A Parsing Scheme for Finding the Design Pattern and Reducing the Development Cost of Reusable Object Oriented Software

Because of the importance of object oriented methodologies, the research in developing new measure for object oriented system development is getting increased focus. The most of the metrics need to find the interactions between the objects and modules for developing necessary metric and an influential software measure that is attracting the software developers, designers and researchers. In this paper a new interactions are defined for object oriented system. Using these interactions, a parser is developed to analyze the existing architecture of the software. Within the design model, it is necessary for design classes to collaborate with one another. However, collaboration should be kept to an acceptable minimum i.e. better designing practice will introduce low coupling. If a design model is highly coupled, the system is difficult to implement, to test and to maintain overtime. In case of enhancing software, we need to introduce or remove module and in that case coupling is the most important factor to be considered because unnecessary coupling may make the system unstable and may cause reduction in the system's performance. So coupling is thought to be a desirable goal in software construction, leading to better values for external software qualities such as maintainability, reusability and so on. To test this hypothesis, a good measure of class coupling is needed. In this paper, based on the developed tool called Design Analyzer we propose a methodology to reuse an existing system with the objective of enhancing an existing Object oriented system keeping the coupling as low as possible.Comment: 15 page

E-CLoG: Counting edge-centric local graphlets

In recent years, graphlet counting has emerged as an important task in topological graph analysis. However, the existing works on graphlet counting obtain the graphlet counts for the entire network as a whole. These works capture the key graphical patterns that prevail in a given network but they fail to meet the demand of the majority of real-life graph related prediction tasks such as link prediction, edge/node classification, etc., which require to build features for an edge (or a vertex) of a network. To meet the demand for such applications, efficient algorithms are needed for counting local graphlets within the context of an edge (or a vertex). In this work, we propose an efficient method, titled E-CLOG, for counting all 3,4 and 5 size local graphlets with the context of a given edge for its all different edge orbits. We also provide a shared-memory, multi-core implementation of E-CLOG, which makes it even more scalable for very large real-world networks. In particular, We obtain strong scaling on a variety of graphs (14x-20x on 36 cores). We provide extensive experimental results to demonstrate the efficiency and effectiveness of the proposed method. For instance, we show that E-CLOG is faster than existing work by multiple order of magnitudes; for the Wordnet graph E-CLOG counts all 3,4 and 5-size local graphlets in 1.5 hours using a single thread and in only a few minutes using the parallel implementation, whereas the baseline method does not finish in more than 4 days. We also show that local graphlet counts around an edge are much better features for link prediction than well-known topological features; our experiments show that the former enjoys between 10% to 45% of improvement in the AUC value for predicting future links in three real-life social and collaboration networks

Effects of Hard Real-Time Constraints in Implementing the Myopic Scheduling Algorithm

Myopic is a hard real-time process scheduling algorithm that selects a suitable process based on a heuristic function from a subset (Window) of all ready processes instead of choosing from all available processes, like original heuristic scheduling algorithm. Performance of the algorithm significantly depends on the chosen heuristic function that assigns weight to different parameters like deadline, earliest starting time, processing time etc. and the size of the Window since it considers only processes from processes (where, knnk≤). This research evaluates the performance of the Myopic algorithm for different parameters to demonstrate the merits and constraints of the algorithm. A comparative performance of the impact of window size in implementing the Myopic algorithm is presented and discussed through a set of experiments

Predicting interval time for reciprocal link creation using survival analysis

The majority of directed social networks, such as Twitter, Flickr and Google+, exhibit reciprocal altruism, a social psychology phenomenon, which drives a vertex to create a reciprocal link with another vertex which has created a directed link toward the former. In existing works, scientists have already predicted the possibility of the creation of reciprocal link—a task known as “reciprocal link prediction”. However, an equally important problem is determining the interval time between the creation of the first link (also called parasocial link) and its corresponding reciprocal link. No existing works have considered solving this problem, which is the focus of this paper. Predicting the reciprocal link interval time is a challenging problem for two reasons: First, there is a lack of effective features, since well-known link prediction features are designed for undirected networks and for the binary classification task; hence, they do not work well for the interval time prediction; Second, the presence of ever-waiting links (i.e., parasocial links for which a reciprocal link is not formed within the observation period) makes the traditional supervised regression methods unsuitable for such data. In this paper, we propose a solution for the reciprocal link interval time prediction task. We map this problem to a survival analysis task and show through extensive experiments on real-world datasets that survival analysis methods perform better than traditional regression, neural network-based models and support vector regression for solving reciprocal interval time prediction

Numerical solution of infinite boundary integral equation by using Galerkin method with Laguerre polynomials.

In this paper the exact solution of infinite boundary integral equation (IBIE) of the second kind with degenerate kernel is presented. Moreover Galerkin method with Laguerre polynomial is applied to get the approximate solution of IBIE. Numerical examples are given to show the validity of the method presented

Dynamic Mechanical Behavior & Analysis of the Jute-Glass Fiber Reinforced Polyester Hybrid Composites

The development of composite materials based on the reinforcement of two or more fiber types in a matrix leads to the production of hybrid composites. In the present work, hessian jute cloth, non-woven E-glass and polyester resin were used to prepare jute/polyester, glass/polyester and jute-glass hybrid polyester composites by hand lay-up and heat press molding techniques and their mechanical properties were evaluated for different stacking sequences. In Jute/polyester and glass/polyester composites, mechanical properties such as tensile properties, bending properties and impact strength increase with the increases of stacking sequences. In case of jute-glass hybrid composites, the composites which content more glass layer than that of jute layer shows the higher mechanical properties. Water uptake (%) of these composites demonstrate that water absorption rate is initially higher for jute/polyester composite and at a stage it become steady (31.11%), but in case of glass/polyester and jute-glass hybrid composites the absorption rate is very low which is almost less than 1% due to the hydrophobic nature of glass fiber and polyester resin. Soil degradation test of all types of composites were evaluated and the deterioration of the mechanical properties revealed for all the composites where jute/polyester composites showed the higher degree but E-glass/polyester composites retained major portion of its original integrity and their hybrid declined more than glass but less than jute composites. The composites were also radiated under gamma radiation (50 kCi Cobalt 60 Source) of various doses (1-12.5 kGy). It was found that by using gamma radiation, the mechanical properties of the composites were improved

Global financial crisis and multiscale systematic risk: Evidence from selected European stock markets

In this paper, we have investigated the impact of the global financial crisis on the multi-horizon nature of systematic risk and market risk using daily data of eight major European equity markets over the period of 2005-2018. The method is based on a wavelet multiscale approach within the framework of a capital asset pricing model. Empirical results demonstrate that beta coefficients have a multiscale tendency and betas tend to increase at higher scales (lower frequencies). In addition, the size of betas and R2s tend to increase during the crisis period compared with the pre-crisis period. The multiscale nature of the betas is consistent with the fact that stock market investors have different time horizons due to different trading strategies. Our results based on scale dependent value-at-risk (VaR) suggest that market risk tends to be more concentrated at lower time scales (higher frequencies) of the data. Moreover, the scale-by-scale estimates of VaR have increased almost three fold for every market during the crisis period compared with the pre-crisis period. Finally, our approach allows for accurately forecasting time-dependent betas and VaR