Corpus-Based Transcription as an Approach to the Compositional Control of Timbre

Timbre space is a cognitive model useful to address the problem of structuring timbre in electronic music. The recent concept of corpus-based concatenative sound synthesis is proposed as an approach to timbral control in both real- and deferred-time applications. Using CataRT and related tools in the FTM and Gabor libraries for Max/MSP we describe a technique for real-time analysis of a live signal to pilot corpus-based synthesis, along with examples of compositional realizations in works for instruments, electronics, and sound installation. To extend this technique to computer-assisted composition for acoustic instruments, we develop tools using the Sound Description Interchange Format (SDIF) to export sonic descriptors to OpenMusic where they may be further manipulated and transcribed into an instrumental score. This presents a flexible technique for the compositional organization of noise-based instrumental sounds

A Study of the Hoesch-Houben Synthesis in the Preparation of Aromatic Ketimines and Hydroxy-Phenyl Iminoesters

This synthesis involves the condensation of a phenol with a nitrile (aliphatic or aromatic). It is effected by the passage of dry hydrogen chloride through their solution in anhydrous ether, with or without the addition of dry zinc chloride. Anhydrous aluminum chloride was substituted for zinc chloride in some cases

Password-based group key exchange in a constant number of rounds

Abstract. With the development of grids, distributed applications are spread across multiple computing resources and require efficient security mechanisms among the processes. Although protocols for authenticated group Diffie-Hellman key exchange protocols seem to be the natural mechanisms for supporting these applications, current solutions are either limited by the use of public key infrastructures or by their scalability, requiring a number of rounds linear in the number of group members. To overcome these shortcomings, we propose in this paper the first provably-secure password-based constant-round group key exchange protocol. It is based on the protocol of Burmester and Desmedt and is provably-secure in the random-oracle and ideal-cipher models, under the Decisional Diffie-Hellman assumption. The new protocol is very efficient and fully scalable since it only requires four rounds of communication and four multi-exponentiations per user. Moreover, the new protocol avoids intricate authentication infrastructures by relying on passwords for authentication.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem

Convergence and Energy Landscape for Cheeger Cut Clustering

This paper provides both theoretical and algorithmic results for the l 1-relaxation of the Cheeger cut problem. The l2- relaxation, known as spectral clustering, only loosely relates to the Cheeger cut; however, it is convex and leads to a simple optimization problem. The l1-relaxation, in contrast, is non-convex but is provably equivalent to the original problem. The l1-relaxation therefore trades convexity for exactness, yielding improved clustering results at the cost of a more challenging optimization. The first challenge is understanding convergence of algorithms. This paper provides the first complete proof of convergence for algorithms that minimize the l1-relaxation. The second challenge entails comprehending the l1-energy landscape, i.e. the set of possible points to which an algorithm might converge. We show that l 1-algorithms can get trapped in local minima that are not globally optimal and we provide a classification theorem to interpret these local minima. This classification gives meaning to these suboptimal solutions and helps to explain, in terms of graph structure, when the l1-relaxation provides the solution of the original Cheeger cut problem

Decreasing time consumption of microscopy image segmentation through parallel processing on the GPU

The computational performance of graphical processing units (GPUs) has improved significantly. Achieving speedup factors of more than 50x compared to single-threaded CPU execution are not uncommon due to parallel processing. This makes their use for high throughput microscopy image analysis very appealing. Unfortunately, GPU programming is not straightforward and requires a lot of programming skills and effort. Additionally, the attainable speedup factor is hard to predict, since it depends on the type of algorithm, input data and the way in which the algorithm is implemented. In this paper, we identify the characteristic algorithm and data-dependent properties that significantly relate to the achievable GPU speedup. We find that the overall GPU speedup depends on three major factors: (1) the coarse-grained parallelism of the algorithm, (2) the size of the data and (3) the computation/memory transfer ratio. This is illustrated on two types of well-known segmentation methods that are extensively used in microscopy image analysis: SLIC superpixels and high-level geometric active contours. In particular, we find that our used geometric active contour segmentation algorithm is very suitable for parallel processing, resulting in acceleration factors of 50x for 0.1 megapixel images and 100x for 10 megapixel images

Image Segmentation Model Using Active contour and Image Decomposition

This paper proposes an image segmentation model based on the active contour model, the Mumford-Shah functional and the image decomposition process. Generally speaking, the active contour model detects boundaries in images from sharp intensities variations and the Mumford-Shah model finds smooth regions from homogeneous intensities. Our model merges these two complementary approaches while considering the Four Color Theorem to globally partition any given image. We also consider the textural part lying in natural images by separating it from the geometric part, which contains the meaningful objects, to help the segmentation process. Our segmentation model is experimented with a 1-D signal and 2-D images

ProvablySecure Authenticated Group Diffie-Hellman Key Exchange

Abstract: Authenticated key exchange protocols allow two participants A and B, communicating over a public network and each holding an authentication means, to exchange a shared secret value. Methods designed to deal with this cryptographic problem ensure A (resp. B) that no other participants aside from B (resp. A) can learn any information about the agreed value, and often also ensure A and B that their respective partner has actually computed this value. A natural extension to this cryptographic method is to consider a pool of participants exchanging a shared secret value and to provide a formal treatment for it. Starting from the famous 2-party Diffie-Hellman (DH) key exchange protocol, and from its authenticated variants, security experts have extended it to the multi-party setting for over a decade and completed a formal analysis in the framework of modern cryptography in the past few years. The present paper synthesizes this body of work on the provably-secure authenticated group DH key exchange. The present paper revisits and combines the full versions of the following four papers

Geometric Moments in Scale-Spaces

In this paper we present a generalization of geometric moments in scale-spaces derived from the general heat diffusion equation, with a particular interest for th