Min-Max-Min Robustness for Combinatorial Problems with Discrete Budgeted Uncertainty

We consider robust combinatorial optimization problems with cost uncertainty where the decision maker can prepare K solutions beforehand and chooses the best of them once the true cost is revealed. Also known as min-max-min robustness (a special case of K-adaptability), it is a viable alternative to otherwise intractable two-stage problems. The uncertainty set assumed in this paper considers that in any scenario, at most Γ of the components of the cost vectors will be higher than expected, which corresponds to the extreme points of the budgeted uncertainty set. While the classical min-max problem with budgeted uncertainty is essentially as easy as the underlying deterministic problem, it turns out that the min-max-min problem is N P-hard for many easy combinatorial optimization problems, and not approximable in general. We thus present an integer programming formulation for solving the problem through a row-and-column generation algorithm. While exact, this algorithm can only cope with small problems, so we present two additional heuristics leveraging the structure of budgeted uncertainty. We compare our row-and-column generation algorithm and our heuristics on knapsack and shortest path instances previously used in the scientific literature and find that the heuristics obtain good quality solutions in short computational times

Faster Algorithms for Min-max-min Robustness for Combinatorial Problems with Budgeted Uncertainty

International audienceWe consider robust combinatorial optimization problems where the decision maker can react to a scenario by choosing from a finite set of k solutions. This approach is appropriate for decision problems under uncertainty where the implementation of decisions requires preparing the ground. We focus on the case that the set of possible scenarios is described through a budgeted uncertainty set and provide three algorithms for the problem. The first algorithm solves heuristically the dualized problem, a non-convex mixed-integer non-linear program (MINLP), via an alternating optimization approach. The second algorithm solves the MINLP exactly for k = 2 through a dedicated spatial branch-and-bound algorithm. The third approach enumerates k-tuples, relying on strong bounds to avoid a complete enumeration. We test our methods on shortest path instances that were used in the previous literature and on randomly generated knapsack instances, and find that our methods considerably outperform previous approaches. Many instances that were previously not solved within hours can now be solved within few minutes, often even faster

Defending Against Insider Use of Digital Steganography

The trusted insider is among the most harmful and difficult to detect threats to information security, according to the Federal Plan for Information Assurance and Cyber Security Research and Development released in April 2006. By default, employees become trusted insiders when granted the set of privileges needed to do their jobs, which typically includes access to the Internet. It is generally presumed the insiders are loyally working to achieve the organization’s goals and objectives and would not abuse the privileges given to them. However, some insiders will inevitably abuse some of their privileges. For example, a trusted insider might abuse their privilege of access to the Internet to download, install, and use an information hiding tool, such as one of the hundreds of digital steganography applications available on the Internet, to steal sensitive, classified, or proprietary information. Effective countermeasures to this threat must begin with an organizational policy prohibiting installation of information hiding tools on user workstations and must also include automated tools capable of detecting attempts to download and use digital steganography applications. This paper will describe the threat from insider use of digital steganography applications; a new approach to detecting the presence or use of these applications; and extraction of hidden information when a known signature of one of these applications is detected. The analytical approach to steganalysis involves the development and use of computer forensic tools that can detect fingerprints and signatures of digital steganography applications. These tools can be employed in both an off-line forensic-based mode as well as a real-time network surveillance mode. Detection of fingerprints or signatures in either mode may lead to the discovery and extraction of hidden information. Accordingly, this approach represents a significant improvement over traditional blind detection techniques which typically only provide a probability that information may be hidden in a given file without providing a capability to extract any hidden information. Keywords: insider, steganography, steganalysis, computer forensics, artifacts, fingerprints, hash values, signature

Spectral classification of the brightest objects in the galactic star forming region W40

We present high S/N, moderate resolution near-infrared spectra, as well as 10 micron imaging, for the brightest members of the central stellar cluster in the W40 HII region, obtained using the SpeX and MIRSI instruments at NASA's Infrared Telescope Facility. Using these observations combined with archival Spitzer Space Telescope data, we have determined the spectral classifications, extinction, distances, and spectral energy distributions for the brightest members of the cluster. Of the eight objects observed, we identify four main sequence (MS) OB stars, two Herbig Ae/Be stars, and two low-mass young stellar objects. Strong HeI absorption at 1.083 micron in the MS star spectra strongly suggests that at least some of these sources are in fact close binaries. Two out of the four MS stars also show significant infrared excesses typical of circumstellar disks. Extinctions and distances were determined for each MS star by fitting model stellar atmospheres to the SEDs. We estimate a distance to the cluster of between 455 and 535 pc, which agrees well with earlier (but far less precise) distance estimates. We conclude that the late-O star we identify is the dominant source of LyC luminosity needed to power the W40 HII region and is the likely source of the stellar wind that has blown a large (~4 pc) pinched-waist bubble observed in wide field mid-IR images. We also suggest that 3.6 cm radio emission observed from some of the sources in the cluster is likely not due to emission from ultra-compact HII regions, as suggested in other work, due to size constraints based on our derived distance to the cluster. Finally, we also present a discussion of the curious source IRS 3A, which has a very strong mid-IR excess (despite its B3 MS classification) and appears to be embedded in a dusty envelope roughly 2700 AU in size.Comment: Accepted for publication in The Astronomical Journal. 29 pages, 10 figure

Mauve Assembly Metrics

Summary: High-throughput DNA sequencing technologies have spurred the development of numerous novel methods for genome assembly. With few exceptions, these algorithms are heuristic and require one or more parameters to be manually set by the user. One approach to parameter tuning involves assembling data from an organism with an available high-quality reference genome, and measuring assembly accuracy using some metrics

Temporal Expression of Bacterial Proteins Instructs Host CD4 T Cell Expansion and Th17 Development

Pathogens can substantially alter gene expression within an infected host depending on metabolic or virulence requirements in different tissues, however, the effect of these alterations on host immunity are unclear. Here we visualized multiple CD4 T cell responses to temporally expressed proteins in Salmonella-infected mice. Flagellin-specific CD4 T cells expanded and contracted early, differentiated into Th1 and Th17 lineages, and were enriched in mucosal tissues after oral infection. In contrast, CD4 T cells responding to Salmonella Type-III Secretion System (TTSS) effectors steadily accumulated until bacterial clearance was achieved, primarily differentiated into Th1 cells, and were predominantly detected in systemic tissues. Thus, pathogen regulation of antigen expression plays a major role in orchestrating the expansion, differentiation, and location of antigen-specific CD4 T cells in vivo