In this article, we propose a system with RFID and sensor networks to guarantee the keeping quality of low-temperature logistics. 3G network and GPS transportations are incorporated to this system to create a full-time monitoring system and all the processing will be transparent to the customers so that it could be a keeping-quality guarantee to the customers as well as a good strategy for differentiated marketing. This system can be connected with the customers’ system so that all the processing, storage, and transportation temperatures can be sent to the customers through extranet and WEB server of suppliers. The customers’ system can judge whether temperature data is normal or not before the foods receive. Owing to the fact that all the RFID tags and readers can be reused and not expensive at all, this system is very practical to be applied in the cold-chain logistics. A format of data exchange needs to be standardized in the future for broad applications.

One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed using classifiers in both homogeneous ensemble classifiers using bagging and heterogeneous ensemble classifiers using arcing classifier and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of real and benchmark data sets of data mining applications like intrusion detection, direct marketing and signature verification. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase and combining phase. A wide range of comparative experiments are conducted for real and benchmark data sets of direct marketing. The accuracy of base classifiers is compared with homogeneous and heterogeneous models for data mining problem. The proposed ensemble methods provide significant improvement of accuracy compared to individual Classifiers and also heterogeneous models exhibit better results than homogeneous models for real and benchmark data sets of data mining applications.

The increasing demand for multi-degree-of-freedom (DOF) continuum robot in presence of highly nonlinear dynamic parameters in a number of industries has motivated a flurry of research in the development of soft computing nonlinear methodology. This research contributes to the on-going research effort by exploring alternate methods for controlling the continuum robot manipulator. This research addresses two basic issues related to the control of a continuum robots; (1) a more accurate representation of the dynamic model of an existing prototype, and (2) the design of a robust feedback controller. The robust back stepping controller proposed in this research is used to further demonstrate the appealing features exhibited by the continuum robot. Robust feedback controller is used to position control of continuum robot in presence of uncertainties. Using Lyapunov type stability arguments, a robust back stepping controller is designed to achieve this objective. The controller developed in this research is designed into two steps. Firstly, a robust stabilizing torque is designed for the nominal continuum robot dynamics derived using the constrained Lagrangian formulation. Next, the fuzzy logic methodology applied to it to solution uncertainty problem. The fuzzy model free problem is formulated to minimize the nonlinear formulation of continuum robot. The eventual stability of the controller depends on the torque generating capabilities of the continuum robots.

Software repositories contain wealth of information about software code, designs, execution history, code and design changes, bug database, software release and software evolution. To meet increased pressure of releasing updated or new versions of software systems due to changing requirements of stakeholder, software are rarely built from scratch. Software reusability is a primary attribute of software quality which aims to create new software systems with a likelihood of using existing software components to add, modify or delete functionalities in order to adapt to new requirements imposed by stakeholders. Software reuse using software components or modules provide a vehicle for planning and re-using already built software components efficiently. In this paper, we propose a framework for our approach to predict software reusable components from existing software repository on the basis of (1) stakeholders intention (requirement) match and (2) similarity index count for better reuse prediction. To effectively manage storage and retrieval of relevant information we use concept of situational method engineering to match and analyze the information for reuse. We use Genetic algorithm, Rabin Karp algorithm for feature selection and classification and k-means clustering methods of data mining to refine our results of prediction in order to better manage and produce high quality software systems within estimated time and cost.

73rd Panchayati Raj Act came into existence in 1993 and it paved the way for a strong and effective decentralized administrative system in India. The Indian Constitution added 11th schedule to it detailing 29 subjects which are devolved to the local self-government institutions [LSGIs]. It is nearly two decades passed and still LSGIs are hesitant to adapt with their roles to develop them as self-sufficient administrating regions. The devolved function is not fully exercised by the LSGIs. The transferred the departments connected with the 29 subjects are still working in a bureaucratic manner. This study reveals the real reasons behind the poor performance of LSGIs and coming up with a technological solution to overcome the problem through an interactive E-Governance system. Even though 29 subjects are given to the LSGIs, 4 departments are considered in this research due to time constrains.

Nowadays biometric is playing a key role in the field of forensic and commercial applications. The vein biometrics is a robust biometric in recent trends.The vein pattern is very difficult to forge or fake. The traits are not going to be changed from birth to death. This paper discusses image enhancement operations and its result when applied on multispectral palm vein image. The image enhancement operations are much helpful to extract the vein patternas features.The experiments can be used to highlight or trace a vein pattern lies at palm region of hand. The proposed work gains vein pattern and considered as the stepping stone towards feature extraction. The paperalso discusses the comparison of statistical properties such as mean, standard deviation and coefficient of original image and images resulting out through enhancement operations. The enhancement operation is a key to gain the vein pattern. The image analysis can be framed well usingstatistical image measurements.

Artificial Bee Colony (ABC), a recently proposed population based search heuristics which takes its inspiration from the intelligent foraging behavior of honey bees. In this study we have studied the impact of modification rate (MR) in basic ABC by gradually increasing it from 0.1 to 0.9. This impact is studied on four engineering design problems taken from literature. The simulated results show that it is beneficial to set the modification rate to a lower value.

Social search is a variant of information retrieval where a document or website is considered relevant if individuals from the searcher’s social network have interacted with it. To the best of our knowledge, there is no new detailed paper which covers discovery method in social network; therefore, in this paper we surveyed searching methods in social network which have been presented so far. We classified the existing methods in four main categories: people search, job search, keyword search and web service discovery. Also we conclude the paper with some implications for future research and practice.