Symmetric inclusion-exclusion

One form of the inclusion-exclusion principle asserts that if A and B are functions of finite sets then A(S) is the sum of B(T) over all subsets T of S if and only if B(S) is the sum of (-1)^|S-T| A(T) over all subsets T of S. If we replace B(S) with (-1)^|S| B(S), we get a symmetric form of inclusion-exclusion: A(S) is the sum of (-1)^|T| B(T) over all subsets T of S if and only if B(S) is the sum of (-1)^|T| A(T) over all subsets T of S. We study instances of symmetric inclusion-exclusion in which the functions A and B have combinatorial or probabilistic interpretations. In particular, we study cases related to the Polya-Eggenberger urn model in which A(S) and B(S) depend only on the cardinality of S.Comment: 10 page

Electronic structure and magnetic properties of Gd-doped and Eu-rich EuO

The effects of Gd doping and O vacancies on the magnetic interaction and Curie temperature of EuO are studied using first-principles calculations. Linear response calculations in the virtual crystal approximation show a broad maximum in the Curie temperature as a function of doping, which results from the combination of the saturating contribution from indirect exchange and a decreasing contribution from the f-d hopping mechanism. Non-Heisenberg interaction at low doping levels and its effect on the Curie temperature are examined. The electronic structure of a substitutional Gd and of an O vacancy in EuO are evaluated. When the 4f spins are disordered, the impurity state goes from single to double occupation, but correlated bound magnetic polarons are not ruled out. At higher vacancy concentrations typical for Eu-rich EuO films, the impurity states broaden into bands and remain partially filled. To go beyond the homogeneous doping picture, magnetostructural cluster expansions are constructed, which describe the modified exchange parameters near Gd dopants or O vacancies. Thermodynamic properties are studied using Monte Carlo simulations. The Curie temperature for Gd-doped EuO agrees with the results of the virtual crystal approximation and shows a maximum of about 150 K. At 3.125% vacancy concentration the Curie temperature increases to 120 K, consistent with experimental data for Eu-rich film samples.Comment: 15 pages, 13 figures, under review in Physical Review

Learning from accidents : machine learning for safety at railway stations

In railway systems, station safety is a critical aspect of the overall structure, and yet, accidents at stations still occur. It is time to learn from these errors and improve conventional methods by utilizing the latest technology, such as machine learning (ML), to analyse accidents and enhance safety systems. ML has been employed in many fields, including engineering systems, and it interacts with us throughout our daily lives. Thus, we must consider the available technology in general and ML in particular in the context of safety in the railway industry. This paper explores the employment of the decision tree (DT) method in safety classification and the analysis of accidents at railway stations to predict the traits of passengers affected by accidents. The critical contribution of this study is the presentation of ML and an explanation of how this technique is applied for ensuring safety, utilizing automated processes, and gaining benefits from this powerful technology. To apply and explore this method, a case study has been selected that focuses on the fatalities caused by accidents at railway stations. An analysis of some of these fatal accidents as reported by the Rail Safety and Standards Board (RSSB) is performed and presented in this paper to provide a broader summary of the application of supervised ML for improving safety at railway stations. Finally, this research shows the vast potential of the innovative application of ML in safety analysis for the railway industry

Reference face graph for face recognition

Face recognition has been studied extensively; however, real-world face recognition still remains a challenging task. The demand for unconstrained practical face recognition is rising with the explosion of online multimedia such as social networks, and video surveillance footage where face analysis is of significant importance. In this paper, we approach face recognition in the context of graph theory. We recognize an unknown face using an external reference face graph (RFG). An RFG is generated and recognition of a given face is achieved by comparing it to the faces in the constructed RFG. Centrality measures are utilized to identify distinctive faces in the reference face graph. The proposed RFG-based face recognition algorithm is robust to the changes in pose and it is also alignment free. The RFG recognition is used in conjunction with DCT locality sensitive hashing for efficient retrieval to ensure scalability. Experiments are conducted on several publicly available databases and the results show that the proposed approach outperforms the state-of-the-art methods without any preprocessing necessities such as face alignment. Due to the richness in the reference set construction, the proposed method can also handle illumination and expression variation

Enhancing network robustness for malicious attacks

In a recent work [Proc. Natl. Acad. Sci. USA 108, 3838 (2011)], the authors proposed a simple measure for network robustness under malicious attacks on nodes. With a greedy algorithm, they found the optimal structure with respect to this quantity is an onion structure in which high-degree nodes form a core surrounded by rings of nodes with decreasing degree. However, in real networks the failure can also occur in links such as dysfunctional power cables and blocked airlines. Accordingly, complementary to the node-robustness measurement ($R_{n}$), we propose a link-robustness index ($R_{l}$). We show that solely enhancing $R_{n}$ cannot guarantee the improvement of $R_{l}$. Moreover, the structure of $R_{l}$-optimized network is found to be entirely different from that of onion network. In order to design robust networks resistant to more realistic attack condition, we propose a hybrid greedy algorithm which takes both the $R_{n}$ and $R_{l}$ into account. We validate the robustness of our generated networks against malicious attacks mixed with both nodes and links failure. Finally, some economical constraints for swapping the links in real networks are considered and significant improvement in both aspects of robustness are still achieved.Comment: 6 pages, 6 figure

A meshless, integration-free, and boundary-only RBF technique

Based on the radial basis function (RBF), non-singular general solution and dual reciprocity method (DRM), this paper presents an inherently meshless, integration-free, boundary-only RBF collocation techniques for numerical solution of various partial differential equation systems. The basic ideas behind this methodology are very mathematically simple. In this study, the RBFs are employed to approximate the inhomogeneous terms via the DRM, while non-singular general solution leads to a boundary-only RBF formulation for homogenous solution. The present scheme is named as the boundary knot method (BKM) to differentiate it from the other numerical techniques. In particular, due to the use of nonsingular general solutions rather than singular fundamental solutions, the BKM is different from the method of fundamental solution in that the former does no require the artificial boundary and results in the symmetric system equations under certain conditions. The efficiency and utility of this new technique are validated through a number of typical numerical examples. Completeness concern of the BKM due to the only use of non-singular part of complete fundamental solution is also discussed

An Incomes Policy for the Professions: the Dutch Experience

In 1951 the United States began moving toward an incomes policy, an attempt to end postwar wage and price inflation by linking changes in these prices to gains in productivity. Other countries later followed suit; some countries had already adopted wage and price control policies. The Netherlands moved toward an incomes policy immediately after World War II. Initially, the Dutch program involved wages only, but in the 1970s it became an accepted principle that private professional income should be comparable with the salaries of government officials and civil servants with comparable training and responsibilities. In the Netherlands (as in the United States and, before medicine was socialized, the United Kingdom) health professionals operate on a fee-for-service basis and their incomes escalated as a result of both inflation and monopoly power. So they were subjected to the incomes policy. The policy's effectiveness in curbing income escalation cannot be determined with certainty—reliable data are lacking. However, the evidence indicates that the policy failed to achieve its original purpose.Incomes policy, Netherlands