Computer Science Journal (AGH University of Science and Technology, Krakow)
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GENERATING TURING MACHINES BY USE OF OTHER COMPUTATION MODELS
Get PDFFor each problem that can be solved there exists algorithm, which can be described with a program of Turing machin . Because this is very simple model programs tend to be very complicated and hard to analyse by human. The best practice to solve given type of problems istode neanewmodelofcomputationthatallowsforquickandeasyprogramming,andthen to emulate its operation with Turing machin . This article shows how to define most suitable model for computation on natural numbers and defines Turing machin that emulates its operation
FORMAL VERIFICATION OF REAL-TIME SYSTEM REQUIREMENTS
No full textThe methodology of system reąuirements verification presented in this paper is a proposition of a practical procedurę for reducing some negatives of the specification of reąuirements. The main problem that is considered is to create a complete description o f the system reąuirements without any negatives. Verification of the initially deftned reąuirements is based on the coloured Pctri nets. Those nets are useful for testing some properties of system reąuirements such as complete- ness, consistency and optimality. An example of the lift controller is presented
Causal Reversibility in Individual Token Interpretation of Petri Nets
Get PDFCausal reversibility in concurrent systems means that events that the origin of other events can only be undone after undoing of its consequences. In opposite to backtracking, the events which are independent of each other can be reversed in an arbitrary order, in the other words, we have flexible reversibility w.r.t the causality relation. An implementation of Individual token interpretation ofPetri Nets (IPNs) was been proposed by Rob Van Glabbeek et al, the present paper investigates into a study of causal reversibility within IPNs. Given N be an IPN, by adding an intuitive firing rule to undo transitions according to the causality relation, the coherence of N is assured, i.e., the set of all reachable states of N in the reversible version and that of the original one are identical. Furthermore, reversibility in N is flexible and their initial state can be accessible in reverse from any state. In this paper an approach for controllingcausal-reversibility within IPNs is proposed
Knowledge Graphs Effectiveness in Neural Machine Translation Improvement
Get PDFNeural Machine Translation (NMT) systems require a massive amount of Maintaining semantic relations between words during the translation process yields more accurate target-language output from Neural Machine Translation (NMT). Although difficult to achieve from training data alone, it is possible to leverage Knowledge Graphs (KGs) to retain source-language semantic relations in the corresponding target-language translation. The core idea is to use KG entity relations as embedding constraints to improve the mapping from source to target. This paper describes two embedding constraints, both of which employ Entity Linking (EL)---assigning a unique identity to entities---to associate words in training sentences with those in the KG: (1) a monolingual embedding constraint that supports an enhanced semantic representation of the source words through access to relations between entities in a KG; and (2) a bilingual embedding constraint that forces entity relations in the source-language to be carried over to the corresponding entities in the target-language translation. The method is evaluated for English-Spanish translation exploiting Freebase as a source of knowledge. Our experimental results show that exploiting KG information not only decreases the number of unknown words in the translation but also improves translation quality
Real-time interpolation of streaming data
Get PDFOne of the key elements of real-time -continuous cubic spline interpolation of streaming data is an estimator of the first derivative of the interpolated function that is more accurate than the ones based on finite difference schemas.Two such greedy look-ahead heuristic estimators (denoted as MinBE and MinAJ2) based on Calculus of Variations are formally defined (in closed form) together with the corresponding cubic splines they generate, and then comparatively evaluated in a series of numerical experiments involving different types of performance measures. The results presented show that the cubic Hermite splines generated by heuristic MinAJ2 significantly outperformed these based on finite difference schemas in terms of all tested performance measures (including convergence).The proposed approach is quite general. It can be directly applied to streams of univariate functional data like time-series. Multidimensional curves defined parametrically, after splitting, can be handled as well. The streaming character of the algorithm means that it can also be useful in processing data sets that are too large to fit in memory (e.g., edge computing devices, embedded time-series databases)
Alternating directions parallel hybrid memory iGRM direct solver for non-stationary simulations
Get PDFThe three-dimensional isogeometric analysis (IGA-FEM) is a modern method for simulation. The idea is to utilize B-splines or NURBS basis functions for both computational domain descriptions and the engineering computations. Refined isogeometric analysis (rIGA) employs a mixture of patches of elements with B-spline basis functions, and separators between them. It enables a reduction of the computational cost of direct solvers. Both IGA and rIGA come with challenging sparse matrix structure, that is expensive to generate. In this paper, we show a hybrid parallelization method to reduce the computational cost of the integration phase using hybrid-memory parallel machines. The two-level parallelization includes the partitioning of the computational mesh into sub-domains on the first level (MPI), and loop parallelization on the second level (OpenMP). We show that hybrid parallelization of the integration reduces the contribution of this phase significantly. Thus, alternative algorithms for fast isogeometric integration are not necessary
Extraction of Scores and Average From Algerian High-School Degree Transcripts
Get PDFA system for extracting scores and average from Algerian High School Degree Transcripts is proposed. The system extracts the scores and the average based on the localization of the tables gathering this information and it consists of several stages. After preprocessing, the system locates the tables using ruling-lines information as well as other text information. Therefore, the adopted localization approach can work even in the absence of certain ruling-lines or the erasure and discontinuity of lines. After that, the localized tables are segmented into columns and the columns into information cells. Finally, cells labeling is done based on the prior knowledge of the tables structure allowing to identify the scores and the average. Experiments have been conducted on a local dataset in order to evaluate the performances of our system and compare it with three public systems at three levels, and the obtained results show the effectiveness of our system
THE USE OF NEUTRAL NETWORK AND PORTFOLIO ANALYSIS IN FORECASTING SHARE PRICES AT THE STOCK EXCHANGE
No full textThe article presents the use of neural networks in decision making process on the Capital market. The author tried to show the efficiency of established solution in Polish reality which features different conditions in comparison with the markets of higher developed countries. The aim of the paper was to prove that neural networks are flexible tools which on one hand might be adju sted to investor’s reąuirements and on the other, can reduce equirements to his experience. The article is based on the author’s own research carried out by modelling neural network operation with a simulation program.The established Solutions are input which employs stocks portfolio computed on the basis of Markowitz portfolio theory and Sharpe’s model. According to the established propositions, the portfolio created in such a way is modified by neutral network in order to optimise a criterion which maximises the income of such a modified portfolio.A dctailed genesis of the established input vector and network structure are presented. It allows the reader to carry out his own research and create his own attitude towards applied values.The research results based on a real stock market database with the use of one-output networks predicting the price of a single company - Agros as well as networks predicting the desirable structure of the whole portfolio are presented. The effect of the network structure leaming para meters, input vector (not only as to the input quantity but also as to period of time they were col- lected) was examined. The dependence between the factors mentioned above such as input vec- tor and network structure were discussed.It seems that the presented paper has proved that some not widely spread methods with neural networks can become a competitive tool to optimisation methods
Functional Integrity of Some Class of Multi-Agent Systems
No full textThe interest in decentralized systems that arose in the eighties led to the development of multi-agent systems based on the concept of an autonomous agent. Multi-agent systems have a number of advantages and open up many new possibilities in creating IT systems, but many problems related to the operation of these systems remain to be solved. Such problems include the functional integrity of multi-agent systems. The functional integrity of a multiagent system can be defined, generally speaking, as the preservation of the basic functions of the system during its functioning. It can be analyzed from the point of view of various system functions (which should remain preserved) as well as from the point of view of various factors that may affect the loss or preservation of functional integrity by the system. The study examines the functional integrity of a multi-agent system depending on the number of agents (global and individual types). Agents during the system work generate agents of the same or different type, depending on their capabilities and needs of the system. The agent, having the opportunity to perceive the environment in his environment, does not have direct access to certain global information in the system. As a result, in many cases a given agent, when generating a new agent, cannot take into account all the important factor systems from the point of view of functional integrity. As a consequence, this leads to an excessive number of agents (system blockage), or an insufficient number, and to a complete lack of agents of a given type (loss of system function implemented by agents of a given type). The authors analyzing the behavior of multi-agent systems [8] point out that in addition to the numerous advantages that decentralized systems may have, they may also have a significant disadvantage. It consists in the fact that system elements, acting in a decentralized way, too often will take the initiative to communicate with other system elements. This will cause a large number of transmissions that are often unnecessary, and as a consequence, overloading the system with excessive transmissions and, as a result, a decrease in system performance, or even blocking it. The considerations were based on a simulation study of a certain class of multi-agent systems
Object Pose Estimation in Monocular Image Using Modified FDCM
Get PDFIn this paper, a new method for object detection and pose estimation in a monocular image is proposed based on FDCM method. it can detect object with high speed running time, even if the object was under the partial occlusion or in bad illumination. In addition, It requires only single template without any training process. The Modied FDCM based on FDCM with improvments, the LSD method was used in MFDCM instead of the line tting method, besides the integral distance transform was replaced with a distance transform image, and using an angular Voronoi diagram. In addition, the search process depends on Line segments based search instead of the sliding window search in FDCM. The MFDCM was evaluated by comparing it with FDCM in dierent scenarios and with other four methods: COF, HALCON, LINE2D, and BOLD using D-textureless dataset. The comparison results show that MFDCM was at least 14 times faster than FDCM in tested scenarios. Furthermore, it has the highest correct detection rate among all tested method with small advantage from COF and BLOD methods, while it was a little slower than LINE2D which was the fasted method among compared methods. The results proves that MFDCM able to detect and pose estimation of the objects in the clear or clustered background from a monocular image with high speed running time, even if the object was under the partial occlusion which makes it robust and reliable for real-time applications