Towards an Informational Pragmatic Realism

I discuss the design of the method of entropic inference as a general framework for reasoning under conditions of uncertainty. The main contribution of this discussion is to emphasize the pragmatic elements in the derivation. More specifically: (1) Probability theory is designed as the uniquely natural tool for representing states of incomplete information. (2) An epistemic notion of information is defined in terms of its relation to the Bayesian beliefs of ideally rational agents. (3) The method of updating from a prior to a posterior probability distribution is designed through an eliminative induction process that singles out the logarithmic relative entropy as the unique tool for inference. The resulting framework includes as special cases both MaxEnt and Bayes’ rule. It therefore unifies entropic and Bayesian methods into a single general inference scheme. I find that similar pragmatic elements are an integral part of Putnam’s internal realism, of Floridi’s informational structural realism, and also of van Fraasen’s empiricist structuralism. I conclude with the conjecture that their valuable insights can be incorporated into a single coherent doctrine—an informational pragmatic realism.     

Monitoring stealthy diffusion

A broad variety of problems, such as targeted marketing and the spread of viruses and malware, have been modeled as maximizing the reach of diffusion through a network. In cyber-security applications, however, a key consideration largely ignored in this literature is stealth. In particular, an attacker who has a specific target in mind succeeds only if the target is reached before the malicious payload is detected and corresponding countermeasures deployed. The dual side of this problem is deployment of a limited number of monitoring units, such as cyber-forensics specialists, to limit the success of such targeted and stealthy diffusion processes. We investigate the problem of optimal monitoring of targeted stealthy diffusion processes. While natural variants of this problem are NP-hard, we show that if stealthy diffusion starts from randomly selected nodes, the defender’s objective is submodular and can be approximately optimized. In addition, we present approximation algorithms for the setting where the choice of the starting point is adversarial. We further extend our results to settings where the diffusion starts at multiple-seed nodes simultaneously, and where there is an inherent delay in detecting the infection. Our experimental results show that the proposed algorithms are highly effective and scalable.     

A survey on Mesh Segmentation Techniques

We present a review of the state of the art of segmentation and partitioning techniques of boundary meshes. Recently, these have become a part of many mesh and object manipulation algorithms in computer graphics, geometric modelling and computer aided design. We formulate the segmentation problem as an optimization problem and identify two primarily distinct types of mesh segmentation, namely part segmentation and surface‐patch segmentation. We classify previous segmentation solutions according to the different segmentation goals, the optimization criteria and features used, and the various algorithmic techniques employed. We also present some generic algorithms for the major segmentation techniques.     

Hierarchical scheduling strategies for parallel tasks and advance reservations in grids

Recently, the advance reservation functionality gained high importance in grids due to increasing popularity of modern applications that require interactive tasks, co-allocation of multiple resources, and performance guarantees. However, simultaneous scheduling, both advance reservations and batch tasks affects the performance. Advance reservations significantly deteriorate flow time of batch tasks and the overall resource utilization, especially in hierarchical scheduling structures. This is a consequence of unknown batch task processing times and the lack of possibility of altering allocations of advance reservations. To address these issues we present a common model for scheduling both computational batch tasks and tasks with advance reservation requests. We propose simple on-line scheduling policies and generic advices that reduce negative impact of advance reservations on a schedule quality. We also propose novel data structures and algorithms for efficient scheduling of advance reservations. A comprehensive experimental analysis is presented to show the influence of advance reservations on resource utilization, mean flow time, and mean tardiness—the criteria significant for administrators, users submitting batch tasks, and users requesting advance reservations, respectively. All experiments were performed with a well-known real workload using the GSSIM simulator.     

Fast Garbling of Circuits Under Standard Assumptions

Protocols for secure computation enable mutually distrustful parties to jointly compute on their private inputs without revealing anything, but the result. Over recent years, secure computation has become practical and considerable effort has been made to make it more and more efficient. A highly important tool in the design of two-party protocols is Yao’s garbled circuit construction (Yao 1986), and multiple optimizations on this primitive have led to performance improvements in orders of magnitude over the last years. However, many of these improvements come at the price of making very strong assumptions on the underlying cryptographic primitives being used (e.g., that AES is secure for related keys, that it is circular-secure, and even that it behaves like a random permutation when keyed with a public fixed key). The justification behind making these strong assumptions has been that otherwise it is not possible to achieve fast garbling and thus fast secure computation. In this paper, we take a step back and examine whether it is really the case that such strong assumptions are needed. We provide new methods for garbling that are secure solely under the assumption that the primitive used (e.g., AES) is a pseudorandom function. Our results show that in many cases, the penalty incurred is not significant, and so a more conservative approach to the assumptions being used can be adopted.     

Time-resolved momentum imaging system for molecular dynamics studies using a tabletop ultrafast extreme-ultraviolet light source

We describe a momentum imaging setup for direct time-resolved studies of ionization-induced molecular dynamics. This system uses a tabletop ultrafast extreme-ultraviolet (EUV) light source based on high harmonic upconversion of a femtosecond laser. The high photon energy (around 42 eV) allows access to inner-valence states of a variety of small molecules via single photon excitation, while the sub--10-fs pulse duration makes it possible to follow the resulting dynamics in real time. To obtain a complete picture of molecular dynamics following EUV induced photofragmentation, we apply the versatile cold target recoil ion momentum spectroscopy reaction microscope technique, which makes use of coincident three-dimensional momentum imaging of fragments resulting from photoexcitation. This system is capable of pump-probe spectroscopy by using a combination of EUV and IR laser pulses with either beam as a pump or probe pulse. We report several experiments performed using this system.     

Does fragmentation avoidance improve the performance of dynamic spectrum allocation in elastic optical networks?

Most spectrum allocation algorithms in elastic optical networks apply a greedy approach: A new connection is allocated as long as there are enough spectrum slots to accommodate it. Recently, a different approach was proposed. Named Deadlock–Avoidance (DA), it only establishes a new connection if the portion of spectrum left after allocating it is zero (full-link utilization) or is big enough to accommodate future requests. Otherwise, the connection request is blocked as a way to avoid fragmentation. The performance of DA has been evaluated in a single-link scenario, where its performance is not affected by the slot continuity constraint. In this paper, we evaluate for the first time the blocking performance and fragmentation level of DA in a fully dynamic network scenario with different bitrates and number of slots for a single link, a 4-node bus and a mesh topology. The performance was evaluated by simulation, and a lower bound was also derived using a continuous Markov chain model. Results are obtained for DA and three greedy algorithms: First Fit, Exact Fit and First–Last Fit. Results show that DA significantly decreases fragmentation, and thus, it exhibits a much lower blocking due to fragmentation than the greedy algorithms. However, this decrease is compensated by a new type of blocking due to the selective acceptance of connections. As a result, the extra computational complexity of DA does not compensate a gain in performance.     

Pyrolysis shaker reactor for the production of biochar

Intermediate pyrolysis reactors are preferred for processes focused on the production of high-quality biochar. The main types are rotary drums, augers, and moving beds agitated with either grates or paddles. These reactors are usually operated in continuous mode, and are designed to provide a pure, homogeneous biochar product by ensuring near plug flow of the reacting particles. There is a need for laboratory reactors that can provide enough biochar for testing in applications such as soil amendment, fillers for concrete or polymers, coke substitution, or pollutant capture. The pyrolysis shaker reactor (PSR) is a new laboratory reactor that is inexpensive, provides good mixing and temperature control, is easy to operate and allows for rapid turnaround between runs. It provides a homogeneous biochar product. Its use was demonstrated with digestate from the anaerobic digestion of food waste. The rapid and thorough testing program made possible with the PSR indicated that this digestate should be pyrolyzed at 250°C to maximize the release of mineral from the biochar to water, and at 400°C to minimize the release of minerals. Its biochar would require post-treatment to be applied as a substitute for activated carbon.     

A perspective on surrogate endpoints in controlled clinical trials

The last couple of decades have seen a large amount of activity in the area of surrogate marker and surrogate endpoint validation, both from a clinical and a statistical perspective. Prentice made a pivotal contribution in the context of a single trial. Subsequently, the framework he proposed has been discussed, criticized, and extended. An important class of extensions considers several rather than a single trial. Recently, a lot of work has been done in this so-called hierarchical or meta-analytic framework. In this paper, we review both the single trial and the hierarchical framework. A number of applications, scattered throughout the literature, are brought together. We outline the statistical issues involved in trying to validate surrogate endpoints. Clearly statistical evidence should only be seen as a component in a decision making process that also involves a number of clinical and biological considerations.