Search results for: M. Rutkowski
4 Properties of Hot-Pressed Alumina-Graphene Composites
Authors: P. Rutkowski, G. Górny, L. Stobierski, D. Zientara, W. Piekarczyk, K. Tran
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The polycrystalline dense alumina shows thermal conductivity about 30 W/mK and very high electrical resistivity. These last two properties can be modified by introducing commercial relatively cheap graphene nanoparticles which, as two-dimensional flakes show very high thermal and electrical properties. The aim of this work is to show that it is possible to manufacture the anisotropic alumina-graphene material with directed multilayer graphene particles. Such materials can show the anisotropic properties mentioned before.Keywords: alumina, composite, hot-pressed, graphene, properties
Procedia PDF Downloads 2623 Security Analysis of Mod. S Transponder Technology and Attack Examples
Authors: M. Rutkowski, J. Cwiklak, M. Grzegorzewski, M. Adamski
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All class A Airplanes have to be equipped with Mod. S transponder for ATC surveillance purposes. This technology was designed to provide a robust and dependable solution to localize, identify and exchange data with the airplane. The purpose of this paper is to analyze potential hazards that are a result of lack of any security or encryption on a design level. Secondary Surveillance Radars rely on an active response from an airplane. SSR radar installation is broadcasting a directional interrogation signal to the planes in range on 1030MHz frequency with DPSK modulation. If the interrogation is correctly received by the transponder located on the plane, a proper answer is sent on 1090MHz with PPM modulation containing plane’s SQUAWK, barometric altitude, GPS coordinates and 24bit unique address code. This technology does not use any kind of encryption. All of the specifications from the previous chapter can be found easily on the internet. Since there is no encryption or security measure to ensure the credibility of the sender and message, it is highly hazardous to use such technology to ensure the safety of the air traffic. The only thing that identifies the airplane is the 24-bit unique address. Most of the planes have been sniffed by aviation enthusiasts and cataloged in web databases. In the moment of writing this article, The PoFung Technologies has announced that they are planning to release all band SDR transceiver – this device would be more than enough to build your own Mod. S Transponder. With fake transponder, a potential terrorist can identify as a different airplane. By replacing the transponder in a poorly controlled airspace, hijackers can enter another airspace identifying themselves as another plane and land in the desired area.Keywords: flight safety, hijack, mod S transponder, security analysis
Procedia PDF Downloads 2922 Effect of Acid Activation of Vermiculite on Its Carbon Dioxide Adsorption Behaviors
Authors: Katarzyna Wal, Wojciech Stawiński, Piotr Rutkowski
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The scientific community is paying more and more attention to the problem of air pollution. Carbon dioxide is classified as one of the most harmful gases. Its emissions are generated during fossil fuel burning, waste management, and combustion and are responsible for global warming. Clay minerals constitute a group of promising materials for the role of adsorbents. They are composed of two types of phyllosilicate sheets: tetrahedral and octahedral, which form 1:1 or 2:1 structures. Vermiculite is one of their best-known representative, which can be used as an adsorbent from water and gaseous phase. The aim of the presented work was carbon dioxide adsorption on vermiculite. Acid-activated samples (W_NO3_x) were prepared by acid treatment with different concentrations of nitric acid (1, 2, 3, 4 mol L⁻¹). Vermiculite was subjected to modification in order to increase its porosity and adsorption properties. The prepared adsorbents were characterized using the BET-specific surface area analysis, thermogravimetry (TG), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM). Applied modifications significantly increase the specific surface area from 78,21 m² g⁻¹ for the unmodified sample (W_REF) to 536 m² g-1 for W_NO3_4. Obtained results showed that acid treatment tunes the material’s functional properties by increasing the contact surface and generating more active sites in its structure. The adsorption performance in terms carbon dioxide adsorption capacities follows the order of W_REF (25.91 mg g⁻¹) < W_NO3_1 (38.54 mg g⁻¹) < W_NO3_2 (44.03 mg g⁻¹) W_NO3_4 (67.51 mg g⁻¹) < W_NO3_3 (70.48 mg g⁻¹). Acid activation significantly improved the carbon dioxide adsorption properties of modified samples compared to raw material. These results demonstrate that vermiculite-based samples have the potential to be used as effective CO₂ adsorbents. Furthermore, acid treatment is a promising technique for improving the adsorption properties of clay minerals.Keywords: adsorption, adsorbent, clay minerals, air pollution, environment
Procedia PDF Downloads 1441 Learning to Translate by Learning to Communicate to an Entailment Classifier
Authors: Szymon Rutkowski, Tomasz Korbak
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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning
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