Small animal PET image super-resolution using Tikhonov and modified total variation regularisation

Positron emission tomography (PET) is an imaging procedure used mainly in the diagnosis and treatment of diseases. PET is also used in the preclinical research studies of small animals. However, researchers may have difficulty interpreting the particularly low-resolution images obtained via this procedure. This paper presents a new method of increasing the resolution of PET images through the use of super-resolution techniques. Aside from being resistant to the noise and other degradations that plague PET images, our proposed algorithm is also capable of preserving important structures (e.g. lesions). To this end, the proposed objective function includes a term based on the modified total variation model which allows the user to preserve texture and to deal with noise without incurring the artefacts that typically arise when the total variation norm is used. The present study shows the effectiveness of the method in recovering structures and details and indicates that, in most cases, it outperforms other state-of-the-art methods.     

A systematic literature review of the Teleo-Reactive paradigm

The Teleo-Reactive approach designed by N. J. Nilsson offers a high-level programming model for the development of reactive systems such as robotic vehicles. Teleo-Reactive programs are written in a way that allows engineers to define behaviour taking account of goals and changes in the state of the environment. Since Nilsson’s original definition, published in 1994, various researchers have used the Teleo-Reactive paradigm, either applied to a particular domain or extended by adding more capabilities to the original definition. This article provides a systematic literature review of 53 previous Teleo-Reactive-based studies in journals, conference proceedings and the like. The aim of this paper is to identify, appraise, select and synthesize all this high-quality research evidence relating to the use of the Teleo-Reactive paradigm. The literature has been systematically reviewed to offer an overview of the present state of this field of study and identify the principal results that have been obtained thanks to the Teleo-Reactive approach. Finally, this article details the challenges and difficulties that have to be overcome to ensure further advances in the use of this technique.     

Difference equation matrix model (DEMM) for the control of wind turbines

In this paper, a new algorithm, difference equation matrix model (DEMM), in the framework of model predictive control (MPC) is introduced. Instead of the standard dynamic matrix control (DMC), which is based upon step response method that has been used in most research works, we propose a new approach based upon a DEMM for model prediction. It has shown that DEMM has proven to be less computational and thus faster than the original DMC for real time applications. Thus, the drawbacks of DMC for online identification or adaptive design could be avoided. The control of wind turbines is carried out in order to decrease the cost of wind energy by increasing the efficiency, and thus the energy capture, or by reducing structural loading and increasing the lifetimes of the components and turbine structures. Modeling of wind turbine has been carried out. Effect of noise and disturbance on the system has been also studied. The results obtained show that the proposed DEMM minimizes the effect of the disturbance and produces an accurate and smooth control. Significant improvements in the regulation of rotor speed at high wind speeds are obtained from the proposed DEMM, where control set points are obtained ahead of the disturbance, saving the turbine of the negative effects of them and thus increasing its lifetime. Copyright © 2012 John Wiley & Sons, Ltd.     

Frame selection for OCR from video stream of book flipping

Multimedia Tools and Applications - Optical Character Recognition (OCR) in video stream of flipping pages is a challenging task because flipping at random speed causes difficulties in identifying...     

Anthocyanin profile of red fruits and black carrot juices,purees and concentrates by HPLC‐DAD‐ESI/MS‐QTOF

A fast and reliable method for anthocyanin extraction and identification by HPLC‐DAD‐ESI/MS‐QTOF was used to analyse the anthocyanin composition of commercial red fruit juices (blackberry, redcurrant and pomegranate), purees (strawberry, cherry and raspberry) and concentrates (elderberry, blueberry and red grape). The anthocyanin profile of black carrot juice is also reported. The extraction and analysis method allowed us to detect and quantify a wide range of individual anthocyanins in a simple and rapid way. Pelargonidin‐3‐glucoside was detected in redcurrant for the first time and petunidin‐3‐galactoside quantified for the first time in blueberries. Considering the health benefits that have been associated with anthocyanin consumption, all these fruit and vegetables processed products could appear as a good source of this group of phytochemical compounds for their direct consumption or their use as ingredients for the design of new food product or food supplements.     

Design of AVS/RS under group constraint

Distribution centers, which are essential to our society, are becoming increasingly important. Although the efficiency of an AVS/RS (Autonomous vehicle storage and retrieval system) makes it a promising system, there is still much to be studied regarding its effective use and design. This paper proposes a method of designing AVS/RSs through a quantitative consideration of group constraint by utilizing probability theory. The proposed algorithm also deals with the problem of designing the sizes of several buffers, and considers the effect of load fluctuations, which are important for real-world operation, by use of queuing network theory. Effectiveness of the proposed algorithm is shown with simulations of various number of groups, those of various safety factors for fluctuations, and those of various evasion rates for buffer overflow. The design results are shown to be much different from those which do not consider those factors. The results prove that the proposed method provides an accurate quantitative assessment of the AVS/RS’s constraints.     

Case-base maintenance with multi-objective evolutionary algorithms

Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solving ability of the Case-Base Reasoning system. However, when the case-base has many cases, then performance problems arise due to the time needed to find those similar cases to the input problem. At this point, Case-Base Maintenance algorithms can be used to reduce the number of cases and maintain the accuracy of the Case-Base Reasoning system at the same time. Whereas Case-Base Maintenance algorithms typically use a particular heuristic to remove (or select) cases from the case-base, the resulting maintained case-base relies on the proportion of redundant and noisy cases that are present in the case-base, among other factors. That is, a particular Case-Base Maintenance algorithm is suitable for certain types of case-bases that share some indicators, such as redundancy and noise levels. In the present work, we consider Case-Base Maintenance as a multi-objective optimization problem, which is solved with a Multi-Objective Evolutionary Algorithm. To this end, a fitness function is introduced to measure three different objectives based on the Complexity Profile model. Our hypothesis is that the Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance may be used in a wider set of case-bases, achieving a good balance between the reduction of cases and the problem-solving ability of the Case-Based Reasoning system. Finally, from a set of the experiments, our proposed Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance shows regularly good results with different sets of case-bases with different proportion of redundant and noisy cases.     

Effect of Poly(vinyl pyrrolidone) on Antifouling Properties of Asymmetric Poly(ethylene‐co‐vinyl alcohol) Membranes

Poly(ethylene‐co‐vinyl alcohol)/poly(vinyl pyrrolidone) (EVAL/PVP) blend membranes with antifouling properties were prepared by nonsolvent induced phase separation. Residual PVP in the sample was calculated by infrared spectroscopic data and confirmed by thermogravimetric analysis. The effect of residual PVP on hydrophilicity and permeation characteristics of the membranes was evaluated. Porosity and equilibrium water content of the membranes were influenced by the addition of PVP. The effect of protein fouling on flux using bovine serum albumin as a model system was studied in detail. The residual PVP content could enhance the antifouling property of the membrane. All membranes proved to have sufficient mechanical strength to withstand pressure‐driven filtrations.     

A graph‐based postoptimization approach for covering arrays

Covering arrays (CAs) are combinatorial objects with interesting features that have practical applications such as experimental design and fault detection in hardware and software. We introduce a graph‐based postoptimization (GBPO) approach to reduce the size of CAs exploiting the redundancy in CAs previously constructed. To evidence the advantages of using GBPO, we have instantiated it with 2 sets of CAs: (1) 560 CAs of strength 2≤t≤6, alphabet 2≤v≤6, and parameters 3≤k≤32 generated by an optimized version of In‐Parameter‐Order‐Generalized (IPOG‐F) and GBPO improved all CAs, and 37 cases matched the best‐known upper bounds; and (2) 32 CAs of strength t=2, alphabet 3≤v≤6, and number of parameters 8≤k≤146; in this set, 16 cases were improved, and 16 cases were matched.