A 2D processing algorithm for detecting landmines using Ground Penetrating Radar data

Ground Penetrating Radar(GPR) is one of a number of technologies that have been used to improve landmine detection efficiency. The clutter environment within the first few cm of the soil where landmines are buried, exhibits strong reflections with highly non-stationary statistics. An antipersonnel mine(AP) can have a diameter as low as 2cm whereas many soils have very high attenuation frequencies above 3GHZ. The landmine detection problem can be solved by carrying out system level analysis of the issues involved to synthesise an image which people can readily understand. The SIMCA (’SIMulated Correlation Algorithm’) is a technique that carries out correlation between the actual GPR trace that is recorded at the field and the ideal trace which is obtained by carrying out GPR simulation. The SIMCA algorithm firstly calculates by forward modelling a synthetic point spread function of the GPR by using the design parameters of the radar and soil properties to carry out radar simulation. This allows the derivation of the correlation kernel. The SIMCA algorithm then filters these unwanted components or clutter from the signal to enhance landmine detection. The clutter removed GPR B scan is then correlated with the kernel using the Pearson correlation coefficient. This results in a image which emphasises the target features and allows the detection of the target by looking at the brightest spots. Raising of the image to an odd power >2 enhances the target/background separation. To validate the algorithm, the length of the target in some cases and the diameter of the target in other cases, along with the burial depth obtained by the SIMCA system are compared with the actual values used during the experiments for the burial depth and those of the dimensions of the actual target. Because, due to the security intelligence involved with landmine detection and most authors work in collaboration with the national government military programs, a database of landmine signatures is not existant and the authors are also not able to publish fully their algorithms. As a result, in this study we have compared some of the cleaned images from other studies with the images obtained by our method, and I am sure the reader would agree that our algorithm produces a much clearer interpretable image

The SIMCA algorithm for processing Ground Penetrating Radar data and its use in landmine detection

The main challenge of ground penetrating radar (GPR) based land mine detection is to have an accurate image analysis method that is capable of reducing false alarms. However an accurate image relies on having sufficient spatial resolution in the received signal. But because the diameter of an AP mine can be as low as 2cm and many soils have very high attenuations at frequencies above 3GHz, the accurate detection of landmines is accomplished using advanced algorithms. Using image reconstruction and by carrying out the system level analysis of the issues involved with recognition of landmines allows the landmine detection problem to be solved. The SIMCA (’SIMulated Correlation Algorithm’) is a novel and accurate landmine detection tool that carries out correlation between a simulated GPR trace and a clutter1 removed original GPR trace. This correlation is performed using the MATLAB R processing environment. The authors tried using convolution and correlation. But in this paper the correlated results are presented because they produced better results. Validation of the results from the algorithm was done by an expert GPR user and 4 other general users who predict the location of landmines. These predicted results are compared with the ground truth data

The SIMCA algorithm for processing Ground Penetrating Radar data and its use in locating foundations in demolished buildings

Abstract—The main challenge of ground penetrating radar GPR) based foundation detection is to have an accurate image analysis method. In order to solve the detection problem a system level analysis of the issues involved with the recognition of foundations using image reconstruction is required. The SIMCA (’SIMulated Correlation Algorithm’) is a technique based on an area correlation between the trace that would be returned by an ideal point reflector in the soil conditions at the site and the actual trace. During an initialization phase, SIMCA carries out radar simulation using the design parameters of the radar and soil properties. Then SIMCA takes the raw data as the radar is scanned over the ground and in real-time uses a clutter removal technique to remove various clutter such as cross talk, initial ground reflection and antenna ringing. The trace which would be returned by a target under these conditions is then used to form a correlation kernel. The GPR b-scan is then correlated with the kernel using the Pearson correlation coefficient, resulting in a correlated image which is brightest at points most similar to the canonical target. This image is then raised to an odd power >2 to enhance the target/background separation. To validate and compare the algorithm, photographs of the building before it was demolished along with processed data using the REFLEXW package were used. The results produced by the SIMCA algorithm were very promising and were able to locate some features that the REFLEXW package were not able to identify

Switching on electrocatalytic activity in solid oxide cells

Solid oxide cells (SOCs) can operate with high efficiency in two ways - as fuel cells, oxidizing a fuel to produce electricity, and as electrolysis cells, electrolysing water to produce hydrogen and oxygen gases. Ideally, SOCs should perform well, be durable and be inexpensive, but there are often competitive tensions, meaning that, for example, performance is achieved at the expense of durability. SOCs consist of porous electrodes - the fuel and air electrodes - separated by a dense electrolyte. In terms of the electrodes, the greatest challenge is to deliver high, long-lasting electrocatalytic activity while ensuring cost- and time-efficient manufacture. This has typically been achieved through lengthy and intricate ex situ procedures. These often require dedicated precursors and equipment; moreover, although the degradation of such electrodes associated with their reversible operation can be mitigated, they are susceptible to many other forms of degradation. An alternative is to grow appropriate electrode nanoarchitectures under operationally relevant conditions, for example, via redox exsolution. Here we describe the growth of a finely dispersed array of anchored metal nanoparticles on an oxide electrode through electrochemical poling of a SOC at 2 volts for a few seconds. These electrode structures perform well as both fuel cells and electrolysis cells (for example, at 900 °C they deliver 2 watts per square centimetre of power in humidified hydrogen gas, and a current of 2.75 amps per square centimetre at 1.3 volts in 50% water/nitrogen gas). The nanostructures and corresponding electrochemical activity do not degrade in 150 hours of testing. These results not only prove that in operando methods can yield emergent nanomaterials, which in turn deliver exceptional performance, but also offer proof of concept that electrolysis and fuel cells can be unified in a single, high-performance, versatile and easily manufactured device. This opens up the possibility of simple, almost instantaneous production of highly active nanostructures for reinvigorating SOCs during operation

Cation-swapped homogeneous nanoparticles in perovskite oxides for high power density

Exsolution has been intensively studied in the fields of energy conversion and storage as a method for the preparation of catalytically active and durable metal nanoparticles. Under typical conditions, however, only a limited number of nanoparticles can be exsolved from the host oxides. Herein, we report the preparation of catalytic nanoparticles by selective exsolution through topotactic ion exchange, where deposited Fe guest cations can be exchanged with Co host cations in PrBaMn1.7Co0.3O5+delta. Interestingly, this phenomenon spontaneously yields the host PrBaMn1.7Fe0.3O5+delta, liberating all the Co cations from the host owing to the favorable incorporation energy of Fe into the lattice of the parent host (Delta E-incorporation = -0.41 eV) and the cation exchange energy (Delta E-exchange = -0.34 eV). Remarkably, the increase in the number of exsolved nanoparticles leads to their improved catalytic activity as a solid oxide fuel cell electrode and in the dry reforming of methane

Conductivity and redox stability of new double perovskite oxide Sr 1.6 K 0.4 Fe 1+ x Mo 1− x O 6− δ (x= 0.2, 0.4, 0.6)

A series of new perovskite oxides Sr1.6K0.4Fe1+xMo1−xO6−δ (x = 0.2, 0.4, 0.6) were synthesised by solid state reaction method. Synthesis of Sr1.6K0.4Fe1+xMo1−xO6−δ (x = 0.2, 0.4, 0.6) was achieved above 700 °C in 5 % H2/Ar, albeit with the formation of impurity phases. Phase stability upon redox cycling was only observed for sample Sr1.6K0.4Fe1.4Mo0.6O6−δ. Redox cycling of Sr1.6K0.4Fe1+xMo1−xO6−δ (x = 0.2, 0.4, 0.6) demonstrates a strong dependence on high temperature reduction to achieve high conductivities. After the initial reduction at 1200 °C in 5 %H2/Ar, then re-oxidation in air at 700 °C and further reduction at 700 °C in 5 %H2/Ar, the attained conductivities were between 0.1 and 58.4 % of the initial conductivity after reduction 1200 °C in 5 %H2/Ar depending on the composition. In the investigated new oxides, sample Sr1.6K0.4Fe1.4Mo0.6O6−δ is most redox stable also retains reasonably high electrical conductivity, ~70 S/cm after reduction at 1200 °C and 2–3 S/cm after redox cycling at 700 °C, indicating it is a potential anode for SOFCs

Exsolution trends and co-segregation aspects of self-grown catalyst nanoparticles in perovskites

In perovskites, exsolution of transition metals has been proposed as a smart catalyst design for energy applications. Although there exist transition metals with superior catalytic activity, they are limited by their ability to exsolve under a reducing environment. When a doping element is present in the perovskite, it is often observed that the surface segregation of the doping element is changed by oxygen vacancies. However, the mechanism of co-segregation of doping element with oxygen vacancies is still an open question. Here we report trends in the exsolution of transition metal (Mn, Co, Ni and Fe) on the PrBaMn2O5+?? layered perovskite oxide related to the co-segregation energy. Transmission electron microscopic observations show that easily reducible cations (Mn, Co and Ni) are exsolved from the perovskite depending on the transition metal-perovskite reducibility. In addition, using density functional calculations we reveal that co-segregation of B-site dopant and oxygen vacancies plays a central role in the exsolution

Hygrothermal effects on the translaminar fracture toughness of a highly toughened aerospace CFRP: Experimental characterisation and model prediction

The translaminar fracture toughness of wet (fully saturated) and dry (as manufactured) IM7/8552 laminates was measured using compact tension tests. Cross-ply ([90/0]8S) and quasi-isotropic ([90/45/0/-45]4S) laminates were tested at three different temperatures, namely 23 °C, 40 °C and 90 °C. The translaminar fracture toughness decreases non-linearly with the temperature for the dry laminates. However, for the wet laminates, the translaminar fracture toughness increases. The room-temperature tested wet cross-ply laminates exhibited a lower fracture toughness than the dry laminates. However, the initiation fracture toughness of the wet quasi-isotropic laminates is higher than for the dry laminates at all the test temperatures. The fractographic analysis of the failed specimens revealed that the hot-wet conditions promote additional fibre pull-out, which increases the fracture energy. The degradation of the epoxy matrix in the wet multi-directional laminates affected the progressive failure mechanism, and either increased or decreased the overall fracture energy depending on the lay-up sequence. For example, the initiation fracture toughness of the elevated temperature (90 °C) in wet quasi-isotropic specimens is ~17% higher than the room temperature (23 °C) dry laminates

Concomitant jejunal sarcomatoid carcinoma and gastric GIST in patient with polymyalgia rheumatica: A case report

Introduction: Sarcomatoid carcinoma (SCA) of the small bowel is an extremely rare tumor with only 21 cases reported in literature and GISTs are relatively rare gastrointestinal neoplasms. Presentation of case: We report a case of an 85 year-old female admitted with intestinal obstruction in June 2010. She suffered from polymyalgia rheumatica and was under surveillance for a presumed gastric GIST. A laparotomy was performed with resection of the jejunal obstruction and complete excision of the gastric mass. Histology confirmed a gastric GIST and sarcomatoid carcinoma of the small bowel. The patient was discharged 21 days after the operation and died on the 88th post-operative day. Discussion: Synchronous GISTs and other malignancies have been reported over the last years with increasing frequency. Sarcomatoid carcinoma of the small bowel is an aggressive neoplasm with poor survival rates and surgery is the cornerstones of treatment. Given its unpredictable clinical behaviour and concomitant association with other malignancies, GISTs require adequate surgical resection with careful, long-term follow-up. Conclusion: This is the first case of concomitant gastric GIST with Sarcomatoid carcinoma of the small bowel, and the first report of sarcomatoid small bowel carcinoma in association with polymyalgia rheumatica

Characterization and Evaluation of <i>Metarhizium</i> spp. (Metsch.) Sorokin Isolates for Their Temperature Tolerance

A field survey was done in teak (Tectona grandis F.) forests in South India to explore the entomopathogenic effect of Metarhizium anisopliae (Ascomycota: Sordariomycetes) against teak defoliator, Hyblaea puera (Lepidoptera: Hyblaeidae). About 300 soils and infected insect samples were collected during the survey and thirty-six fungal isolates were isolated from soil and insect samples and characterized. The fungi were cultured on PDAY with dodine and antibiotics. Generally, the EPF culture was incubated at 27 °C in darkness for 15 days. Virulence of the Entomopathogenic Fungi (EPF) ability to germinate under cold and heat temperatures was assessed in a culture impregnated with conidia. In the experiment, it was found that for the first time Metarhizium quizhouense, Metarhizium robertsii, and Metarhizium majus species caused significantly higher mortality to hosts. These isolates of M. anisopliae, M. robertsii, M. majus, and M. quizhouense were all considered to be effective virulent and environmentally adaptive. The Metarhizium isolates were recommended as effective bio-control agents through the field investigation of teak defoliator Hyblaea puera from South India forest. This study paves the way to utilize the indigenous isolates of EPF for the control of teak defoliator and to combat the pests thatare resistant to insecticide