Literature Survey on Underwater Threat Detection

This paper presents a concise review on extant literature in threat detection within the maritime domain with specific emphasis on solution methodologies, sensing technologies, regional affiliations of authors and research contributions related to underwater threat detection. The review attempts to provide an introductory framework on threat detection and surveillance within the maritime domain as opposed to its widely studied terrestrial counterpart. In all, over 200 engineering/science journal papers and conference proceedings were identified. Of these, a total of 136 articles are eventually chosen and reviewed. The analysis of this review suggests that opportunities abound in the research area, especially in Operations Research/ Management Science. Specifically, Sensor placement and deployment for underwater threat detection is identified as a significant sub -research area worth studying

An Information Based Routing Model for Hazardous Material Route Selection Problem

oai:iser.sisengr.org:article/2In this paper, we address some key research questions concerning the alternative routing policy of hazardous materials in real time using stochastic dynamic networks based on real life situations. The scenario that we address in this paper involves the use of sophisticated communication tools to provide information on the current condition of the optimal path and incorporate them in our optimization model to generate alternative routes for hazmat vehicles. We address the issues of designing a framework and requirements for an adaptive routing system. To overcome system instability and information overloading, a feeback based routing policy within the framework has been developed. We show the implementation of the framework and disucss the potential benefits of our approach with the help of numerical experiments based on a real hazmat transportation network

A clustering approach for optimizing beam angles in IMRT planning

In this paper we introduce a p-median problem based clustering heuristic for selecting efficient beam angles for intensity-modulated radiation therapy. The essence of the method described here is the clustering of beam angles according to probability that an angle will be observed in the final solution and similarities among different angles and the selection of a representative angle from each of the p resulting cluster cells. We conduct experiments using several combinations of modeling parameters to find the conditions where the heuristic best performs. We found a combination of such parameters that outperformed all other parameters on three of the four tested instances

Solving the p-Median Problem with Insights from Discrete Vector Quantization

The goals of this paper are twofold. First, we formally equate the p-median problem from facility location to the optimal design of a vector quantizer. Second, we use the equivalence to show that the Maranzana Algorithm can be interpreted as a projected Lloyd Algorithm, a fact that improves complexity. Numerical results verify significant improvements in run-time

Liquefied Natural Gas Ship Route Planning Model Considering Market Trend Change

We consider a new biannual liquefi ed natural gas (LNG) ship routing and scheduling problem and a stochastic extension under boil-off gas (BOG) uncertainty while serving geographically dispersed multiple customers using a fl eet of heterogeneous vessels. We are motivated not only by contract trend changes to shorter ones but also by technological advances in LNG vessel design. The mutual coincidence of both transitions enables developing a new LNG shipping strategy to keep up with emerging market trend. We fi rst propose a deterministic LNG scheduling model formulated as a multiple vehicle routing problem (VRP). The model is then extended to consider BOG using a two-stage stochastic modeling approach in which BOG is a random variable. Since the VRP is typically a combinatorial optimization problem, its stochastic extension is much harder to solve. In order to overcome this computational burden, a Monte Carlo sampling optimization is used to reduce the number of scenarios in the stochastic model while ensuring good quality of solutions. The solutions are evaluated using expected value of perfect information (EVPI) and value of stochastic solution (VSS). The result shows that our proposed model yields more stable solutions than the deterministic model. The study was made possible by the NPRP award [NPRP 4-1249-2-492] from the Qatar National Research Fund (a member of the Qatar Foundation)

Acute Achilles tendon rupture: minimally invasive surgery versus non operative treatment, with immediate full weight bearing. Design of a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>We present the design of an open randomized multi-centre study on surgical versus conservative treatment of acute Achilles tendon ruptures. The study is designed to evaluate the effectiveness of conservative treatment in reducing complications when treating acute Achilles tendon rupture.</p> <p>Methods/Design</p> <p>At least 72 patients with acute Achilles tendon rupture will be randomized to minimally invasive surgical repair followed by functional rehabilitation using tape bandage or conservative treatment followed by functional rehabilitation with use of a functional bracing system. Both treatment arms use a 7 weeks post-rupture rehabilitation protocol. Four hospitals in the Netherlands will participate. Primary end-point will be reduction in complications other than re-rupture. Secondary end-point will be re-rupturing, time off work, sporting activity post rupture, functional outcome by Leppilahti score and patient satisfaction. Patient follow-up will be 12 month.</p> <p>Discussion</p> <p>By making this design study we wish to contribute to more profound research on AT rupture treatment and prevent publication bias for this open-labelled randomized trial.</p> <p>Trial registration</p> <p>ISRCTN50141196</p

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV