341,311 research outputs found

    Low-power emerging memristive designs towards secure hardware systems for applications in internet of things

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    Emerging memristive devices offer enormous advantages for applications such as non-volatile memories and in-memory computing (IMC), but there is a rising interest in using memristive technologies for security applications in the era of internet of things (IoT). In this review article, for achieving secure hardware systems in IoT, low-power design techniques based on emerging memristive technology for hardware security primitives/systems are presented. By reviewing the state-of-the-art in three highlighted memristive application areas, i.e. memristive non-volatile memory, memristive reconfigurable logic computing and memristive artificial intelligent computing, their application-level impacts on the novel implementations of secret key generation, crypto functions and machine learning attacks are explored, respectively. For the low-power security applications in IoT, it is essential to understand how to best realize cryptographic circuitry using memristive circuitries, and to assess the implications of memristive crypto implementations on security and to develop novel computing paradigms that will enhance their security. This review article aims to help researchers to explore security solutions, to analyze new possible threats and to develop corresponding protections for the secure hardware systems based on low-cost memristive circuit designs

    Instructional strategies and tactics for the design of introductory computer programming courses in high school

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    This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

    Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

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    In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation and development of CNNs, several software frameworks have been released, primarily targeting power-hungry CPUs and GPUs. In this context, reconfigurable hardware in the form of FPGAs constitutes a potential alternative platform that can be integrated in the existing deep learning ecosystem to provide a tunable balance between performance, power consumption and programmability. In this paper, a survey of the existing CNN-to-FPGA toolflows is presented, comprising a comparative study of their key characteristics which include the supported applications, architectural choices, design space exploration methods and achieved performance. Moreover, major challenges and objectives introduced by the latest trends in CNN algorithmic research are identified and presented. Finally, a uniform evaluation methodology is proposed, aiming at the comprehensive, complete and in-depth evaluation of CNN-to-FPGA toolflows.Comment: Accepted for publication at the ACM Computing Surveys (CSUR) journal, 201

    Managing knowledge in organizations : a Nonaka’s SECI model operationalization

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    Purpose: The SECI model (Nonaka, 1994) is the best-known conceptual framework for understanding knowledge generation processes in organizations. To date, however, empirical support for this framework has been overlooked. The present study aims to provide an evidence-based groundwork for the SECI model by testing a multidimensional questionnaire Knowledge Management SECI Processes Questionnaire (KMSP-Q) designed to capture the knowledge conversion modes theorized by Nonaka. Methodology: In a twofold study, the SECI model was operationalized via the KMSP-Q. Specifically, Study One tested its eight-dimensional structure through exploratory and confirmatory factorial analyses on 372 employees from different sectors. Study Two examined the construct validity and reliability by replicating the KMSP-Q factor structure in knowledge-intensive contexts (on a sample of 466 health-workers), and by investigating the unique impact of each dimension on some organizational outcomes (i.e., performance, innovativeness, collective efficacy). Findings: The overall findings highlighted that the KMSP-Q is a psychometrically robust questionnaire in terms of both dimensionality and construct validity, the different knowledge generation dimensions being specifically linked to different organizational outcomes. Research/Practical Implications: The KMSP-Q actualizes and provides empirical consistency to the theory underlying the SECI model. Moreover, it allows for the monitoring of an organization’s capability to manage new knowledge and detect the strengths/weaknesses of KM-related policies and programs. Originality/Value: This paper proposes a comprehensive measure of knowledge generation in work contexts, highlighting processes that organizations are likely to promote in order to improve their performance through the management of their knowledge resources

    Memory Rehabilitation Strategies in Nonsurgical Temporal Lobe Epilepsy: A Review

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    open8siPeople with temporal lobe epilepsy (TLE) who have not undergone epilepsy surgery often complain of memory deficits. Cognitive re- habilitation is employed as a remedial intervention in clinical settings, but research is limited and findings concerning efficacy and the criteria for choosing different approaches have been inconsistent. We aimed to appraise existing evidence on memory rehabilitation in nonsurgical individuals with temporal lobe epilepsy and to ascertain the effectiveness of specific strategies. A scoping review was preferred given the het- erogeneous nature of the interventions. A comprehensive literature search using MEDLINE, EMBASE, CINAHL, AMED, Scholars Portal/ PSYCHinfo, Proceedings First, and ProQuest Dissertations and Theses identified articles published in English before February 2016. The search retrieved 372 abstracts. Of 25 eligible studies, six were included in the final review. None included pediatric populations. Strategies included cognitive training, external memory aids, brain training, and noninvasive brain stimulation. Selection criteria tended to be general. Overall, there was insufficient evidence to make definitive conclusions regarding the efficacy of traditional memory rehabilitation strategies, brain training, and noninvasive brain stimulation. The review suggests that cognitive rehabilitation in nonsurgical TLE is underresearched and that there is a need for a systematic evaluation in this population.embargoed_20180216DEL FELICE, Alessandra; Alderighi, Marzia; Martinato, Matteo; Grisafi, Davide; Bosco, Anna; Thompson, Pamela J.; Sander, Josemir W.; Masiero, StefanoDEL FELICE, Alessandra; Alderighi, Marzia; Martinato, Matteo; Grisafi, Davide; Bosco, Anna; Thompson, Pamela J.; Sander, Josemir W.; Masiero, Stefan
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