Particulate mechanics of granular soils

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Design of Hybrid Network Anomalies Detection System (H-NADS) Using IP Gray Space Analysis

In Network Security, there is a major issue to secure the public or private network from abnormal users. It is because each network is made up of users, services and computers with a specific behavior that is also called as heterogeneous system. To detect abnormal users, anomaly detection system (ADS) is used. In this paper, we present a novel and hybrid Anomaly Detection System with the uses of IP gray space analysis and dominant scanning port identification heuristics used to detect various anomalous users with their potential behaviors. This methodology is the combination of both statistical and rule based anomaly detection which detects five types of anomalies with their three types of potential behaviors and generates respective alarm messages to GUI.Network Security, Anomaly Detection, Suspicious Behaviors Detection

A Savonius Wind Turbine with Electric Generator: Model and Test

The overall goal of this research is to study the performance of Savonius wind tur-bine. Some of the advantages of a Savonius wind turbine include simple construction, good startup characteristics, low noise, and reduced wear. The applications of this type of wind machine include water pumping and small scale electricity generation. In the present re-search, an experimental model of the Savonius wind turbine is studied including the for-mulation of a mathematical model. The mathematic model for the torque acting on the Savonius rotor has been developed and the permanent magnet synchronous generator (PMSG) model has been simulated using the d-q synchronous reference frame theory. In the present research, the mathematic model of the wind turbine system has been simulated in MATLAB/Simulink environment. The model includes the wind turbine model and the permanent magnet synchronous generator (PMSG) model. The wind turbine pa-rameters of the experimental system have been used for the simulation purpose. A 1kW PMSG has been coupled with the wind turbine to study the dynamic performance of the wind turbine system. The system response and performance have been evaluated at 3 dif-ferent wind speeds of 16.9 m/sec, 19.8 m/sec, and 21.9 m/sec corresponding to the wind speeds of the blower used for experimental system. The experimental Savonius wind turbine has been developed to compare the nu-merical and experimental results. The experimental system includes Savonius rotor, PMSG, charge controller and rectifier, current and voltage transducers, frequency to analog converters, electrical load, and a National Instruments Data Acquisition Device (NI DAQ). The current and voltage transducers are used to measure the current and voltage in the system and the outputs are connected to the NI DAQ. The frequency to analog converters are used to measure the rpm of the rotor and the anemometer. The charge controller is meant for battery charging applications of the system. The numerical and experimental results have been obtained at three different wind speeds (16.9 m/sec, 19.8 m/sec, and 21.9 m/sec). The maximum value of the electric power generated is 2.7 Watts at a wind speed of 21.9 m/sec. Comparison of experimental and numerical results at the wind speed of 21.9 m/sec shows there is an approximate difference of 16%, 11%, 61% and 4% for the angular velocity, voltage, current, and electrical power generated, respectively. The difference in the values may be attributed to the fact that the mathematical model does not include the three-dimensional (3D) fluid effects and environ-mental factors

Multi-response Optimization in Dry Turning Process Using Taguchi's Approach and Utility Concept

AbstractTaguchi's technique is used for optimizing the process parameters of a single response problem. A single setting of process parameters may be optimal for single quality characteristic but the same settings may yield detrimental results for other quality features. Under such circumstances, multi-characteristics response optimization may be the solution to optimize multi-responses simultaneously. In this case study, a multi-characteristics response optimization based on Taguchi's design of approach and utility concept is used to optimize multiple performance characteristics, namely, axial force, radial force, main cutting force and material removal rate (MRR) during dry turning of EN-47 steel. Taguchi's L-18 orthogonal array is selected for the experiment. The optimal values obtained using the multi-characteristics optimization model have been validated by confirmation experiments

A New Approach for Handling Null Values in Web Log Using KNN and Tabu Search KNN

Abstract When the data mining procedures deals with the extraction of interesting knowledge from web logs is known as Web usage mining. The result of any mining is successful, only if the dataset under consideration is well preprocessed. One of the important preprocessing steps is handling of null/missing values. Handlings of null values have been a great bit of test for researcher. Various methods are available for estimation of null value such as k-means clustering algorithm, MARE algorithm and fuzzy logic approach. Although all these process are not always efficient. We propose an efficient approach for handling null values in web log. We are using a hybrid tabu search – k nearest neighbor classifier with multiple distance function. Tabu search – KNN classifier perform feature selection of K-NN rules. We are handling null values efficiently by using different distance function. It is called Ensemble of function. It gives different set of feature vector. Feature selection is useful for improving the classification accuracy of NN rule. We are using different distance metric with different set of feature, so it reduces the possibility that some error will common. Therefore, proposed method is better for handling null values. The proposed method is using hybrid classifier with different distance metrics and different feature vector. It is evaluated using our MANIT database. Results have indicated that a significant increase in the performance when compared with simple K-NN classifier. Original Source URL : http://aircconline.com/ijdkp/V1N5/0911ijdkp02.pdf For more details : http://airccse.org/journal/ijdkp/vol1.htm

Nanocarbon Reinforced Rubber Nanocomposites: Detailed Insights about Mechanical, Dynamical Mechanical Properties, Payne, and Mullin Effects

The reinforcing ability of the fillers results in significant improvements in properties of polymer matrix at extremely low filler loadings as compared to conventional fillers. In view of this, the present review article describes the different methods used in preparation of different rubber nanocomposites reinforced with nanodimensional individual carbonaceous fillers, such as graphene, expanded graphite, single walled carbon nanotubes, multiwalled carbon nanotubes and graphite oxide, graphene oxide, and hybrid fillers consisting combination of individual fillers. This is followed by review of mechanical properties (tensile strength, elongation at break, Young modulus, and fracture toughness) and dynamic mechanical properties (glass transition temperature, crystallization temperature, melting point) of these rubber nanocomposites. Finally, Payne and Mullin effects have also been reviewed in rubber filled with different carbon based nanofillers

Min Max Normalization Based Data Perturbation Method for Privacy Protection

Data mining system contain large amount of private and sensitive data such as healthcare, financial and criminal records. These private and sensitive data can not be share to every one, so privacy protection of data is required in data mining system for avoiding privacy leakage of data. Data perturbation is one of the best methods for privacy preserving. We used data perturbation method for preserving privacy as well as accuracy. In this method individual data value are distorted before data mining application. In this paper we present min max normalization transformation based data perturbation. The privacy parameters are used for measurement of privacy protection and the utility measure shows the performance of data mining technique after data distortion. We performed experiment on real life dataset and the result show that min max normalization transformation based data perturbation method is effective to protect confidential information and also maintain the performance of data mining technique after data distortion

Perturb and Observe Maximum Power Point Tracking for Photovoltaic Cell

Maximum power point tracking (MPPT) techniques are used in photovoltaic (PV) systems to maximize the PV array output power by tracking continuously the maximum power point (MPP) which depends on panel’s temperature and on irradiance conditions. The issue of MPPT has been addressed in different ways in the literature but, especially for low-cost implementations, the perturb and observe (P&O) maximum power point tracking algorithm is the most commonly used method due to its ease of implementation. A drawback of P&O is that, at steady state, the operating point oscillates around the MPP giving rise to the waste of some amount of available energy; moreover, it is well known that the P&O algorithm can be confused during those time intervals characterized by rapidly changing atmospheric conditions. In order to limit the negative effects associated to the above drawbacks, the P&O MPPT parameters must be customized to the dynamic behavior of the specific converter adopted. A theoretical analysis allowing the optimal choice of such parameters is also carried out. In this paper MATLAB-based M file programming scheme suitable for monitoring the I-V and P-V characteristics of a PV array under a nonuniform insolation due to partial shading condition for different configuration (modules in series parallel) of solar PV. It can also be used for developing and evaluating new maximum power point tracking techniques, especially for shaded conditions. Implementation of a novel MPPT technique has been developed using P&O algorithm has been done using MATLAB-based M file programming scheme without applying shading effect to solar array. Keywords: Maximum power point (MPP), maximum power point tracking (MPPT), perturb and observe (P&O), photovoltaic (PV

Induction of photoautotrophy in Chlorophytum borivilianum Sant. et Fernand, regenerated in vitro

The potential for photoautotrophic growth was studied in in vitro cultures of Chlorophytum borivilianum Sant. et Fernand. Best in vitro shoot differentiation was observed on MS medium supplemented with BAP 5 mg L-1, whereas MS + IBA 2 mg L-1 produced maximum root number and root length. The regenerated plantlets were then sequentially transferred to liquid basal medium having a gradual decrease in sucrose concentration [3%, 2%, 1.5%, 1%, 0.5% and 0%] after 48 hours stay in each. The plantlets thus formed were successfully hardened and transferred to sand-soil and farmyard manure mixture [1:1:1]. Approx. 90% of C. borivilianum regenerants survived after successful hardening