In this paper, we propose an achievable rate region for discrete memoryless interference channels with conferencing at the transmitter side. We employ superposition block Markov encoding, combined with simultaneous superposition coding, dirty paper coding, and random binning to obtain the achievable rate region. We show that, under respective conditions, the proposed achievable region reduces to Han and Kobayashi's achievable region for interference channels, the capacity region for degraded relay channels, and the capacity region for the Gaussian vector broadcast channel. Numerical examples for the Gaussian case are given.Index terms -interference channels, dirty paper coding, superposition block Markov encoding, random binning.

In this paper, we study capacity bounds for discrete memoryless broadcast channels with confidential messages. Two private messages as well as a common message are transmitted; the common message is to be decoded by both receivers, while each private message is only for its intended receiver. In addition, each private message is to be kept secret from the unintended receiver where secrecy is measured by equivocation. We propose both inner and outer bounds to the rate equivocation region for broadcast channels with confidential messages. The proposed inner bound generalizes Csiszár and Körner's rate equivocation region for broadcast channels with a single confidential message, Liu et al's achievable rate region for broadcast channels with perfect secrecy, Marton's and Gel'fand and Pinsker's achievable rate region for general broadcast channels. Our proposed outer bounds, together with the inner bound, helps establish the rate equivocation region of several classes of discrete memoryless broadcast channels with confidential messages, including less noisy, deterministic, and semi-deterministic channels. Furthermore, specializing to the general broadcast channel by removing the confidentiality constraint, our proposed outer bounds reduce to new capacity outer bounds for the discrete memory broadcast channel.

TiO 2 is a very promising photocatalytic material due to its merits including low cost, nontoxicity, high chemical stability, and photocorrosion resistance. However, it is also known that TiO 2 is a wide bandgap material, and it is still challenging to achieve high photocatalytic performance driven by solar light. In this paper, silicon-doped TiO 2 nanorod arrays are vertically grown on fluorine-doped tin oxide substrates and then are heat treated both in air and in vacuum. It is found that the silicon doping together with the heat treatment brings synergic effect to TiO 2 nanorod films by increasing the crystallinity, producing abundant oxygen vacancies, enhancing the hydrophilicity as well as improving the electronic properties. When used as photoanodes in photoelectrochemical water splitting, under the condition of AM 1.5G simulated solar irradiation and without using any cocatalysts, these nanorod films show photocurrent density as high as 0.83 mA cm −2 at a potential of 1.23 V versus reversible hydrogen electrode, which is much higher than that of the TiO 2 nanorod films without doping or heat treating. The silicon-doped TiO 2 nanorod array films described in this paper are envisioned to provide valuable platforms for supporting catalysts and cocatalysts for efficient solar-light-assisted water oxidation and other solar-light-driven photocatalytic applications.

Electronic government (e-government) uses information and communication technologies to deliver public services to individuals and organisations effectively, efficiently and transparently. E-government is one of the most complex systems which needs to be distributed, secured and privacy-preserved, and the failure of these can be very costly both economically and socially. Most of the existing e-government systems such as websites and electronic identity management systems (eIDs) are centralized at duplicated servers and databases. A centralized management and validation system may suffer from a single point of failure and make the system a target to cyber attacks such as malware, denial of service attacks (DoS), and distributed denial of service attacks (DDoS). The blockchain technology enables the implementation of highly secure and privacy-preserving decentralized systems where transactions are not under the control of any third party organizations. Using the blockchain technology, exiting data and new data are stored in a sealed compartment of blocks (i.e., ledger) distributed across the network in a verifiable and immutable way. Information security and privacy are enhanced by the blockchain technology in which data are encrypted and distributed across the entire network. This paper proposes a framework of a decentralized e-government peer-to-peer (p2p) system using the blockchain technology, which can ensure both information security and privacy while simultaneously increasing the trust of the public sectors. In addition, a prototype of the proposed system is presented, with the support of a theoretical and qualitative analysis of the security and privacy implications of such system.

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This paper considers a two-hop interference network, where two users transmit independent messages to their respective receivers with the help of two relay nodes. The transmitters do not have direct links to the receivers; instead, two relay nodes serve as intermediaries between the transmitters and receivers. Each hop, one from the transmitters to the relays and the other from the relays to the receivers, is modeled as a Gaussian interference channel, thus the network is essentially a cascade of two interference channels. For this network, achievable symmetric rates for different parameter regimes under decodeand-forward relaying and amplify-and-forward relaying are proposed and the corresponding coding schemes are carefully studied. Numerical results are also provided.

Network intrusion detection systems identify malicious connections and thus help protect networks from attacks. Various data-driven approaches have been used in the development of network intrusion detection systems, which usually lead to either very complex systems or poor generalization ability due to the complexity of this challenge. This paper proposes a data-driven network intrusion detection system using fuzzy interpolation in an effort to address the aforementioned limitations. In particular, the developed system equipped with a sparse rule base not only guarantees the online performance of intrusion detection, but also allows the generation of security alerts from situations which are not directly covered by the existing knowledge base. The proposed system has been applied to a well-known data set for system validation and evaluation with competitive results generated.

The concept of a compact, economical FTIR-based analyzer for estimating the properties of hydrocarbon fuels with small amounts of fuel is proposed. The high correlations between mid-IR FTIR absorption spectra of fuel vapor in the range 3300 to 3550 nm and 15 physical and chemical properties, such as density, initial boiling point, surface tension, kinematic viscosity, number of carbon and hydrogen per average molecule, and derived cetane number, for 64 hydrocarbon fuels are demonstrated. Lasso-regularized linear models based on linear combination of absorption cross sections at selected wavelengths are built for each of these physical and chemical properties, yielding accurate estimations.