Efficient identity-based online/offline encryption and signcryption with short ciphertext

The technique of online/offline is regarded as a promising approach to speed up the computation of encryption, because the most part of computation, such as pairing over points on elliptic curve and exponentiation in groups, can be pre-computed in the offline phase without knowing the message to be encrypted and/or recipient’s identity. The online phase only requires light computation, such as modular multiplication. In this paper, we propose two novel identity-based online/offline schemes: a full secure identity-based online/offline encryption scheme and an identity-based online/offline signcryption scheme. Compared to the other schemes in the literature, our schemes achieve the shortest ciphertext size in both offline and online phases and demonstrate the best performance in offline computation. Our schemes are applicable to devices with limited computation power. They are proven secure in the random oracle model.     

Identity-based trapdoor mercurial commitments and applications

In this paper, we first introduce the notion of identity-based trapdoor mercurial commitment which enjoys the advantages of both the identity-based trapdoor commitment and trapdoor mercurial commitment, while using the idea of “Customized Identity”. Inherently, an identity-based trapdoor mercurial commitment is an underlying building block for constructing identity-based (non-interactive) zero-knowledge sets. That is, a prover can commit to a set S in a way that reveals nothing about S and prove to a verifier, in zero-knowledge, statements of the form x∈S and x∉S. Besides, although the (non-interactive) proof is publicly verifiable, it is also bound to the identity of the prover in a way which is recognizable to any verifier.     

Human pathogenic streptococcal proteomics and vaccine development

Gram-positive streptococci are non-motile, chain-forming bacteria commonly found in the normal oral and bowel flora of warm-blooded animals. Over the past decade, a proteomic approach combining 2-DE and MS has been used to systematically map the cellular, surface-associated and secreted proteins of human pathogenic streptococcal species. The public availability of complete streptococcal genomic sequences and the amalgamation of proteomic, genomic and bioinformatic technologies have recently facilitated the identification of novel streptococcal vaccine candidate antigens and therapeutic agents. The objective of this review is to examine the constituents of the streptococcal cell wall and secreted proteome, the mechanisms of transport of surface and secreted proteins, and describe the current methodologies employed for the identification of novel surface-displayed proteins and potential vaccine antigens.     

ICT in higher education: evaluating outcomes for health education

Abstract This paper presents an investigation that examined and compared the effectiveness of collaborative tutorial activities carried out in both web-based and face-to-face learning environments within an undergraduate health education subject. Effectiveness of the different learning environments was measured in terms of observed learning outcomes, analysis of learner interactions and reported perceptions of the learners regarding their experience. Results demonstrated that web-based environments, with embedded collaborative activities, can effectively foster rich learning experiences that result in attaining positive learning outcomes.     

Noisy Time Series Prediction using Recurrent Neural Networks and Grammatical Inference

Financial forecasting is an example of a signal processing problem which is challenging due to small sample sizes, high noise, non-stationarity, and non-linearity. Neural networks have been very successful in a number of signal processing applications. We discuss fundamental limitations and inherent difficulties when using neural networks for the processing of high noise, small sample size signals. We introduce a new intelligent signal processing method which addresses the difficulties. The method proposed uses conversion into a symbolic representation with a self-organizing map, and grammatical inference with recurrent neural networks. We apply the method to the prediction of daily foreign exchange rates, addressing difficulties with non-stationarity, overfitting, and unequal a priori class probabilities, and we find significant predictability in comprehensive experiments covering 5 different foreign exchange rates. The method correctly predicts the directionof change for the next day with an error rate of 47.1%. The error rate reduces to around 40% when rejecting examples where the system has low confidence in its prediction. We show that the symbolic representation aids the extraction of symbolic knowledge from the trained recurrent neural networks in the form of deterministic finite state automata. These automata explain the operation of the system and are often relatively simple. Automata rules related to well known behavior such as tr end following and mean reversal are extracted.     

The Added Value of Understanding Informal Social Networks in an Adaptive Capacity Assessment: Explorations of an Urban Water Management System in Indonesia

Social networks play an important role in environmental governance regimes, and they are a key to the adaptive capacity of systems that deal with complex, contextual and multi-faceted issues. Urban water systems are typical examples of complex systems facing many pressures, such as increased population, water quality deterioration, and climate change. This paper explores social networks of the key stakeholders engaged in urban water management, in Makassar City, Indonesia, in the context of exploring ways to improve management of an increasingly complex urban water system. Three social networks were explored; those constituted by formal and informal interactions and networks perceived by stakeholders to be “ideal”. Formal networks were identified through an examination of the legislative instruments and government agencies’ documents relating to water provision in Makassar, while the informal and “ideal” networks were investigated in collaboration with the stakeholders. The research found that the informal social network was more extensive than were the formally required networks, and the investigation of informal networks created a potentially more robust and adaptive water management system than would have occurred through inclusion of formal institutional arrangements. We suggest that in examination of the adaptive capacity of an urban water system, one also considers the informal arrangements and linkages, as this additional information about the system is necessary to enhance our understanding of potential adaptation of water management and improved urban water systems.     

On the effect of Multiple Access Interference in a Space Time Spreading Time Hopping PPM UWB system

This study investigates the effect of multiple sources using STS across a Time-Hopping-PPM Modulation that is over an UWB Saleh-Valenzuela channel with each source using two transmit antennas. We model and analyze this system, showing that the presence of such MAI results in a significant degradation in BER performance. Simulation results show that for strong signal strength of interfering MAI signals degradation in BER performance is observed for the cases where we have five and 10 distinct MAI sources present when using Walsh-Hadamard thirty two chip spreading sequences. Using simulation, we investigate the use of other sets of orthogonal spreading sequences with improved cross correlation properties and find that for some sequences a significant improvement is seen compared to Walsh-Hadamard sequences when they are similarly misaligned. We show that MAI degrades the BER performance of such systems and that selection of improved cross correlation spreading code sequence sets improves BER.     

Oxidation behaviors of Ni-Cr-Al superalloy foams at 1 000 ℃ in air

The oxidation behaviors of Ni-16Cr-xAl （x=4.5%, 9.0%, mass fraction） superalloy foams in air at 1000℃ were investigated. The effects of AI content on the resistance to high temperature oxidation were examined. The oxidation mechanisms of the foams were discussed. The results show that the resistance to the oxidation of the Ni-16Cr-xA1 based alloy at 1 000 ℃ increases with the content of A1 increasing from 4.5% to 9.0%. Complex oxide products are formed on the surface of the superalloy foams after the oxidation. Cr203 and A1203 are the predominant oxides for the scales of the foams with 4.5% A1 and 9% A1, respectively. Excellent high temperature oxidation resistance and superior pore conformation stability for the Ni-16Cr-xA1 based superalloy foam with 9% A1 can be mainly attributed to the formation of relatively continuous and protective A1203 oxides on the surface of the foam.