When the lines go down [telecommunications]

Telecommunications planning for national security and emergency preparedness in the post-divestiture (of AT&T) environment is examined. To ensure emergency telecommunications, a web of emergency structures, plans, and procedures are in place, with links from the local provider level to the national level. Involved in this web are: individual companies and providers, regional and national corporate entities, and state and local emergency management centers. Some of the measures in place are discussed. The augmentations or other equipment that can be deployed in any emergency and the role of satellite and wireless communication are described. The importance of human preparation is addressed. Lessons learned in past emergencies and the potential impact of emerging technologies in future emergencies are discussed     

Intelligent network requirements for personal communicationsservices

It is shown that a moderate set of capabilities within the service switching point (SSP), service control point (SCP), and intelligent peripheral (IP), which are the intelligent network (IN) components directly responsible for the real-time execution and control of end-user services, can engender a wide range of end-user personal communication service (PCS) features. These capabilities could be used as the starting point for an economic analysis of IN implementation costs versus service worth. From a very large target set of call model trigger check points (TCPs), the dozen or so identified in the CCITT Capability Set 1 are shown to be sufficient. The SCP and IP functional entity actions identified are also sufficient to support PCS core network functions     

Single-chip design of bit-error-correcting stack decoders

The design of a single-chip VLSI system to implement the Zigangirov-Jelinek sequential decoding algorithm for bit-error-correction is described and the dependence of performance on design parameters is discussed. By virtue of being self-contained, having few input and output pins, and processing stack elements once each clock cycle, the system should be capable of high-speed decoding. For constraint length 21, rate 1/2 codes, and 3-b soft decision detection, it is found that a system containing approximately 25000 stack cells reduces errors in a 3-dB signal-to-noise level environment, corresponding to 7.8% hard decision error rate, by two orders of magnitude. Higher decoding gain is obtained at lower noise levels through the use of a relatively long constraint length. The constraint length is not limited by the architecture. Chip area estimates needed to obtain prescribed decoded error rates and average decoding rates are also described and indicate that an effective system is potentially achievable with current technology     

HeLa cell transfection using a novel sonoporation system

Sonoporation has been shown to have an important role in biotechnology for gene therapy and drug delivery. This paper presents a novel microfluidic sonoporation system that achieves high rates of cell transfection and cell viability by operating the sonoporation chamber at resonance. The paper presents a theoretical analysis of the resonant sonoporation chamber design, which achieves sonoporation by forming an ultrasonic standing wave across the chamber. A piezoelectric transducer (PZT 26) is used to generate the ultrasound and the different material thicknesses have been identified to give a chamber resonance at 980 kHz. The efficiency of the sonoporation system was determined experimentally under a range of sonoporation conditions and different exposures time (5, 10, 15, and 20 s, respectively) using HeLa cells and plasmid (peGFP-N1). The experimental results achieve a cell transfection efficiency of 68.9% (analysis of variance, ANOVA, p < 0.05) at the resonant frequency of 980 kHz at 100 V(p-p) (19.5 MPa) with a cell viability of 77% after 10 s of insonication.     

Integrated approach to electrode and AlN depositions for bulk acoustic wave (BAW) devices

This paper investigates the (002) texture of AlN films deposited by reactive pulsed direct current sputtering on Al, Al–Cu, W and Mo metal electrodes. X-Ray diffraction and atomic force microscopy studies show that the AlN texture is dependent on the deposition conditions and nature of the underlayers. A smooth underlayer with a sharp texture represents the best combination of properties. AlN films with a full width at half maximum less than 1.5 have been deposited on the electrodes studied. It is also possible to deposit well-textured electrodes with a roughness less than 2.5 nm.     

Wavelength shift in vertical cavity laser arrays on a patternedsubstrate

The authors demonstrate a spatially chirped emission wavelength in vertical cavity surface emitting laser (VCSEL) arrays grown by molecular beam epitaxy. The wavelength shift is due to a lateral thickness variation in the Al_0.2Ga_0.8As cavity, which is induced by a substrate temperature profile during growth. A 20 nm shift in lasing wavelength is obtained in a VCSEL array     

Multiple-quantum-well GaInNAs-GaNAs ridge-waveguide laser diodesoperating out to 1.4 μm

In this letter, results from a ridge waveguide laser diode (LD) structure, with three GaInNAs quantum wells (QWs) and GaNAs barriers, are presented. The sample was grown by solid source molecular beam epitaxy with an RF plasma nitrogen source. These devices differ from previously reported GaInNAs QWs LDs that used GaAs as the barrier material. The introduction of nitrogen into the barriers reduces the spectral blue shift caused by post-growth annealing. Long wavelength emission out to 1.405 μm was observed. The devices exhibited threshold current densities as low as 1.5 kA/cm², high differential efficiency of 0.67 W/A, and a maximum output power of 350 mW     

Software defi ned radio: Part 22 in a series of tutorials on instrumentation and measurement

A software defined radio (SDR) [1] is a communication system that performs many of its required signal processing tasks in a programmable digital signal processing (DSP) engine. The engine is coupled to the air interface of analog circuits and antennae by analog-to-digital and digital-to-analog converters (ADCs and DACs). The SDR's software reprograms the DSP segment of the radio's physical layer to reconFigure the radio system parameters and can thus synthesize multiple radios. The software can also select and alter the air interface components as well as the higher level data processing layers of the radio system.     

Mitigating Performance Degradation in Congested Sensor Networks

Data generated in wireless sensor networks may not all be alike: some data may be more important than others and hence may have different delivery requirements. In this paper, we address differentiated data delivery in the presence of congestion in wireless sensor networks. We propose a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. The basic protocol, called congestion-aware routing (CAR), discovers the congested zone of the network that exists between high-priority data sources and the data sink and, using simple forwarding rules, dedicates this portion of the network to forwarding primarily high-priority traffic. Since CAR requires some overhead for establishing the high-priority routing zone, it is unsuitable for highly mobile data sources. To accommodate these, we define MAC-enhanced CAR (MCAR), which includes MAC-layer enhancements and a protocol for forming high-priority paths on the fly for each burst of data. MCAR effectively handles the mobility of high-priority data sources, at the expense of degrading the performance of low-priority traffic. We present extensive simulation results for CAR and MCAR, and an implementation of MCAR on a 48-node testbed.     

Ascertaining the importance of neurons to develop better brain-machine interfaces

In the design of brain-machine interface (BMI) algorithms, the activity of hundreds of chronically recorded neurons is used to reconstruct a variety of kinematic variables. A significant problem introduced with the use of neural ensemble inputs for model building is the explosion in the number of free parameters. Large models not only affect model generalization but also put a computational burden on computing an optimal solution especially when the goal is to implement the BMI in low-power, portable hardware. In this paper, three methods are presented to quantitatively rate the importance of neurons in neural to motor mapping, using single neuron correlation analysis, sensitivity analysis through a vector linear model, and a model-independent cellular directional tuning analysis for comparisons purpose. Although, the rankings are not identical, up to sixty percent of the top 10 ranking cells were in common. This set can then be used to determine a reduced-order model whose performance is similar to that of the ensemble. It is further shown that by pruning the initial ensemble neural input with the ranked importance of cells, a reduced sets of cells (between 40 and 80, depending upon the methods) can be found that exceed the BMI performance levels of the full ensemble.