Radiation amplification with help of the intrinsic Josephson effect

The use of the intrinsic Josephson effect in layered high-T_c superconductors for amplification of a signal in the presence of a strong pump radiation is investigated. Calculations are done both for thin films and massive material with a surface parallel to the c-direction, assuming normal incidence of the radiation with electric field parallel to the c-direction for parameter values relevant for high-T_c materials. In both cases high signal gain is obtained in a limited range of frequencies and pump power.     

Retransmission Error Control with Memory

Automatic-repeat-request (ARQ) is one of the most commonly used error control techniques today. In this paper, an error control technique that is a basic improvement over ARQ is presented. The technique uses the simple idea of utilizing erroneously received blocks in an ARQ system for error control, retaining most of the other aspects of ARQ. The technique is termed ARQ-with-memory (MRQ). The general MRQ system is described, and simple upper and lower bounds are derived on the throughput achievable by MRQ. The performance of MRQ with respect to throughput, message delay and probability of error is compared to that of ARQ by simulating both systems using error data from a VHF satellite channel being operated in the ALOHA packet broadcasting mode [9].     

Effect of simultaneous substitution of La and Mn on dielectric behavior of barium titanate ceramic

A few compositions in the valence compensated system Ba_1−x La _x Ti_1−x Mn _x O₃ were synthesized by solid-state ceramic method to study the effect of co-doping lanthanum and manganese in equimolar amounts on dielectric behavior of BaTiO₃. Compositions with x ≤ 0.10 have shown solid solution formation. Compositions with x ≤ 0.05 are found to have tetragonal structure at room temperature while composition with x = 0.10 is cubic. Plots of relative dielectric constant, ε_r versus temperature for composition with x = 0.01 show dielectric anomalies around 376 ± 2, 264 ± 2 and 179 ± 2 K which correspond to cubic to tetragonal (T _C–T), tetragonal to orthorhombic (T _T–O) and orthorhombic to rhombohedral (T _O–R) transition, respectively, similar to BaTiO₃. Curie temperature has been found to decrease with increasing concentration of lanthanum and manganese simultaneously in barium titanate. The broadening in the dielectric peak at cubic to tetragonal (T _C–T) transition temperature increases with increasing x. For x = 0.10, only one anomaly at 100 K is observed in its ε_r versus T plots. The observation of this single anomaly may be due to pinching effect of the substitutions on the three phase transitions.     

EGFR Mutations in Head and Neck Squamous Cell Carcinoma

EGFR is a prototypical receptor tyrosine kinase that is overexpressed in multiple cancers including head and neck squamous cell carcinoma (HNSCC). The standard of care for HNSCC remains largely unchanged despite decades of research. While EGFR blockade is an attractive target in HNSCC patients and anti-EGFR strategies including monoclonal antibodies and kinase inhibitors have shown some clinical benefit, efficacy is often due to the eventual development of resistance. In this review, we discuss how the acquisition of mutations in various domains of the EGFR gene not only alter drug binding dynamics giving rise to resistance, but also how mutations can impact radiation response and overall survival in HNSCC patients. A better understanding of the EGFR mutational landscape and its dynamic effects on treatment resistance hold the potential to better stratify patients for targeted therapies in order to maximize therapeutic benefits.     

Fractional-order Proportional-integral-derivative-based Automatic Generation Control in Deregulated Power Systems

Abstract—In this article, implementation of a fractional-order proportional-integral-derivative controller is proposed as supplementary automatic generation control of interconnected multi-area deregulated power systems that operates under the effects of bilateral contracts on the dynamics. The tuning of the fractional-order proportional-integral-derivative controller parameters is formulated as an optimization problem and solved by employing a genetic algorithm. The traditional automatic generation control loop incorporated with the concept of the distribution company participation matrix and fractional-order proportional-integral-derivative supplementary controller is simulated for different operating cases; a comparison among the conventional integral controller, hybrid fuzzy proportional-integral controller, genetic algorithm-tuned proportional-integral controller, and genetic algorithm-tuned proportional-integral-derivative controllers is presented. The simulation results show that the system employing a genetic algorithm-tuned fractional-order proportional-integral-derivative controller has better performance than the integer-order hybrid fuzzy proportional-integral, genetic algorithm-tuned proportional-integral, and genetic algorithm-tuned proportional-integral-derivative controllers in terms of settling time and overshoot.     

Enhancing activity and stability of Burkholderia cepacia lipase by immobilization on surface-functionalized mesoporous silicates

Burkholderia cepacia lipase was immobilized on various types of phenyl-functionalized mesoporous silicates (MPS). MPS, anchored with a phenyl group on the silica wall and with three dimensional (3D) mesoporosity, showed highest lipase adsorption capacity and best activities both in aqueous and organic reagents.     

Decision tree based light weight intrusion detection using a wrapper approach

The objective of this paper is to construct a lightweight Intrusion Detection System (IDS) aimed at detecting anomalies in networks. The crucial part of building lightweight IDS depends on preprocessing of network data, identifying important features and in the design of efficient learning algorithm that classify normal and anomalous patterns. Therefore in this work, the design of IDS is investigated from these three perspectives. The goals of this paper are (i) removing redundant instances that causes the learning algorithm to be unbiased (ii) identifying suitable subset of features by employing a wrapper based feature selection algorithm (iii) realizing proposed IDS with neurotree to achieve better detection accuracy. The lightweight IDS has been developed by using a wrapper based feature selection algorithm that maximizes the specificity and sensitivity of the IDS as well as by employing a neural ensemble decision tree iterative procedure to evolve optimal features. An extensive experimental evaluation of the proposed approach with a family of six decision tree classifiers namely Decision Stump, C4.5, Naive Baye’s Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern has been introduced.     

Normal and hypoacoustic infant cry signal classification using time-frequency analysis and general regression neural network

Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and it has been proven to be an excellent tool to investigate the pathological status of an infant. This paper proposes short-time Fourier transform (STFT) based time-frequency analysis of infant cry signals. Few statistical features are derived from the time-frequency plot of infant cry signals and used as features to quantify infant cry signals. General Regression Neural Network (GRNN) is employed as a classifier for discriminating infant cry signals. Two classes of infant cry signals are considered such as normal cry signals and pathological cry signals from deaf infants. To prove the reliability of the proposed features, two neural network models such as Multilayer Perceptron (MLP) and Time-Delay Neural Network (TDNN) trained by scaled conjugate gradient algorithm are also used as classifiers. The experimental results show that the GRNN classifier gives very promising classification accuracy compared to MLP and TDNN and the proposed method can effectively classify normal and pathological infant cries.     

A hybrid expert system approach for telemonitoring of vocal fold pathology

Acoustical parameters extracted from the recorded voice samples are actively pursued for accurate detection of vocal fold pathology. Most of the system for detection of vocal fold pathology uses high quality voice samples. This paper proposes a hybrid expert system approach to detect vocal fold pathology using the compressed/low quality voice samples which includes feature extraction using wavelet packet transform, clustering based feature weighting and classification. In order to improve the robustness and discrimination ability of the wavelet packet transform based features (raw features), we propose clustering based feature weighting methods including k-means clustering (KMC), fuzzy c-means (FCM) clustering and subtractive clustering (SBC). We have investigated the effectiveness of raw and weighted features (obtained after applying feature weighting methods) using four different classifiers: Least Square Support Vector Machine (LS-SVM) with radial basis kernel, k-means nearest neighbor (kNN) classifier, probabilistic neural network (PNN) and classification and regression tree (CART). The proposed hybrid expert system approach gives a promising classification accuracy of 100% using the feature weighting methods and also it has potential application in remote detection of vocal fold pathology.