The popularity of social networks make them most efficient to integrate into the Emergency Management process. Posts on social networking sites can help people by ensuring timely detection of an emergency. Often during the situations of a natural disaster, there is an information chasm created between the affected and the unaffected area that further compounds the confusion and chaos. In this paper, we examine the various challenges that exist while attempting to integrate social networks and Emergency Management and trace the state-of-art techniques that exist in various domains that come together for this Emergency Management system. We propose an end-to-end framework that takes public posts from social networking sites and converts it into a structured format that makes the information actionable. A summarization technique may be applied to the acquired information post mining of social media feed to convert everything into a text message that can be released into various social platforms. To increase the reach of this post and to warrant better public participation in the crisis in a timely manner, we apply influence maximization techniques and monitor the diffusion process of this generated post through a diffusion modelling technique that we propose. We conduct experiments to analyze the performance of this model and of the influence maximization process and conclude with an analysis of the experiments and the observed results and list out improvements that we intend to incorporate in future versions of this work.

Estimating the criticality of each link in a transportation network is a crucial step for guiding the design and deployment of vulnerability reduction measures. Using exhaustive simulations based on user-equilibrium assignment to evaluate the effect of the failure of each link (or set of links) can be prohibitively time-consuming for reasonably-sized transportation networks. In this paper, we propose an alternative heuristic approach to the estimation the vulnerability of network links employing efficient graph-theoretical algorithms. In particular, our model estimates the cost of single link failure based on the increase in shortest path travel time taking into account the effect of congestion. Results show that the proposed method can reliably be used to estimate the relative effect of each link failure on the system travel time and rank links accordingly.

In this paper we study the important problems of message routing, sorting, and selection in a radio network. A radio network consists of stations where each station is a hand-held device. We consider a single-hop radio network. In a single-hop network it is assumed that each station is within the transmission range of every other station. Let RN(p; k) stand for a single-hop network that has p stations and k communication channels. The problems of sorting and selection have been studied on RN(p; k). For these problems it is assumed that there are n/p elements to start with at each station. At the end of sorting, the least n/p elements should be in the first station, the next smallest n/p elements should be in the second station, and so on. The best known prior algorithm for sorting takes 4n/k +o(n/k) broadcast rounds on a RN(p; k). In this paper we present a randomized algorithm that takes only 3n/k +o(n/k) broadcast rounds with high probability. For the selection problem, it is known that the maximum or minimum element can be found in O(log n) rounds on a RN(n; 1), provided broadcast conflicts can be resolved in O(1) time. The problem of general selection has not been addressed. In this paper we present a randomized selection algorithm that takes O(p/k) rounds on a RN(p; k) with high probability. An important message routing problem that is considered in the literature is one where there are n/p packets originating from each station and there are n/p packets destined for each station. The best known routing algorithms take nearly 2n/k times slots. An important open question has been if there exist algorithms that take only close to n/k time slots. Note that a trivial lower bound for routing is n/k. The existence of such algorithms will be highly relevant especially in emergencies and time critical situations. In this paper we answer this question by presenting a randomized algorithm that takes nearly n/k time slots with high probability.

The multiplex polymerase chain reaction (MP-PCR) is a quick and inexpensive technique in molecular biology for amplifying multiple DNA loci in a single Polymerase Chain Reaction (PCR). One of the criteria to achieve highly specific reaction products is to keep the concentration of the amplification primers low. In research, the dilemma associated with primer minimization for MP-PCR reactions has been formulated as the Multiple Degenerate Primer Selection Problem (MDPSP). MDPSP is related to the earlier Degenerate Primer Design (DPD) problem that has proven to be NP-complete. This paper formulates a new, so far, unexplored variant, the Multiple Degenerate Primer Selection Problem with Errors (MDPSPE) and introduces new algorithms for solving this new version. Furthermore, we implement an exact algorithm, DPS-HDR for solving the earlier MDPSP and compare the algorithm's performance on randomly generated data sets with DPS-HD, thus far the most efficient algorithm for solving MDPSP introduced in. We expect to reduce the execution time of the algorithm in comparison to DPS-HD.

Extracting meaningful patterns from voluminous amount of biological data is a very big challenge. Motifs are biological patterns of great interest to biologists. There are different versions of the Motif Finding Problem. In this paper we concentrate on the Planted (l, d) Motif Search Problem. There have been numerous algorithms designed to solve this problem. Many instances of the Planted (l, d) Motif Problem have been identified as challenging instances. The algorithm proposed here is an extension of PMS3. It uses a very simple approach and solves challenging instances ((21, 8), for example) that have not been reported solved before in the literature. We also propose a new algorithm PMS3p. We expect PMS3p to be significantly faster than PMS3.

The problem of sorting has been studied extensively and many algorithms have been suggested in the literature for the problem. Literature on parallel sorting is abundant. Many of the algorithms proposed, though being theoretically important, may not perform satisfactorily in practice owing to large constants in their time bounds. The algorithms presented in this paper have the potential of being practical. We suggest some novel sorting mechanisms specific to the cell broadband engine. We try to utilize the specifics of its architecture in order to get the optimum performance. As part of our comparative analysis we juxtapose these algorithms with similar ones implemented on Itanium 2 processor as well as the Pentium 4 processor.