Computer Science Journal (AGH University of Science and Technology, Krakow)
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A Survey on Syntactic Pattern Recognition Methods in Bioinformatics: Invited paper
No full textFormal tools and models of syntactic pattern recognition which are used in bioinformatics are introduced and characterized in the paper. They include, among others: stochastic (string) grammars and automata, hidden Markov models, programmed grammars, attributed grammars, stochastic tree grammars, Tree Adjoining Grammars (TAGs), algebraic dynamic programming, NLC- and NCE-type graph grammars, and algebraic graph transformation systems. The survey of applications of these formal tools and models in bioinformatics is presented
Efficient Selection Methods in Evolutionary Algorithms
Full text linkEvolutionary algorithms mimic some elements of the theory of evolution. The survival of individuals and the possibility of producing offspring play a huge role in the process of natural evolution. This process is called a natural selection. This mechanism is responsible for eliminating poor population members and gives the possibility of development for good ones. The evolutionary algorithm - an instance of evolution in the computer environment also requires a selection method, a computer version of natural selection. Widely used standard selection methods applied in evolutionary algorithms are usually derived from nature and prefer competition, randomness and some kind of ``fight\u27\u27 among individuals. But computer environment is quite different from nature. Computer populations of individuals are usually small, they easily suffer from a premature convergence to local extremes. To avoid this drawback, computer selection methods must have different features than natural selection. In the computer selection methods randomness, fight and competition should be controlled or influenced to operate to the desired extent. Several new methods of individual selection are proposed in this work: several kinds of mixed selection, an interval selection and a taboo selection. Also advantages of passing them into the evolutionary algorithm are shown, using examples based on searching for the maximum α-clique problem and traditional TSP in comparison with traditionally considered as very efficient tournament selection, considered ineffective proportional (roulette) selection and similar classical methods
Explainable Spark-based PSO Clustering for Intrusion Detection
Full text linkGiven the exponential growth of available data in large networks, the existence of rapid, transparent and explainable intrusion detection systems has become of high necessity to effectively discover attacks in such huge networks. To deal with this challenge, we propose a novel explainable intrusion detection system based on Spark, Particle Swarm Optimization (PSO) clustering and eXplainable Artificial Intelligence (XAI) techniques. Spark is used as a parallel processing model for the effective processing of large-scale data, PSO is integrated for improving the quality of the intrusion detection system by avoiding sensitive initialization and premature convergence of the clustering algorithm and finally, XAI techniques are used to enhance interpretability and explainability of intrusion recommendations by providing both micro and macro explanations of detected intrusions. Experiments are conducted on several large collections of real datasets to show the effectiveness of the proposed intrusion detection system in terms of explainability, scalability and accuracy. The proposed system has shown high transparency in assisting security experts and decision-makers to understand and interpret attack behavior
Formalization and analysis of uml 2.0 interaction overview diagram using maude rewriting logic language: Using Maude Rewriting Logic Language
No full textThe visual modeling language UML embodies object-oriented design principles.It provides a standard way to visualize the design of a system. It exploits a richset of well-defined graphical notations for creating abstract models. However,the power of UML is lessened through partially specified formal semantics. Indeed, UML notations are semi-formal and do not lead to fully formalized andexecutable semantics. Fortunately, UML diagrams are prone to early formalization. Formal methods are a valuable tool that can help overcome the UMLconstructs’ shortage of firm semantics. It is a powerful way to ascribe precise semantics to the graphical notations used in UML diagrams and models.Our work aims to support the semantics of the UML Interaction Overview Diagram. It introduces an approach to leveraging the strengths of the MaudeRewriting Logic language as a formal specification language. The proposal relies on a model-driven engineering approach. It aims to automate the UMLInteraction Overview Diagram’s mapping to a Maude language specification.The Maude language and its linked tools, including the Maude Model Checker,are used to analyze and verify the resulting Maude specification. Finally, anapplication example shows the feasibility and benefits of the proposed approach
Sentiment-aware Enhancements of PageRank-based Citation Metric, Impact Factor, and H-index for Ranking the Authors of Scholarly Articles
Full text linkHeretofore, the only way to evaluate an author has been frequency-based citation metrics. However, citations with a neutral sentiment possibly can not be considered in the same light as those expressing a positive or negative sentiment. We present sentiment-enhanced alternatives to three conventional metrics namely Impact Factor, H-index, and PageRank-based index. The proposal studies the impact of the proposed metrics on the ranking of authors. We experimented with two datasets, collectively comprising almost 20,000 citation sentences. The evaluation of the proposed metrics revealed a significant impact of sentiments on author ranking, evidenced by a weak Kendall coefficient for the Author Impact Factor and H-index. However, the PageRank-based metric showed a moderate to strong correlation, perhaps due to its prestige-based attributes. Furthermore, a remarkable Rank-biased deviation exceeding 28% was seen in all cases, indicating a stronger rank deviation in top-ordered ranks
Cv19t, a novel bio-socially inspired method, belonging to a new nature-inspired metaheuristics class
Full text linkThe paper presents CV19T, a novel bio-socially inspired meta-heuristic, wherethe cornerstone on which rests is the relationship between humans crowdingdensity, on one side, influenced by their mobility, mutual attractiveness to eachother and individual consciousness, and on the other side, the amazing speedof COVID-19 propagation. CV19T originality resides in the fact of combining features from two completely distinct and famous classes, namely: swarm intelligence and Evolutionary Algorithms. Moreover, CV19T extends elitismconcept (i.e. survival of the most powerful), on which are based courant evolutionist approaches to the survival of the most beneficial one. Also, CV19T shows that additional parameters can increase control of its behaviour, in manycases, leading to rise in its results relevance. To validate CV19T, it was testedon benchmarks set, including 23 functions (unimodal, multimodal and fixeddimensional multimodal) and 4 real-world problems
Finding The Inverse of A Polynomial Modulo in The Ring Z[X] Based on The Method of Undetermined Coefficients
Full text linkThis paper presents the theoretical foundations of finding the inverse of a polynomial modulo in the ring Z[x] based on the method of undetermined coefficients. The use of the latter makes it possible to significantly reduce the time complexity of calculations avoiding the operation of finding the greatest common divisor. An example of calculating the inverse of a polynomial modulo in the ring Z[x] based on the proposed approach is given. Analytical expressions of the time complexities of the developed and classical methods depending on the degrees of polynomials are built. The graphic dependence of the complexity of performing the operation of finding the inverse of a polynomial in the ring Z[x] is presented, which shows the advantages of the method based on undetermined coefficients. It is found that the efficiency of the developed method increases logarithmically with an increase in the degrees of polynomials. 
Securing centralized sdn control with distributed blockchain technology
Full text linkSoftware Defined Networks (SDN) advocates segregation of network control logic, forwarding functions and management applications into different planes to achieve network programmability, automated and dynamic flow control in next generation networks. It promotes deployment of novel and augmented network management functions to have flexible, robust, scalable and cost-effective network deployments. All these features introduce new research challenges and require secure communication protocols among the segregated network planes. This manuscript focuses on the security issue of southbound interface which operates between the SDN control and data plane. We have highlighted the security threats associated with an unprotected southbound interface and the issues related with the existing TLS based security solution. A lightweight blockchain based decentralized security solution is proposed for southbound interface to secure the resources of logically centralized SDN controllers and distributed forwarding devices from opponents. The proposed mechanism can operate in multi-domain SDN deployment and can be used with wide range of network controllers and data plane devices. In addition to it, the proposed security solution is analyzed in terms of security features, communication and reauthentication overhead
Hybrid end-to-end approach integrating online learning with face-identyfication system
Full text linkTo date, facial recognition has been one of the most intriguing, interesting research topics over years. It requires some specific face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition as well; however, all of these algorithms derive from heavy deep learning architectures that cause limitations for development, scalability, flawed accuracy, and deployment into publicity with mere CPU servers. It also calls for large datasets containing hundreds of thousands of records for training purposes. In this paper, we propose a full pipeline for an effective face recognition application which only uses a small Vietnamese celebrity dataset and CPU for training that can solve the leakage of data and the need for GPU devices. It is based on a face vector-to-string tokens algorithm then saves face’s properties into Elasticsearch for future retrieval, so the problem of online learning in Facial Recognition is also tackled. Comparison with another popular algorithm on the dataset, our proposed pipeline not only outweighs the accuracy counterpart, but it also achieves a very speedy time inference for a real-time face recognition application
A nature inspired hybrid partitional clustering method based on grey wolf optimization and JAYA algorithm: A NATURE INSPIRED HYBRID PARTITIONAL CLUSTERING METHOD BASED ON GWO AND JAYA ALGORITHM
No full textThis paper presents a hybrid meta-heuristic algorithm using Grey Wolf optimization (GWO) and JAYA algorithm for data clustering. The idea is use exploitative capability of JAYA algorithm in the explorative phase of GWO to form compact clusters. Here, instead of using one best and one worst solution for generating offspring, three best wolfs and three worst omega wolfs of the population are used. So, the best wolfs and worst omega wolfs assist in moving the new solutions towards the best solutions and simultaneously helps in staying away from the worst solutions. This enhances the chances of reaching the near optimal solutions. The superiority of the proposed method is compared with five promising algorithms, namely GWO, Sine-Cosine Algorithm (SCA), Particle Swarm Optimization (PSO), JAYA and K-means algorithms. The result obtained from the Duncan’s multiple range test and Nemenyi hypothesis based statistical test confirms the superiority and robustness of our proposed method