Secure group communications using key graphs

Many emerging network applications are based upon a group communications model. As a result, securing group communications, i.e., providing confidentiality, authenticity, and integrity of messages delivered between group members, will become a critical networking issue. We present, in this paper, a novel solution to the scalability problem of group/multicast key management. We formalize the notion of a secure group as a triple (U,K,R) where U denotes a set of users, K a set of keys held by the users, and R a user-key relation. We then introduce key graphs to specify secure groups. For a special class of key graphs, we present three strategies for securely distributing rekey messages after a join/leave and specify protocols for joining and leaving a secure group. The rekeying strategies and join/leave protocols are implemented in a prototype key server we have built. We present measurement results from experiments and discuss performance comparisons. We show that our group key management service, using any of the three rekeying strategies, is scalable to large groups with frequent joins and leaves. In particular, the average measured processing time per join/leave increases linearly with the logarithm of group size     

Estimation of typical sum of lognormal random variables using log shifted gamma approximation

The sum of lognormal distributions is a well-known problem that no closed-form expression exists and it is difficult to evaluate numerically. In this paper, log shifted gamma (LSG) approximation method is proposed to represent the sum of lognormal distributions and to derive a closed-form expression of the typical value of the sum. Illustrative results show that the LSG model provides much more accurate approximation than other previous methods for a wide range of lognormal variances.     

A novel integrated micromachined tunable laser using polysilicon3-D mirror

A prototype tunable laser of ~2 mm×1.5 mm size has been developed for wavelength-division-multiplexing (WDM) application. This device is an integrated micromachined polysilicon three-dimensional (3-D) mirror with a single-mode Fabry-Perot laser diode and an antireflection-coated optical fiber. The micromirror can be driven to move laterally by an electrostatic comb-drive that changes the external cavity length of laser diode enabling wavelength tuning. A wavelength-tunable range of 16 nm is obtained using a driving voltage within ±3 V at a bias voltage of 10 V     

Engineering Sensor Arrays Using Aggregation‐Induced Emission Luminogens for Pathogen Identification

Lacking rapid and reliable pathogen diagnostic platforms, inadequate or delayed antimicrobial therapy could be made, which greatly threatens human life and accelerates the emergence of antibiotic‐resistant pathogens. In this contribution, a series of simple and reliable sensor arrays based on tetraphenylethylene (TPE) derivatives are successfully developed for detection and discrimination of pathogens. Each sensor array consists of three TPE‐based aggregation‐induced emission luminogens (AIEgens) that bear cationic ammonium group and different hydrophobic substitutions, providing tunable logP (n‐octanol/water partition coefficient) values to enable the different multivalent interactions with pathogens. On the basis of the distinctive fluorescence response produced by the diverse interaction of AIEgens with pathogens, these sensor arrays can identify different kinds of pathogens, even normal and drug‐resistant bacteria, with nearly 100% accuracy. Furthermore, blends of pathogens can also be identified accurately. The sensor arrays exhibit rapid response (about 0.5 h), high‐throughput, and easy‐to‐operate without washing steps.     

A Modular Vaccine Platform Combining Self‐Assembled Peptide Cages and Immunogenic Peptides

Subunit vaccines use delivery platforms to present minimal antigenic components for immunization. The benefits of such systems include multivalency, self‐adjuvanting properties, and more specific immune responses. Previously, the design, synthesis, and characterization of self‐assembling peptide cages (SAGEs) have been reported. In these, de novo peptides are combined to make hubs that assemble into nanoparticles when mixed in aqueous solution. Here it is shown that SAGEs are nontoxic particles with potential as accessible synthetic peptide scaffolds for the delivery of immunogenic components. To this end, SAGEs functionalized with the model antigenic peptides tetanus toxoid_632‐651 and ovalbumin_323‐339 drive antigen‐specific responses both in vitro and in vivo, eliciting both CD4⁺ T cell and B cell responses. Additionally, SAGEs functionalized with the antigenic peptide hemagglutinin_518‐526 from the influenza virus are also able to drive a CD8⁺ T cell response in vivo. This work demonstrates the potential of SAGEs to act as a modular scaffold for antigen delivery, capable of inducing and boosting specific and tailored immune responses.     

Fast detection of venous air embolism in Doppler heart sound usingthe wavelet transform

The introduction of air bubbles into the systemic circulation can result in significant morbidity. Real-time monitoring of continuous heart sound in patients detected by precordial Doppler ultrasound is, thus, vital for early detection of venous air embolism (VAE) during surgery. In this study, the multiscale feature of wavelet transforms (WT's) is exploited to examine the embolic Doppler heart sound (DHS) during intravenous air injections in dogs. As both humans and dogs share similar physiological conditions, the authors' methods and results for dogs are expected to be applicable to humans. The WT of DHS at scale 2 ^j(j=1,2) selectively magnified the power of embolic, but not the normal, heart sound. Statistically, the enhanced embolic power was found to be sensitive (P<0.01 at 0.01 ml of injected air) and correlated significantly (P<0.0005, τ=0.83) with the volume of injected air from 0.01 to 0.10 ml. A fast detection algorithm of O(N) complexity with unit complexity constant for VAE was developed (processing speed=8 ms per heartbeat), which confirmed the feasibility of real-time processing for both humans and dogs     

Influence of AIN protective film thickness on the hardness and electrophotographic properties of organic photoconductors

The deposition of a protective film to increase the hardness of an organic photoconductor (OPC) surface is an effective method to lengthen the lifetime of the OPC. In this work, A1N protective films were deposited onto OPC samples by rf reactive magnetron sputtering with low substrate temperature. The A1N films were deposited with optimized sputtering conditions and exhibited very high transmissivity in the visible wavelength range 300-800 nm. The films caused a remarkable increase in the hardness of the OPC surface, by between 32 and 62%. The acceptance voltage, dark decay rate, photodischarge rate, difference between the residual potential and the acceptance voltage of the OPC protected by A1N film were improved. These results show A1N is a suitable protective film for OPC.     

Monitoring for nitrate in UK-grown lettuce and spinach

To comply with European Commission requirements, the UK is carrying out a monitoring programme on nitrate concentrations in lettuce and spinach. This paper reports the results obtained between June 1996 and April 1998. A total of 182 samples of protected lettuce, 131 samples of outdoor-grown lettuce and 34 samples of fresh spinach were taken from the main growing areas of the UK. Nitrate concentrations in protected lettuce were influenced by the season with summer-grown crops (mean of 2382mg/kg) having lower levels than those grown in the winter (mean of 3124mg/kg). Weather conditions also affected concentrations in protected lettuces with long hours of sunshine and low rainfall associated with low nitrate levels. Nitrate concentrations in outdoor-grown lettuces were lower (mean of 1085mg/kg) than those in protected lettuces but there were insufficient data to determine if they were affected by the weather conditions or season. Similarly there were insufficient data to determine if weather conditions or season influenced nitrate concentrations in spinach (mean of 1900mg/kg) but regional differences were observed.     

Adaptive filtering of evoked potentials with radial-basis-function neural network prefilter

Evoked potentials (EPs) are time-varying signals typically buried in relatively large background noise. To extract the EP more effectively from noise, we had previously developed an approach using an adaptive signal enhancer (ASE) (Chen et al., 1995). ASE requires a proper reference input signal for its optimal performance. Ensemble- and moving window-averages were formerly used with good results. In this paper, we present a new method to provide even more effective reference inputs for the ASE. Specifically, a Gaussian radial basis function neural network (RBFNN) was used to preprocess raw EP signals before serving as the reference input. Since the RBFNN has built-in nonlinear activation functions that enable it to closely fit any function mapping, the output of RBFNN can effectively track the signal variations of EP. Results confirmed the superior performance of ASE with RBFNN over the previous method.