Security Implementation in WSN with Symmetric and Matrix Mapping on Asymmetric ECC Cryptographic Techniques

As the wireless sensor networks are easily deployable, the volume of sensor applications has been increased widely in various fields of military and commercial areas. In order to attain security on the data exchanged over the network, a hybrid cryptographic mechanism which includes both symmetric and asymmetric cryptographic functions is used. The public key cryptographic ECC security implementation in this paper performs a matrix mapping of data’s at the points on the elliptical curve, which are further encoded using the private symmetric cipher cryptographic algorithm. This security enhancement with the hybrid mechanism of ECC and symmetric cipher cryptographic scheme achieves efficiency in energy conservation of about 7% and 4% compared to the asymmetric and symmetric cipher security implementations in WSN.

SOME EULER SPACES OF DIFFERENCE SEQUENCES OF ORDER m

Kizmaz [13] studied the difference sequence spaces ∞（A）, c（A）, and co（A）. Several article dealt with the sets of sequences of m-th order difference of which are bounded, convergent, or convergent to zero. Altay and Basar [5] and Altay, Basar, and Mursaleen [7] introduced the Euler sequence spaces e0^r, ec^r, and e∞^r, respectively. The main purpose of this article is to introduce the spaces e0^r△^（m））, ec^r△^（m））, and e∞^r△^（m））consisting of all sequences whose mth order differences are in the Euler spaces e0^r, ec^r, and e∞^r, respectively. Moreover, the authors give some topological properties and inclusion relations, and determine the α-, β-, and γ-duals of the spaces e0^r△^（m））, ec^r△^（m））, and e∞^r△^（m））, and the Schauder basis of the spaces e0^r△^（m））, ec^r△^（m））. The last section of the article is devoted to the characterization of some matrix mappings on the sequence space ec^r△^（m））.

ON THE m^(th) ORDER DIFFERENCE SEQUENCE SPACE OF GENERALIZED WEIGHTED MEAN AND COMPACT OPERATORS

In this article, using generalized weighted mean and difference matrix of order m, we introduce the paranormed sequence space l（u, v, p; △（m））, which consist of the sequences whose generalized weighted △（m）-difference means are in the linear space l（p） defined by I.J.Maddox. Also, we determine the basis of this space and compute its α-, β- and γ-duals. Further, we give the characterization of the classes of matrix mappings from l（u, v, p, △（m）） to l∞, c, and co. Finally, we apply the Hausdorff measure of noncompacness to characterize some classes of compact operators given by matrices on the space lp（U, v, △（m）） （1 ≤ p 〈 ∞）.

Exponential stabilization of networked control systems and design of switching controller

This paper deals with the problem of switching between an open-loop estimator and a close-loop estimator for compensating transmission error and packet dropout of networked control systems. Switching impulse is considered in order to reduce the error between theory and application, a sufficient condition for exponential stabilization of networked control systems under a given switching rule is presented by multiple Lyapunov-like functions. These results are presented for both continuous-time and discrete-time domains. Controllers are designed by means of linear matrix inequalities. Sim- ulation results show the feasibility and efficiency of the proposed method.

Deviations of the lepton mapping matrix from the Harrison-Perkins-Scott form

We propose a simple set of hypotheses governing the deviations of the leptonic mapping matrix from the Harrison-Perkins-Scott （HPS） form. These deviations are supposed to arise entirely from a perturbation of the mass matrix in the charged lepton sector. The perturbing matrix is assumed to be purely imaginary （thus maximally T-violating） and to have a strength in energy scale no greater （but perhaps smaller） than the muon mass. As we shall show, it then follows that the absolute value of the mapping matrix elements pertaining to the tau lepton deviate by no more than O（（mμ/mτ）^2） ≈ 3.5 ×10^-3 from their HPS values. Assuming that （mμ/mτ）^2 can be neglected, we derive two simple constraints on the four parameters θ12,θ23, θ31, and δ of the mapping matrix. These constraints are independent of the details of the imaginary T-violating perturbation of the charged lepton mass matrix. We also show that the e and μ parts of the mapping matrix have a definite form governed by two parameters α and β; any deviation of order mμ/mτ can be accommodated by adjusting these two parameters.

The case for mandatory inclusion of ethics within the zoological sciences curriculum

Traditionally,undergraduate science curricula include little or no“ethics,”either as theory or practice.However,zoologists are currently enjoying considerable media exposure:some of it positive(as in conservation practice),but more often negative(pertaining to issues such as the use of animals for testing of drugs,and genetic engineering).More than ever before,zoologists are being asked to make value judgments,and many of these involve moral assessment;if we accept that zoologists(along with other scientists)are professionals,then we must accept that they are responsible for any decisions they make,and it then follows that they are accountable,which can have serious ramifications in cases of malpractice.Ethics involves the application of morality in a professional setting.In light of this,teaching ethics is mandatory in degree programs such as engineering and medicine.This paper contends that a key output of zoological education is the undergraduate who is cognizant of the ethical framework and constructs within which he/she must function.The paper concludes with comment on the nature and style of delivery of ethics education.

Latent discriminative representation learning for speaker recognition

Extracting discriminative speaker-specific representations from speech signals and transforming them into fixed length vectors are key steps in speaker identification and verification systems.In this study,we propose a latent discriminative representation learning method for speaker recognition.We mean that the learned representations in this study are not only discriminative but also relevant.Specifically,we introduce an additional speaker embedded lookup table to explore the relevance between different utterances from the same speaker.Moreover,a reconstruction constraint intended to learn a linear mapping matrix is introduced to make representation discriminative.Experimental results demonstrate that the proposed method outperforms state-of-the-art methods based on the Apollo dataset used in the Fearless Steps Challenge in INTERSPEECH2019 and the TIMIT dataset.