923 research outputs found

    Mining high utility itemsets in massive transactional datasets

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    Mining High Utility Itemsets from a transaction database is to find itemsets that have utility beyond an user-specified threshold. Existing High Utility Itemsets mining algorithms suffer from many problems when being applied to massive transactional datasets. One major problem is the high memory dependency: the gigantic data structure built is assumed to fit in the computer main memory. This paper proposes a new disk-based High Utility Itemsets mining algorithm, which achieves its efficiency by applying three new ideas. First, transactional data is converted into a new database layout called Transactional Array that prevents multiple scanning of the database during the mining phase. Second, for each frequent item, a relatively small independent tree is built for summarizing co-occurrences. Finally, a simple and non-recursive mining process reduces the memory requirements as minimum candidacy generation and counting is needed. We have tested our algorithm on several very large transactional databases and the results show that our algorithm works efficiently

    Dispatching Vehicles Considering Uncertain Handling Times at Port Container Terminals

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    This paper considers the problem of vehicle dispatching at port container terminals in a dynamic environment. The problem deals with the assignment of delivery orders of containers to vehicles while taking into consideration the uncertainty in the travel times of the vehicles. Thus, a real-time vehicle dispatching algorithm is proposed for adaptation to the dynamic changes in the states of the container terminals. To evaluate the performance of the proposed algorithm, a simulation study was conducted by considering various values of decision parameters under the uncertainty in travel times. Further, the performance of the proposed algorithm was compared with those of heuristic algorithms from previous studies

    EFFECTIVE SOLUTIONS TO MEET STUDENTS' SATISFACTION FOR PHYSICAL EDUCATION ACTIVITIES AT HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION

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    Through the research, the topic has built four solutions to meet students' satisfaction with physical education (PE) activities at Ho Chi Minh City University of Technology and Education (HCMUTE). These include: strengthening movement activities, and extra-curricular activities; supplementing and updating documents and textbooks; improving teaching staff's qualifications, along with improving teaching, testing and evaluation methods; upgrading physical facilities for sports. After a period of application in practice, the solutions proposed by the topic have proven to be effective and meet the satisfaction of learners.  Article visualizations

    On Armstrong relations for strong dependencies

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    The strong dependency has been introduced and axiomatized in [2], [3], [4], [5]. The aim of this paper is to investigate on Armstrong relations for strong dependencies. We give a necessary and sufficient condition for an abitrary relation to be Armstrong relation of a given strong scheme. We also give an effective algorithm finding a relation r such that r is Armstrong relation of a given strong scheme G = (U,S) (i.e. Sr = S+, where Sr is a full family of strong dependencies of r, and S+ is a set of all strong dependencies that can be derived from S by the system of axioms). We estimate this algorithm. We show that the time complexity of this algorithm is polynomial in |U| and |S|

    DESIGNING HEDGE ALGEBRAIC CONTROLLER AND OPTIMIZING BY GENETIC ALGORITHM FOR SERIAL ROBOTS ADHERING TRAJECTORIES

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    In recent years, the application of hedge algebras in the field of control has been studied. The results show that this approach has many advantages. In additions, industrial robots are being well-developed and extensively used, especially in the industrial revolution 4.0. Accurate control of industrial robots is a class of problems that many scientists are interested in. In this paper, we design a controller based on hedge algebra for serial robots. The control rule is given by linguistic rule base system. The goal is to accurately control the moving robot arm which adheres given trajectories. Optimization of fuzzy parameters for the controller is done by genetic algorithms. The system has been simulated on the Matlab-Simulink software. The simulation results show that the orbital deviation is very small. Moreover, the controller worked well with correct control quality. This result once presents the simplicity and efficiency of the hedge algebras approach to control

    Some results related to dense families of database relations

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    The dense families of database relations were introduced by Järvinen [7]. The aim of this paper is to investigate some new properties of dense families of database relations, and their applications. That is, we characterize functional dependencies and minimal keys in terms of dense families. We give a necessary and sufficient condition for an abitrary family to be R— dense family. We prove that with a given relation R the equality set ER is an R—dense family whose size is at most m(m-1)/2, where m is the number of tuples in R. We also prove that the set of all minimal keys of relation R is the transversal hypergraph of the complement of the equality set ER. We give an effective algorithm finding all minimal keys of a given relation R. We also give an algorithm which from a given relation R finds a cover of functional dependencies that holds in R. The complexity of these algorithms is also esimated

    Some problems related to keys and the Boyce-Codd normal form

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    The aim of this paper is to investigate the connections between minimal keys and antikeys for special Sperner-systems by hypergraphs. The Boyce-Codd normal form and some related problems are also studied in this paper
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