A study of project selection and feature weighting for analogy based software cost estimation

A number of software cost estimation methods have been presented in literature over the past decades. Analogy based estimation (ABE), which is essentially a case based reasoning (CBR) approach, is one of the most popular techniques. In order to improve the performance of ABE, many previous studies proposed effective approaches to optimize the weights of the project features (feature weighting) in its similarity function. However, ABE is still criticized for the low prediction accuracy, the large memory requirement, and the expensive computation cost. To alleviate these drawbacks, in this paper we propose the project selection technique for ABE (PSABE) which reduces the whole project base into a small subset that consist only of representative projects. Moreover, PSABE is combined with the feature weighting to form FWPSABE for a further improvement of ABE. The proposed methods are validated on four datasets (two real-world sets and two artificial sets) and compared with conventional ABE, feature weighted ABE (FWABE), and machine learning methods. The promising results indicate that project selection technique could significantly improve analogy based models for software cost estimation.     

Robust speech recognition system using multi-parameter bidirectional Kalman filter

A speech signal processing system using multi-parameter model bidirectional Kalman filter has been proposed in this paper. Conventional unidirectional Kalman filter usually performs estimation of current state speech signal by processing the time varying autoregressive model of speech signals from the past time states. A bidirectional Kalman filter utilizes the past and future measurements to estimate the current state of a speech signal that minimize the mean of the squared error using efficient recursive means. The matrices involved in the difference equations and the measurement equations of the bidirectional Kalman filter algorithm are kept constant throughout the process. With multi-parameter model, the proposed bidirectional Kalman filter relates more measurements from the future and past time states to the current time state. The proposed multi-parameter bidirectional Kalman filter has been implemented into a speech recognition system and its performance has been compared to other conventional speech processing algorithms. Compared to the single-parameter model bidirectional Kalman filter, the multi-parameter bidirectional Kalman filter improves the accuracy in the state prediction, reduces the speech information lost after the filtering process and better word error rate has been achieved at high SNR regions (clean, 20, 15, 10 dB).     

Using one-class and two-class SVMs for multiclass image annotation

We propose using one-class, two-class, and multiclass SVMs to annotate images for supporting keyword retrieval of images. Providing automatic annotation requires an accurate mapping of images' low-level perceptual features (e.g., color and texture) to some high-level semantic labels (e.g., landscape, architecture, and animals). Much work has been performed in this area; however, there is a lack of ability to assess the quality of annotation. In this paper, we propose a confidence-based dynamic ensemble (CDE), which employs a three-level classification scheme. At the base-level, CDE uses one-class support vector machines (SVMs) to characterize a confidence factor for ascertaining the correctness of an annotation (or a class prediction) made by a binary SVM classifier. The confidence factor is then propagated to the multiclass classifiers at subsequent levels. CDE uses the confidence factor to make dynamic adjustments to its member classifiers so as to improve class-prediction accuracy, to accommodate new semantics, and to assist in the discovery of useful low-level features. Our empirical studies on a large real-world data set demonstrate CDE to be very effective.     

Synthesis,structure, and properties of high performance alternating copolyimides

Summary A new diamine monomer, N,N-bis(4-aminophenyl)-2,5-(diisopropoxycarbony)benzene-1,4-dicarboxamide was synthesized. Using the diamine, several alternating copolyimide precursors were successfully synthesized by its condensation polymerization with dianhydrides. The structure and properties (mechanical properties and thermal expansivity) of alternating copolyimides imidized thermally were characterized, and compared with those of the corresponding random copolyimides prepared from the copoly(amic acid)s. The alternating copolyimides exhibited relatively higher chain order and in-plane orientation in films than the random copolyimides. The higher chain order and in-plane orientation led to the higher tensile modulus and lower thermal expansivity in the alternating copolyimides. Such effect of comonomer sequence was found to be highly pronounced in copolyimides consisting of comonomers which have a large difference in the chain rigidity. It was demonstrated in this study that the formation of alternating copolyimides is a suitable route to improve the performance of properties.     

Miscible blends of poly(styrene-co-acrylonitrile) and poly(α-methyl styrene-co-acrylonitrile) with hydroxyl-containing polymethacrylates

Poly(styrene-co-acrylonitrile)(SAN) and poly(α-methyl styrene-co-acrylonitrile)(MSAN) are miscible with poly(2-hydroxyethyl methacrylate) (PHEMA) and with poly(2-hydroxypropyl methacrylate) (PHPMA). That SAN and MSAN are immiscible with poly(n-propyl methacrylate) and with poly(isopropyl methacrylate) but miscible with PHPMA indicates the enhancement of polymer miscibility due to hydroxyl groups. The miscibility of these blends is explained in terms of recent theories for copolymer/homopolymer blends.     

Miscibility of poly(methoxymethyl methacrylate) and poly(methylthiomethyl methacrylate) with poly(methyl methacrylate)

Summary Poly(n-propyl methacrylate) is known to be immiscible with poly(methyl methacrylate) (PMMA). However, we have found that poly(methoxymethyl methacrylate) is miscible with PMMA, indicating the importance of ether oxygen atoms in achieving miscibility. On the other hand, poly(methylthiomethyl methacrylate) is immiscible with PMMA.     

Cumulative probability control charts for geometric and exponential process characteristics

A statistical process control chart called the cumulative probability control chart (CPC-chart) is proposed. The CPC-chart is motivated from two existing statistical control charts, the cumulative count control chart (CCC-chart) and the cumulative quantity control chart (CQC-chart). The CCC- and CQC-charts are effective in monitoring production processes when the defect rate is low and the traditional p - and c -charts do not perform well. In a CPC-chart, the cumulative probability of the geometric or exponential random variable is plotted against the sample number, and hence the actual cumulative probability is indicated on the chart. Apart from maintaining all the favourable features of the CCC- and CQC-charts, the CPC-chart is more flexible and it can resolve a technical plotting inconvenience of the CCC- and CQC-charts.     

Nonlinear Optical Properties of Copolymers of Benzylaminofullerene with Methyl Methacrylate or Ethyl Methacrylate

Abstract

Nonlinear optical properties of a C₆₀ derivative, benzylaminofullerene [C₆₀H_n(NHCH₂C₆H₅)_n] and its copolymers with methyl methacrylate or ethyl methacrylate were observed carefully by using the nanosecond laser pulses at 532 nm. These copolymers have been proved to be promising materials for optical limiting applications.