Search results for: Graph partitioning

Authors: Renáta Iváncsy, István Vajk

Abstract:

The various types of frequent pattern discovery problem, namely, the frequent itemset, sequence and graph mining problems are solved in different ways which are, however, in certain aspects similar. The main approach of discovering such patterns can be classified into two main classes, namely, in the class of the levelwise methods and in that of the database projection-based methods. The level-wise algorithms use in general clever indexing structures for discovering the patterns. In this paper a new approach is proposed for discovering frequent sequences and tree-like patterns efficiently that is based on the level-wise issue. Because the level-wise algorithms spend a lot of time for the subpattern testing problem, the new approach introduces the idea of using automaton theory to solve this problem.

Keywords: Frequent pattern discovery, graph mining, pushdownautomaton, sequence mining, state machine, tree mining.

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Authors: Chetneti Srisa-an

Abstract:

In Knowledge and Data Engineering field, relational database is the best repository to store data in a real world. It has been using around the world more than eight decades. Normalization is the most important process for the analysis and design of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. Normalization is a major task in the design of relational databases. Despite its importance, very few algorithms have been developed to be used in the design of commercial automatic normalization tools. It is also rare technique to do it automatically rather manually. Moreover, for a large and complex database as of now, it make even harder to do it manually. This paper presents a new complete automated relational database normalization method. It produces the directed graph and spanning tree, first. It then proceeds with generating the 2NF, 3NF and also BCNF normal forms. The benefit of this new algorithm is that it can cope with a large set of complex function dependencies.

Keywords: Relational Database, Functional Dependency, Automatic Normalization, Primary Key, Spanning tree.

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Authors: Lu Zhang, Chunping Li, Jun Liu, Hui Wang

Abstract:

Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.

Keywords: Text classification, Text clustering, Text similarity, Wikipedia

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Authors: Dong He Nam, Eric C. Mousset, David C. Levy

Abstract:

The evolution of current modeling specifications gives rise to the problem of generating automated test cases from a variety of application tools. Past endeavours on behavioural testing of UML statecharts have not systematically leveraged the potential of existing graph theory for testing of objects. Therefore there exists a need for a simple, tool-independent, and effective method for automatic test generation. An architecture, codenamed ACUTE-J (Automated stateChart Unit Testing Engine for Java), for automating the unit test generation process is presented. A sequential approach for converting UML statechart diagrams to JUnit test classes is described, with the application of existing graph theory. Research byproducts such as a universal XML Schema and API for statechart-driven testing are also proposed. The result from a Java implementation of ACUTE-J is discussed in brief. The Chinese Postman algorithm is utilised as an illustration for a run-through of the ACUTE-J architecture.

Keywords: Automated testing, model based testing, statechart testing, UML, unit testing.

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Authors: Mohammad Akbarpour, Reza Nasiri Mahalati, Caro Lucas

Abstract:

The existence of many biological systems, especially human societies, is based on cooperative behavior [1, 2]. If natural selection favors selfish individuals, then what mechanism is at work that we see so many cooperative behaviors? One answer is the effect of network structure. On a graph, cooperators can evolve by forming network bunches [2, 3, 4]. In a research, Ohtsuki et al used the idea of iterated prisoners- dilemma on a graph to model an evolutionary game. They showed that the average number of neighbors plays an important role in determining whether cooperation is the ESS of the system or not [3]. In this paper, we are going to study the dynamics of evolution of cooperation in a social network. We show that during evolution, the ratio of cooperators among individuals with fewer neighbors to cooperators among other individuals is greater than unity. The extent to which the fitness function depends on the payoff of the game determines this ratio.

Keywords: Evolution of cooperation, Iterated prisoner's dilemma, Model dynamics, Social network structure, Intensity of selection.

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Authors: Daniel Rivero, Julián Dorado, Juan R. Rabuñal, Alejandro Pazos, Javier Pereira

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The development of Artificial Neural Networks (ANNs) is usually a slow process in which the human expert has to test several architectures until he finds the one that achieves best results to solve a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs. To do this, the GP algorithm had to be changed in order to work with graph structures, so ANNs can be developed. This technique also allows the obtaining of simplified networks that solve the problem with a small group of neurons. In order to measure the performance of the system and to compare the results with other ANN development methods by means of Evolutionary Computation (EC) techniques, several tests were performed with problems based on some of the most used test databases. The results of those comparisons show that the system achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques.

Keywords: Artificial Neural Networks, Evolutionary Computation, Genetic Programming.

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Authors: Mouataz Zreika, Maria Estela Varua

Abstract:

Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: Clustering, force-directed, graph drawing, stock investment analysis.

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Authors: Mohammad Pooyan, Ali Taheri, Morteza Moazami-Goudarzi, Iman Saboori

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In this paper we present a novel approach for wavelet compression of electrocardiogram (ECG) signals based on the set partitioning in hierarchical trees (SPIHT) coding algorithm. SPIHT algorithm has achieved prominent success in image compression. Here we use a modified version of SPIHT for one dimensional signals. We applied wavelet transform with SPIHT coding algorithm on different records of MIT-BIH database. The results show the high efficiency of this method in ECG compression.

Keywords: ECG compression, wavelet, SPIHT.

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Authors: Moustapha Bande, Hakima Ould-Slimane, Hanifa Boucheneb

Abstract:

Software development for complex systems requires efficient and automatic tools that can be used to verify the satisfiability of some critical properties such as security ones. With the emergence of Aspect-Oriented Programming (AOP), considerable work has been done in order to better modularize the separation of concerns in the software design and implementation. The goal is to prevent the cross-cutting concerns to be scattered across the multiple modules of the program and tangled with other modules. One of the key challenges in the aspect-oriented programs is to be sure that all the pieces put together at the weaving time ensure the satisfiability of the overall system requirements. Our paper focuses on this problem and proposes a formal property verification approach for a given property from the woven program. The approach is based on the control flow graph (CFG) of the woven program, and the use of a satisfiability modulo theories (SMT) solver to check whether each property (represented par one aspect) is satisfied or not once the weaving is done.

Keywords: Aspect-oriented programming, control flow graph, satisfiability modulo theories, property verification.

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Authors: Rafat Alshorman, Walter Hussak

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In mobile environments, unspecified numbers of transactions arrive in continuous streams. To prove correctness of their concurrent execution a method of modelling an infinite number of transactions is needed. Standard database techniques model fixed finite schedules of transactions. Lately, techniques based on temporal logic have been proposed as suitable for modelling infinite schedules. The drawback of these techniques is that proving the basic serializability correctness condition is impractical, as encoding (the absence of) conflict cyclicity within large sets of transactions results in prohibitively large temporal logic formulae. In this paper, we show that, under certain common assumptions on the graph structure of data items accessed by the transactions, conflict cyclicity need only be checked within all possible pairs of transactions. This results in formulae of considerably reduced size in any temporal-logic-based approach to proving serializability, and scales to arbitrary numbers of transactions.

Keywords: multi-step transactions, serializability, directed graph.

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Authors: Young Gi Byun, Yong Huh, Kiyun Yu, Yong Il Kim

Abstract:

Spatial outliers in remotely sensed imageries represent observed quantities showing unusual values compared to their neighbor pixel values. There have been various methods to detect the spatial outliers based on spatial autocorrelations in statistics and data mining. These methods may be applied in detecting forest fire pixels in the MODIS imageries from NASA-s AQUA satellite. This is because the forest fire detection can be referred to as finding spatial outliers using spatial variation of brightness temperature. This point is what distinguishes our approach from the traditional fire detection methods. In this paper, we propose a graph-based forest fire detection algorithm which is based on spatial outlier detection methods, and test the proposed algorithm to evaluate its applicability. For this the ordinary scatter plot and Moran-s scatter plot were used. In order to evaluate the proposed algorithm, the results were compared with the MODIS fire product provided by the NASA MODIS Science Team, which showed the possibility of the proposed algorithm in detecting the fire pixels.

Keywords: Spatial Outlier Detection, MODIS, Forest Fire

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Authors: M. Derakhshanfar, B. Minaei-Bidgoli

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Spatial trends are one of the valuable patterns in geo databases. They play an important role in data analysis and knowledge discovery from spatial data. A spatial trend is a regular change of one or more non spatial attributes when spatially moving away from a start object. Spatial trend detection is a graph search problem therefore heuristic methods can be good solution. Artificial immune system (AIS) is a special method for searching and optimizing. AIS is a novel evolutionary paradigm inspired by the biological immune system. The models based on immune system principles, such as the clonal selection theory, the immune network model or the negative selection algorithm, have been finding increasing applications in fields of science and engineering. In this paper, we develop a novel immunological algorithm based on clonal selection algorithm (CSA) for spatial trend detection. We are created neighborhood graph and neighborhood path, then select spatial trends that their affinity is high for antibody. In an evolutionary process with artificial immune algorithm, affinity of low trends is increased with mutation until stop condition is satisfied.

Keywords: Spatial Data Mining, Spatial Trend Detection, Heuristic Methods, Artificial Immune System, Clonal Selection Algorithm (CSA)

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom

Abstract:

Nowadays the promotion of the public transportation system in the Bangkok Metropolitan Area is increased such as the “Free Bus for Thai Citizen” Campaign and the prospect of the several MRT       routes to increase the convenient and comfortable to the Bangkok Metropolitan area citizens. But citizens do not make full use of them it because the citizens are lack of the data and information and also the confident to the public transportation system of Thailand especially in the time and safety aspects. This research is the Public Transport Planning System by Dijkstra Algorithm: Case Study Bangkok Metropolitan Area by focusing on buses, BTS and MRT schedules/routes to give the most information to passengers. They can choose the way and the routes easily by using Dijkstra STAR Algorithm of Graph Theory which also shows the fare of the trip. This Application was evaluated by 30 normal users to find the mean and standard deviation of the developed system. Results of the evaluation showed that system is at a good level of satisfaction (4.20 and 0.40). From these results we can conclude that the system can be used properly and effectively according to the objective.

Keywords: Dijkstra Algorithm, Graph Theory, Shortest Route, Public Transport, Bangkok Metropolitan Area.

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Authors: Noura Boudiaf, Allaoua Chaoui

Abstract:

To analyze the behavior of Petri nets, the accessibility graph and Model Checking are widely used. However, if the analyzed Petri net is unbounded then the accessibility graph becomes infinite and Model Checking can not be used even for small Petri nets. ECATNets [2] are a category of algebraic Petri nets. The main feature of ECATNets is their sound and complete semantics based on rewriting logic [8] and its language Maude [9]. ECATNets analysis may be done by using techniques of accessibility analysis and Model Checking defined in Maude. But, these two techniques supported by Maude do not work also with infinite-states systems. As a category of Petri nets, ECATNets can be unbounded and so infinite systems. In order to know if we can apply accessibility analysis and Model Checking of Maude to an ECATNet, we propose in this paper an algorithm allowing the detection if the ECATNet is bounded or not. Moreover, we propose a rewriting logic based tool implementing this algorithm. We show that the development of this tool using the Maude system is facilitated thanks to the reflectivity of the rewriting logic. Indeed, the self-interpretation of this logic allows us both the modelling of an ECATNet and acting on it.

Keywords: ECATNets, Rewriting Logic, Maude, Finite-stateSystems, Infinite-state Systems, Boundness Property Checking.

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Authors: Omar B. Yaakob, Yasser M. Ahmed, Ahmad F. Said

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There is an essential need for obtaining the mathematical representation of fish body undulations, which can be used for designing and building new innovative types of marine propulsion systems with less environmental impact. This research work presents a case study to derive the mathematical model for fish body movement. Observation and capturing image methods were used in this study in order to obtain a mathematical representation of Clariasbatrachus fish (catfish). An experiment was conducted by using an aquarium with dimension 0.609 m x 0.304 m x 0.304 m, and a 0.5 m ruler was attached at the base of the aquarium. Progressive Scan Monochrome Camera was positioned at 1.8 m above the base of the aquarium to provide swimming sequences. Seven points were marked on the fish body using white marker to indicate the fish movement and measuring the amplitude of undulation. Images from video recordings (20 frames/s) were analyzed frame by frame using local coordinate system, with time interval 0.05 s. The amplitudes of undulations were obtained for image analysis from each point that has been marked on fish body. A graph of amplitude of undulations versus time was plotted by using computer to derive a mathematical fit. The function for the graph is polynomial with nine orders.

Keywords: Fish locomotion, body undulation, steady and unsteady swimming modes.

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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Authors: S. Pramanik

Abstract:

Since the early ages, the Hindu temples have been interpreted through various Vedic philosophies. These temples are visited by pilgrims which demonstrate the rituals and religious belief of communities, reflecting a variety of actions and behaviors. Darsana— a direct seeing, is a part of the pilgrimage activity. During the process of Darsana, a devotee is prepared for entry in the temple to realize the cognizing Truth culminating in visualizing the idol of God, placed at the Garbhagriha (sanctum sanctorum). For this, the pilgrim must pass through a sequential arrangement of spaces. During the process of progress, the pilgrims visualize the spaces differently from various points of views. The viewpoints create a variety of spatial patterns in the minds of pilgrims coherent to the Hindu philosophies. The space organization and its order are perceived by various techniques of spatial analysis. A temple, as examples of Kalinga stylistic variations, has been chosen for the study. This paper intends to demonstrate some visual patterns generated during the process of Darsana (visibility) and its accessibility by Point Isovist Studies and Visibility Graph Analysis from the entrance (Simha Dwara) to The Sanctum sanctorum (Garbhagriha).

Keywords: Hindu Temple Architecture, Point Isovist, space syntax analysis, visibility graph analysis.

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Authors: Kemal Efe, Gui-Liang Feng

Abstract:

The optimal bisection width of r-dimensional N× · · ·× N grid is known to be Nr-1 when N is even, but when N is odd, only approximate values are available. This paper shows that the exact bisection width of grid is Nr -1 N-1 when N is odd.

Keywords: Grids, Parallel Architectures, Graph Bisection, VLSI Layouts.

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Authors: Ferenc Peter Pach, Janos Abonyi

Abstract:

This paper focuses on the data-driven generation of fuzzy IF...THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the a priori fuzzy clustering based partitioning of the continuous input variables. An application study is also presented, where the developed methods are tested on the well known Wisconsin Breast Cancer classification problem.

Keywords:

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Authors: Rupali Verma, Maitreyee Dutta, Renu Vig

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Encryption and decryption in RSA are done by modular exponentiation which is achieved by repeated modular multiplication. Hence efficiency of modular multiplication directly determines the efficiency of RSA cryptosystem. This paper designs a Modified Montgomery Modular Multiplication in which addition of operands is computed by 4:2 compressor. The basic logic operations in addition are partitioned over two iterations such that parallel computations are performed. This reduces the critical path delay of proposed Montgomery design. The proposed design and RSA are implemented on Virtex 2 and Virtex 5 FPGAs. The two factors partitioning and parallelism have improved the frequency and throughput of proposed design.

Keywords: RSA, Montgomery modular multiplication, 4:2 compressor, FPGA.

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Authors: Hui-Chuan Lu

Abstract:

A perfect secret-sharing scheme is a method to distribute a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of participants in any unqualified subset is statistically independent of the secret. The collection of all qualified subsets is called the access structure of the perfect secret-sharing scheme. In a graph-based access structure, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme  realizing the access structure based on G is defined as AR = (Pv2V (G) H(v))/(|V (G)|H(s)), where s is the secret and v is the share of v, both are random variables from  and H is the Shannon entropy. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing a given access structure is called the optimal average information ratio of that access structure. Most known results about the optimal average information ratio give upper bounds or lower bounds on it. In this present structures based on bipartite graphs and determine the exact values of the optimal average information ratio of some infinite classes of them.

Keywords: secret-sharing scheme, average information ratio, star covering, core sequence.

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

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In this paper, the problem of stability criteria for Markovian jumping BAM neural networks with leakage and discrete delays has been investigated. Some new sufficient condition are derived based on a novel Lyapunov-Krasovskii functional approach. These new criteria based on delay partitioning idea are proved to be less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, one numerical example is given to illustrate the the usefulness and feasibility of the proposed main results.

Keywords: Stability, Markovian jumping neural networks, Timevarying delays, Linear matrix inequality.

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Authors: Yuan-Kang Shih, Shu-Li Chang, Shin-Shin Kao

Abstract:

Qk n has been shown as an alternative to the hypercube family. For any even integer k ≥ 4 and any integer n ≥ 2, Qk n is a bipartite graph. In this paper, we will prove that given any pair of vertices, w and b, from different partite sets of Qk n, there exist 2n internally disjoint paths between w and b, denoted by {Pi | 0 ≤ i ≤ 2n-1}, such that 2n-1 i=0 Pi covers all vertices of Qk n. The result is optimal since each vertex of Qk n has exactly 2n neighbors.

Keywords: container, Hamiltonian, k-ary n-cube, m*-connected.

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Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

Abstract:

One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: Malware detection, network security, targeted attack.

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Authors: Shih-Yi Chao

Abstract:

The similarity comparison of RNA secondary structures is important in studying the functions of RNAs. In recent years, most existing tools represent the secondary structures by tree-based presentation and calculate the similarity by tree alignment distance. Different to previous approaches, we propose a new method based on maximum clique detection algorithm to extract the maximum common structural elements in compared RNA secondary structures. A new graph-based similarity measurement and maximum common subgraph detection procedures for comparing purely RNA secondary structures is introduced. Given two RNA secondary structures, the proposed algorithm consists of a process to determine the score of the structural similarity, followed by comparing vertices labelling, the labelled edges and the exact degree of each vertex. The proposed algorithm also consists of a process to extract the common structural elements between compared secondary structures based on a proposed maximum clique detection of the problem. This graph-based model also can work with NC-IUB code to perform the pattern-based searching. Therefore, it can be used to identify functional RNA motifs from database or to extract common substructures between complex RNA secondary structures. We have proved the performance of this proposed algorithm by experimental results. It provides a new idea of comparing RNA secondary structures. This tool is helpful to those who are interested in structural bioinformatics.

Keywords: Clique detection, labeled vertices, RNA secondary structures, subgraph, similarity.

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Authors: Atamas N. A., Atamas A. A.

Abstract:

Energetic and structural results for ethanol-water mixtures as a function of the mole fraction were calculated using Monte Carlo methodology. Energy partitioning results obtained for equimolar water-ethanol mixture and ether organic liquids are compared. It has been shown that at xet=0.22 the RDFs for waterethanol and ethanol-ethanol interactions indicated strong hydrophobic interactions between ethanol molecules and the local structure of solution is less structured at this concentration as at ether ones. Results obtained for ethanol-water mixture as a function of concentration are in good agreement with the experimental data.

Keywords: Ethanol, molecular liquids, Monte Carlo, water, thermodynamics.

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Authors: Kyekyung Kim, Sangseung Kang, Suyoung Chi, Jaehong Kim

Abstract:

In recent years, IT convergence technology has been developed to get creative solution by combining robotics or sports science technology. Object detection and recognition have mainly applied to sports science field that has processed by recognizing face and by tracking human body. But object detection and recognition using vision sensor is challenge task in real world because of illumination. In this paper, object detection and recognition using vision sensor applied to sports simulator has been introduced. Face recognition has been processed to identify user and to update automatically a person athletic recording. Human body has tracked to offer a most accurate way of riding horse simulator. Combined image processing has been processed to reduce illumination adverse affect because illumination has caused low performance in detection and recognition in real world application filed. Face has recognized using standard face graph and human body has tracked using pose model, which has composed of feature nodes generated diverse face and pose images. Face recognition using Gabor wavelet and pose recognition using pose graph is robust to real application. We have simulated using ETRI database, which has constructed on horse riding simulator.

Keywords: Horse riding simulator, Object detection, Object recognition, User identification, Pose recognition.

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Authors: Hui-Chuan Lu

Abstract:

In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.

Keywords: Secret-sharing scheme, average information ratio, star covering, deduction, core cluster.

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Authors: Alessandro Cincotti, Timothee Bossart

Abstract:

Col is a classic combinatorial game played on graphs and to solve a general instance is a PSPACE-complete problem. However, winning strategies can be found for some specific graph instances. In this paper, the solution of Col on complete k-ary trees is presented.

Keywords: Combinatorial game, Complete k-ary tree, Mapcoloring game.

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Authors: Konstantza Tonova, Ivan Svinyarov, Milen G. Bogdanov

Abstract:

Ionic liquids consisting of a phosphonium cationic moiety and a saccharinate anion are synthesized and compared with their precursors, phosphonium chlorides, in reference to their extraction efficiency towards L-lactic acid. On the base of measurements of the acid and the water partitioning in the equilibrium biphasic systems, the molar ratios between acid, water and ionic liquid are estimated which allows to deduce the lactic acid extractive pathway. The effect of a salting-out addition that strengthens hydrophobicity in both phases is studied in view to reveal the best biphasic system with respect to IL low toxicity and high extraction efficiency.

Keywords: Biphasic system, Extraction, Ionic liquids, Lactic acid.

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