The Global Media and Information Literacy Week: Moving Towards MIL Cities

The Global Media and Information Literacy Week commemorates the progress in achieving “MIL for all” by aggregating various MIL-related local and international events and actions across different disciplines around the world.The MIL Global Week 2018, 24 to 31 October, was marked by the United Nations Educational, Scientific and Cultural Organization in collaboration with various organizations including the UN Alliance of Civilizations, the Global Alliance for Partnership on MIL, the International Federation of Library Associations, the International Association of School Libraries, and the UNESCO-UNAOC University Cooperation Programme on Media and Information Literacy and Intercultural Dialogue

Flexual buckling of structural glass columns. Initial geometrical imperfection as a base for Monte Carlo simulation

In this paper Monte Carlo simulations of structural glass columns are presented. The simulation was performed according to the analytical second order theory of compressed elastic rods. A previous research on shape and size of initial geometrical imperfections is briefly summarized. An experimental analysis of glass columns that were performed for evaluation of equivalent geometrical imperfections is mentioned too

Active classification with comparison queries

We study an extension of active learning in which the learning algorithm may ask the annotator to compare the distances of two examples from the boundary of their label-class. For example, in a recommendation system application (say for restaurants), the annotator may be asked whether she liked or disliked a specific restaurant (a label query); or which one of two restaurants did she like more (a comparison query). We focus on the class of half spaces, and show that under natural assumptions, such as large margin or bounded bit-description of the input examples, it is possible to reveal all the labels of a sample of size $n$ using approximately $O(\log n)$ queries. This implies an exponential improvement over classical active learning, where only label queries are allowed. We complement these results by showing that if any of these assumptions is removed then, in the worst case, $\Omega(n)$ queries are required. Our results follow from a new general framework of active learning with additional queries. We identify a combinatorial dimension, called the \emph{inference dimension}, that captures the query complexity when each additional query is determined by $O(1)$ examples (such as comparison queries, each of which is determined by the two compared examples). Our results for half spaces follow by bounding the inference dimension in the cases discussed above.Comment: 23 pages (not including references), 1 figure. The new version contains a minor fix in the proof of Lemma 4.

Efficient Computation of Sequence Mappability

Sequence mappability is an important task in genome re-sequencing. In the $(k,m)$-mappability problem, for a given sequence $T$ of length $n$, our goal is to compute a table whose $i$th entry is the number of indices $j \ne i$ such that length-$m$ substrings of $T$ starting at positions $i$ and $j$ have at most $k$ mismatches. Previous works on this problem focused on heuristic approaches to compute a rough approximation of the result or on the case of $k=1$. We present several efficient algorithms for the general case of the problem. Our main result is an algorithm that works in $\mathcal{O}(n \min\{m^k,\log^{k+1} n\})$ time and $\mathcal{O}(n)$ space for $k=\mathcal{O}(1)$. It requires a carefu l adaptation of the technique of Cole et al.~[STOC 2004] to avoid multiple counting of pairs of substrings. We also show $\mathcal{O}(n^2)$-time algorithms to compute all results for a fixed $m$ and all $k=0,\ldots,m$ or a fixed $k$ and all $m=k,\ldots,n-1$. Finally we show that the $(k,m)$-mappability problem cannot be solved in strongly subquadratic time for $k,m = \Theta(\log n)$ unless the Strong Exponential Time Hypothesis fails.Comment: Accepted to SPIRE 201

Use of Genetic Algorithm in Algorithmic Trading to Optimize Technical Analysis in the International Stock Market (Forex)

Recent studies on financial markets have demonstrated that technical analysis can help us effectively predict the stock market index trend. Business systems are widely used for stock market analysis. This paper uses a genetic algorithm (GA) to develop a stock market trading optimization system. Our proposed system can generate a decision-making strategy for buying, holding, and selling stocks for each day and generate high returns for each stock. The system consists of two stages: removing restricted stocks and producing a stock trading strategy. Accordingly, evolutionary computation, like GA, is highly promising because of its intelligence, flexibility, and search strength (fast and efficient). The multiple-objective nature of the utilized algorithm can be regarded as the center of gravity of the research question. The proper functioning or malfunctioning of the resulting portfolio management can be employed as a benchmark for selecting or discarding the algorithm. On the other hand, the research question is focused on the application of technical analysis indicators. Therefore, both aspects of the research question, namely the multiple-objective nature of the algorithm in terms of the analysis method and technical indicators in terms of features selected for analysis, must be taken into account

Reliability-based assessment procedures for existing concrete structures

A feasibility study of reliability theory as a tool for the assessment of present safety and residual service life of damaged concrete structures has been performed in order to find a transparent methodology for the assessment procedure. It is concluded that the current guidelines are open to interpretation and that the variation in the results obtained regarding the structural safety is too great to be acceptable. Interpretations by the engineer are also included when deterministic methods are used, but probabilistic methods are more sensitive to the assumptions made and the differences in the results will therefore be greater. In a literature survey it is concluded that residual service life predictions should not be expected to be valid for more than 10 to 15 years, due to the large variability of the variables involved in the analysis. Based on these conclusions predictive models that are suitable for the inclusion of new data, and methods for the incorporation of new data are proposed. Information from the field of medical statistics and robotics suggests that linear regression models are well suited for this type of updated monitoring. Two test cases were studied, a concrete dam and a railway bridge. From the dam case, it was concluded that the safety philosophy in the deterministic dam specific assessment guidelines further development. Probabilistic descriptions of important variables, such as ice loads and friction coefficients, are needed if reliability theory is to be used for assessment purposes. During the study of the railway bridge it became clear that model uncertainties for different failure mechanisms used in concrete design are lacking. If Bayesian updating is to be used as a tool for incorporation of test data regarding concrete strength info the reliability analysis, a priori information must be established. A need for a probabilistic description of the hardening process of concrete was identified for the purpose of establishing a priori information. This description can also be used as qualitative assessment of the concrete. If there is a large discrepancy between the predicted value and the measured value, the concrete should be investigated regarding deterioration due to, for example internal frost or alkali silica reactions. Reliability theory is well suited for the assessment process since features of the reliability theory such as sensitivity analysis give good decision support for matters concerning both safety and service life predictions

Reliability-based design optimization of shells with uncertain geometry using adaptive Kriging metamodels

Optimal design under uncertainty has gained much attention in the past ten years due to the ever increasing need for manufacturers to build robust systems at the lowest cost. Reliability-based design optimization (RBDO) allows the analyst to minimize some cost function while ensuring some minimal performances cast as admissible failure probabilities for a set of performance functions. In order to address real-world engineering problems in which the performance is assessed through computational models (e.g., finite element models in structural mechanics) metamodeling techniques have been developed in the past decade. This paper introduces adaptive Kriging surrogate models to solve the RBDO problem. The latter is cast in an augmented space that "sums up" the range of the design space and the aleatory uncertainty in the design parameters and the environmental conditions. The surrogate model is used (i) for evaluating robust estimates of the failure probabilities (and for enhancing the computational experimental design by adaptive sampling) in order to achieve the requested accuracy and (ii) for applying a gradient-based optimization algorithm to get optimal values of the design parameters. The approach is applied to the optimal design of ring-stiffened cylindrical shells used in submarine engineering under uncertain geometric imperfections. For this application the performance of the structure is related to buckling which is addressed here by means of a finite element solution based on the asymptotic numerical method

Iranian Celebrities on the Internet

Celebrities have gained considerable influence in the last one hundred years or so, but the advent of so-called Web 2.0 technologies has given celebrity culture a new momentum. We are living in a world in which celebrities are striving to curve their place in every niche and hence we have to become more media literate in order to avoid being exploited by celebrity media and culture. We have to be aware that celebrities promote commodities that they will never use, that they are carefully working on their image to become pleasant to us, and that if they do humanitarian work, they are mainly doing it for their reputation, and not for a real and authentic cause