The Bi2O3-SrO phase diagram

The phase relations in the Bi₂O₃-SrO system have been examined in air at temperatures above 740 °C. Intermediate phases were found to agree with previous work, but the homogeneity ranges and high-temperature phase relationships were in some cases at variance. A modified phase diagram is proposed.     

Pinhole density measurements of barriers deposited on low-k films

Evaluation of diffusion barrier integrity is an important issue in advanced interconnects. A diffusion barrier separating Cu from low-k must be as thin as possible and must not contain pinholes. We have developed a method for measuring pinhole density in diffusion barriers deposited on low-k materials. The method employs ellipsometric porosimetry for measuring diffusion of toluene in a porous low-k film beneath the barrier in question.     

Neutral fitness landscapes in signalling networks

Biological and technological systems process information by means of cascades of signals. Be they interacting genes, spiking neurons or electronic transistors, information travels across these systems, producing, for each set of external conditions, an appropriate response. In technology, circuits performing specific complex tasks are designed by humans. In biology, however, design has to be ruled out, confronting us with the question of how these systems could have arisen by accumulation of small changes. The key factor is the genotype-phenotype map. With the exception of RNA folding, not much is known about the exact nature of this mapping. Here, we show that structure of the genotype-phenotype map of simple feed-forward circuits is very close to the ones found in RNA; they have a large degree of neutrality, by which a circuit can be completely rewired keeping its input-output function intact, and there is a relatively small neighbourhood of a given circuit containing almost all the phenotypes.     

Learning Read-Constant Polynomials of Constant Degree Modulo Composites

Boolean functions that have constant degree polynomial representation over a fixed finite ring form a natural and strict subclass of the complexity class ACC⁰. They are also precisely the functions computable efficiently by programs over fixed and finite nilpotent groups. This class is not known to be learnable in any reasonable learning model. In this paper, we provide a deterministic polynomial time algorithm for learning Boolean functions represented by polynomials of constant degree over arbitrary finite rings from membership queries, with the additional constraint that each variable in the target polynomial appears in a constant number of monomials. Our algorithm extends to superconstant but low degree polynomials and still runs in quasipolynomial time.     

GPU-OSDDA: a bit-vector GPU-based deadlock detection algorithm for single-unit resource systems

This article presents a GPU-based single-unit deadlock detection methodology and its algorithm, GPU-OSDDA. Our GPU-based design utilizes parallel hardware of GPU to perform computations and thus is able to overcome the major limitation of prior hardware-based approaches by having the capability of handling thousands of processes and resources, whilst achieving real-world run-times. By utilizing a bit-vector technique for storing algorithm matrices and designing novel, efficient algorithmic methods, we not only reduce memory usage dramatically but also achieve two orders of magnitude speedup over CPU equivalents. Additionally, GPU-OSDDA acts as an interactive service to the CPU, because all of the aforementioned computations and matrix management techniques take place on the GPU, requiring minimal interaction with the CPU. GPU-OSDDA is implemented on three GPU cards: Tesla C2050, Tesla K20c, and Titan X. Our design shows overall speedups of 6-595X over CPU equivalents.     

Open Challenges in Relationship-Based Privacy Mechanisms for Social Network Services

Social networking services (SNSs) such as Facebook and Twitter have experienced explosive growth during the few past years. Millions of users have created their profiles on these services because they experience great benefits in terms of friendship. SNSs can help people to maintain their friendships, organize their social lives, start new friendships, and meet others who share their hobbies and interests. However, all these benefits can be eclipsed by the privacy hazards that affect people in SNSs. People expose intimate information about their lives on SNSs, and this information affects the way others think about them. It is crucial that users be able to control how their information is distributed through the SNSs and decide who can access it. This article presents a list of privacy threats that can affect SNS users and what requirements privacy mechanisms should fulfill to prevent this threats. Then the article reviews current approaches and analyzes to what extent they cover the requirements.     

Ensembles of decision trees based on imprecise probabilities and uncertainty measures

In this paper, we present an experimental comparison among different strategies for combining decision trees built by means of imprecise probabilities and uncertainty measures. It has been proven that the combination or fusion of the information obtained from several classifiers can improve the final process of the classification. We use previously developed schemes, known as Bagging and Boosting, along with a new one based on the variation of the root node via the information rank of each feature of the class variable. To this end, we applied two different approaches to deal with missing data and continuous variables. We use a set of tests on the performance of the methods analyzed here, to show that, with the appropriate approach, the Boosting scheme constitutes an excellent way to combine this type of decision tree. It should be noted that it provides good results, even compared with a standard Random Forest classifier, a successful procedure very commonly used in the literature.     

Self-adaptive utility-based web session management

In the Internet, where millions of users are a click away from your site, being able to dynamically classify the workload in real time, and predict its short term behavior, is crucial for proper self-management and business efficiency. As workloads vary significantly according to current time of day, season, promotions and linking, it becomes impractical for some ecommerce sites to keep over-dimensioned infrastructures to accommodate the whole load. When server resources are exceeded, session-based admission control systems allow maintaining a high throughput in terms of properly finished sessions and QoS for a limited number of sessions; however, by denying access to excess users, the website looses potential customers.In the present study we describe the architecture of AUGURES, a system that learns to predict Web user’s intentions for visiting the site as well its resource usage. Predictions are made from information known at the time of their first request and later from navigational clicks. For this purpose we use machine learning techniques and Markov-chain models. The system uses these predictions to automatically shape QoS for the most profitable sessions, predict short-term resource needs, and dynamically provision servers according to the expected revenue and the cost to serve it. We test the AUGURES prototype on access logs from a high-traffic, online travel agency, obtaining promising results.     

Application of top seeding in the melt processing of Nd<Subscript>123</Subscript> thick films on YSZ substrates: I buffer layer optimization

A new concept of a buffer layer in superconducting thick film technology was tested. The idea is based on increasing the NdBa₂Cu₃O_x melt viscosity at the processing temperature near the substrate by using higher ratios of Nd₄Ba₂Cu₂O_z solid phase in the first screen printed pass which is considered as a buffer layer. Different compositions, thicknesses and thermal schedules were used to optimise the buffer layer. The optimised buffer layer was employed in the fabrication of NdBa₂Cu₃O_y thick films on yttria stabilized zirconia (YSZ) substrates using the top seeding melt growth (TSMG) technique. Using the buffer layer was effective in preventing a large amount of liquid (BaCuO₂-CuO) from severe interaction with the substrate during the prolonged time in the TSMG technique. Consequently, a large superconducting single domain was obtained. Thick films were melt processed in 0.1% O₂ in Ar atmosphere to suppress the Nd_{1 + x}Ba_{2 − x}Cu₃O_y (Nd_123SS) solid solution formation. The produced thick films have high transition temperature (T_C) and improved microstructures.