Assessment of odour and H(2)S impact in WWTPs by cryo-condensation

Stability of gaseous samples is a major concern when dealing with odours and airborne pollutants sampling. In terms of odours, the representativeness of the sample can be very seriously compromised, despite the rigorous application of the maximum storage time established by EN-13725. The present paper is focused on the use of the cryo-condensation technique (Cryocore) for time-weighted-average (TWA) sampling in waste water treatment plants (WWTPs), with the aim of comparing the values of TWA odour and H(2)S concentration when using the Cryocore system and other well established sampling methods, such as those described in EN-13725 and passive sampling. The study showed comparable results when comparing all the methodologies tested.     

Parallel modular exponentiation using load balancing without precomputation

The modular exponentiation operation of the current algorithms for asymmetric cryptography is the most expensive part in terms of computational cost. The RSA algorithm, for example, uses the modular exponentiation algorithm in encryption and decryption procedure. Thus, the overall performance of those asymmetric cryptosystems depends heavily on the performance of the specific algorithm used for modular exponentiation. This work proposes new parallel algorithms to perform this arithmetical operation and determines the optimal number of processors that yields the greatest speedup. The optimal number is obtained by balancing the processing load evenly among the processors. Practical implementations are also performed to evaluate the theoretical proposals.     

Birefringence: calculation of refracted ray paths in biaxial crystals

The phenomenon of birefringence may be observed when light arrives at an anisotropic crystal surface and refracts through it, causing the incident light ray to split into two rays; these become polarized in mutually orthogonal directions, and two images are formed. The principal goal of this paper is the study of the directional issues involved in the behavior of light when refracting through a homogeneous, non-participating medium, including both isotropic and anisotropic media (uniaxial and, for the first time, biaxial). The paper focuses on formulating and solving the non-linear algebraic system that is obtained when the refraction process is simulated using the geometric model of Huygens. The main contribution focuses on the case of biaxial media. In the case of uniaxial media, we rely on symbolic calculus techniques to formulate and solve the problem.     

Face pose estimation with automatic 3D model creation in challenging scenarios

This paper proposes a new method to perform real-time face pose estimation for ± 90° yaw rotations and under low light conditions. The algorithm works on the basis of a completely automatic and run-time incremental 3D face modelling. The model is initially made up upon a set of 3D points derived from stereo grey-scale images. As new areas of the subject face appear to the cameras, new 3D points are automatically added to complete the model. In this way, we can estimate the pose for a wide range of rotation angles, where typically 3D frontal points are occluded.     

The importance of considering unauthentic transactions in trust management systems

In peer-to-peer (P2P) networks, trust management is a key tool to minimize the impact of malicious nodes. EigenTrust is claimed to be one of the most powerful distributed reputation management systems focused on P2P file-sharing applications. It is the theoretical base of other systems, and it has also been directly modified in an attempt to improve its performance. However, none of them give appropriate importance to all the information about transactions. This paper proposes an enhancement of EigenTrust, which considers unsatisfactory transactions in greater depth. Pos&Neg EigenTrust is able to obtain a blacklist of the identities of the malicious nodes. Therefore, it is able to significantly reduce the number of unsatisfactory transactions in the network.     

The design of FFML: A rule-based policy modelling language for proactive fraud management in financial data streams

Developing fraud management policies and fraud detection systems is a vital capability for financial institutions towards minimising the effect of fraud upon customer service delivery, bottom line financial losses and the adverse impact on the organisation’s brand image reputation. Rapidly changing attacks in real-time financial service platforms continue to demonstrate fraudster’s ability to actively re-engineer their methods in response to ad hoc security protocol deployments, and highlights the distinct gap between the speed of transaction execution within streaming financial data and corresponding fraud technology frameworks that safeguard the platform. This paper presents the design of FFML, a rule-based policy modelling language and encompassing architecture for facilitating the conceptual level expression and implementation of proactive fraud controls within multi-channel financial service platforms. It is demonstrated how a domain specific language can be used to abstract the financial platform into a data stream based information model to reduce policy modelling complexity and deployment latencies through an innovative policy mapping language usable by both expert and non-expert users. FFML is part of a comprehensive suite of assistive tools and knowledge-based systems developed to support fraud analysts’ daily work of designing new high level fraud management policies, mapping into executable code of the underpinning application programming interface and deployment of active monitoring and compliance functionality within the financial platform.     

Robust stability analysis of filtered Smith predictor for time-varying delay processes

This paper focuses on the robust stability analysis of the filtered Smith predictor (FSP) dead-time compensator for uncertain processes with time-varying delays. For this purpose, a delay-dependent LMI-based condition is used to compute a maximum delay interval and tolerance to model uncertainties such that the closed-loop system remains stable. Some simulation results illustrate that the proposed controller gives larger delays intervals or better performance than similar approaches proposed in literature applied both to stable and unstable processes.     

Globally exponentially stable cascade observers for attitude estimation

This paper presents the design, analysis, and performance evaluation of a novel cascade observer for attitude estimation. A sensor-based observer, which resorts to rate gyro readings and a set of vector observations, estimates the rate gyro bias. Afterwards, a cascaded observer explicitly estimates the attitude in the form of a rotation matrix based on the rate gyro measurements, the vector observations, and the estimated gyro bias. The overall error dynamics are globally exponentially stable and the proposed system is computationally efficient. Finally, the resulting estimator is successfully evaluated, in simulation and experimentally, with ground truth data in both cases.