Inverse Problem Solution in Landmines Detection Based on Active Thermography

Landmines still affect numerous territories in the whole world and pose a serious threat, mostly to civilians. Widely used non-metallic landmines are undetectable using metal detector. Therefore, there is an urging need to improve methods of detecting such objects. In the present study we introduce relatively new method of landmines' detection: active infrared thermography with microwave excitation. In this paper we present the optimization based method of solving inverse problem for microwave heating. This technique will be used in the reconstruction of detected landmines geometric and material properties

Study of Electron Transport in Fullerene (C60) Quantum Confined Channel Layer Based Field Effect Transistor

In this work, we modelled a simple n-channel Si Metal-Quantum confined layer-Semiconductor Field Effect Transistor (MQSFET), which resembles exactly as the conventional Si Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) where SiO2 dielectric layer is replaced with a wide band gap C60 quantum confined layer of thickness 3nm and gold (Ψ=5.1eV) as metal contact. The capacitance and voltage characteristics at different temperatures from 100 K to 500 K and energy band gap are studied using Multi-dielectric Energy Band Diagram Program (MEBDP) simulation software, performed current-voltage transistor characteristics and analyzed the mobility of the charge carrier in the MQS sandwiched device structure using the Caughey-Thomas high saturation mobility model and the Lombardi surface mobility model. In these studies, we inferred a very low threshold voltage, when the donor concentration in the p-Si substrate is tuned between 1E16 to 1E17 cm-3 and a saturated flow of nanoamperes range of charge carrier at a low gate potential is even possible

Accelerated discovery of two crystal structure types in a complex inorganic phase field

The discovery of new materials is hampered by the lack of efficient approaches to the exploration of both the large number of possible elemental compositions for such materials, and of the candidate structures at each composition1. For example, the discovery of inorganic extended solid structures has relied on knowledge of crystal chemistry coupled with time-consuming materials synthesis with systematically varied elemental ratios2,3. Computational methods have been developed to guide synthesis by predicting structures at specific compositions4,5,6 and predicting compositions for known crystal structures7,8, with notable successes9,10. However, the challenge of finding qualitatively new, experimentally realizable compounds, with crystal structures where the unit cell and the atom positions within it differ from known structures, remains for compositionally complex systems. Many valuable properties arise from substitution into known crystal structures, but materials discovery using this approach alone risks both missing best-in-class performance and attempting design with incomplete knowledge8,11. Here we report the experimental discovery of two structure types by computational identification of the region of a complex inorganic phase field that contains them. This is achieved by computing probe structures that capture the chemical and structural diversity of the system and whose energies can be ranked against combinations of currently known materials. Subsequent experimental exploration of the lowest-energy regions of the computed phase diagram affords two materials with previously unreported crystal structures featuring unusual structural motifs. This approach will accelerate the systematic discovery of new materials in complex compositional spaces by efficiently guiding synthesis and enhancing the predictive power of the computational tools through expansion of the knowledge base underpinning them

PMN, PMN-2 and PMF-1 Landmines Detection Using Active Infrared Thermography with Microwave Excitation

W pracy przedstawiono wyniki zastosowania aktywnej termografii podczerwonej z wymuszeniem mikrofalowym do wykrywania zakopanych w piasku ćwiczebnych min przeciwpiechotnych: PMN, PMN-2 oraz PMF-1. Wspomniane miny mają obudowy wykonane z tworzyw sztucznych oraz odznaczają się niską zawartością metalu, przez co są trudno wykrywalne standardowymi wykrywaczami metalu. Prezentowana nowa metoda wykrywania min lądowych wykorzystuje źródło mikrofal o dużej mocy do podgrzania gruntu wraz z zakopaną w nim miną. Wytworzona różnica temperatur jest obserwowana na powierzchni gruntu za pomocą czułej kamery termowizyjnej.In this paper, active infrared thermography is used to detect antipersonnel landmines: PMN, PMN-2 and PMF-1. Mentioned landmines have very low metal content and their casings are made of plastic, therefore are considered as hard to detect using metal detectors. Presented new method of landmines detection, uses high power microwave source to heat the ground with buried landmine. Obtained temperature difference can be observed on the ground surface with sensitive thermovision camera

Thermograms analysis using image processing algorithms

Technika aktywnej termografii podczerwonej jest jedną z najpopularniejszych metod wykorzystywanych w badaniach nieniszczących. Proponowanym przez nas źródłem ciepła indukującym różnicę temperatur w badanym obiekcie jest generator mikrofal wysokiej mocy. Opracowany układ grzewczo - detekcyjny jest segmentem bazowym urządzenia do wykrywania niemetalicznych min lądowych. Niniejszy artykuł prezentuje rezultaty zastosowania metod przetwarzania obrazów do analizy otrzymanych termogramów. Przy użyciu metody wykorzystującej interpolację biliniową oraz metodę wirtualnego przesunięcia kamery z termogramów zostały usunięte zniekształcenia perspektywiczne.Active infrared thermography is one of the most popular methods used in non destructive testing. In our system, the temperature difference is induced using microwave radiation. Developed setup is used to detection of the nonmetallic landmines. In this paper we present the results of thermograms analysis using image processing algorithms. The method using bilinear transformation and virtual camera shifting were used to remove the perspective distortions

Nonmetallic landmine detection using microwave enchanced infrared thermography

Niniejszy artykuł prezentuje nową metodę wykrywania min lądowych (zarówno przeciwczołgowych, jak i przeciwpiechotnych). Oparta na połączeniu objętościowego grzania mikrofalowego oraz termografii podczerwonej technika pozwala na otrzymanie sygnatur termicznych płytko położonych obiektów niemetalicznych.In this paper we present the new method of the antipersonnel and antitank landmines' detection. This technique, based on connection of the volumetric microwave heating and active infrared thermography, can be used to detect thermal signatures of buried nonmetallic objects

Logic and Cognition: Special Issue of Best Papers of the ESSLLI 2012 Workshop

The explanatory power of logic is vast and therefore it has proved a valuable tool for many disciplines, including the building-blocks of cognitive science, such as philosophy, computer science, mathematics, artificial intelligence, and linguistics. Logic has a great track record in providing interesting insights by means of formalization, and as such it is very useful in disambiguating psychological theories. Logically formalized cognitive theories are not only the source of unequivocal experimental hypotheses, but they also lend themselves naturally to computational modeling. Most importantly, modern logic has at its service a rich variety of tools to assess and compare such psychological theories. This toolbox can be utilized in evaluating cognitive models along the following dimensions: (a) logical relationships, for example, incompatibility or identity of models; (b) explanatory power, for example, what can be expressed by means of a model? (c) computational plausibility, for example, are computations postulated by cognitive models tractable, do they scale-up? In this way, logic can play a major role in the process of psychological explanation. For some interesting examples, see Stenning and van Lambalgen (2008). Marr (1983) has argued that any particular task computed by a cognitive system must ultimately be analyzed at three levels of explanation (in order of decreasing abstraction)