Remediation of PCE-contaminated aquifer by an in situ two-layer biobarrier: laboratory batch and column studies

The industrial solvent tetrachloroethylene (PCE) is among the most ubiquitous chlorinated compounds found in groundwater contamination. The objective of this study was to develop an in situ two-layer biobarrier system consisting of an organic-releasing material layer followed by an oxygen-releasing material layer. The organic-releasing material, which contained sludge cakes from a domestic wastewater treatment plant, is able to release biodegradable organics continuously. The oxygen-releasing material, which contained calcium peroxide, is able to release oxygen continuously upon contact with water. The first organic-releasing material layer was to supply organics (primary substrates) to reductively dechlorinate PCE in situ. The second oxygen-releasing material layer was to release oxygen to aerobic biodegrade or cometabolize PCE degradation byproducts from the first anaerobic layer. Batch experiments were conducted to design and identify the components of the organic and oxygen-releasing materials, and evaluate the organic substrate (presented as chemical oxygen demand (COD) equivalent) and oxygen release rates from the organic-releasing material and oxygen-releasing materials, respectively. The observed oxygen and COD release rates were approximately 0.0368 and 0.0416 mg/d/g of material, respectively. A laboratory-scale column experiment was then conducted to evaluate the feasibility of this proposed system for the bioremediation of PCE-contaminated groundwater. This system was performed using a series of continuous-flow glass columns including a soil column, an organic-releasing material column, two consecutive soil columns, and an oxygen-releasing material column, followed by two other consecutive soil columns. Anaerobic acclimated sludges were inoculated in the first four columns, and aerobic acclimated sludges were inoculated in the last three columns to provide microbial consortia for contaminant biodegradation. Simulated PCE-contaminated groundwater with a flow rate of 0.25 L/d was pumped into this system. Effluent samples from each column were analyzed for PCE and its degradation byproducts. Results show that up to 99% of PCE removal efficiency was obtained in this passive system. Thus, the biobarrier treatment scheme has the potential to be developed into an environmentally and economically acceptable remediation technology for the in situ treatment of PCE-contaminated aquifer.     

A Popov criterion for networked systems

We consider robustness analysis of heterogeneous and homogeneous networked systems based on integral quadratic constraints (IQCs). First, we show how the analysis decomposes into lower dimensional problems if the interconnection structure is exploited. This generally leads to a significant reduction of the computational complexity. Secondly, by considering a set of IQCs that characterizes the eigenvalues of the interconnection matrices of symmetrically networked systems, we derive a Popov-like criterion for such systems. In particular, when the nodes of the networked system are single-input–single-output linear time-invariant operators, the criterion can be illustrated using a generalized Popov plot. In such cases, the Popov criterion is also a necessary condition in the sense that if the criterion is violated then a destabilizing network with the specified eigenvalue distribution can be constructed.     

Modeling of Viscoelastic Contacts and Evolution of Limit Surface for Robotic Contact Interface

Viscoelastic contact is a type of contact which includes, in addition to linear or nonlinear elastic response, time-dependent response due to relaxation or creep phenomena that govern the contact behavior. The characteristics of the time-dependent relaxation of such a viscoelastic contact are typically exponentially decaying functions, and exponentially growing functions for creep, respectively. Such contacts can be found in anthropomorphic robotic fingers, soft materials, viscoelastic skin with rigid core, and human fingers and feet. In this paper, the nature of viscoelastic contacts is investigated, and the evolution of their friction limit surfaces and of the pressure distributions at the contact interface are studied. Two cases commonly found in robotic grasping and manipulation are discussed. Based on the modeling formulation, it is found that the two important parameters of analysis and modeling for such contacts, i.e., the radius of contact area and the profile of pressure distribution, can be chosen using proposed coupling equations as the viscoelastic contact interface evolves with time. The new contribution of this paper includes a proposal of coupling equations between the two important parameters to describe the viscoelastic contact interface, and a study of the evolution of limit surfaces for viscoelastic contact interface due to temporal dependency, and the implication on grasp stability. It is found from the evolution of limit surfaces that when normal force is applied with typical viscoelastic contacts, grasp becomes more stable as time elapses. The modeling can be applied to the design of fingertips and the analysis of robotic grasping and manipulation involving viscoelastic fingers     

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.     

The oxidation behavior of an Fe61B15Zr8Mo7Co5Y2Cr2 bulk metallic glass at 650 °C in various oxygen-containing environments

The oxidation behavior of an Fe₆₁B₁₅Zr₈Mo₇Co₅Y₂Cr₂ bulk metallic glass (Fe7-BMG) was investigated in three oxygen-containing atmospheres over the oxygen partial pressure range of 10³–10⁵ Pa at 650 °C. The oxidation kinetics of the Fe7-BMG followed the parabolic rate law in all cases, indicating that solid-state diffusion is the rate-controlling step during oxidation. The oxidation rate constants (k_p values) increased with increasing oxygen partial pressure, implying a typical scaling behavior with a p-type semiconductivity. Duplex scales formed on the Fe7-BMG consisted of an outer layer of mostly iron oxides (Fe₂O₃/Fe₃O₄) and minor amounts of B₂O₃, and a heterophasic inner layer of mostly tetragonal-ZrO₂ (t-ZrO₂) intermixed with non-oxidized intermetallic phases.