An optimized cluster density matrix embedding theory

We propose an optimized cluster density matrix embedding theory(CDMET).It reduces the computational cost of CDMET with simpler bath states.And the result is as accurate as the original one.As a demonstration,we study the distant correlations of the Heisenberg J_(1)-J_(2)model on the square lattice.We find that the intermediate phase(0.43≤sssim J_(2)≤sssim 0.62)is divided into two parts.One part is a near-critical region(0.43≤J_(2)≤0.50).The other part is the plaquette valence bond solid(PVB)state(0.51≤J_(2)≤0.62).The spin correlations decay exponentially as a function of distance in the PVB.

A new fast algorithm for multitarget tracking in dense clutter

A fast joint probabilistic data association （FJPDA） algorithm is proposed in tiffs paper. Cluster probability matrix is approximately calculated by a new method, whose elements βi^t（K） can be taken as evaluation functions. According to values of βi^t（K）, N events with larger joint probabilities can be searched out as the events with guiding joint probabilities, tiros, the number of searching nodes will be greatly reduced. As a result, this method effectively reduces the calculation load and nnkes it possible to be realized on real-thne, Theoretical ,analysis and Monte Carlo simulation results show that this method is efficient.

Spectral clustering based on matrix perturbation theory

This paper exposes some intrlnsic chsracterlstlca of the spectral clustering method by using the tools from the mstrlx perturbation theory. We construct s welght mstrix of s graph and study Its elgenvalues and elgenvectors. It shows that the number of clusters Is equal to the number of elgenvslues that are larger than 1, and the number of polnts In each of the clusters can be spproxlmsted by the associated elgenvslue. It also shows that the elgenvector of the weight rnatrlx can be used dlrectly to perform clusterlng; that Is, the dlrectlonsl angle between the two-row vectors of the mstrlx derlved from the elgenvectors Is s sultable distance measure for clustsrlng. As s result, an unsupervised spectral clusterlng slgorlthm based on welght mstrlx （USCAWM） Is developed. The experlmental results on s number of srtlficisl and real-world data sets show the correctness of the theoretical analysis.

A New Approach to Analyzing Behavioral Change Propagation in Redesigning of Drone Camera Stabilizer

Redesigning of complex products is not an easy task. Engineering change requirements can be extracted at any stage of the product redesign process, and it makes the management of engineering change become a challenging mission. The motivation for this study is to find the shortest path of behavioral change propagation (BCP), minimize the BCP, access to the special behavioral elements in order to better managing the BCP and classifying the behavioral attribute of the elements in terms of their relationship to change by betweenness centrality coefficient (BNCC), clustering coefficient (CLC), reachability coefficient (RC) and change propagation index (CPI). In this article, the procedure of managerial decision-making is proposed by combining system restrictions in behavioral clustering design structure matrix (BCDSM) with optimization algorithms. The practicality of suggested method is verified in redesign procedure of a phantom drone camera stabilizer as a case study. The results, indicate that the absorption of change by behavioral elements is dominant in the mechanical (63.9%), electrical (61.1%) and thermal (38.9%) behaviors of the drone camera stabilizer system in redesign process. These elements are best candidates for reducing the cost and time of behavioral changes in the system redesign and are desirable for the designer.

Infrared spectroscopic probing of dimethylamine clusters in an Ar matrix

Amines have many atmospheric sources and their clusters play an important role in aerosol nucleation processes. Clusters of a typical amine, dimethylamine（DMA）, of different sizes were measured with matrix isolation IR（infrared） and NIR（near infrared）spectroscopy. The NIR vibrations are more separated and therefore it is easier to distinguish different sizes of clusters in this region. The DMA clusters, up to DMA tetramer, have been optimized using density functional methods, and the geometries, binding energies and thermodynamic properties of DMA clusters were obtained. The computed frequencies and intensities of NH-stretching vibrations in the DMA clusters were used to interpret the experimental spectra. We have identified the fundamental transitions of the bonded NH-stretching vibration and the first overtone transitions of the bonded and free NH-stretching vibration in the DMA clusters. Based on the changes in vibrational intensities during the annealing processes, the growth of clusters was clearly observed. The results of annealing processes indicate that DMA molecules tend to form larger clusters with lower energies under matrix temperatures, which is also supported by the calculated reaction energies of cluster formation.