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In this paper we report a novel application-based model as a suitable alternative for the classification and identification of attacks on a computer network, and thus guarantee its safety from HTTP protocol-based malicious commands. The proposed model is built on a self-recurrent neural network architecture based on wavelets with multidimensional radial wavelons, and is therefore suited to work online by analyzing non-linear patterns in real time to self-adjust to changes in its input environment. Six different neural network based systems have been modeled and simulated for comparison purposes in terms of overall performance, namely, a feed-forward neural network, an Elman network, a fully connected recurrent neural network, a recurrent neural network based on wavelets, a self-recurrent wavelet network and the proposed self-recurrent wavelet network with multidimensional radial wavelons. Within the models studied, this paper presents two recurrent architectures which use wavelet functions in their functionality in very distinct ways. The results confirm that recurrent architectures using wavelets obtain superior performance than their peers, in terms not only of the identification and classification of attacks, but also the speed of convergence.

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An automatic technique to improve the plantar surface model via Bezier networks is presented. This technique generates the foot sole model via Bezier networks based on surface points, which are retrieved via line projection. The surface model is defined by means of network weights and the control points, which are measured via line position by a Bezier network. Thus, the model represents the plantar surface with high accuracy. It is because the model passes through by all control points of the physical surface. Furthermore, the network reduces operations and memory size to calculate the surface. It is because the model is implemented with less mathematical terms than the traditional models. Also, the calibration of vision parameters is performed via laser line to avoid external calibration, which determines vision parameters outside of the vision system and increases the surface representation inaccuracy. Additionally, the shoe-last bottom is adjusted to plantar surface model. The viability of the proposed surface modeling is corroborated by an evaluation based on the speed, accuracy and memory size of the traditional surface models. Thus, the contribution of the proposed technique is elucidated.

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Speech recognition is one of the fundamental requirements for fully autonomous robotic systems nowadays. The objective of the presented work is to offer a smartphone based speech recognition system for ROS (Robot Operating System) based autonomous robotic systems. The proposed recognition process consists of three steps, namely acquisition, preprocessing, and

result extraction. In the contribution we also present a comparison by applying the proposed recognition process using Online

and Offline speech servers. The Online method uses Google speech server whereas the Offline uses Simon speech server. The

speech recognition and the robotic controlling system work under a server-client architecture. For the evaluation of the Online, we used an Android smartphone, a Pioneer-3DX robot, and Google speech server. For the Offline recognition evaluation, an

Android smartphone, a Pioneer-3AT and a standalone Simon speech server are used. The applications running on the smartphone

act like clients and communicate with both speech server and robotic system. The contribution provided in this paper is two fold: One using smartphone with Offline speech recognition server SimonDQGRQWKHRWKHUKDQGXWLOL]LQJ6LPRQ¶VYRLFHUHFRJQLWLRQ feature with robotic navigation on ROS platform.

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Recently, Li proposed a new password authentication and user anonymity scheme based on elliptic curve cryptography. In WKLVSDSHUZHZLOOVKRZWKDW/L¶VVFKHPHLVYXOQHUDEOHWRWKHLPSHUVRQDWLRQDWWDFNDQGWKHGHQLDORIVHUYLFHDWWDFN0RUHRYHr, we also point out that there is an error in his scheme. To overcome the weaknHVVHV RI /L¶V VFKHPH ZH SURSRVHG DQ HIILFLHQW password authentication scheme based on elliptic curve cryptography. The proposed scheme improves the security and efficiency of the authentication process.

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The article describes the parsing system of Lithuanian language and its accuracy. It is founded, why the rule-based method was chosen and it is shown, that the use of statistical methods for the Lithuanian language is not optimal. English language is few inflected and Lithuanian has very large amount of endings. One root can give 5-7 words with different endings in the English language, and in Lithuanian one root can give hundreds or even more than one thousand word forms. The statistical method needs all forms to have in corpus. Thus the Lithuanian language demands thousand times more text corpus than English. We have now thousand times less corpus. Thus we need to enlarge the Lithuanian corpus one million times and it is hard to realize because of small number of users, which can produce the Lithuanian texts.

In the English language, word order in a sentence is the most important criterion by determining the syntactic function of a ZRUG,Q/LWKXDQLDQODQJXDJHWKHZRUGRUGHUDOPRVWGRHVQ¶WKDYHDQ\V\QWDFWLFLQIRUPDWLRQ± it is cumulated in the endings. By reading the sentence we try to find agreeing endings and if it fails, the sentence remain inapprehensible. The sequence of lemmas gives us no thought, no meaning. In the systems of parsing of the English language the taking the syntactic information from word endings is not unforeseen. Thus we needed to create our own method of parsing, which takes into account the specific features of the Lithuanian language ± high inflection and free word order.

The software was tested with two sets of sentences. The sentences for the first test were selected at random from a variety of printed publications as well as from the corpus. The sentences for the second test were taken from coherent text. The difference of accuracy is very little ± 93.8% and 92%. This shows the stability of parsing method for the Lithuanian simple sentences.

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In recent years, both academia and the industry have seen a push for converting unstructured data, most commonly text, into structured representations. A relatively poorly explored challenge in this area is that of domain template construction: for a domain, we wish to find the attributes with which texts from that domain can be meaningfully represented. For example, given WKH GRPDLQ RI QHZV UHSRUWV RQ ERPELQJ DWWDFNV ZH ZRXOG OLNH WR LGHQWLI\ WKH H[LVWHQFH RI FRQFHSWV OLNH ³YLFWLP´ DQG ³SHUSHWUDWRU´ :H LQWURGXFH WZR QHZ PHWKRGV IRU WKLV WDVN ERWK RSHUDWLQJ RQ VHPDQWLF UHSUHsentations of input data and exploiting the hierarchical organization of features, something not explored in prior art. We evaluate on multiple GDWDVHWVGRPDLQV DQG DFKLHYH SHUIRUPDQFH DW OHDVW FRPSDUDEOH WR D VWDWH RI WKH DUW PHWKRG RQ D VHW RI ³UHDO ZRUOG´ VFHQDULRV while additionally identifying fine-grained type information for properties: for example, the bombing attack victim is found to be RIW\SH³GHIHQGHU´SROLFHPDQJXDUG:HDOVRSURYLGHWKHILUVWIXOO\GRFXPHQWHGHYDOXDWLRQPHWKRGRORJ\SXblicly available labeled datasets and golden standard outputs for this research problem, supporting and facilitating future work in the area.

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We studied outlier document filtering (ODF) for extractive sentence summarization. Our results are superior compared to WKHDYHUDJHRIWKHSDUWLFLSDQWV\VWHPV¶XVLQJ'8&)XUWKHUPRUHZHDGGH[WUDFWLYHSDUDJUDSKVXPPDUL]DWLRQWRWKHVDPH system. It is surprising that the results are nearly the same for ROUGE metrics. Although extractive paragraph summarization has a better performance for precision, extractive sentence summarization has a slightly better performance on the recall and F-Score which is the harmonic mean of recall and precision. The ODF is successful for both extractive sentence and paragraph summarization. The similarity metric (match percent) suggested in the article prevents the domination of longer sentences/paragraphs on shorter sentences/paragraphs in selection. As a result, the ODF provides the flexibility of paragraph extraction instead of sentence extraction for simplicity and readability and less work load.

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Hardware Description Languages (HDL) like VHDL are used to design and simulate programmable logic devices. Usually the description of the device under test consists of several processes. This concept introduces problems of how to test and verify complex systems. In this paper, we present a new framework called TestBenchMulti that is able to generate test stimuli for parallel VHDL designs. The framework combines Control Flow Graphs (CFGs), extension of Symbolic Execution (SE) and Satisfiability Modulo Theories (SMT) into a sequence of methods to generate stimuli capable of obtaining high code coverage. The experiments were carried out on synthesizable VHDL circuits at the behavioural level. The obtained code coverage results were confirmed in the real implementation using Xilinx FPGA hardware.

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SSN 1392±124X (print), ISSN 2335±884X (online) INFORMATION TECHNOLOGY AND CONTROL, 2014, T.43, Nr.4

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