Research on the Deviation Sensing of V-groove Weld Seam based on a Novel Two Channel Acoustic Sensor

It is essential to sense the deviation of weld seam real-timely in robotic welding process. However, welding process always accompanied with high temperature, strong arc light and background noises, which significantly affects the application of sensors. In this study, a novel acoustic sensor was developed. This sensor consists of two microphones. Based on the sound signals collected by these two microphones, the deviation of weld seam was detected. The frequency response of the developed acoustic sensor was studied through simulation method firstly, and then the sensing performance of it was analyzed with experiments. The experimental results show that the developed acoustic sensor has a linear property for the deviation detection of V-groove weld seam. This research provides a novel method for weld seam tracking.

Non-linear Analysis of Models for Biological Pattern Formation: Application to Ocular Dominance Stripes

We present a technique for the analysis of pattern formation by a class of models for the formation of ocular dominance stripes in the striate cortex of some mammals. The method, which employs the adiabatic approximation to derive a set of ordinary differential equations for patterning modes, has been successfully applied to reaction-diffusion models for striped patterns. Models of ocular dominance stripes have been studied by computation, or by linearization of the model equations. These techniques do not provide a rationale for the origin of the stripes. We show here that stripe formation is a non-linear property of the models. Our analysis indicates that stripe selection is closely linked to a property in the dynamics of the models which arises from a symmetry between ipsilateral and contralateral synapses to the visual cortex of a given hemisphere.

Energy-Delay-Balanced Load Dispatching in Cloud-Assisted Edge Computing of Smart City

As smart city develops, Cloud Assisted Mobile Edge computing (CAME) framework is popular because it has the advantage of low delay and cost. But the computing capacity of mobile users is constrained in energy consumption, especially how to overcome the tradeoff between system latency and energy. In this article, an energy-delay-balanced load dispatching algorithm is suggested by exploiting the Karush-Kuhn-Tucker (KKT) conditions. Its exponential complexity is circumvented by taking the advantage of the linear property of constraints, rather than directly figuring out the KKT conditions. Compared to the fair ratio algorithm and the greedy algorithm, our suggested one is proved to provide better performance by simulation, which can decrease the delay by 35% and 49% respectively on the basis of the same energy consumption. The results indicate that the designed algorithm provides desirable tradeoff between system latency and energy.

Projected Wirtinger Gradient Descent for Digital Waves Reconstruction

This work attempts to recover digital signals from a few stochastic samples in time domain. The target signal is the linear combination of one-dimensional complex sine components with R different but continuous frequencies. These frequencies control the continuous values in the domain of normalized frequency [0, 1), contrary to the previous research into compressed sensing. To recover the target signal, the problem was transformed into the completion of a low-rank structured matrix, drawing on the linear property of the Hankel matrix. Based on the completion of the structured matrix, the authors put forward a feasible-point algorithm, analyzed its convergence, and speeded up the convergence with the fast iterative shrinkage-thresholding (FIST) algorithm. The initial algorithm and the speed up strategy were proved effective through repeated numerical simulations. The research results shed new lights on the signal recovery in various fields.

Acetylenic Carbon-Containing Stable Five-Membered Metallacycles

Due to the linear property around an acetylenic carbon, the introduction of such an atom to a small cycle would result in high ring strain. Currently, the smallest isolated rings are five-membered, including metallacycloalkynes and metallapentalynes. Both types contain at least one unusual small bond angle around the acetylenic carbon, thus exhibiting abnormal reactivities. This feature article gives a comprehensive overview on these two kind complexes. The synthesis and reactivities are extensively described, the source of stability is presented, and the future prospect is discussed. The article aims to provide a better development for the chemical diversity of five-membered metallacycloalkynes and metallapentalynes.

Development of Quantum Hartley Transform for Signal Processing Applications

The present paper deals with the q-analogue of Hartley transform which is the q-extension of Hartley transform. It is an orthogonal transform which is defined in the domain -∞ to ∞ whose kernel is (cosinusidal) function ‘cas’ which is a combination of trigonometrical functions ‘sin’ and ‘cos’. The q-analogue of Hartley transform is defined in the domain -∞ to ∞ whose kernel is ‘cas_q’ function which is a q-extension of ‘cas’ function. In the similar manner ‘cas_q’ is a q-extension of combination of q-extension of trigonometrical functions ‘sin_q’ and ‘cos_q’ defined in Kack and Chengue book [18]. In this paper we will establish some basic properties of q-Hartley transform, for instance linear property, change of scale property.

Weighted and Directed Graph Approaches

It is interesting to look at the types of social networks that are directed or weighted, or social networks with the combination of both. In many cases, the relationship between vertices may be quantifiable (weighted) or asymmetrical (directed). In this chapter, the authors first introduce the concept of weighted social networks and present an anonymization algorithm for these networks called the anonymity generalization algorithm. After that, they discuss k-anonymous path privacy and introduce the MSP algorithm. Next, the authors introduce the (k1, k2)-shortest path privacy and a (k1, k2)-shortest path privacy algorithm. Then they introduce directed weighted social networks and present the k-multiple paths anonymization on PV+NV (KMPPN). Also, the authors present a technique to convert directed networks into undirected networks. Finally, the authors present the linear property preserving anonymization approach for social networks.