A Parallel ATPG Algorithm Based on Big Function Block

The paper presents a parallel ATPG algorithm - PTGBP, which aims at decreasing the complexity of the ATPG by partitioning circuit under test (CUT) to big function blocks (BFB) and processing them parallelly. PTGBP adopts hybrid circuit mode and hybrid fault model, and organizes the parallel course in term of master/slave mode. Master processor loads the whole netlist of CUT based on BFB, every slave processor loads logic level (gate/function block/basic logic units) netlist of a BFB. Test generation (TG) uses BFB input/output s-a-0/s-a-1 fault model; fault simulation uses logic level single stuck fault model. Master controls the PTGBP’s running course and ensures the correctness of its running result; slaves provide the results of fault sensitization compatible computation and fault simulation to master parallelly. PTGBP algorithm is under implementation.

Numerical Solution of Two-Dimensional Nonlinear Stochastic Ito-Volterra Integral Equations by Applying Block Pulse Functions

This paper investigates the numerical solution of two-dimensional nonlinear stochastic Itô-Volterra integral equations based on block pulse functions. The nonlinear stochastic integral equation is transformed into a set of algebraic equations by operational matrix of block pulse functions. Then, we give error analysis and prove that the rate of convergence of this method is efficient. Lastly, a numerical example is given to confirm the method.

DOA estimation method for wideband signals by block sparse reconstruction

For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed.First,a prolate spheroidal wave function（PSWF） is used to fit the wideband signals,then the block sparse reconstruction technology is employed for DOA estimation.The proposed method uses orthogonalization to choose the matching atoms,ensuring that the residual components correspond to the minimum absolute value.Meanwhile,the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules,so the extra atoms are abandoned in the course of iteration,and the residual components of current iteration are reduced.Thus the original sparse signals are reconstructed.The proposed method reduces iteration times comparing with the traditional reconstruction methods,and the estimation precision is better than the classical two-sided correlation transformation（TCT）algorithm when the snapshot is small or the signal-to-noise ratio（SNR） is low.

The Attributes of Social Media as a Strategic Marketing Communication Tool

New digital trends are transforming the media industry landscape, modifying elemental characteristics and attitudes of companies as well as of consumers. Firms often claim that their presence in social media （SM） is a key element to success. SM helps companies rethink the traditional one-way flow of their marketing messages and to incorporate a new interactive pattern into their communications. Nevertheless, these tendencies involve problems of strategic myopia for firms that do not structurally integrate these tools. One main problem is that institutions can rarely differentiate between the various types of SM and the attributes thereof, while the literature equally reveals a number of contradictions in the subject. The present conceptual paper lays the foundations of a strategic approach to SM and discusses its theoretical implications. Following an overview on the concept of SM, through a content analysis of the specialized management literature （n = 14）, we present various best practices and reflect on the apparent lack of strategic thinking in using SM as a marketing application. Then, we compare these practical examples with general marketing strategy theory. By merging theory and practice, we aim to provide an insight towards a well-founded application of SM as a genuinely strategic marketing tool.

Supplementary motor area deactivation impacts the recovery of hand function from severe peripheral nerve injury

Although some patients have successful peripheral nerve regeneration,a poor recovery of hand function often occurs after peripheral nerve injury.It is believed that the capability of brain plasticity is crucial for the recovery of hand function.The supplementary motor area may play a key role in brain remodeling after peripheral nerve injury.In this study,we explored the activation mode of the supplementary motor area during a motor imagery task.We investigated the plasticity of the central nervous system after brachial plexus injury,using the motor imagery task.Results from functional magnetic resonance imaging showed that after brachial plexus injury,the motor imagery task for the affected limbs of the patients triggered no obvious activation of bilateral supplementary motor areas.This result indicates that it is difficult to excite the supplementary motor areas of brachial plexus injury patients during a motor imagery task,thereby impacting brain remodeling.Deactivation of the supplementary motor area is likely to be a serious problem for brachial plexus injury patients in terms of preparing,initiating and executing certain movements,which may be partly responsible for the unsatisfactory clinical recovery of hand function.

Enabling data-driven anomaly detection by design in cyber-physical production systems

Designing and developing distributed cyber-physical production systems(CPPS)is a time-consuming,complex,and error-prone process.These systems are typically heterogeneous,i.e.,they consist of multiple components implemented with different languages and development tools.One of the main problems nowadays in CPPS implementation is enabling security mechanisms by design while reducing the complexity and increasing the system’s maintainability.Adopting the IEC 61499 standard is an excellent approach to tackle these challenges by enabling the design,deployment,and management of CPPS in a model-based engineering methodology.We propose a method for CPPS design based on the IEC 61499 standard.The method allows designers to embed a bio-inspired anomaly-based host intrusion detection system(A-HIDS)in Edge devices.This A-HIDS is based on the incremental Dendritic Cell Algorithm(iDCA)and can analyze OPC UA network data exchanged between the Edge devices and detect attacks that target the CPPS’Edge layer.This study’s findings have practical implications on the industrial security community by making novel contributions to the intrusion detection problem in CPPS considering immune-inspired solutions,and cost-effective security by design system implementation.According to the experimental data,the proposed solution can dramatically reduce design and code complexity while improving application maintainability and successfully detecting network attacks without negatively impacting the performance of the CPPS Edge devices.

A Note on Expanding Planar Real Cellular Automata

In this paper, we deal with one-parameter families of real cellular automata in R2. We prove that for a wide class of block functions from R2 to R, the corresponding real cellular automaton is expanding when the value of the parameter is large enough.

Modeling and analysis of singular systems via orthogonal triangular functions

This paper presents a new approach to singular system analysis by modeling the system in terms of orthog- onal triangular functions （TFs）. The proposed method is more accurate compared to block pulse function-based analysis with respect to mean integral square error （MISE）. A numerical example involving four states of a singular system is treated and solutions obtained thereof. Four tables and relevant curves are presented to compare the respective coefficients in block pulse function （BPF） domain as well as in TF domain. The percentage error of the samples determined via TF domain are compared with the exact samples of the states. Furthermore, MISE for both BPF and TF analysis are computed and compared to reveal the efficiency of TF-based analysis.