Plasma Properties Effect on Fluorescent Tube Plasma Antenna Performance

This paper presents the analysis on the performance of monopole antenna with fluorescent tubes. In this research, the simulation and experimental approach is conducted. The fluorescent tube with different length and size is designed using Computer Simulation Technology (CST) software and the characteristics of antenna parameter are simulated throughout the software. CST was used to simulate antenna parameters such as return loss, resonant frequency, gain and directivity. Vector Network Analyzer (VNA) was used to measure the return loss of plasma antenna in order to validate the simulation results. In the simulation and experiment, the supply frequency is set starting from 1 GHz to 10 GHz. The results show that the return loss of plasma antenna changes when size of fluorescent tubes is varied, correspond to the different plasma properties. It shows that different values of plasma properties such as plasma frequency and collision frequency gives difference result of return loss, gain and directivity. For the gain, the values range from 2.14 dB to 2.36 dB. The return loss of plasma antenna offers higher value range from -22.187 dB to -32.903 dB. The higher the values of plasma frequency and collision frequency, the higher return loss can be obtained. The values obtained are comparative to the conventional type of metal antenna.

Mediating Role of Social Responsibility on the Relationship between Consumer Awareness of Green Marketing and Purchase Intentions

This research aims to examine the influence of mediating effect of corporate social responsibility on the relationship between consumer awareness of green marketing and purchase intentions in the retail setting. Data from 200 valid questionnaires was analyzed using the partial least squares (PLS) approach for the analysis of structural equation models with SmartPLS computer program version 2.0 as research data does not necessarily have a multivariate normal distribution and is less sensitive to sample size than other covariance approaches. PLS results revealed that corporate social responsibility partially mediated the link between consumer awareness of green marketing and purchase intentions of the product in the retail setting. Marketing managers should allocate a sufficient portion of their budget to appropriate corporate social responsibility activities by engaging in voluntary programs for positive return on investment leading to increased business profitability and long run business sustainability. The outcomes of the mediating effects of corporate social responsibility add a new impetus to the growing literature and preceding discoveries on consumer green marketing awareness, which is inadequately researched in the Malaysian setting. Direction for future research is also presented.

Fracture Mechanics Modeling of a Shear-Cracked RC Beams Shear-Strengthened with FRP Sheets

So far, the conventional experimental and theoretical analysis in fracture mechanics have been applied to study concrete flexural- cracked beams, which are strengthened using fiber reinforced polymer (FRP) composite sheets. However, there is still little knowledge about the shear capacity of a side face FRP- strengthened shear-cracked beam. A numerical analysis is herein presented to model the fracture mechanics of a four-point RC beam, with two inclined initial notch on the supports, which is strengthened with side face FRP sheets. In the present study, the shear crack is forced to conduct by using an initial notch in supports. The ABAQUS software is used to model crack propagation by conventional cohesive elements. It is observed that the FRP sheets play important roles in preventing the propagation of shear cracks.

Direct Design of Steel Bridge Using Nonlinear Inelastic Analysis

In this paper, a direct design using a nonlinear inelastic analysis is suggested. Also, this paper compares the load carrying capacity obtained by a nonlinear inelastic analysis with experiment results to verify the accuracy of the results. The allowable stress design results of a railroad through a plate girder bridge and the safety factor of the nonlinear inelastic analysis were compared to examine the safety performance. As a result, the load safety factor for the nonlinear inelastic analysis was twice as high as the required safety factor under the allowable stress design standard specified in the civil engineering structure design standards for urban magnetic levitation railways, which further verified the advantages of the proposed direct design method.

Design and Implementation of a Memory Safety Isolation Method Based on the Xen Cloud Environment

In view of the present cloud security problem has increasingly become one of the major obstacles hindering the development of the cloud computing, put forward a kind of memory based on Xen cloud environment security isolation technology implementation. And based on Xen virtual machine monitor system, analysis of the model of memory virtualization is implemented, using Xen memory virtualization system mechanism of super calls and grant table, based on the virtual machine manager internal implementation of access control module (ACM) to design the security isolation system memory. Experiments show that, the system can effectively isolate different customer domain OS between illegal access to memory data.

Analysis of Heat Exchanger Network of Distillation Unit of Shiraz Oil Refinery

The reduction of energy consumption through improvements in energy efficiency has become an important goal for all industries, in order to improve the efficiency of the economy, and to reduce the emissions of Co2 caused by power generation. The objective of this paper is to investigate opportunities to increase process energy efficiency at the distillation unit of Shiraz oil refinery in south of Iran. The main aim of the project is to locate energy savings by use of pinch technology and to assess them. At first all the required data of hot and cold streams in preheating section of distillation unit has been extracted from the available flow sheets and then pinch analysis has been conducted. The present case study is a threshold one which does not need any utilities. After running range, targeting several heat exchanger networks were designed with respect to operating conditions and different ΔTmin. The optimal value of ΔTmin was calculated to be 22.3 °C. Based on this optimal value, there will be 5% reduction in annual total cost of heat exchanger network.

Thermal Conductivity of Al2O3/Water-Based Nanofluids: Revisiting the Influences of pH and Surfactant

The present work focuses on the preparation and the stabilization of Al2O3-water based nanofluids. Though they have been widely considered in the past, to the best of our knowledge, there is no clear consensus about a proper way to prepare and stabilize them by the appropriate surfactant. In this paper, a careful experimental investigation is performed to quantify the combined influence of pH and the surfactant on the stability of Al2O3-water based nanofluids. Two volume concentrations of nanoparticles and three nanoparticle sizes have been considered. The good preparation and stability of these nanofluids are evaluated through thermal conductivity measurements. The results show that the optimum value for the thermal conductivity is obtained mainly by controlling the pH of the mixture and surfactants are not necessary to stabilize the solution.

Evaluation of Heat Transfer and Entropy Generation by Al2O3-Water Nanofluid

In this numerical work, natural convection and entropy generation of Al2O3–water nanofluid in square cavity have been studied. A two-dimensional steady laminar natural convection in a differentially heated square cavity of length L, filled with a nanofluid is investigated numerically. The horizontal walls are considered adiabatic. Vertical walls corresponding to x=0 and x=L are respectively maintained at hot temperature, Th and cold temperature, Tc. The resolution is performed by the CFD code "FLUENT" in combination with GAMBIT as mesh generator. These simulations are performed by maintaining the Rayleigh numbers varied as 103 ≤ Ra ≤ 106, while the solid volume fraction varied from 1% to 5%, the particle size is fixed at dp=33 nm and a range of the temperature from 20 to 70 °C. We used models of thermophysical nanofluids properties based on experimental measurements for studying the effect of adding solid particle into water in natural convection heat transfer and entropy generation of nanofluid. Such as models of thermal conductivity and dynamic viscosity which are dependent on solid volume fraction, particle size and temperature. The average Nusselt number is calculated at the hot wall of the cavity in a different solid volume fraction. The most important results is that at low temperatures (less than 40 °C), the addition of nanosolids Al2O3 into water leads to a decrease in heat transfer and entropy generation instead of the expected increase, whereas at high temperature, heat transfer and entropy generation increase with the addition of nanosolids. This behavior is due to the contradictory effects of viscosity and thermal conductivity of the nanofluid. These effects are discussed in this work.

Effect of Waste Bottle Chips on Strength Parameters of Silty Soil

Laboratory consolidated undrained triaxial (CU) tests were carried out to study the strength behavior of silty soil reinforced with randomly plastic waste bottle chips. Specimens mixed with plastic waste chips in triaxial compression tests with 0.25, 0.50, 0.75, 1.0, and 1.25% by dry weight of soil and tree different length including 4, 8, and 12 mm. In all of the samples, the width and thickness of plastic chips were kept constant. According to the results, the amount and size of plastic waste bottle chips played an important role in the increasing of the strength parameters of reinforced silt compared to the pure soil. Because of good results, the suggested method of soil improvement can be used in many engineering problems such as increasing the bearing capacity and settlement reduction in foundations.

Fuzzy Based Particle Swarm Optimization Routing Technique for Load Balancing in Wireless Sensor Networks

Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to reduce the energy consumption using particle swarm optimization algorithm, the cluster head sends its information along data packets to the heads with link. The simulation results show that the presented routing protocol can perform load balancing effectively and reduce the energy consumption of cluster heads.

A Study to Design a Survey to Encourage the University-Industry Relation

The purpose of this research is to present a survey to be applied to professors of public universities, to identify the factors that benefit or hinder the university-industry relation. Hence, this research studies some elements that integrate the variables: Knowledge management, technology management, and technology transfer; to define the existence of a relation between these variables and the industry necessities of innovation. This study is exploratory, descriptive and non-experimental. The research question is: What is the impact of the knowledge management, the technology management, and the technology transfer, made by administrative support areas of the public universities, in the industries innovation? Thus, literature review was made to identify some elements that should be considered to design a survey that allows to obtain valid information to the study variables. After this, the survey was developed, and the Content Validity Analysis was made through the Lawshe Model. The analysis indicated that the Content Validity Index (CVI) was 0.80. Hence, it was determined that this survey presents acceptable psychometric properties to be used as an evaluation tool.

Influence of Organic Modifier Loading on Particle Dispersion of Biodegradable Polycaprolactone/Montmorillonite Nanocomposites

Natural sodium montmorillonite (NaMMT), Cloisite Na+ and two organophilic montmorillonites (OMMTs), Cloisites 20A and 15A were used. Polycaprolactone (PCL)/MMT composites containing 1, 3, 5, and 10 wt% of Cloisite Na+ and PCL/OMMT nanocomposites containing 5 and 10 wt% of Cloisites 20A and 15A were prepared via solution intercalation technique to study the influence of organic modifier loading on particle dispersion of PCL/ NaMMT composites. Thermal stabilities of the obtained composites were characterized by thermal analysis using the thermogravimetric analyzer (TGA) which showed that in the presence of nitrogen flow the incorporation of 5 and 10 wt% of filler brings some decrease in PCL thermal stability in the sequence: Cloisite Na+>Cloisite 15A > Cloisite 20A, while in the presence of air flow these fillers scarcely influenced the thermoxidative stability of PCL by slightly accelerating the process. The interaction between PCL and silicate layers was studied by Fourier transform infrared (FTIR) spectroscopy which confirmed moderate interactions between nanometric silicate layers and PCL segments. The electrical conductivity (σ) which describes the ionic mobility of the systems was studied as a function of temperature and showed that σ of PCL was enhanced on increasing the modifier loading at filler content of 5 wt%, especially at higher temperatures in the sequence: Cloisite Na+

Markov Chain Based QoS Support for Wireless Body Area Network Communication in Health Monitoring Services

Wireless Body Area Networks (WBANs) are essential for real-time health monitoring of patients and in diagnosing of many diseases. WBANs comprise many sensors to monitor a large range of ambient conditions. Quality of Service (QoS) is a key challenge in WBAN, because the different state information of the neighboring nodes has to be monitored in an accurate manner. However, energy consumption gets increased while predicting and maintaining the exact information in highly dynamic environments. In order to reduce energy consumption and end to end delay, Markov Chain Based Quality of Service Support (MC-QoSS) method is designed in the health monitoring services of WBAN communication. The energy consumption gets reduced by forming a Markov chain with high energy nodes in the sensor networks communication path. The low energy level sensor nodes are removed using transitional probability in order to reduce end to end delay. High energy nodes are formed in the chain structure of its corresponding path to enhance communication. After choosing the communication path through high energy nodes, the packets are sent to the sink node from the source node with a higher Packet Delivery Ratio. The simulation result shows that MC-QoSS method improves the packet delivery ratio and reduces energy consumption with minimum end to end delay, compared to existing methods.

Two-Stage Launch Vehicle Trajectory Modeling for Low Earth Orbit Applications

This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Application of Metakaolin from Northeast of Thailand Used as Binder in Casting Process of Rice Polishing Cylinder

The objective of this research was to apply metakaolin from northeast of Thailand as a binder in the casting process of rice polishing cylinder in replacement of the imported calcined magnesite cement and to reduce the production cost of the cylinder. Metakaolin was obtained from three different regions (Udon Thani, Nakhon Phanom, and Ubon Ratchathani). The design of experiment analysis using the MINITAB Release 14 based on the compressive strength and tensile strength testing was conducted. According to the analysis results, it was found that the optimal proportions were calcined magnesite cement: metakaolin from Udon Thani, Nakhon Phanom and Ubon Ratchathani equal to 63:37, 71:29, and 100:0, respectively. When used this formula to cast the cylinder and test the rice milling, it was found that the average broken rice percent was 32.52 and 38.29 for the cylinder contained the metakaolin from Udon Thani and Nakhon Phanom, respectively, which implied that the cylinder which contained the metakaolin from Udon Thani has higher efficiency than the cylinder which contained the metakaolin from Nakhon Phanom at 0.05 level of statistical significance. Whereas, the average wear rate of cylinder from both resources were 7.27 and 6.53 g/h, respectively.

Efficacy of Three Different Herbicides to the Control of Wild Barley (Hordeum spontaneum C. Koch) in Relation to Plant Growth Stage and Nitrogen Fertilizer Additive

To study the effect of nitrogenous additive spray solution on the efficacy of three herbicides i.e. pinoxaden (Trade name: Axial), sulfosulfuron+metsulfuron-methyl (Trade name: Total) and sulfosulfuron (Trade name: Apirus) in controlling wild barley (Hordeum spontaneum C. Koch), in different growth stages, a greenhouse experiment as a split plot in a completely randomized design in three replications was conducted. One month after treatments, all plants were harvested and growth parameters were determined. The data were analyzed with computer. The results showed that the herbicide applications with and without nitrogen additive caused significant reductions in growth parameters of wild barley at 2-4 leaf stage. However, the plants were not killed by this herbicide. Plants were killed completely due to applications of the two other herbicides i.e. Apirus and Total at 2-4 leaf. There was no significant difference between the effect of these two herbicides. There was no significant difference between the highest rate of each herbicide used alone and that of the lowest rate with nitrogenous additive.

Application of Voltage Stability Indices for Proper Placement of STATCOM under Load Increase Scenario

In today’s world, electrical energy has become an indispensable component of all aspects of modern human life. Reliability, security and stability are the key aspects of any power system. Failure to meet any of these three aspects results into a great impediment to modern life. Modern power systems are being subjected to heavily stressed conditions leading to voltage stability problems. If the voltage stability problems are not mitigated properly through proper voltage stability assessment methods, cascading events may occur which may lead to voltage collapse or blackout events. Modern FACTS devices like STATCOM are one of the measures to overcome the blackout problems. As these devices are very costly, they must be installed properly at suitable locations, mostly at weak bus. Line voltage stability indices such as FVSI, Lmn and LQP play important role for identification of a weak bus. This paper presents evaluation of these line stability indices for the assessment of reliable information about the closeness of the power system to voltage collapse. PSAT is a user-friendly MATLAB toolbox, of which CPF is an important feature which has been extensively used for the placement of STATCOM to assess the stability. Novelty of the present research work lies in that the active and reactive load has been changed simultaneously at all the load buses under consideration. MATLAB code has been developed for the same and tested successfully on various standard IEEE test systems. The results for standard IEEE14 bus test system, specifically, are presented in this paper.

Procedure Model for Data-Driven Decision Support Regarding the Integration of Renewable Energies into Industrial Energy Management

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

A Neural Network Classifier for Estimation of the Degree of Infestation by Late Blight on Tomato Leaves

Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm

The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.