Proposing a Crisis Portfolio for Telecommunications Companies

The aim of the current paper is to classify crises that threaten the telecommunications sector. The design of the crisis portfolio is based on managers’ assessments. Forty eight middle and senior managers working for the three major telecommunications companies in Greece were asked to rate the 16 crises on three major criteria: predictability, severity of consequences/ impact and probability to occur. Based on the results, a bubble chart was created. The present study engages three classification criteria, namely the predictability of a crisis, the impact/severity of consequences and the probability of a crisis occurring. Based on the above criteria, a new typology of totally four crises groups that has been adapted to the telecommunications industry is introduced and discussed. The concept of a crisis portfolio could strongly assist managers in preparing for and coping with crises because being prepared for one crisis in each cluster may provide valuable information for each of the other crises in the same cluster

Performance of spatial Multi-LRU caching under traffic with temporal locality

International audienceIn this work a novel family of decentralised caching policies for wireless networks is introduced, referred to as spatial multi-LRU. These improve cache-hit probability by exploiting multi-coverage. Two variations are proposed, the multi-LRU-One and-All, which differ in the number of replicas inserted in the covering edge-caches. The evaluation is done under spatial traffic that exhibits temporal locality, with varying content catalogue and dependent demands. The performance metric is hit probability and the policies are compared to (1) the single-LRU and (2) an upper bound for all centralised policies with periodic popularity updates. Numerical results show the multi-LRU policies outperform both comparison policies. The reason is their passive adaptability to popularity changes. Between the-One and-All variation, which one is preferable strongly depends on the available storage space and on traffic characteristics. The performance also depends on the popularity shape

Episodic Nonlinearity in Leading Global Currencies

We perform non-linearity tests using daily data for leading currencies that include the Australian dollar, British pound, Brazilian real, Canadian dollar, euro, Japanese yen, Mexican peso, and the Swiss franc to resolve the issue of whether these currencies are driven by fundamentals or exogenous shocks to the global economy. In particular, we use a new method of testing for linear and nonlinear lead/lag relationships between time series, introduced by Brooks and Hinich (1999), based on the concepts of cross-correlation and cross-bicorrelation. Our evidence points to a relatively rare episodic nonlinearity within and across foreign exchange rates. We also test the validity of specifying ARCH-type error structures for foreign exchange rates. In doing so, we estimate Bollerslevs (1986) general- ized ARCH (GARCH) model and Nelsons (1988) exponential GARCH (EGARCH) model,using a variety of error densities [including the normal, the Student-t distribution, and the Generalized Error Distribution (GED)] and a comprehensive set of diagnostic checks. We apply the Brooks and Hinich (1999) nonlinearity test to the standardized residuals of the optimal GARCH/EGARCH model for each exchange rate series and show that the nonlinearity in the exchange rates is not due to ARCH-type e¤ects. This result has important implications for the interpretation of the recent voluminous literature which attempts to model fi nancial asset returns using this family of models.Global nancial markets; Currencies; Episodic nonlinearity; Conditional heteroskedasticity.

Characterisation of the Perseid meteoroid stream through SPOSH observations between 2010–2016

We have characterised the Perseid meteoroid stream from data acquired in a series of observing campaigns between 2010 and 2016. The data presented in this work were obtained by the Smart Panoramic Optical Sensor Head (SPOSH), an all-sky camera system designed to image faint transient noctilucent phenomena on dark planetary hemispheres. For the data reduction, a sophisticated software package was developed that utilises the high geometric and photometric quality of images obtained by the camera system. We identify 934 meteors as Perseids, observed over a long period between late July (~124°) and mid-to-late August (~147°). The maximum meteor activity contributing to the annual shower was found at λ⊙ = 140°.08 ± 0°.07. The radiant of the shower was estimated at RA = 47°.2 and Dec = 57°.5 with a median error of 0°.6 and 0°.2, respectively. The mean population index of the shower between solar longitudes of 120°.68 and 145°.19 was r = 2.36 ± 0.05, showing strong temporal variation. A predicted outburst in shower activity for the night of August 11–12, 2016 was confirmed, with a peak observed 12.75 hr before the annual maximum at 23:30 ± 15′ UT. We measure a peak flux of 6.1 × 10−4 km−2 hr−1 for meteoroids of mass 1.6 × 10−2 g or more, appearing in the time period between 23:00 and 00:00 UT. We estimate the measured flux of the outburst meteoroids to be approximately twice as high as the annual meteoroid flux of the same mass. The population index of r = 2.19 ± 0.08, computed from the outburst Perseids in 2016, is higher than the value of r = 1.92 ± 0.06 derived from meteors observed in 2015 belonging to the annual Perseid shower which was active near the time of the outburst. A dust trail with an unusually high population index of r = 3.58 ± 0.24 was encountered in 2013 between solar longitudes 136°.261 and 137°.442. The relatively high r-value implies an encounter with a dust trail rich in low-mass particles

Energy Sector Pricing: One the Role of Neglected Nonlinearity

Modern economies have been subjected to a number of shocks during the past several years such as the burst of the Internet bubble, terrorist attacks, corporate scandals, the war in Iraq, the uncertainty about energy prices, and the recent subprime mortgage crisis. In particular, during the last few years, the energy shock has caused concerns for potential stagflation for both the United States and numerous other countries. We perform numerous univariate tests for non-linearity and chaotic structure using price data from the energy sector to resolve whether the sector\u27s fundamentals or exogenous shocks drive these prices

Efficient Distributed Outlier Detection in Data Streams

Anomaly detection is one of the major data mining tasks in modern applications. An element that shows significant deviation from the "usual" behavior is marked as an outlier. This means that this element either corresponds to noise or it requires more careful examination because it may be important. Also, many clustering algorithms are very sensitive to outliers. In any case, outliers must be identified and explored further, meaning that efficient outlier mining techniques are required. In this paper, we focus on distributed density-based outlier detection over multi-dimensional data streams. In particular, we focus on the approximation method for computing the Local Correlation Integral (LOCI) of multi-dimensional points. Each object p is assigned a score score(p) which represents the outlier score of p. Thus, one can select the top-k elements from the dataset that have the highest outlier scores. Our proposal has been implemented in Apache Spark using Scala and experiments have been conducted in a physical cluster running Apache Hadoop 2.7 and Apache Spark 2.4.0. Performance evaluation results demonstrate that the proposed algorithm is efficient and scalable and therefore it can be used to mine outliers in large distributed datasets

EPIDEMIOLOGY OF TRACK & FIELD INJURIES: A ONE YEAR EXPERIENCE IN ATHLETIC SCHOOLS

The purpose of this study was to record injuries in track & field events that were sustained by students who attended the athletic schools during a one-year period. From September 2009 to May 2010, the researchers observed 2045 students (883 males and 1163 females), who were participating in track and field events at the mentioned schools. During the study period 150 injuries were recorded, which accounted for 13.3% of all injuries sustained by students. Most of the injuries (34%) according to the diagnosis were sprains and strains and occurred during the months of February, December and January. A large percentage of the injuries (45.4%) were sustained by students who attended the Athletic Schools, which operated in the urban region. Students who attended the second class sustained more injuries than the other classes (first and third). Students who were practising or competing on a tartan playing surface were more likely to sustain an injury. Knee and ankle were the most frequent anatomical sites in which injuries (43.9%) occurred. Additionally, 80.0% of injuries occurred in students who were practising or competing in running events. No statistical differences were observed in all above mentioned parameters amongst male and female students. Physical education (P.E.) teachers should place more emphasis on prevention measures. These measures should include proper supervision of students during training, warming up and cooling down sessions with stretching techniques. By following these suggestions students will compete in a safe and healthy environment

Continuous Outlier Mining of Streaming Data in Flink

In this work, we focus on distance-based outliers in a metric space, where the status of an entity as to whether it is an outlier is based on the number of other entities in its neighborhood. In recent years, several solutions have tackled the problem of distance-based outliers in data streams, where outliers must be mined continuously as new elements become available. An interesting research problem is to combine the streaming environment with massively parallel systems to provide scalable streambased algorithms. However, none of the previously proposed techniques refer to a massively parallel setting. Our proposal fills this gap and investigates the challenges in transferring state-of-the-art techniques to Apache Flink, a modern platform for intensive streaming analytics. We thoroughly present the technical challenges encountered and the alternatives that may be applied. We show speed-ups of up to 117 (resp. 2076) times over a naive parallel (resp. non-parallel) solution in Flink, by using just an ordinary four-core machine and a real-world dataset. When moving to a three-machine cluster, due to less contention, we manage to achieve both better scalability in terms of the window slide size and the data dimensionality, and even higher speed-ups, e.g., by a factor of 510. Overall, our results demonstrate that oulier mining can be achieved in an efficient and scalable manner. The resulting techniques have been made publicly available as open-source software

Episodic Nonlinearity in Leading Global Currencies

We perform non-linearity tests using daily data for leading currencies that include the Australian dollar, British pound, Brazilian real, Canadian dollar, euro, Japanese yen, Mexican peso, and the Swiss franc to resolve the issue of whether these currencies are driven by fundamentals or exogenous shocks to the global economy. In particular, we use a new method of testing for linear and nonlinear lead/lag relationships between time series, introduced by Brooks and Hinich (1999), based on the concepts of cross-correlation and crossbicorrelation. Our evidence points to a relatively rare episodic nonlinearity within and across foreign exchange rates. We also test the validity of specifying ARCH-type error structures for foreign exchange rates. In doing so, we estimate Bollerslevs (1986) generalized ARCH (GARCH) model and Nelsons (1988) exponential GARCH (EGARCH) model, using a variety of error densities [including the normal, the Student-t distribution, and the Generalized Error Distribution (GED)] and a comprehensive set of diagnostic checks. We apply the Brooks and Hinich (1999) nonlinearity test to the standardized residuals of the optimal GARCH/EGARCH model for each exchange rate series and show that the nonlinearity in the exchange rates is not due to ARCH-type e⁄ects. This result has important implications for the interpretation of the recent voluminous literature which attempts to model nancial asset returns using this family of models