An under-Sampled Approach for Handling Skewed Data Distribution using Cluster Disjuncts

In Data mining and Knowledge Discovery hidden and valuable knowledge from the data sources is discovered. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability. Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class(es). Researchers have rigorously studied several techniques to alleviate the problem of class imbalance, including resampling algorithms, and feature selection approaches to this problem. In this paper, we present a new hybrid frame work dubbed as Majority Under-sampling based on Cluster Disjunct (MAJOR_CD) for learning from skewed training data. This algorithm provides a simpler and faster alternative by using cluster disjunct concept. We conduct experiments using twelve UCI data sets from various application domains using five algorithms for comparison on six evaluation metrics. The empirical study suggests that MAJOR_CD have been believed to be effective in addressing the class imbalance problem

Improving Management and Understanding of Major Diseases of Sugar Beet

Sugar beet is a sugar-yielding crop, that contributes 25% of the global sucrose production. Economic production of sugar beet is hampered by Cercospora leaf spot (CLS) (Cercospora beticola), Rhizoctonia crown and root rot (RCRR) (Rhizoctonia solani), Sclerotinia root rot (SRR) (Sclerotinia sclerotiorum), and Rhizopus root rot (Rhizopus arrhizus) diseases. These diseases can reduce yield by 15 to 40%. On CLS, buildup of fungicide-resistance strains is a major issue due to poor implementation of fungicides and understanding of disease development at early stages. The identification of germplasm resistant to RCRR disease is hindered by the lack of effective inoculation methods. Identification of SRR and RRR pathogens is crucial for their proper management. The objectives of this research were 1. to evaluate the role of adjuvants in improving the efficacy of fungicides on CLS, 2. to characterize the infection process during early stages of infection by C. beticola, 3. to identify an effective inoculation method for RCRR, and 4. to identify and characterize the causal organisms of SSR and RRR. The value of adjuvants was evaluated in greenhouse and field conditions. Application of fungicides with or without adjuvants before disease onset reduced disease severity of CLS in greenhouse condition. In field conditions, additions of adjuvants did not improve the effectiveness of fungicides and few of them negatively impacted root yield. The initial stage of infection on CLS susceptible and resistant sugar beet variety were compared using confocal microscopy. C. beticola biomass accumulation, percent leaf cell death and disease severity were all significantly greater in the susceptible variety compared to the resistant variety (P<0.05). R. solani inoculated on the crown and roots were compared in a replicated trial in greenhouse conditions. The root inoculation method provided a more consistent disease rating of the sugar beet variety in the greenhouse for screening of RCRR cultivars in a resistance breeding program. Based on morphological and molecular techniques, causal organisms of SRR and RRR were characterized and was found to be pathogenic to sugar beet varieties tested in-vitro and in the greenhouse conditions

Segmenting Supply Chain Process for Optimal Performance by Adopting Postponement: A Randomized Trial

Even though extensive technologies have been applied to all stages of a supply-chain, the performance of many supply chains has been quite dismal. One potential cause for failure is the lack of comprehending the nature of the demand and therefore being unable to device a supply-chain that would better satisfy that demand. A common mistake is to use an efficient supply chain that calls for a responsive supply chain and vice versa. The paper aims to develop the first wave of empirical investigations related to the impact of supply chain design practices on performance. It investigated a supply chain design model that linked efficiency with responsiveness to optimize performance by deploying postponement. An inâ€depth case study methodology was adopted to uncover the strategies undertaken by one of the Bangladesh's fastest growing cement manufacturers to create a competitive advantage through its management of the supply chain design alignment. The major elements were verified by surveys. Applicability and exploitability of the diagnostic instrument was validated using action research. Generally, the adoption of segmenting the supply chain process by diffusing the postponing style led to an improved performance, which, in turn, positively impact operational performance. Operational performance enhances organizational performance. Just as processes can be broken into parts, so can supply-chain processes be segmented to achieve optimal performance. Practitioners are provided with a framework for assessing the synergistic impact of postponing practices on supply chain design performance. Keywords: Action Research on Supply Chain, Alignment, Efficient, Responsive, Optimal Performance, Postponement, Supply-chain design

Mechanical Performance of Natural / Natural Fiber Reinforced Hybrid Composite Materials Using Finite Element Method Based Micromechanics and Experiments

A micromechanical analysis of the representative volume element (RVE) of a unidirectional flax/jute fiber reinforced epoxy composite is performed using finite element analysis (FEA). To do so, first effective mechanical properties of flax fiber and jute fiber are evaluated numerically and then used in evaluating the effective properties of ax/jute/epoxy hybrid composite. Mechanics of Structure Genome (MSG), a new homogenization tool developed in Purdue University, is used to calculate the homogenized effective properties. Numerical results are compared with analytical solution based on rule of mixture, Halpin-Tsai as well as Tsai-Hahn equations. The effect of the volume fraction of the two different fibers is studied. Mechanical performance of hybrid composite is compared with the mechanical performance of single fiber composites. Synergistic effect due to hybridization is studied using analytical method given in literature, finite element method based MSG and Classical Lamination Theory (CLT). It is found that, when Poisson ratio is taken into consideration, elastic modulus shows synergy due to hybridization. Finally, impact properties of ax/jute/epoxy hybrid composite material are studied using Charpy impact testing

Cyber Police: An Idea for Securing Cyber Space with Unique Identification

The advancement of cyber technology completely depends on how conveniently we use it. Many people deceived in different ways in our current cyber system. We can prosper ourselves through the utilization of this internet technology. However any country can improve their online security through improving cyber system. On the other hand it may cause precarious outcome if it is incorrectly handled by any unplanned administration. An appropriate mechanism can move forward our cyber world with a safer e-biosphere. The purpose of this paper is to propose an idea that will ensure security and justice in cyber world. This idea proposes to diminish all types of anarchy from the cyber space by ensuring authentic identification to every internet user; securing website browsing; preventing any kind of fraud as well as guarantee truth and justice in the online world

Websites of Library and Information Network in India: A Webometric Analysis

The websites of the Library and Information Networks are one of the main sources of information in academic, management and other research fields. This type of network creates a cooperative bonding between various types of the subject area in the field of research. As we know library consortia and library resource sharing is one activity that promotes Network connectivity and communication between various areas of the subject field. In terms of research, Library and Information Network websites can give the existence and relevance of the achievements of individuals, research groups, institutions and various departments. This study tries to examine the 9 websites of Library and Information Networks in India. Various Data of the library network websites belong to the web meta information, page quality & structure, performance & accessibility score, SEO score, internal links, external links and metrics time limitation, domain analysis, traffic & engagement and also web ranking in India and Global & Alexa Rank. As we calculate WIFs find that ERNET and NKN are good position compare to others. After the analysis note that INFLIBNET, NICNET, ERNET, ADINET, and NKN is the most popular network in India among them

Network traffic modelling and router performance optimization using fuzzy logic and genetic algorithms

University of Technology, Sydney. Faculty of Information Technology.Accurate computer network traffic models are required for many network tasks such as network analysis, performance optimization and areas of traffic engineering such as avoiding congestion or guaranteeing a specific quality of service (QoS) to an application. Existing traffic modelling techniques rely on precise mathematical analysis of extensive measured data such as packet arrival time, packet size and server-side or client-side round trip time. With the advent of high speed broadband networks, gathering an acceptable quantity of data needed for the precise representation of traffic is a difficult, time consuming, expensive and in some cases almost an impossible task. A possible alternative is to employ fuzzy logic based models which can represent processes characterized by imprecise data, which is generally easier to gather. The effectiveness of these models has been demonstrated in many industrial applications. This work develops fuzzy logic based traffic models using imprecise data sets that can be obtained realistically. Optimizing the performance of a router requires the optimization of a number of conflicting objectives. A possible approach is to express it as a multi-objective problem. Multi-objective evolutionary algorithms (MOEA) can be used for solving such problems. This research proposes two fuzzy logic based traffic models: fuzzy group model and fuzzy state model. These models together with MOEA are used to propose a simple and fast router buffer management scheme. The developed fuzzy group model includes a parameter which is also useful for measuring the irregular traffic patterns known as burstiness. The experimental results are promising