Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease

Coronary artery disease (CAD) is one of the major causes of mortality worldwide. Knowledge about risk factors that increase the probability of developing CAD can help to understand the disease better and assist in its treatment. Recently, modern computer‐aided approaches have been used for the prediction and diagnosis of diseases. Swarm intelligence algorithms like particle swarm optimization (PSO) have demonstrated great performance in solving different optimization problems. As rule discovery can be modelled as an optimization problem, it can be mapped to an optimization problem and solved by means of an evolutionary algorithm like PSO. An approach for discovering classification rules of CAD is proposed. The work is based on the real‐world CAD data set and aims at the detection of this disease by producing the accurate and effective rules. The proposed algorithm is a hybrid binary‐real PSO, which includes the combination of categorical and numerical encoding of a particle and a different approach for calculating the velocity of particles. The rules were developed from randomly generated particles, which take random values in the range of each attribute in the rule. Two different feature selection methods based on multi‐objective evolutionary search and PSO were applied on the data set, and the most relevant features were selected by the algorithms. The accuracy of two different rule sets were evaluated. The rule set with 11 features obtained more accurate results than the rule set with 13 features. Our results show that the proposed approach has the ability to produce effective rules with highest accuracy for the detection of CAD.     

Preparation and characterization of chemically deposited lead sulphide thin films

A chemical method for the deposition of PbS thin films has been developed using appropriate amounts of lead acetate, thioacetamide and triethanolamine. The thickness of the films are in the range 0.3 to 1 m. The films are polycrystalline and p-type. The dependence of the film thickness as a function of the bath parameters has also been studied and explained on the basis of ion-ion condensation theory.     

Exertion of Inhibiting Effect by Aluminosilicate Layers on Swelling of Solution Blended EVA/Clay Nanocomposite

Summary: Ethylene vinyl acetate (EVA) copolymer/dodecyl ammonium ion intercalated montmorillonite (12Me‐MMT) nanocomposites were swelled in xylene under atmospheric condition. Swelling index of these nanocomposites decreased with filler loading indicating that the solvent uptake of these nanocomposites was inversely related to the filler contents. The volume fractions of nanocomposites showed an increasing trend with filler concentration because of unswelling effect exerted by aluminosilicate layers. The cross‐link density was determined using the Flory‐Rehner equation and it was observed that the cross‐link density of these nanocomposites also showed an increasing trend with increasing filler loading. Free energy change (ΔG_mix) and the change in entropy (ΔS_mix) on swelling of EVA/12Me‐MMT nanocomposites in xylene were calculated and these values reaffirmed that the interaction between polymer chains and silicate layers was very strong which induced remarkable inhibiting ability on EVA matrix when swelled in xylene.

TEM photograph of EVA/12Me‐MMT nanocomposite containing 8 wt.‐% 12Me‐MMT.     

Conduction nature of conical pores in PET membrane

Summary The preparation of conical pores in polyethylene terepthlate (PET) membrane is described. The conical pores prepared in PET by track etching technique. For this purpose, Cl⁹⁺ ion irradiated film was placed into an electrolytic cell and etched from one side while other side of membrane was protected by a stopping medium. During etching, current was recorded as a function of time, which shows a sudden change, indicating the pores breakthrough. After breakthrough, the etch process is interrupted by replacing the etching solution. After etching, the current voltage characteristics were determined under symmetric bath conditions. The resulting conical pores show non ohmic behavior, similar to that of an electronic diode.     

Systems engineering principles for the design of biomedical signal processing systems

Systems engineering aims to produce reliable systems which function according to specification. In this paper we follow a systems engineering approach to design a biomedical signal processing system. We discuss requirements capturing, specification definition, implementation and testing of a classification system. These steps are executed as formal as possible. The requirements, which motivate the system design, are based on diabetes research. The main requirement for the classification system is to be a reliable component of a machine which controls diabetes. Reliability is very important, because uncontrolled diabetes may lead to hyperglycaemia (raised blood sugar) and over a period of time may cause serious damage to many of the body systems, especially the nerves and blood vessels. In a second step, these requirements are refined into a formal CSP‖ B model. The formal model expresses the system functionality in a clear and semantically strong way. Subsequently, the proven system model was translated into an implementation. This implementation was tested with use cases and failure cases.Formal modeling and automated model checking gave us deep insight in the system functionality. This insight enabled us to create a reliable and trustworthy implementation. With extensive tests we established trust in the reliability of the implementation.     

Exploring the Steady Operation of a Continuous Pilot Plant for the Di‐Nitration Reaction

Continuous‐flow synthesis of the selective herbicide pendimethalin was demonstrated in both a laboratory‐scale and a pilot‐scale reactor using only concentrated nitric acid as nitrating agent. The di‐nitration reaction follows second‐order kinetics where the reaction is first order with respect to both reactant and nitric acid. The pinched‐tube reactor was chosen for pilot‐scale reactor fabrication due to its excellent mixing and mass transfer characteristics compared to a straight‐tube reactor. The estimated mass transfer coefficient showed similar nature in the laboratory‐scale and the pilot‐scale pinched‐tube reactor, ensuring similar performance at the pilot scale. Di‐nitration in continuous flow, inline quenching, extraction, and phase separation are some of the salient features of the developed pilot plant. The importance of the start‐up time for achieving steady state in the flow system at the large scale is highlighted.     

Preconditioning, write width, and recording properties of Co-Cr-Pt-O perpendicular media with various underlayer designs

The effect of magnetic "preconditioning" on the recording performance of perpendicular media is investigated. Furthermore, the dependence of the magnetic write width (MWW) of shielded-pole heads (SPH) on soft-underlayer (SUL) type and thickness (t/sub SUL/) and the recording performance of perpendicular media with thin SULs are examined. The MWW dependence on SUL structure is influenced by the pole-to-trailing shield spacing. For a wide-gap (/spl sim/80 nm) SPH, thick single-layer, SULs are preferred. For a narrow-gap (/spl sim/50 nm) SPH, MWW is less sensitive to the SUL type. For both narrow and wide-gap SPH and for media with an antiferromagnetically-coupled SUL, MWW is reduced for t/sub SUL/<100 nm. Comparable performance is achieved relative to media with t/sub SUL//spl sim/150 nm.     

Integrated services packet networks with mobile hosts: Architecture and performance

This paper considers the support of real-time services to mobile users in an Integrated Services Packet Network. In the currently existing architectures, the service guarantees provided to the mobile hosts are mobility dependent, i.e., mobile hosts experience wide variation in the quality of service and often service disruption when hosts move from one location to another. The network performance degrades significantly when mobile hosts are provided with mobility independent service guarantees. In this paper we have proposed a service model for mobile hosts that can support adaptive applications which can withstand service degradation and disruption, as well as applications which require mobility independent service guarantees. We describe an admission control scheme for implementing this service model and evaluate its performance by simulation experiments. Simulation results show that, if sufficient degree of multiplexing of the mobility dependent and independent services are allowed, the network does not suffer any significant performance degradation and in particular our admission control scheme achieves high utilization of network resources.     

Detection and differentiation of breast cancer using neural classifiers with first warning thermal sensors

Breast cancer occurs when cells in the breast begin to grow out of control and invade nearby tissues or spread throughout the body. It is one of the leading causes of death in women. Cancer development appears to generate an increase in the temperature on the breast surface. The limitations of mammography as a screening modality, especially in young women with dense breasts, necessitated the development of novel and more effective screening strategies with high sensitivity and specificity. The aim of this study was to evaluate the feasibility of discrete thermal data (DTD) as a potential tool for the early detection of the breast cancer.Our protocol uses 1170, 16-sensor data collected from 54 individuals consisting of three different kinds of breast conditions: namely, normal, benign and cancerous breast. We compared two different kinds of neural network classifiers: the feedforward neural network and the radial basis function classifier. Temperature data from the 16 temperature sensors on the surface of the two breasts (eight sensors on each side) are fed as input to the classifiers. We demonstrated a sensitivity of 84% and 91% for these classifiers (feedforward and radial basis function, respectively) with a specificity of 100%. Our classifying systems are ready to run on large data sets.