Informatica

Similarity searching has become widely available in many on-line archives of multimedia data. Users accessing such systems look for data items similar to their specific query object and typically refine results by re-running the search with a query from the results. We study this issue and propose a mechanism of approximate kNN query evaluation that incorporates statistics of accessing index data partitions. Apart from the distance between database objects, it also considers the prior query answers to prioritize index partitions containing frequently retrieved data, so evaluating repetitive similar queries more efficiently. We verify this concept in a number of experiments.

Computational thinking is an increasingly important focus in computer science or informatics curricula around the world, and ways of incorporating it into the school curricula are being sought. The Bebras contest on informatics, which originated 12 years ago and now involves around 50 countries, consists of short problem-solving tasks based on topics in informatics. Bebras tasks engender the development of computational thinking skills by incorporating abstraction, algorithmic thinking, decomposition, evaluation and generalization. Bebras tasks cover a range of informatics concepts including algorithms and data structures, programming, networking, databases and social and ethical issues. Having built up a substantial number of Bebras tasks over 12 years it is important to be able to categorize them so that they can be easily accessed by the Bebras community and teachers within schools. The categorization of tasks within Bebras is important as it ensures that tasks span a wide range of topics; there have been several categorization schemes suggested to date. In this paper we present a new two-dimensional categorization system that takes account of computational thinking skills as well as content knowledge. Examples are given from recent tasks that illustrate the role that Bebras can play in the development of computational thinking skills.

Data involving spatial and/or temporal attributes are often represented at different levels of granularity in different source schemata. In this work, a model of such multigranular data is developed, which supports not only the usual order structure on granules, but also lattice-like join and disjointness operators for relating such granules in much more complex ways. In addition, a model for multigranular thematic attributes, to which aggregation operators are applied, is provided. Finally, the notion of a thematic multigranular comparison dependency, generalizing ordinary functional and order dependencies but specifically designed to model the kinds of functional and order dependencies which arise in the multigranular context, and in particular incorporating aggregation into the definition of the constraint, is developed.

The redundancy allocation problem (RAP) has been studied for many different system structures, objective functions, and distribution assumptions. In this paper, we present a problem formulation and a solution methodology to maximize the system steady-state availability and minimize the system cost for the repairable series-parallel system designs. In the proposed approach, the components’ time-to-failure (TTF) and time-to-repair (TTR) can follow any distribution such as the Gamma, Normal, Weibull, etc. We estimate an approximation of the steady-state availability of each subsystem in the series-parallel system with an individual meta-model. Design of experiment (DOE), simulation and the stepwise regression are used to build these meta-models. Face centred design, which is a type of central composite design is used to design experiments. According to a max–min approach, obtained meta-models are utilized for modelling the problem alongside the cost function of the system. We use the augmented ε-constraint method to reformulate the problem and solve the model. An illustrative example which uses the Gamma distribution for TTF and TTR is explained to represent the performance of the proposed approach. The results of the example show that the proposed approach has a good performance to obtain Pareto (near-Pareto) optimal solutions (system configurations).

Analysing massive amounts of data and extracting value from it has become key across different disciplines. As the amounts of data grow rapidly, current approaches for data analysis are no longer efficient. This is particularly true for clustering algorithms where distance calculations between pairs of points dominate overall time: the more data points are in the dataset, the bigger the share of time needed for distance calculations.

Continuous query is a monitoring query issued by a moving object to keep the query condition satisfied. In the continuous query, the safe-region method is preferable to reduce the load for several requests on the server. A safe-region is a region in which the query result is unchanged, and it is created and sent to the moving object with the query result. The moving object always checks the current position in the region. When it leaves the region, it requests a new result to the server. Safe-region generation methods have been eagerly discussed for simple query types, including kNN, distance range, and RkNN queries. This paper challenges to generate the safe-region for trip route planning queries (TRPQ). This type of query is very time consuming even for snap-shot queries, and therefore, there are many restrictions on the safe-region generation methods in existing studies. This paper first investigates the property of the safe-region on TRPQ, and then proposes two types of efficient algorithms, the preceding rival addition (PRA) and the tardy rival addition (TRA) algorithms. The former algorithm runs fast, however, it still requires long processing time when the density of the data object is high. The latter algorithm is very fast independent of the density of data objects, however, the safe-region generated by TRA becomes about 5% larger in the size of generated safe-region. We evaluate the performance through intensive experiments.

A novel approach to pricing on data marketplaces is proposed, which is based on the Name Your Own Price (NYOP) principle: customers suggest their own price for a (relational) data product and in return receive a custom-tailored one. The result is a fair pricing scheme where sellers can achieve a higher revenue, while buyers receive a product which matches both their preferences and budget. NYOP is contrasted with previous research on view-based pricing on data marketplaces as well as on discount schemes to increase revenue.

The aim of this manuscript is to propose a new extension of the MULTIMOORA method adapted for usage with a neutrosophic set. By using single valued neutrosophic sets, the MULTIMOORA method can be more efficient for solving complex problems whose solving requires assessment and prediction, i.e. those problems associated with inaccurate and unreliable data. The suitability of the proposed approach is presented through an example.

To provide better overall performance, identity (ID)-based signcryption (IBSC) has been constructed by combining ID-based signature (IBS) and ID-based encryption (IBE) in a secure manner. Undoubtedly, the IBSC fulfills the authentication and the confidentiality by signature and encryption, respectively. All the previously proposed IBSC schemes are inseparable in the sense that the two-layer sign-then-encrypt procedure must be performed only by the same entity. However, the entities, such as wireless sensors and smart cards, are resource-constrained and become time consuming in executing the two-layer sign-then-encrypt procedure. Nowadays, the usage of mobile cloud computing is gaining expanding interest which provides scalable and virtualized services over the Internet or wireless networks while users with resource-constrained devices can enjoy the advantages of mobile cloud computing environments. Hence, we aim to reduce the computational cost for resource-constrained devices by employing a third party. In this article, we present the first separable ID-based signcryption (SIBSC) scheme in which the signing and encrypting layers are performed by the device and a third party, respectively. Under the computation Diffie–Hellman (CDH) and bilinear Diffie–Hellman (BDH) assumptions, we demonstrate that the proposed SIBSC scheme offers the provable security of authentication and confidentiality while retaining communication performance.