Cyclic decomposition of k-permutations and eigenvalues of the arrangement graphs

The (n,k)-arrangement graph A(n,k) is a graph with all the k-permutations of an n-element set as vertices where two k-permutations are adjacent if they agree in exactly k-1 positions. We introduce a cyclic decomposition for k-permutations and show that this gives rise to a very fine equitable partition of A(n,k). This equitable partition can be employed to compute the complete set of eigenvalues (of the adjacency matrix) of A(n,k). Consequently, we determine the eigenvalues of A(n,k) for small values of k. Finally, we show that any eigenvalue of the Johnson graph J(n,k) is an eigenvalue of A(n,k) and that -k is the smallest eigenvalue of A(n,k) with multiplicity O(n^k) for fixed k.Comment: 18 pages. Revised version according to a referee suggestion

DIGITAL TRANSFORMATION AND ORGANIZATIONAL DYSFUNCTIONS: A CASE STUDY IN OPERATION IN CHINA

The socio-technical perspective has been recognized as the mainstream of Information Systems (IS) philosophy for decades. Besides, a complementary perspective in the IS philosophy, the socio-economic theory, would allow identifying more precisely the business problems, considered “Organizational Dysfunction”. Digital transformation is supposed to fix the specific business problem as cross-department communication, and it is essential to involve the analysis of organizational dysfunctions ahead. A case study was conducted in operation in China, where digital transformation was implemented to solve cross-department communication business problems. Beyond this specific business problem, this case study relies on the relevance of the theories “Organizational Dysfunctions” and “Socio-Economic Approach to Management (SEAM).” Focus group was adopted to figure out the key business problem, and semi-structured interviewing for the main root causes. It revealed digital transformation significance on the inefficient cross-department communication through the identification of the analytical results and the theories of Organizational Dysfunctions and SEAM

Determination of optimal reversed field with maximal electrocaloric cooling by a direct entropy analysis

Application of a negative field on a positively poled ferroelectric sample can enhance the electrocaloric cooling and appears as a promising method to optimize the electrocaloric cycle. Experimental measurements show that the maximal cooling does not appear at the zero-polarization point, but around the shoulder of the P-E loop. This phenomenon cannot be explained by the theory based on the constant total entropy assumption under adiabatic condition. In fact, adiabatic condition does not imply constant total entropy when irreversibility is involved. A direct entropy analysis approach based on work loss is proposed in this work, which takes the entropy contribution of the irreversible process into account. The optimal reversed field determined by this approach agrees with the experimental observations. This study signifies the importance of considering the irreversible process in the electrocaloric cycles

Robust Correlation Tracking for UAV with Feature Integration and Response Map Enhancement

Recently, correlation filter (CF)-based tracking algorithms have attained extensive interest in the field of unmanned aerial vehicle (UAV) tracking. Nonetheless, existing trackers still struggle with selecting suitable features and alleviating the model drift issue for online UAV tracking. In this paper, a robust CF-based tracker with feature integration and response map enhancement is proposed. Concretely, we develop a novel feature integration method that comprehensively describes the target by leveraging auxiliary gradient information extracted from the binary representation. Subsequently, the integrated features are utilized to learn a background-aware correlation filter (BACF) for generating a response map that implies the target location. To mitigate the risk of model drift, we introduce saliency awareness in the BACF framework and further propose an adaptive response fusion strategy to enhance the discriminating capability of the response map. Moreover, a dynamic model update mechanism is designed to prevent filter contamination and maintain tracking stability. Experiments on three public benchmarks verify that the proposed tracker outperforms several state-of-the-art algorithms and achieves a real-time tracking speed, which can be applied in UAV tracking scenarios efficiently

Positive and negative electrocaloric effect in BaTiO3_3 in the presence of defect dipoles

The influence of defect dipoles on the electrocaloric effect (ECE) in acceptor doped BaTiO$_3$ is studied by means of lattice-based Monte-Carlo simulations. A Ginzburg-Landau type effective Hamiltonian is used. Oxygen vacancy-acceptor associates are described by fixed defect dipoles with orientation parallel or anti-parallel to the external field. By a combination of canonical and microcanoncial simulations the ECE is directly evaluated. Our results show that in the case of anti-parallel defect dipoles the ECE can be positive or negative depending on the density of defect dipoles. Moreover, a transition from a negative to positive ECE can be observed from a certain density of anti-parallel dipoles on when the external field increases. These transitions are due to the delicate interplay of internal and external fields, and are explained by the domain structure evolution and related field-induced entropy changes. The results are compared to those obtained by MD simulations employing an {\it{ab initio}} based effective Hamiltonian, and a good qualitative agreement is found. In addition, a novel electrocaloric cycle, which makes use of the negative ECE and defect dipoles, is proposed to enhance the cooling effect

Application of Probabilistic and Nonprobabilistic Hybrid Reliability Analysis Based on Dynamic Substructural Extremum Response Surface Decoupling Method for a Blisk of the Aeroengine

For the nondeterministic factors of an aeroengine blisk, including both factors with sufficient and insufficient statistical data, based on the dynamic substructural method of determinate analysis, the extremum response surface method of probabilistic analysis, and the interval method of nonprobabilistic analysis, a methodology called the probabilistic and nonprobabilistic hybrid reliability analysis based on dynamic substructural extremum response surface decoupling method (P-NP-HRA-DS-ERSDM) is proposed. The model includes random variables and interval variables to determine the interval failure probability and the interval reliability index. The extremum response surface function and its flow chart of mixed reliability analysis are given. The interval analysis is embedded in the most likely failure point in the iterative process. The probabilistic analysis and nonprobabilistic analysis are investigated alternately. Tuned and mistuned blisks are studied in a complicated environment, and the results are compared with the Monte Carlo method (MCM) and the multilevel nested algorithm (MLNA) to verify that the hybrid model can better handle reliability problems concurrently containing random variables and interval variables; meanwhile, it manifests that the computational efficiency of this method is superior and more reasonable for analysing and designing a mistuned blisk. Therefore, this methodology has very important practical significance

Who Motivates My Participation in Virtual Interorganizational Communities of Practice: Self, Peers, or the Firm?

Virtual interorganizational communities of practice (IOCoPs) enable professionals in different organizations to exchange and share knowledge via computer-mediated interactions. Prior literature mainly focuses on internal motivating factors at the individual level. However, knowledge sharing requires social interactions thus influences from external entities play an important role in individuals’ community participation. In this research, we study external motivating factors generated from two different channels: peer effects within and organizational influences outside the virtual community. We apply a novel econometric identification method to analyze a virtual IOCoP in the financial trading sector. We find that external motivating factors from online peers and offline organizations are influential in determining community participation. In addition, our results suggest that virtual IOCoPs and organizations are two complementary learning channels. Differentiating motivating factors across multiple levels enables us to shed new light on various mechanisms with which IOCoPs can engage collective learning and knowledge management across organizations