Tardos fingerprinting is better than we thought

We review the fingerprinting scheme by Tardos and show that it has a much better performance than suggested by the proofs in Tardos' original paper. In particular, the length of the codewords can be significantly reduced. First we generalize the proofs of the false positive and false negative error probabilities with the following modifications: (1) we replace Tardos' hard-coded numbers by variables and (2) we allow for independently chosen false positive and false negative error rates. It turns out that all the collusion-resistance properties can still be proven when the code length is reduced by a factor of more than 2. Second, we study the statistical properties of the fingerprinting scheme, in particular the average and variance of the accusations. We identify which colluder strategy forces the content owner to employ the longest code. Using a gaussian approximation for the probability density functions of the accusations, we show that the required false negative and false positive error rate can be achieved with codes that are a factor 2 shorter than required for rigid proofs. Combining the results of these two approaches, we show that the Tardos scheme can be used with a code length approximately 5 times shorter than in the original construction.Comment: Modified presentation of result

Privacy Preserving Multi-Server k-means Computation over Horizontally Partitioned Data

The k-means clustering is one of the most popular clustering algorithms in data mining. Recently a lot of research has been concentrated on the algorithm when the dataset is divided into multiple parties or when the dataset is too large to be handled by the data owner. In the latter case, usually some servers are hired to perform the task of clustering. The dataset is divided by the data owner among the servers who together perform the k-means and return the cluster labels to the owner. The major challenge in this method is to prevent the servers from gaining substantial information about the actual data of the owner. Several algorithms have been designed in the past that provide cryptographic solutions to perform privacy preserving k-means. We provide a new method to perform k-means over a large set using multiple servers. Our technique avoids heavy cryptographic computations and instead we use a simple randomization technique to preserve the privacy of the data. The k-means computed has exactly the same efficiency and accuracy as the k-means computed over the original dataset without any randomization. We argue that our algorithm is secure against honest but curious and passive adversary.Comment: 19 pages, 4 tables. International Conference on Information Systems Security. Springer, Cham, 201

Kinematic landslide monitoring with Kalman filtering

International audienceLandslides are serious geologic disasters that threat human life and property in every country. In addition, landslides are one of the most important natural phenomena, which directly or indirectly affect countries' economy. Turkey is also the country that is under the threat of landslides. Landslides frequently occur in all of the Black Sea region as well as in many parts of Marmara, East Anatolia, and Mediterranean regions. Since these landslides resulted in destruction, they are ranked as the second important natural phenomenon that comes after earthquake in Turkey. In recent years several landslides happened after heavy rains and the resulting floods. This makes the landslide monitoring and mitigation techniques an important study subject for the related professional disciplines in Turkey. The investigations on surface deformations are conducted to define the boundaries of the landslide, size, level of activity and direction(s) of the movement, and to determine individual moving blocks of the main slide. This study focuses on the use of a kinematic deformation analysis based on Kalman Filtering at a landslide area near Istanbul. Kinematic deformation analysis has been applied in a landslide area, which is located to the north of Istanbul city. Positional data were collected using GPS technique. As part of the study, conventional static deformation analysis methodology has also been applied on the same data. The results and comparisons are discussed in this paper

Project PROMETHEUS: Design and Construction of a Radio Frequency Quadrupole at TAEK

The PROMETHEUS Project is ongoing for the design and development of a 4-vane radio frequency quadrupole (RFQ) together with its H+ ion source, a low energy beam transport (LEBT) line and diagnostics section. The main goal of the project is to achieve the acceleration of the low energy ions up to 1.5 MeV by an RFQ (352 MHz) shorter than 2 meter. A plasma ion source is being developed to produce a 20 keV, 1 mA H+ beam. Simulation results for ion source, transmission and beam dynamics are presented together with analytical studies performed with newly developed RFQ design code DEMIRCI. Simulation results shows that a beam transmission 99% could be achieved at 1.7 m downstream reaching an energy of 1.5 MeV. As the first phase an Aluminum RFQ prototype, the so-called cold model, will be built for low power RF characterization. In this contribution the status of the project, design considerations, simulation results, the various diagnostics techniques and RFQ manufacturing issues are discussed.Comment: 4 pages, 8 figures, Proceedings of the 2nd International Beam Instrumentation Conference 2013 (IBIC'13), 16-19 Sep 2013, WEPC02, p. 65

Fluid Flows of Mixed Regimes in Porous Media

In porous media, there are three known regimes of fluid flows, namely, pre-Darcy, Darcy and post-Darcy. Because of their different natures, these are usually treated separately in literature. To study complex flows when all three regimes may be present in different portions of a same domain, we use a single equation of motion to unify them. Several scenarios and models are then considered for slightly compressible fluids. A nonlinear parabolic equation for the pressure is derived, which is degenerate when the pressure gradient is either small or large. We estimate the pressure and its gradient for all time in terms of initial and boundary data. We also obtain their particular bounds for large time which depend on the asymptotic behavior of the boundary data but not on the initial one. Moreover, the continuous dependence of the solutions on initial and boundary data, and the structural stability for the equation are established.Comment: 33 page

Graph Mining for Object Tracking in Videos

International audienceThis paper shows a concrete example of the use of graph mining for tracking objects in videos with moving cameras and without any contextual information on the objects to track. To make the mining algorithm efficient, we benefit from a video representation based on dy- namic (evolving through time) planar graphs. We then define a number of constraints to efficiently find our so-called spatio-temporal graph pat- terns. Those patterns are linked through an occurrences graph to allow us to tackle occlusion or graph features instability problems in the video. Experiments on synthetic and real videos show that our method is effec- tive and allows us to find relevant patterns for our tracking application

Time-to-birth prediction models and the influence of expert opinions

Preterm birth is the leading cause of death among children under five years old. The pathophysiology and etiology of preterm labor are not yet fully understood. This causes a large number of unnecessary hospitalizations due to high--sensitivity clinical policies, which has a significant psychological and economic impact. In this study, we present a predictive model, based on a new dataset containing information of 1,243 admissions, that predicts whether a patient will give birth within a given time after admission. Such a model could provide support in the clinical decision-making process. Predictions for birth within 48 h or 7 days after admission yield an Area Under the Curve of the Receiver Operating Characteristic (AUC) of 0.72 for both tasks. Furthermore, we show that by incorporating predictions made by experts at admission, which introduces a potential bias, the prediction effectiveness increases to an AUC score of 0.83 and 0.81 for these respective tasks