UTag: Long-range Ultra-wideband Passive Radio Frequency Tags

Long-range, ultra-wideband (UWB), passive radio frequency (RF) tags are key components in Radio Frequency IDentification (RFID) system that will revolutionize inventory control and tracking applications. Unlike conventional, battery-operated (active) RFID tags, LLNL's small UWB tags, called 'UTag', operate at long range (up to 20 meters) in harsh, cluttered environments. Because they are battery-less (that is, passive), they have practically infinite lifetimes without human intervention, and they are lower in cost to manufacture and maintain than active RFID tags. These robust, energy-efficient passive tags are remotely powered by UWB radio signals, which are much more difficult to detect, intercept, and jam than conventional narrowband frequencies. The features of long range, battery-less, and low cost give UTag significant advantage over other existing RFID tags

Neural networks in geophysical applications

Neural networks are increasingly popular in geophysics. Because they are universal approximators, these tools can approximate any continuous function with an arbitrary precision. Hence, they may yield important contributions to finding solutions to a variety of geophysical applications. However, knowledge of many methods and techniques recently developed to increase the performance and to facilitate the use of neural networks does not seem to be widespread in the geophysical community. Therefore, the power of these tools has not yet been explored to their full extent. In this paper, techniques are described for faster training, better overall performance, i.e., generalization,and the automatic estimation of network size and architecture

Remote Monitoring and Tracking of UF6 Cylinders Using Long-Range Passive Ultra-wideband (UWB) RFID Tags

An IAEA Technical Meeting on Techniques for IAEA Verification of Enrichment Activities identified 'smart tags' as a technology that should be assessed for tracking and locating UF6 cylinders. Although there is vast commercial industry working on RFID systems, the vulnerabilities of commercial products are only beginning to emerge. Most of the commercially off-the-shelf (COTS) RFID systems operate in very narrow frequency bands, making them vulnerable to detection, jamming and tampering and also presenting difficulties when used around metals (i.e. UF6 cylinders). Commercial passive RFID tags have short range, while active RFID tags that provide long ranges have limited lifetimes. There are also some concerns with the introduction of strong (narrowband) radio frequency signals around radioactive and nuclear materials. Considering the shortcomings of commercial RFID systems, in their current form, they do not offer a promising solution for continuous monitoring and tracking of UF6 cylinders. In this paper, we identify the key challenges faced by commercial RFID systems for monitoring UF6 cylinders, and introduce an ultra-wideband approach for tag/reader communications that addresses most of the identified challenges for IAEA safeguards applications

A Token Ring Protocol for Dynamic Ad-hoc Wireless Environments

A wireless ad-hoc networking protocol is presented. The protocol is designed to be flexible, easy to use and adaptable to a wide variety of potential applications. The primary considerations in design are small code size, guaranteed bandwidth access, limited delay, and error resilience in a highly dynamic ad-hoc environment. These considerations are achieved through the use of token ring protocol

Model-based Layer Estimation using a Hybrid Genetic/Gradient Search Optimization Algorithm

A particle swarm optimization (PSO) algorithm is combined with a gradient search method in a model-based approach for extracting interface positions in a one-dimensional multilayer structure from acoustic or radar reflections. The basic approach is to predict the reflection measurement using a simulation of one-dimensional wave propagation in a multi-layer, evaluate the error between prediction and measurement, and then update the simulation parameters to minimize the error. Gradient search methods alone fail due to the number of local minima in the error surface close to the desired global minimum. The PSO approach avoids this problem by randomly sampling the region of the error surface around the global minimum, but at the cost of a large number of evaluations of the simulator. The hybrid approach uses the PSO at the beginning to locate the general area around the global minimum then switches to the gradient search method to zero in on it. Examples of the algorithm applied to the detection of interior walls of a building from reflected ultra-wideband radar signals are shown. Other possible applications are optical inspection of coatings and ultrasonic measurement of multilayer structures

Final Report: 03-LW-005 Space-Time Secure Communications for Hostile Environments

The development of communications for highly reverberative environments is a major concern for both the private and military sectors whether the application is aimed at the securing a stock order or stalking hostile in a tunnel or cave. Other such environments can range from a hostile urban setting populated with a multitude of buildings and vehicles to the simple complexity of a large number of sound sources that are common in the stock exchange, or military operations in an environment with a topographic features hills, valleys, mountains or even a maze of buried water pipes attempting to transmit information about any chemical anomalies in the water system servicing a city or town. These inherent obstructions cause transmitted signals to reflect, refract and disperse in a multitude of directions distorting both their shape and arrival times at network receiver locations. Imagine troops attempting to communicate on missions in underground caves consisting of a maze of chambers causing multiple echoes with the platoon leader trying to issue timely commands to neutralize terrorists. This is the problem with transmitting information in a complex environment. Waves are susceptible to multiple paths and distortions created by a variety of possible obstructions, which may exist in the particular propagation medium. This is precisely the communications problem we solve using the physics of wave propagation to not only mitigate the noxious effects created by the hostile medium, but also to utilize it in a constructive manner enabling a huge benefit in communications. We employ time-reversal (T/R) communications to accomplish this task. This project is concerned with the development of secure communications techniques that can operate even in the most extreme conditions while maintaining a secure link between host and client stations. We developed an approach based on the concept of time-reversal (T/R) signal processing. In fact, the development of T/R communication systems is a recent signal processing research area dominated by applying these techniques to communicate in hostile environments. The fundamental concept is based on time-reversing the impulse response or Green's function characterizing the uncertain communications channel to mitigate deleterious dispersion and multipath effects. In this project, we have performed proof-of-principle experiments to demonstrate point-to-point and array-to-point communications by first establishing the basic theory to define and solve the underlying multi-channel communications problem and then developing various realizations of the resulting T/R receivers. We showed that not only do these receivers perform well in a hostile environment, but they also can be implemented with a ''1-bit'' analog-to-digital (A/D) converter design structure. We validated these results by performing the proof-of-principle acoustic communications simulations and experiments in air as well as electromagnetic (EM) simulation/experiments. It was shown that the resulting T/R receivers are capable of extracting the transmitted coded sequence from noisy microphone array measurements with zero (bit) error. We chose to perform the bulk of our work in the acoustics medium for simplicity in implementation and cost compared to the EM modality. However, we did perform some simple simulations and experiments using the LLNL micro-impulse transceiver system

Enhanced gas sensing and photocatalytic activity of reduced graphene oxide loaded TiO2 nanoparticles

In the present study, we have evaluated the gas sensing and photocatalytic activity of reduced graphene oxide (rGO) conjugated titanium dioxide (TiO2) nanoparticles (NPs) formed by the hydrothermal method. The as-synthesized rGO-TiO2 nanocomposite were characterized for the physicochemical properties such as the nature of crystallinity, functionalization, and morphology by making use of the powder X-ray diffraction, Fourier transform-infrared spectroscopy, and scanning electron microscopy, respectively. On testing the gas sensing properties, we found that the rGO-TiO2 nanocomposite can serve as the chemoresistive-type sensor because of its sensitivity and selectivity towards different concentrations of hydrogen and oxygen at room temperature conditions. However, the rGO-TiO2 sensor’s response and recovery speed towards hydrogen and oxygen needs further optimization. Test of photocatalytic activity of TiO2-rGO catalyst for the removal of two model contaminant dyes, RhB and MB showed effective removal, with respective degradation percentages of about 80 and 90% within the first 50 min of irradiation under visible light irradiation. Besides, MB was more effectively degraded using TiO2-rGO than pure TiO2 during the first 30 min of irradiation and this enhanced activity can be attributed to the increased capacity of light absorption, the efficiency of charge carriers separation, and the specific surface area maintained by the rGO-TiO2 nanocomposite to effectively utilize the photo-generated holes (h+) and superoxide radicals (O2−radical dot), responsible for the degradation of the dye. Based on the overall analysis, the formation of rGO-TiO2 nanocomposite can significantly improve the gas sensing and photocatalytic properties of TiO2 NPs and thus can be potential for practical applications in future nanotechnology

Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

Landslide susceptibility and hazard assessments are the most important steps in landslide risk mapping. The main objective of this study was to investigate and compare the results of two artificial neural network (ANN) algorithms, i.e., multilayer perceptron (MLP) and radial basic function (RBF) for spatial prediction of landslide susceptibility in Vaz Watershed, Iran. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 136 landside locations were constructed from various sources. Then the landslide inventory map was randomly split into a training dataset 70 % (95 landslide locations) for training the ANN model and the remaining 30 % (41 landslides locations) was used for validation purpose. Nine landslide conditioning factors such as slope, slope aspect, altitude, land use, lithology, distance from rivers, distance from roads, distance from faults, and rainfall were constructed in geographical information system. In this study, both MLP and RBF algorithms were used in artificial neural network model. The results showed that MLP with Broyden–Fletcher–Goldfarb–Shanno learning algorithm is more efficient than RBF in landslide susceptibility mapping for the study area. Finally the landslide susceptibility maps were validated using the validation data (i.e., 30 % landslide location data that was not used during the model construction) using area under the curve (AUC) method. The success rate curve showed that the area under the curve for RBF and MLP was 0.9085 (90.85 %) and 0.9193 (91.93 %) accuracy, respectively. Similarly, the validation result showed that the area under the curve for MLP and RBF models were 0.881 (88.1 %) and 0.8724 (87.24 %), respectively. The results of this study showed that landslide susceptibility mapping in the Vaz Watershed of Iran using the ANN approach is viable and can be used for land use planning

Financing micro-entrepreneurs for poverty alleviation: a performance analysis of microfinance services offered by BRAC, ASA, and Proshika from Bangladesh

Microfinance services have emerged as an effective tool for financing microentrepreneurs to alleviate poverty. Since the 1970s, development theorists have considered non-governmental microfinance institutions (MFIs) as the leading practitioners of sustainable development through financing micro-entrepreneurial activities. This study evaluates the impact of micro-finance services provided by MFIs on poverty alleviation. In this vein, we examine whether microfinance services contribute to poverty alleviation, and also identify bottlenecks in micro-finance programs and operations. The results indicate that the micro-loans have a statistically significant positive impact on the poverty alleviation index and consequently improve the living standard of borrowers by increasing their level of income

UTag: Long-range Ultra-wideband Passive Radio Frequency Tags

Long-range, ultra-wideband (UWB), passive radio frequency (RF) tags are key components in Radio Frequency IDentification (RFID) system that will revolutionize inventory control and tracking applications. Unlike conventional, battery-operated (active) RFID tags, LLNL's small UWB tags, called 'UTag', operate at long range (up to 20 meters) in harsh, cluttered environments. Because they are battery-less (that is, passive), they have practically infinite lifetimes without human intervention, and they are lower in cost to manufacture and maintain than active RFID tags. These robust, energy-efficient passive tags are remotely powered by UWB radio signals, which are much more difficult to detect, intercept, and jam than conventional narrowband frequencies. The features of long range, battery-less, and low cost give UTag significant advantage over other existing RFID tags