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2842. Automated reverse Engineering of CAN protocols
- Creator:
- Weiß, Nils, Pozzobon, Enrico, Mottok, Jürgen, and Matoušek, Václav
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- controller area networks, statistical analysis, and neural networks
- Language:
- English
- Description:
- Car manufacturers define proprietary protocols to be used inside their vehicular networks, which are kept an industrial secret, therefore impeding independent researchers from extracting information from these networks. This article describes a statistical and a neural network approach that allows reverse engineering proprietary controller area network (CAN)-protocols assuming they were designed using the data base CAN (DBC) file format. The proposed algorithms are tested with CAN traces taken from a real car. We show that our approaches can correctly reverse engineer CAN messages in an automated manner.
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
2843. Automatic classification of agricultural grains: comparison of neural networks
- Creator:
- Kayabasi, Ahmet , Toktas, Abdurrahim , Sabanci, Kadir , and Yigit, Enes
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- classification, agricultural grains, wheat grains, neural networks, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM)
- Language:
- English
- Description:
- In this study, applications of well-known neural networks such as artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and support vector machine (SVM) for wheat grain classification into three species are comparatively presented. The species of wheat grains which are Kama (#70), Rosa (#70) and Canadian (#70) are designated as outputs of neural network models. The classification is carried out through data of wheat grains (#210) acquired using X-ray technique. The data set includes seven grain's geometric parameters: Area, perimeter, compactness, length, width, asymmetry coefficient and groove length. The neural networks input with the geometric parameters are trained through 189 wheat grain data and their accuracies are tested via 21 data. The performance of neural network models is compared to each other with regard to their accuracy, efficiency and convenience. For testing data, the ANN, ANFIS and SVM models numerically calculate the outputs with mean absolute error (MAE) of 0.014, 0.018 and 0.135, and classify the grains with accuracy of 100 %, 100% and 95.23 %, respectively. Furthermore, data of 210 grains is synthetically increased to 3210 in order to investigate the proposed models under big data. It is seen that the models are more successful if the size of data is increased, as well. These results point out that the neural networks can be successfully applied to classification of agricultural grains whether they are properly modelled and trained.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
2844. Automatic determination of the deflections of the vertical: first scientific results
- Creator:
- Kudrys, Jacek
- Format:
- print, bez média, and svazek
- Type:
- article, články, model:article, and TEXT
- Subject:
- Geologie. Meteorologie. Klimatologie, geodynamika, geodynamics, deflection of the vertical, CCD observation, geoid determination, 7, and 551
- Language:
- English
- Description:
- The astrogeodetic method of detailed geoid determination need astronomical observations of longitude and latitude. Together with GPS observations it may be used to vertical deflections determination. In the article the portable system for automatic determination of astrogeodetic vertical deflection components developed at AGH University of Science and Technology is described. The design, main error sources, and preliminary results of the test measurements are presented., Jacek Kudrys., and Obsahuje bibliografii
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
2845. Automatic determination of vertical deflection components from GPS and zenithal star observations
- Creator:
- Kudrys, Jacek
- Format:
- print, bez média, and svazek
- Type:
- article, články, model:article, and TEXT
- Subject:
- Geologie. Meteorologie. Klimatologie, geodynamika, geodynamics, vertical deflection, CCD observation, geoid determination, 7, and 551
- Language:
- English
- Description:
- The known vertical deflection values can be utilised to increase geoid’s accuracy. One of the methods of vertical deflection components (ξ, η) determination is to compare astronomic and geodetic coordinates. Presently it is easy possible to obtain geodetic coordinates with high accuracy from GPS observation. In the article the methods of astronomical CCD observation with aid of two different optical systems are discussed. Project realisation is in preliminary stage and there are no results available yet., Jacek Kudrys., and Obsahuje bibliografické odkazy
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
2846. Automatic differentiation and its program realization
- Creator:
- Hartman, Jan, Lukšan, Ladislav, and Zítko, Jan
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- automatic differentiation, modeling languages, and systems for optimization
- Language:
- English
- Description:
- Automatic differentiation is an effective method for evaluating derivatives of function, which is defined by a formula or a program. Program for evaluating of value of function is by automatic differentiation modified to program, which also evaluates values of derivatives. Computed values are exact up to computer precision and their evaluation is very quick. In this article, we describe a program realization of automatic differentiation. This implementation is prepared in the system UFO, but its principles can be applied in other systems. We describe, how the operations are stored in the first part of the derivative computation and how the obtained records are effectively used in the second part of the computation.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
2847. Automatic Fingerprints Recording Systems. Ratha N., Boole R.
- Creator:
- Novák, Mirko
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Language:
- English
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
2848. Automatic generation of neural network structures using genetic algorithm
- Creator:
- Spišiak , Michal and Kozák, Štefan
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Artificial neural network, genetic algorithm, occurrence matrix, and nonlinear systems
- Language:
- English
- Description:
- This paper deals with a generalized automatic method used for designing artificial neural network (ANN) structures. One of the most important problems is designing the optimal ANN for many real applications. In this paper, two techniques for automatic finding an optimal ANN structure are proposed. They can be applied in real-time applications as well as in fast nonlinear processes. Both techniques proposed in this paper use the genetic algorithms (GA). The first proposed method deals with designing a structure with one hidden layer. The optimal structure has been verified on a nonlinear model of an isothermal reactor. The second algorithm allows designing ANN with an unlimited number of hidden layers each of which containing one neuron. This structure has been verified on a highly nonlinear model of a polymerization reactor. The obtained results have been compared with the results yielded by a fully connected ANN.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
2849. Automatic modularization of anns
- Creator:
- Jakša, Rudolf
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- structured (or modular) neural networks, structure optimization, modularization, and adaptive critic method
- Language:
- English
- Description:
- We propose automatic modularization method for artificial neural networks (ANNs). We treat modularization as an optimization task, therefore the optimization criteria are defined and the topology capable of continuous iterative modularization is introduced. The modularization process starts with unstructured plain network topology and iteratively builds up a modular structure. Automatic modularization approach not only learns to map inputs to outputs but it also tries to discover a structure of knowledge represented by training patterns.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
2850. Automobil na vodíkový pohon: realita a vyhliadky do budúcnosti
- Creator:
- Komanický, Vladimír
- Format:
- Type:
- model:article and TEXT
- Subject:
- fyzika, vodíkový pohon, physics, fuel cell cars, 6, and 53
- Language:
- Czech and English
- Description:
- Automobily na vodíkový pohon ponúkajú mnoho výhod v porovnaní s automobilom s tradičným spal'ovacím motorom. Ekologicky čistá a tichá prevádzka spojená s vysokou účinnosťou vodíkového palivového článku (VPČ) z nich robí atraktívnych kandidátov na automobily budúcnosti. V tomto článku stručne rozoberám históriu a vývoj VPČ, jeho dizajn ako aj problémy, ktoré je nutné odstranit aby mohla byť táto technológia uvedená v masovom rozsahu do praxe., Fuel cell (FC) cars offer many advantages when compared to cars with combustion engines. Ecologically clean, noise-free and their high fuel efficiency makes fuel cell powered cars attractive candidates for future automobiles. In this paper I briefly discuss the history, development and design of the FC as well as the problems still plaguing this technology and preventing its deployment on the mass scale., Vladimír Komanický., and Obsahuje seznam literatury
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public