State of Alaska Election Security Project Phase 2 Report

A laska’s election system is among the most secure in the country, and it has a number of safeguards other states are now adopting. But the technology Alaska uses to record and count votes could be improved— and the state’s huge size, limited road system, and scattered communities also create special challenges for insuring the integrity of the vote. In this second phase of an ongoing study of Alaska’s election security, we recommend ways of strengthening the system—not only the technology but also the election procedures. The lieutenant governor and the Division of Elections asked the University of Alaska Anchorage to do this evaluation, which began in September 2007.Lieutenant Governor Sean Parnell. State of Alaska Division of Elections.List of Appendices / Glossary / Study Team / Acknowledgments / Introduction / Summary of Recommendations / Part 1 Defense in Depth / Part 2 Fortification of Systems / Part 3 Confidence in Outcomes / Conclusions / Proposed Statement of Work for Phase 3: Implementation / Reference

Liouville theory and uniformization of four-punctured sphere

Few years ago Zamolodchikov and Zamolodchikov proposed an expression for the 4-point classical Liouville action in terms of the 3-point actions and the classical conformal block. In this paper we develop a method of calculating the uniformizing map and the uniformizing group from the classical Liouville action on n-punctured sphere and discuss the consequences of Zamolodchikovs conjecture for an explicit construction of the uniformizing map and the uniformizing group for the sphere with four punctures.Comment: 17 pages, no figure

Characterization of a dense aperture array for radio astronomy

EMBRACE@Nancay is a prototype instrument consisting of an array of 4608 densely packed antenna elements creating a fully sampled, unblocked aperture. This technology is proposed for the Square Kilometre Array and has the potential of providing an extremely large field of view making it the ideal survey instrument. We describe the system,calibration procedures, and results from the prototype.Comment: 17 pages, accepted for publication in A&

Chemical composition, fibre types and enzymes activates of longissimus thoracis muscle of the one humped camel

Thirty samples of Longissimus thoracis (LT) muscle were collected from 2-3 years old male camels slaughtered according to seasons of the year (winter, summer and autumn). The samples were then subjected to chemical analysis to study the chemical composition, fibre types and metabolic enzymes activities and variations among seasons. The results showed that chemical composition, ultimate pH (pHu) and calor were significantly influenced by season. Enzymes activities of isocitrate dehydrogenase (ICDH) and phosphofructokinase (PFK) were higher during autumn season compared to summer and winter (2.7 and 1.8 uml/min per g muscle, respectively). Quantification of muscle myosin heavy chain isoforms by SOS-PAGE electrophoresis and image analysis indicated higher proportions rn winter for type I muscle fibres and in autumn for type I la muscle fibres. Positive correlation was observed (0.84) between the proportion of fibre type I and lsocitrate Dehydrogenase (ICDH) enzyme activity. These findings indicated that muscle characteristics in camels are highly regulated by season. (Résumé d'auteur

Distributed Minimum Cut Approximation

We study the problem of computing approximate minimum edge cuts by distributed algorithms. We use a standard synchronous message passing model where in each round, $O(\log n)$ bits can be transmitted over each edge (a.k.a. the CONGEST model). We present a distributed algorithm that, for any weighted graph and any $\epsilon \in (0, 1)$, with high probability finds a cut of size at most $O(\epsilon^{-1}\lambda)$ in $O(D) + \tilde{O}(n^{1/2 + \epsilon})$ rounds, where $\lambda$ is the size of the minimum cut. This algorithm is based on a simple approach for analyzing random edge sampling, which we call the random layering technique. In addition, we also present another distributed algorithm, which is based on a centralized algorithm due to Matula [SODA '93], that with high probability computes a cut of size at most $(2+\epsilon)\lambda$ in $\tilde{O}((D+\sqrt{n})/\epsilon^5)$ rounds for any $\epsilon>0$. The time complexities of both of these algorithms almost match the $\tilde{\Omega}(D + \sqrt{n})$ lower bound of Das Sarma et al. [STOC '11], thus leading to an answer to an open question raised by Elkin [SIGACT-News '04] and Das Sarma et al. [STOC '11]. Furthermore, we also strengthen the lower bound of Das Sarma et al. by extending it to unweighted graphs. We show that the same lower bound also holds for unweighted multigraphs (or equivalently for weighted graphs in which $O(w\log n)$ bits can be transmitted in each round over an edge of weight $w$), even if the diameter is $D=O(\log n)$. For unweighted simple graphs, we show that even for networks of diameter $\tilde{O}(\frac{1}{\lambda}\cdot \sqrt{\frac{n}{\alpha\lambda}})$, finding an $\alpha$-approximate minimum cut in networks of edge connectivity $\lambda$ or computing an $\alpha$-approximation of the edge connectivity requires $\tilde{\Omega}(D + \sqrt{\frac{n}{\alpha\lambda}})$ rounds

Naturalistic Affective Expression Classification by a Multi-Stage Approach Based on Hidden Markov Models

In naturalistic behaviour, the affective states of a person change at a rate much slower than the typical rate at which video or audio is recorded (e.g. 25fps for video). Hence, there is a high probability that consecutive recorded instants of expressions represent a same affective content. In this paper, a multi-stage automatic affective expression recognition system is proposed which uses Hidden Markov Models (HMMs) to take into account this temporal relationship and finalize the classification process. The hidden states of the HMMs are associated with the levels of affective dimensions to convert the classification problem into a best path finding problem in HMM. The system was tested on the audio data of the Audio/Visual Emotion Challenge (AVEC) datasets showing performance significantly above that of a one-stage classification system that does not take into account the temporal relationship, as well as above the baseline set provided by this Challenge. Due to the generality of the approach, this system could be applied to other types of affective modalities