Testability of Switching Lattices in the Cellular Fault Model

A switching lattice is a two-dimensional array of four-terminal switches implemented in its cells. Each switch is linked to the four neighbors and is connected with them when the switch is ON, or is disconnected when the switch is OFF. Recently, with the advent of a variety of emerging nanoscale technologies based on regular arrays of switches, lattices of multi-terminal switches, originally introduced by Akers in 1972, have found a renewed interest. In this paper, the testability under the Cellular Fault Model (CFM) of switching lattices is defined and analyzed. Moreover, some techniques for improving the testability of lattices are discussed and experimentally evaluated

Computing the full quotient in bi-decomposition by approximation

Bi-decomposition is a design technique widely used to realize logic functions by the composition of simpler components. It can be seen as a form of Boolean division, where a given function is split into a divisor and quotient (and a remainder, if needed). The key questions are how to find a good divisor and then how to compute the quotient. In this paper we choose as divisor an approximation of the given function, and characterize the incompletely specified function which describes the full flexibility for the quotient. We report at the end preliminary experiments for bi-decomposition based on two AND-like operators with a divisor approximation from 1 to 0, and discuss the impact of the approximation error rate on the final area of the components in the case of synthesis by three-level XOR-AND-OR forms

Computing with nano-crossbar arrays: Logic synthesis and fault tolerance

Nano-crossbar arrays have emerged as a strong candidate technology to replace CMOS in near future. They are regular and dense structures, and can be fabricated such that each crosspoint can be used as a conventional electronic component such as a diode, a FET, or a switch. This is a unique opportunity that allows us to integrate well developed conventional circuit design techniques into nano-crossbar arrays. Motivated by this, our project aims to develop a complete synthesis and performance optimization methodology for switching nano-crossbar arrays that leads to the design and construction of an emerging nanocomputer. First two work packages of the project are presented in this paper. These packages are on logic synthesis that aims to implement Boolean functions with nano-crossbar arrays with area optimization, and fault tolerance that aims to provide a full methodology in the presence of high fault densities and extreme parametric variations in nano-crossbar architectures

Data protection in Cloud scenarios

We present a brief overview of the main challenges related to data protection that need to be addressed when data are stored, processed, or managed in the cloud. We also discuss emerging approaches and directions to address such challenges

Utility Promises of Self-Organising Maps in Privacy Preserving Data Mining

Data mining techniques are highly efficient in sifting through big data to extract hidden knowledge and assist evidence-based decisions. However, it poses severe threats to individuals’ privacy because it can be exploited to allow inferences to be made on sensitive data. Researchers have proposed several privacy-preserving data mining techniques to address this challenge. One unique method is by extending anonymisation privacy models in data mining processes to enhance privacy and utility. Several published works in this area have utilised clustering techniques to enforce anonymisation models on private data, which work by grouping the data into clusters using a quality measure and then generalise the data in each group separately to achieve an anonymisation threshold. Although they are highly efficient and practical, however guaranteeing adequate balance between data utility and privacy protection remains a challenge. In addition to this, existing approaches do not work well with high-dimensional data, since it is difficult to develop good groupings without incurring excessive information loss. Our work aims to overcome these challenges by proposing a hybrid approach, combining self organising maps with conventional privacy based clustering algorithms. The main contribution of this paper is to show that, dimensionality reduction techniques can improve the anonymisation process by incurring less information loss, thus producing a more desirable balance between privacy and utility properties

Uma abordagem para o ensino de produtos notáveis em uma classe inclusiva: o caso de uma aluna com deficiência visual

Acompanha: Produtos notáveisThe research has as its theme the Math teaching and the inclusion of visually challenged students in regular education. This is a research with qualitative approach using a study case as strategy. It aims at the development of didactic-methodological procedures that enable visually challenged included in regular education, as well as other students, to appropriate of mathematical knowledge. This study was based on the socio-historical current for the development of a pedagogical intervention in an 8th grade classroom of a secondary public school in the countryside of Paraná, which had a visually challenged student included. In the intervention were approached concepts of Geometry, Algebra, Values and Measurements such as Area, Perimeter and Volume, with inference of Notable Products. The developed activities were grounded in the Theory of Piotr Yakovlevich Galperin (2009) for the formation of concepts. For the activities development was elaoreted the teaching material “Notable Products” with adaptations for visually challenged students. After the activities implementation it was realized that it is possible to teach Mathematics to visually challenged students with others in a classroom that everyone, regardless of their limitations, are able to elaborate necessary concepts for their autonomy and citizenship practice.Esta pesquisa apresenta como tema o ensino de Matemática e a inclusão de alunos deficientes visuais no ensino regular. Trata-se de uma pesquisa com abordagem qualitativa, utilizando-se do estudo de caso como estratégia. Seu objetivo é o desenvolvimento de procedimentos didático - metodológicos que possibilitem aos deficientes visuais inclusos no ensino regular a apropriação dos conhecimentos matemáticos, assim como os demais alunos. Fundamentou-se nos pressupostos da corrente sócio – histórica para o desenvolvimento de uma intervenção pedagógica em uma turma do oitavo ano do Ensino Fundamental de um colégio público do interior do Paraná, que contava com uma aluna deficiente visual inclusa. Na intervenção foram abordados conceitos matemáticos em Geometria, Álgebra e Grandezas e Medidas como Área, Perímetro e Volume, com inferência aos Produtos Notáveis. As atividades desenvolvidas foram elaboradas fundamentadas na Teoria de Piotr Yakovlevich Galperin (2009) para a formação de conceitos. Para o desenvolvimento das atividades elaborou-se o material didático “Produtos Notáveis”, com adaptações para alunos com deficiência visual. Após a aplicação das atividades, percebeu-se que é possível ensinar Matemática, aos alunos com deficiência visual, juntamente com os demais em uma turma e que todos, independente das limitações, são capazes de elaborar conceitos necessários para a autonomia e o exercício da cidadania

Data security issues in cloud scenarios

The amount of data created, stored, and processed has enormously increased in the last years. Today, millions of devices are connected to the Internet and generate a huge amount of (personal) data that need to be stored and processed using scalable, efficient, and reliable computing infrastructures. Cloud computing technology can be used to respond to these needs. Although cloud computing brings many benefits to users and companies, security concerns about the cloud still represent the major impediment for its wide adoption. We briefly survey the main challenges related to the storage and processing of data in the cloud. In particular, we focus on the problem of protecting data in storage, supporting fine-grained access, selectively sharing data, protecting query privacy, and verifying the integrity of computations

Privacy in Microdata Release: Challenges, Techniques, and Approaches

Releasing and disseminating useful microdata while ensuring that no personal or sensitive information is improperly exposed is a complex problem, heavily investigated by the scientific community in the past couple of decades. Various microdata protection approaches have then been proposed, achieving different privacy requirements through appropriate protection techniques. This chapter discusses the privacy risks that can arise in microdata release and illustrates some well-known privacy-preserving techniques and approaches

Access Control for Data Integration in Presence of Data Dependencies

International audienceDefining access control policies in a data integration scenario is a challenging task. In such a scenario typically each source specifies its local access control policy and cannot anticipate data inferences that can arise when data is integrated at the mediator level. Inferences, e.g., using functional dependencies, can allow malicious users to obtain, at the mediator level, prohibited information by linking multiple queries and thus violating the local policies. In this paper, we propose a framework, i.e., a methodology and a set of algorithms, to prevent such violations. First, we use a graph-based approach to identify sets of queries, called violating transactions, and then we propose an approach to forbid the execution of those transactions by identifying additional access control rules that should be added to the mediator. We also state the complexity of the algorithms and discuss a set of experiments we conducted by using both real and synthetic datasets. Tests also confirm the complexity and upper bounds in worst-case scenarios of the proposed algorithms

A two-phase approach for real-world train unit scheduling

A two-phase approach for the train unit scheduling problem is proposed. The first phase assigns and sequences train trips to train units temporarily ignoring some station infrastructure details. Real-world scenarios such as compatibility among traction types and banned/restricted locations and time allowances for coupling/ decoupling are considered. Its solutions would be near-operable. The second phase focuses on satisfying the remaining station detail requirements, such that the solutions would be fully operable. The first phase is modeled as an integer fixed-charge multicommodity flow (FCMF) problem. A branch-and-price approach is proposed to solve it. Experiments have shown that it is only capable of handling problem instances within about 500 train trips. The train company collaborating in this research operates over 2400 train trips on a typical weekday. Hence, a heuristic has been designed for compacting the problem instance to a much smaller size before the branch-and-price solver is applied. The process is iterative with evolving compaction based on the results from the previous iteration, thereby converging to near-optimal results. The second phase is modeled as a multidimensional matching problem with a mixed integer linear programming (MILP) formulation. A column-and-dependentrow generation method for it is under development