Search results for: proposed module
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9404

Search results for: proposed module

8894 An Efficient Resource Management Algorithm for Mobility Management in Wireless Mesh Networks

Authors: Mallikarjuna Rao Yamarthy, Subramanyam Makam Venkata, Satya Prasad Kodati

Abstract:

The main objective of the proposed work is to reduce the overall network traffic incurred by mobility management, packet delivery cost and to increase the resource utilization. The proposed algorithm, An Efficient Resource Management Algorithm (ERMA) for mobility management in wireless mesh networks, relies on pointer based mobility management scheme. Whenever a mesh client moves from one mesh router to another, the pointer is set up dynamically between the previous mesh router and current mesh router based on the distance constraints. The algorithm evaluated for signaling cost, data delivery cost and total communication cost performance metrics. The proposed algorithm is demonstrated for both internet sessions and intranet sessions. The proposed algorithm yields significantly better performance in terms of signaling cost, data delivery cost, and total communication cost.

Keywords: data delivery cost, mobility management, pointer forwarding, resource management, wireless mesh networks

Procedia PDF Downloads 363
8893 Clean Sky 2 – Project PALACE: Aeration’s Experimental Sound Velocity Investigations for High-Speed Gerotor Simulations

Authors: Benoît Mary, Thibaut Gras, Gaëtan Fagot, Yvon Goth, Ilyes Mnassri-Cetim

Abstract:

A Gerotor pump is composed of an external and internal gear with conjugate cycloidal profiles. From suction to delivery ports, the fluid is transported inside cavities formed by teeth and driven by the shaft. From a geometric and conceptional side it is worth to note that the internal gear has one tooth less than the external one. Simcenter Amesim v.16 includes a new submodel for modelling the hydraulic Gerotor pumps behavior (THCDGP0). This submodel considers leakages between teeth tips using Poiseuille and Couette flows contributions. From the 3D CAD model of the studied pump, the “CAD import” tool takes out the main geometrical characteristics and the submodel THCDGP0 computes the evolution of each cavity volume and their relative position according to the suction or delivery areas. This module, based on international publications, presents robust results up to 6 000 rpm for pressure greater than atmospheric level. For higher rotational speeds or lower pressures, oil aeration and cavitation effects are significant and highly drop the pump’s performance. The liquid used in hydraulic systems always contains some gas, which is dissolved in the liquid at high pressure and tends to be released in a free form (i.e. undissolved as bubbles) when pressure drops. In addition to gas release and dissolution, the liquid itself may vaporize due to cavitation. To model the relative density of the equivalent fluid, modified Henry’s law is applied in Simcenter Amesim v.16 to predict the fraction of undissolved gas or vapor. Three parietal pressure sensors have been set up upstream from the pump to estimate the sound speed in the oil. Analytical models have been compared with the experimental sound speed to estimate the occluded gas content. Simcenter Amesim v.16 model was supplied by these previous analyses marks which have successfully improved the simulations results up to 14 000 rpm. This work provides a sound foundation for designing the next Gerotor pump generation reaching high rotation range more than 25 000 rpm. This improved module results will be compared to tests on this new pump demonstrator.

Keywords: gerotor pump, high speed, numerical simulations, aeronautic, aeration, cavitation

Procedia PDF Downloads 129
8892 Symmetric Arabic Language Encryption Technique Based on Modified Playfair Algorithm

Authors: Fairouz Beggas

Abstract:

Due to the large number of exchanges in the networks, the security of communications is essential. Most ways of keeping communication secure rely on encryption. In this work, a symmetric encryption technique is offered to encrypt and decrypt simple Arabic scripts based on a multi-level security. A proposed technique uses an idea of Playfair encryption with a larger table size and an additional layer of encryption to ensure more security. The idea of the proposed algorithm aims to generate a dynamic table that depends on a secret key. The same secret key is also used to create other secret keys to over-encrypt the plaintext in three steps. The obtained results show that the proposed algorithm is faster in terms of encryption/decryption speed and can resist to many types of attacks.

Keywords: arabic data, encryption, playfair, symmetric algorithm

Procedia PDF Downloads 83
8891 A Local Invariant Generalized Hough Transform Method for Integrated Circuit Visual Positioning

Authors: Wei Feilong

Abstract:

In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment

Procedia PDF Downloads 262
8890 Design and Implementation of Reliable Location-Based Social Community Services

Authors: B. J. Kim, K. W. Nam, S. J. Lee

Abstract:

Traditional social network services provide users with more information than is needed, and it is not easy to verify the authenticity of the information. This paper proposes a system that can only post messages where users are located to enhance the reliability of social networking services. The proposed system implements a Google Map API to post postings on the map and to read postings within a range of distances from the users’ location. The proposed system will only provide alerts, memories, and information about locations within a given range depending on the users' current location, providing reliable information that they believe will be necessary in real time. It is expected that the proposed system will be able to meet the real demands of users and create a more reliable social network services environment.

Keywords: social network, location, reliability, posting

Procedia PDF Downloads 253
8889 Real-Time Aerial Marine Surveillance System for Safe Navigation

Authors: Vinesh Thiruchelvam, Umar Mumtaz Chowdry, Sathish Kumar Selvaperumal

Abstract:

The prime purpose of the project is to provide a sophisticated system for surveillance specialized for the Port Authorities in the Maritime Industry. The current aerial surveillance does not have a wide dimensioning view. The channels of communication is shared and not exclusive allowing for communications errors or disturbance mainly due to traffic. The scope is to analyze the various aspects as real-time aerial and marine surveillance is one of the most important methods which could ensure the domain security of the sailors. The system will improve real time data as obtained for the controller base station. The key implementation will be based on camera speed, angle and adherence to a sustainable power utilization module.

Keywords: SMS, real time, GUI, maritime industry

Procedia PDF Downloads 492
8888 Directionally-Sensitive Personal Wearable Radiation Dosimeter

Authors: Hai Huu Le, Paul Junor, Moshi Geso, Graeme O’Keefe

Abstract:

In this paper, the authors propose a personal wearable directionally-sensitive radiation dosimeter using multiple semiconductor CdZnTe detectors. The proposed dosimeter not only measures the real-time dose rate but also provide the direction of the radioactive source. A linear relationship between radioactive source direction and the radiation intensity measured by each detectors is established and an equation to determine the source direction is derived by the authors. The efficiency and accuracy of the proposed dosimeter is verified by simulation using Geant4 package. Results have indicated that in a measurement duration of about 7 seconds, the proposed dosimeter was able to estimate the direction of a 10μCi 137/55Cs radioactive source to within 2 degrees.

Keywords: dose rate, Geant4 package, radiation dosimeter, radioactive source direction

Procedia PDF Downloads 322
8887 Functional and Stimuli Implementation and Verification of Programmable Peripheral Interface (PPI) Protocol

Authors: N. N. Joshi, G. K. Singh

Abstract:

We present the stimuli implementation and verification of a Programmable Peripheral Interface (PPI) 8255. It involves a designing and verification of configurable intellectual property (IP) module of PPI protocol using Verilog HDL for implementation part and System Verilog for verification. The overview of the PPI-8255 presented then the design specification implemented for the work following the functional description and pin configuration of PPI-8255. The coverage report of design shows that our design and verification environment covered 100% functionality in accordance with the design specification generated by the Questa Sim 10.0b.

Keywords: Programmable Peripheral Interface (PPI), verilog HDL, system verilog, questa sim

Procedia PDF Downloads 518
8886 Habitat Model Review and a Proposed Methodology to Value Economic Trade-Off between Cage Culture and Habitat of an Endemic Species in Lake Maninjau, Indonesia

Authors: Ivana Yuniarti, Iwan Ridwansyah

Abstract:

This paper delivers a review of various methodologies for habitat assessment and a proposed methodology to assess an endemic fish species habitat in Lake Maninjau, Indonesia as a part of a Ph.D. project. This application is mainly aimed to assess the trade-off between the economic value of aquaculture and the fisheries. The proposed methodology is a generalized linear model (GLM) combined with GIS to assess presence-absence data or habitat suitability index (HSI) combined with the analytical hierarchy process (AHP). Further, a cost of habitat replacement approach is planned to be used to calculate the habitat value as well as its trade-off with the economic value of aquaculture. The result of the study is expected to be a scientific consideration in local decision making and to provide a reference for other areas in the country.

Keywords: AHP, habitat, GLM, HSI, Maninjau

Procedia PDF Downloads 143
8885 Developing Curricula for Signaling and Communication Course at Malaysia Railway Academy (MyRA) through Industrial Collaboration Program

Authors: Mohd Fairus Humar, Ibrahim Sulaiman, Pedro Cruz, Hasry Harun

Abstract:

This paper presents the propose knowledge transfer program on railway signaling and communication by Original Equipment Manufacturer (OEM) Thales Portugal. The fundamental issue is that there is no rail related course offered by local universities and colleges in Malaysia which could be an option to pursue student career path. Currently, dedicated trainings related to the rail technology are provided by in-house training academies established by the respective rail operators such as Malaysia Railway Academy (MyRA) and Rapid Rail Training Centre. In this matter, the content of training and facilities need to be strengthened to keep up-to-date with the dynamic evolvement of the rail technology. This is because rail products have evolved to be more sophisticated and embedded with high technology components which no longer exist in the mechanical form alone but combined with electronics, information technology and others. These demand for a workforce imbued with knowledge, multi-skills and competency to deal with specialized technical areas. Talent is needed to support sustainability in Southeast Asia. Keeping the above factors in mind, an Industrial Collaboration Program (ICP) was carried out to transfer knowledge on curricula of railway signaling and communication to a selected railway operators and tertiary educational institution in Malaysia. In order to achieve the aim, a partnership was formed between Technical Depository Agency (TDA), Thales Portugal and MyRA for two years with three main stages of program implementation comprising of: i) training on basic railway signaling and communication for 1 month with Thales in Malaysia; ii) training on advance railway signaling and communication for 4 months with Thales in Portugal and; iii) a series of workshop. Two workshops were convened to develop and harmonize curricula of railway signaling and communication course and were followed by one training for installation equipment of railway signaling and Controlled Train Centre (CTC) system from Thales Portugal. With active involvement from Technical Depository Agency (TDA), railway operators, universities, and colleges, in planning, executing, monitoring, control and closure, the program module of railway signaling and communication course with a lab railway signaling field equipment and CTC simulator were developed. Through this program, contributions from various parties help to build committed societies to engage important issues in relation to railway signaling and communication towards creating a sustainable future.

Keywords: knowledge transfer program, railway signaling and communication, curricula, module and teaching aid simulator

Procedia PDF Downloads 187
8884 Measuring Energy Efficiency Performance of Mena Countries

Authors: Azam Mohammadbagheri, Bahram Fathi

Abstract:

DEA has become a very popular method of performance measure, but it still suffers from some shortcomings. One of these shortcomings is the issue of having multiple optimal solutions to weights for efficient DMUs. The cross efficiency evaluation as an extension of DEA is proposed to avoid this problem. Lam (2010) is also proposed a mixed-integer linear programming formulation based on linear discriminate analysis and super efficiency method (MILP model) to avoid having multiple optimal solutions to weights. In this study, we modified MILP model to determine more suitable weight sets and also evaluate the energy efficiency of MENA countries as an application of the proposed model.

Keywords: data envelopment analysis, discriminate analysis, cross efficiency, MILP model

Procedia PDF Downloads 683
8883 Analyzing Large Scale Recurrent Event Data with a Divide-And-Conquer Approach

Authors: Jerry Q. Cheng

Abstract:

Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

Procedia PDF Downloads 161
8882 Enhancement of Pulsed Eddy Current Response Based on Power Spectral Density after Continuous Wavelet Transform Decomposition

Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

Abstract:

The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

Procedia PDF Downloads 232
8881 LGG Architecture for Brain Tumor Segmentation Using Convolutional Neural Network

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

Abstract:

The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

Procedia PDF Downloads 177
8880 Energy Saving Techniques for MIMO Decoders

Authors: Zhuofan Cheng, Qiongda Hu, Mohammed El-Hajjar, Basel Halak

Abstract:

Multiple-input multiple-output (MIMO) systems can allow significantly higher data rates compared to single-antenna-aided systems. They are expected to be a prominent part of the 5G communication standard. However, these decoders suffer from high power consumption. This work presents a design technique in order to improve the energy efficiency of MIMO systems; this facilitates their use in the next generation of battery-operated communication devices such as mobile phones and tablets. The proposed optimization approach consists of the use of low complexity lattice reduction algorithm in combination with an adaptive VLSI implementation. The proposed design has been realized and verified in 65nm technology. The results show that the proposed design is significantly more energy-efficient than conventional K-best MIMO systems.

Keywords: energy, lattice reduction, MIMO, VLSI

Procedia PDF Downloads 324
8879 Sensitive Determination of Copper(II) by Square Wave Anodic Stripping Voltammetry with Tetracarbonylmolybdenum(0) Multiwalled Carbon Nanotube Paste Electrode

Authors: Illyas Md Isa, Mohamad Idris Saidin, Mustaffa Ahmad, Norhayati Hashim

Abstract:

A highly selective and sensitive carbon paste electrode modified with multiwall carbon nanotubes and 2,6–diacetylpyridine-di-(1R)–(-)–fenchone diazine tetracarbonylmolybdenum(0) complex was used for determination of trace amounts of Cu(II) using square wave anodic stripping voltammetry (SWASV). The influences of experimental variables on the proposed electrode such as pH, supporting electrolyte, preconcentration potential and time, and square wave parameters were investigated. Under optimal conditions, the proposed electrode showed a linear relationship with concentration in the range of 1.0 × 10–10 to 1.0 × 10– 6 M Cu(II) with a limit of detection 8.0 × 10–11 M. The relative standard deviation (n = 5) for a solution containing 1.0 × 10– 6 M of Cu(II) was 0.036. The presence of various cations (in 10 and 100-folds concentration) did not interfere. Electrochemical impedance spectroscopy (EIS) showed that the charge transfer at the electrode-solution interface was favourable. The proposed electrode was applied for the determination of Cu(II) in several water samples. Results agreed very well with those obtained by inductively coupled plasma-optical emission spectrometry. The modified electrode was then proposed as an alternative for determination of Cu(II).

Keywords: chemically modified electrode, Cu(II), square wave anodic stripping voltammetry, tetracarbonylmolybdenum(0)

Procedia PDF Downloads 268
8878 Technology Planning with Internal and External Resource for Open Innovation

Authors: Jeonghwan Jeon

Abstract:

Technology planning with both internal capacity and external resource is necessary for successful open innovation. Until now, many types of research have been conducted for this issue. However, technology planning for open innovation at the national level has not been researched sufficiently. This study proposes Open roadmap for open innovation at the national level. The proposed open roadmap can manage the inflow & outflow open innovation systematically. Six types of open roadmap are classified with respect to the innovation direction and characteristics. The proposed open roadmap is applied to the open innovation cases of the Roman period. The proposed open roadmap is expected to be helpful tool for technology policy planning at the national level.

Keywords: technology planning, open innovation, internal resource, external resource, technology management

Procedia PDF Downloads 489
8877 Low Complexity Deblocking Algorithm

Authors: Jagroop Singh Sidhu, Buta Singh

Abstract:

A low computational deblocking filter including three frequency related modes (smooth mode, intermediate mode, and non-smooth mode for low-frequency, mid-frequency, and high frequency regions, respectively) is proposed. The suggested approach requires zero additions, zero subtractions, zero multiplications (for intermediate region), no divisions (for non-smooth region) and no comparison. The suggested method thus keeps the computation lower and thus suitable for image coding systems based on blocks. Comparison of average number of operations for smooth, non-smooth, intermediate (per pixel vector for each block) using filter suggested by Chen and the proposed method filter suggests that the proposed filter keeps the computation lower and is thus suitable for fast processing algorithms.

Keywords: blocking artifacts, computational complexity, non-smooth, intermediate, smooth

Procedia PDF Downloads 458
8876 Convergence Analysis of a Gibbs Sampling Based Mix Design Optimization Approach for High Compressive Strength Pervious Concrete

Authors: Jiaqi Huang, Lu Jin

Abstract:

Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

Procedia PDF Downloads 175
8875 Parameter Estimation of Induction Motors by PSO Algorithm

Authors: A. Mohammadi, S. Asghari, M. Aien, M. Rashidinejad

Abstract:

After emergent of alternative current networks and their popularity, asynchronous motors became more widespread than other kinds of industrial motors. In order to control and run these motors efficiently, an accurate estimation of motor parameters is needed. There are different methods to obtain these parameters such as rotor locked test, no load test, DC test, analytical methods, and so on. The most common drawback of these methods is their inaccuracy in estimation of some motor parameters. In order to remove this concern, a novel method for parameter estimation of induction motors using particle swarm optimization (PSO) algorithm is proposed. In the proposed method, transient state of motor is used for parameter estimation. Comparison of the simulation results purtuined to the PSO algorithm with other available methods justifies the effectiveness of the proposed method.

Keywords: induction motor, motor parameter estimation, PSO algorithm, analytical method

Procedia PDF Downloads 628
8874 Energy Management of Hybrid Energy Source Composed of a Fuel Cell and Supercapacitor for an Electric Vehicle

Authors: Mejri Achref

Abstract:

This paper proposes an energy management strategy for an electrical hybrid vehicle which is composed of a Proton Exchange Membrane (PEM) fuel cell and a supercapacitor storage device. In this paper, the mathematical model for the proposed power train, comprising the PEM Fuel Cell, supercapacitor, boost converter, inverter, and vehicular structure, was modeled in MATLAB/Simulink. The proposed algorithm is evaluated for the Highway Fuel Economy Test (HWFET) driving cycle. The obtained results demonstrate the effectiveness of the proposed energy management strategy in reduction of hydrogen consumption.

Keywords: proton exchange membrane fuel cell, hybrid vehicle, hydrogen consumption, energy management strategy

Procedia PDF Downloads 173
8873 A Survey on Smart Security Mechanism Using Graphical Passwords

Authors: Aboli Dhanavade, Shweta Bhimnath, Rutuja Jumale, Ajay Nadargi

Abstract:

Security to any of our personal thing is our most basic need. It is not possible to directly apply that standard Human-computer—interaction approaches. Important usability goal for authentication system is to support users in selecting best passwords. Users often select text-passwords that are easy to remember, but they are more open for attackers to guess. The human brain is good in remembering pictures rather than textual characters. So the best alternative is being designed that is Graphical passwords. However, Graphical passwords are still immature. Conventional password schemes are also vulnerable to Shoulder-surfing attacks, many shoulder-surfing resistant graphical passwords schemes have been proposed. Next, we have analyzed the security and usability of the proposed scheme, and show the resistance of the proposed scheme to shoulder-surfing and different accidental logins.

Keywords: shoulder-surfing, security, authentication, text-passwords

Procedia PDF Downloads 358
8872 Dissimilarity-Based Coloring for Symbolic and Multivariate Data Visualization

Authors: K. Umbleja, M. Ichino, H. Yaguchi

Abstract:

In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

Procedia PDF Downloads 167
8871 Vibration-Based Data-Driven Model for Road Health Monitoring

Authors: Guru Prakash, Revanth Dugalam

Abstract:

A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

Procedia PDF Downloads 82
8870 Improved Estimation Strategies of Sensitive Characteristics Using Scrambled Response Techniques in Successive Sampling

Authors: S. Suman, G. N. Singh

Abstract:

This research work is an effort to analyse the consequences of scrambled response technique to estimate the current population mean in two-occasion successive sampling when the characteristic of interest is sensitive in nature. The generalized estimation procedures have been proposed using sensitive auxiliary variables under additive and multiplicative scramble models. The properties of resultant estimators have been deeply examined. Simulation, as well as empirical studies, are carried out to evaluate the performances of the proposed estimators with respect to other competent estimators. The results of our studies suggest that the proposed estimation procedures are highly effective under the presence of non-response situation. The result of this study also suggests that additive scrambled response model is a better choice in the perspective of cost of the survey and privacy of the respondents.

Keywords: scrambled response, sensitive characteristic, successive sampling, optimum replacement strategy

Procedia PDF Downloads 173
8869 A Novel Approach of NPSO on Flexible Logistic (S-Shaped) Model for Software Reliability Prediction

Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

Abstract:

In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

Procedia PDF Downloads 341
8868 Low Power CNFET SRAM Design

Authors: Pejman Hosseiniun, Rose Shayeghi, Iman Rahbari, Mohamad Reza Kalhor

Abstract:

CNFET has emerged as an alternative material to silicon for high performance, high stability and low power SRAM design in recent years. SRAM functions as cache memory in computers and many portable devices. In this paper, a new SRAM cell design based on CNFET technology is proposed. The proposed SRAM cell design for CNFET is compared with SRAM cell designs implemented with the conventional CMOS and FinFET in terms of speed, power consumption, stability, and leakage current. The HSPICE simulation and analysis show that the dynamic power consumption of the proposed 8T CNFET SRAM cell’s is reduced about 48% and the SNM is widened up to 56% compared to the conventional CMOS SRAM structure at the expense of 2% leakage power and 3% write delay increase.

Keywords: SRAM cell, CNFET, low power, HSPICE

Procedia PDF Downloads 403
8867 A Common Automated Programming Platform for Knowledge Based Software Engineering

Authors: Ivan Stanev, Maria Koleva

Abstract:

A common platform for automated programming (CPAP) is defined in details. Two versions of CPAP are described: Cloud-based (including the set of components for classic programming, and the set of components for combined programming) and KBASE based (including the set of components for automated programming, and the set of components for ontology programming). Four KBASE products (module for automated programming of robots, intelligent product manual, intelligent document display, and intelligent form generator) are analyzed and CPAP contributions to automated programming are presented.

Keywords: automated programming, cloud computing, knowledge based software engineering, service oriented architecture

Procedia PDF Downloads 340
8866 The Development and Testing of Greenhouse Comprehensive Environment Control System

Authors: Mohammed Alrefaie, Yaser Miaji

Abstract:

Greenhouses provide a convenient means to grow plants in the best environment. They achieve this by trapping heat from the sunlight and using artificial means to enhance the environment of the greenhouse. This includes controlling factors such as air flow, light intensity and amount of water among others that can have a big impact on plant growth. The aim of the greenhouse is to give maximum yield from plants possible. This report details the development and testing of greenhouse environment control system that can regulate light intensity, airflow and power supply inside the greenhouse. The details of the module development to control these three factors along with results of testing are presented.

Keywords: greenhouse, control system, light intensity, comprehensive environment

Procedia PDF Downloads 476
8865 Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests

Authors: Julius Onyancha, Valentina Plekhanova

Abstract:

One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

Procedia PDF Downloads 261