Regional chemotherapy of liver tumors

In the absence of adequate autogenous vein for tibial artery bypass in limb salvage surgery, the use of prosthetic grafts with a distal anastomotic vein cuff or patch has shown promising results. Here, we describe how the Florester Internal Vessel Occluder (Meadox UK, Bedfordshire, UK) can facilitate the construction of a distal anastomotic vein cuff.     

Modeling the tensile properties in β-processed α/β Ti alloys

The development of a set of computational tools that permit microstructurally based predictions for the tensile properties of commercially important titanium alloys, such as Ti-6Al-4V, is a valuable step toward the accelerated maturation of materials. This paper will discuss the development of neural network models based on a Bayesian framework to predict the yield and ultimate tensile strengths of Ti-6Al-4V at room temperature. The development of such rules-based model requires the population of extensive databases, which in the present case are microstructurally based. The steps involved in database development include producing controlled variations of the microstructure using novel approaches to heat treatments, the use of standardized stereology protocols to characterize and quantify microstructural features rapidly, and mechanical testing of the heat-treated specimens. These databases have been used to train and test neural network models for prediction of tensile properties. In addition, these models have been used to identify the influence of individual microstructural features on the tensile properties, consequently guiding the efforts toward development of more robust mechanistically based models. Based on the neural network model, it is possible to investigate the influence of individual microstructural features on the tensile properties, and in certain cases these dependencies can point toward unrecognized phenomena. For example, the apparently unexpected trend of increase in tensile strength with increasing prior β-grain size has led to the determination of the pronounced role of the basketweave microstructure in strengthening these alloys, especially in case of larger prior β grains. This article is based on a presentation made in the symposium “Computational Aspects of Mechanical Properties of Materials,” which occurred at the 2005 TMS Annual Meeting, February 13–17, 2005, in San Francisco, CA, under the auspices of the MPMD-Computational Materials Science & Engineering (Jt. ASM-MSCTS) Committee.     

Acidolysis Reaction of Sal Fat (Shorea robusta) with Palmitic Acid

Acidolysis reaction of sal fat (Shorea robusta) with palmitic acid has been studied in relation to the operating variables like catalyst system and concentration, reaction temperature and time and molar ratios of reactants with the object of introducing more palmitic acid which is low in sal fat. The results demonstrate that as low as 2.5% and as high as 39% palmitic acid can be introduced in sal fat at the expense of other acids under the influence of various operating conditions. The products obtained differ from original sal fat in respect of chemical composition and slip point. The importance of such study is that there are possibilities of getting plastic fats of diverse properties for edible and industrial uses.     

Harmony search algorithm for infinite impulse response system identification

In this paper, optimal sets of filter coefficients are searched by a meta-heuristic optimization technique called Harmony Search (HS) algorithm for infinite impulse response (IIR) system identification problem. For different optimization problems, HS algorithm undergoes three basic rules; namely Random Selection (RS), Harmony Memory Consideration (HMC), and Pitch Adjustment (PA) rules, which are inspired from the process that the musicians use to improvise a perfect state of harmony with the consummate skill of blending notes in tune. With the help of the properly selected control parameters, a perfect balance is achieved in exploration and exploitation in searching phases. The detailed analysis of simulation results emphasizes the strength of HS algorithm to find the near-global optimal solution, quality of convergence profile and the speed of convergence while tested against standard benchmark examples for same and reduced order models.     

Delay‐dependent LMI condition for global asymptotic stability of discrete‐time uncertain state‐delayed systems using quantization/overflow nonlinearities

A delay‐dependent criterion for the global asymptotic stability of a class of uncertain discrete‐time state‐delayed systems using various combinations of quantization and overflow nonlinearities is presented. The proposed criterion is in the form of a linear matrix inequality and, hence, computationally tractable. A numerical example highlighting the usefulness of the proposed criterion is given. Copyright © 2010 John Wiley & Sons, Ltd.     

A waveform concatenation technique for text-to-speech synthesis

Designing text-to-speech systems capable of producing natural sounding speech segments in different Indian languages is a challenging and ongoing problem. Due to the large number of possible pronunciations in different Indian languages, a number of speech segments are needed to be stored in the speech database while a concatenative speech synthesis technique is used to achieve highly natural speech segments. However, the large speech database size makes it unusable for small hand held devices or human computer interactive systems with limited storage resources. In this paper, we proposed a fraction-based waveform concatenation technique to produce intelligible speech segments from a small footprint speech database. The results of all the experiments performed shows the effectiveness of the proposed technique in producing intelligible speech segments in different Indian languages even with very less storage and computation overhead compared to the existing syllable-based technique.     

Analyzing collective behavior from blogs using swarm intelligence

With the rapid growth of the availability and popularity of interpersonal and behavior-rich resources such as blogs and other social media avenues, emerging opportunities and challenges arise as people now can, and do, actively use computational intelligence to seek out and understand the opinions of others. The study of collective behavior of individuals has implications to business intelligence, predictive analytics, customer relationship management, and examining online collective action as manifested by various flash mobs, the Arab Spring (2011) and other such events. In this article, we introduce a nature-inspired theory to model collective behavior from the observed data on blogs using swarm intelligence, where the goal is to accurately model and predict the future behavior of a large population after observing their interactions during a training phase. Specifically, an ant colony optimization model is trained with behavioral trend from the blog data and is tested over real-world blogs. Promising results were obtained in trend prediction using ant colony based pheromone classier and CHI statistical measure. We provide empirical guidelines for selecting suitable parameters for the model, conclude with interesting observations, and envision future research directions.