A global piecewise smooth Newton method for fast large-scale model predictive control

In this paper, the strictly convex quadratic program (QP) arising in model predictive control (MPC) for constrained linear systems is reformulated as a system of piecewise affine equations. A regularized piecewise smooth Newton method with exact line search on a convex, differentiable, piecewise-quadratic merit function is proposed for the solution of the reformulated problem. The algorithm has considerable merits when applied to MPC over standard active set or interior point algorithms. Its performance is tested and compared against state-of-the-art QP solvers on a series of benchmark problems. The proposed algorithm is orders of magnitudes faster, especially for large-scale problems and long horizons. For example, for the challenging crude distillation unit model of Pannocchia, Rawlings, and Wright (2007) with 252 states, 32 inputs, and 90 outputs, the average running time of the proposed approach is 1.57 ms.     

Volumetric Curved Planar Reformation for virtual endoscopy

Curved Planar Reformation (CPR) has proved to be a practical and widely used tool for the visualization of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for large, tubular, structures such as the trachea and the colon because abnormalities may be smaller relative to the size of the structure and may not have such distinct density and shape characteristics. Our new approach improves on this situation by using volume rendering for hollow regions and standard CPR for the surrounding tissue. This effectively combines gray scale contextual information with detailed color information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative to virtual endoscopy. Because the CPR and the volume rendering are tightly coupled, the projection method used has a significant effect on properties of the volume renderer, such as distortion and isometry. We describe and compare the different CPR projection methods and how they affect the volume rendering process. A version of the algorithm is also presented which makes use of importance driven techniques; this ensures the users attention is always focused on the area of interest and also improves the speed of the algorithm.     

A process model of cyberbullying in adolescence

Cyberbullying is an emerging form of aggression that utilizes information and communication technologies (ICTs). While cyberbullying incidents attract considerable attention, research on the causes and psychosocial predictors of cyberbullying is still limited. The present study used an integrated theoretical model incorporating empathy, moral disengagement, and social cognitions related to cyberbullying. Structured questionnaires were administered to 355 randomly selected adolescents (M = 14.7, SD = 1.20). Linear regression analysis showed that social norms, prototype similarity and situational self-efficacy directly predicted cyberbullying expectations. Multiple mediation modelling indicated that normative influences mediated the effects of moral disengagement and affective empathy on cyberbullying expectations. These findings provide valuable information regarding the effect of both distal and proximal risk factors for cyberbullying in adolescence, highlight the relationship between normative processes and moral self-regulation, and set the basis for related educational and preventive interventions.     

Enabling applicability of energy saving applications on the appliances of the home environment

Given the energy waste problem in contemporary households and the consequent need for optimal energy use, this article presents a novel network architecture that is generically applicable on domestic appliances, such as white goods, and audiovisual and communication equipment, and is capable of performing real-time management of their energy consumption. Deploying the latest information and communication technology, the proposed architecture enables definition of energy saving applications that perform three main functions: real-time estimation of the energy consumption of the home environment, without exploiting smart metering devices; control of domestic appliances energy use so that energy consumption of the home environment is kept within user-defined limits; and autonomous identification and management of standby devices, targeting minimal energy consumption.     

A threshold-based algorithm for continuous monitoring of k nearest neighbors

Assume a set of moving objects and a central server that monitors their positions over time, while processing continuous nearest neighbor queries from geographically distributed clients. In order to always report up-to-date results, the server could constantly obtain the most recent position of all objects. However, this naive solution requires the transmission of a large number of rapid data streams corresponding to location updates. Intuitively, current information is necessary only for objects that may influence some query result (i.e., they may be included in the nearest neighbor set of some client). Motivated by this observation, we present a threshold-based algorithm for the continuous monitoring of nearest neighbors that minimizes the communication overhead between the server and the data objects. The proposed method can be used with multiple, static, or moving queries, for any distance definition, and does not require additional knowledge (e.g., velocity vectors) besides object locations.     

Continuous spatial assignment of moving users

Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), there is currently no method for dynamic settings. In this paper, we consider the continuous assignment problem (CAP), where an optimal assignment must be constantly maintained between mobile users and a set of servers. The fact that the users are mobile necessitates real-time reassignment so that the quality of service remains high (i.e., their distance from their assigned servers is minimized). The large scale and the time-critical nature of targeted applications require fast CAP solutions. We propose an algorithm that utilizes the geometric characteristics of the problem and significantly accelerates the initial assignment computation and its subsequent maintenance. Our method applies to different cost functions (e.g., average squared distance) and to any Minkowski distance metric (e.g., Euclidean, L ₁ norm, etc.).     

An integrated cyber security risk management framework and risk predication for the critical infrastructure protection

Neural Computing and Applications - Cyber security risk management plays an important role for today’s businesses due to the rapidly changing threat landscape and the existence of evolving...     

Catalytic Conversions in Aqueous Media. Part 2. A Novel and Highly Efficient Biphasic Hydrogenation of Renewable Methyl Esters of Linseed and Sunflower Oils to High Quality Biodiesel Employing Rh/TPPTS Complexes

An unusual high catalytic activity (TOF = 117,000 h⁻¹) and high catalyst productivity (TON = 9,700) have been achieved in the first example of partial hydrogenation of renewable polyunsaturated crude methyl esters of linseed and sunflower oils catalyzed by water soluble Rh/TPPTS complexes [TPPTS = P(C₆H₄-m-SO₃Na)₃] in aqueous/organic two-phase systems to afford monounsaturated fatty esters which is biodiesel first generation of improved oxidative stability, energy and environmental performance at a low pour point. This exceptionally high catalytic activity contrast with the general perception that industrially applied water soluble Rh/TPPTS catalysts normally exhibit very low rates in the conversions of higher molecular weight starting materials in aqueous/organic two-phase systems. For part 1 of this series see Ref. [14].     

CuO–CeO2 mixed oxide catalysts for the selective oxidation of carbon monoxide in excess hydrogen

A series of mixed oxide CuO–CeO₂ catalysts were prepared by coprecipitation and tested for the selective oxidation of carbon monoxide in the presence of excess hydrogen. These catalysts were found to be very active and exceptionally selective for this reaction and exhibited a good resistance towards CO₂ and H₂O. The catalytic performance of these non-noble metal containing catalysts is compared with that of other selective CO oxidation catalysts reported in literature.