter BCL. E-4031 induced a concentration-dependent increase in APD at both stimulation BCL. The increase in APD was significantly more pronounced in fibres stimulated at a BCL of 1000 ms than in fibres stimulated at a BCL of 300 ms, characterising the reverse-frequency dependent effect of class III antiarrhythmic agents. The reverse-frequency dependence in action potential prolongation induced by E-4031 was significantly reduced in the presence of a low concentration of verapamil (0.3 microM), nitrendipine (0.03 microM), or ryanodine (0.1 microM. CONCLUSION: The results show that BRL-32872, in contrast to azimilide, does not induce the reverse-rate dependency of action potential prolongation typically produced by class III antiarrhythmic agents such as E-4031. Our results also show that reverse-rate dependency induced by E-4031 can be reduced by the simultaneous administration of a low concentration of a calcium channel antagonist or an inhibitor of the release of calcium from the sarcoplasmic reticulum. It is thus suggested that compounds with a suitable balance of potassium and calcium antagonistic activities may have less adverse effects than purely selective potassium channel blockers.     

A better technique using multisegment modeling and analysis of high-density and high-speed connectors

A useful and rather new simulation technique for connectors up to 6.25 GHz is presented and discussed in this paper. The proposed model extracts electrical parameters of a connector using time-domain reflectometry (TDR) measurements. A new technique was developed to obtain accurate impedance profiles using TDR and a multisegment approach that is effectively a distributed coupled model. The parameter extraction and characterization of connectors are discussed. The performance of the proposed segmented transmission line model is verified by simulation of the model in SPICE and by experimental measurement. The results show that the proposed model can simulate the electrical characteristics, including crosstalk and impedance, of high-density and high-speed connectors with satisfactory accuracy. Based on the proposed modeling and CAD simulators, the design and analysis of complicated high-density and high-speed connectors can be executed accurately and effectively. Compared with other previous models, the proposed model can significantly improve the accuracy of simulation.