Search results for: Superior Predictive Ability
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1661

Search results for: Superior Predictive Ability

1151 The Application of an Experimental Design for the Defect Reduction of Electrodeposition Painting on Stainless Steel Washers

Authors: Chansiri Singhtaun, Nattaporn Prasartthong

Abstract:

The purpose of this research is to reduce the amount of incomplete coating of stainless steel washers in the electrodeposition painting process by using an experimental design technique. The surface preparation was found to be a major cause of painted surface quality. The influence of pretreating and painting process parameters, which are cleaning time, chemical concentration and shape of hanger were studied. A 23 factorial design with two replications was performed. The analysis of variance for the designed experiment showed the great influence of cleaning time and shape of hanger. From this study, optimized cleaning time was determined and a newly designed electrical conductive hanger was proved to be superior to the original one. The experimental verification results showed that the amount of incomplete coating defects decreased from 4% to 1.02% and operation cost decreased by 10.5%.

Keywords: Defect reduction, design of experiments, electrodeposition painting, stainless steel.

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1150 Design Modification of Lap Joint of Fiber Metal Laminates (CARALL)

Authors: Shaher Bano, Samia Fida, Asif Israr

Abstract:

The synergistic effect of properties of metals and fibers reinforced laminates has diverted attention of the world towards use of robust composite materials known as fiber-metal laminates in many high performance applications. In this study, modification of an adhesively bonded joint as a single lap joint of carbon fibers based CARALL FML has done to increase interlaminar shear strength of the joint. The effect of different configurations of joint designs such as spews, stepped and modification in adhesive by addition of nano-fillers was studied. Both experimental and simulation results showed that modified joint design have superior properties as maximum force experienced stepped joint was 1.5 times more than the simple lap joint. Addition of carbon nano-tubes as nano-fillers in the adhesive joint increased the maximum force due to crack deflection mechanism.

Keywords: Adhesive joint, carbon reinforced aluminium laminate, CARALL, fiber metal laminates, spews.

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1149 Greywater Treatment Using Activated Biochar Produced from Agricultural Waste

Authors: Pascal Mwenge, Tumisang Seodigeng

Abstract:

The increase in urbanisation in South Africa has led to an increase in water demand and a decline in freshwater supply. Despite this, poor water usage is still a major challenge in South Africa, for instance, freshwater is still used for non-drinking applications. The freshwater shortage can be alleviated by using other sources of water for non-portable purposes such as greywater treated with activated biochar produced from agricultural waste. The success of activated biochar produced from agricultural waste to treat greywater can be both economically and environmentally beneficial. Greywater treated with activated biochar produced from agricultural waste is considered a cost-effective wastewater treatment.  This work was aimed at determining the ability of activated biochar to remove Total Suspended Solids (TSS), Ammonium (NH4-N), Nitrate (NO3-N), and Chemical Oxygen Demand (COD) from greywater. The experiments were carried out in 800 ml laboratory plastic cylinders used as filter columns. 2.5 cm layer of gravel was used at the bottom and top of the column to sandwich the activated biochar material. Activated biochar (200 g and 400 g) was loaded in a column and used as a filter medium for greywater. Samples were collected after a week and sent for analysis. Four types of greywater were treated: Kitchen, floor cleaning water, shower and laundry water. The findings showed: 95% removal of TSS, 76% of NO3-N and 63% of COD on kitchen greywater and 85% removal of NH4-N on bathroom greywater, as highest removal of efficiency of the studied pollutants. The results showed that activated biochar produced from agricultural waste reduces a certain amount of pollutants from greywater. The results also indicated the ability of activated biochar to treat greywater for onsite non-potable reuse purposes.

Keywords: Activated biochar produced from agriculture waste, ammonium (NH4-N), chemical oxygen demand (COD), greywater, nitrate (NO3-N), total suspended solids (TSS).

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1148 A Real-Time Bayesian Decision-Support System for Predicting Suspect Vehicle’s Intended Target Using a Sparse Camera Network

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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1147 Ensembling Adaptively Constructed Polynomial Regression Models

Authors: Gints Jekabsons

Abstract:

The approach of subset selection in polynomial regression model building assumes that the chosen fixed full set of predefined basis functions contains a subset that is sufficient to describe the target relation sufficiently well. However, in most cases the necessary set of basis functions is not known and needs to be guessed – a potentially non-trivial (and long) trial and error process. In our research we consider a potentially more efficient approach – Adaptive Basis Function Construction (ABFC). It lets the model building method itself construct the basis functions necessary for creating a model of arbitrary complexity with adequate predictive performance. However, there are two issues that to some extent plague the methods of both the subset selection and the ABFC, especially when working with relatively small data samples: the selection bias and the selection instability. We try to correct these issues by model post-evaluation using Cross-Validation and model ensembling. To evaluate the proposed method, we empirically compare it to ABFC methods without ensembling, to a widely used method of subset selection, as well as to some other well-known regression modeling methods, using publicly available data sets.

Keywords: Basis function construction, heuristic search, modelensembles, polynomial regression.

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1146 Solution of Density Dependent Nonlinear Reaction-Diffusion Equation Using Differential Quadrature Method

Authors: Gülnihal Meral

Abstract:

In this study, the density dependent nonlinear reactiondiffusion equation, which arises in the insect dispersal models, is solved using the combined application of differential quadrature method(DQM) and implicit Euler method. The polynomial based DQM is used to discretize the spatial derivatives of the problem. The resulting time-dependent nonlinear system of ordinary differential equations(ODE-s) is solved by using implicit Euler method. The computations are carried out for a Cauchy problem defined by a onedimensional density dependent nonlinear reaction-diffusion equation which has an exact solution. The DQM solution is found to be in a very good agreement with the exact solution in terms of maximum absolute error. The DQM solution exhibits superior accuracy at large time levels tending to steady-state. Furthermore, using an implicit method in the solution procedure leads to stable solutions and larger time steps could be used.

Keywords: Density Dependent Nonlinear Reaction-Diffusion Equation, Differential Quadrature Method, Implicit Euler Method.

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1145 FPGA-based Systems for Evolvable Hardware

Authors: Cyrille Lambert, Tatiana Kalganova, Emanuele Stomeo

Abstract:

Since 1992, year where Hugo de Garis has published the first paper on Evolvable Hardware (EHW), a period of intense creativity has followed. It has been actively researched, developed and applied to various problems. Different approaches have been proposed that created three main classifications: extrinsic, mixtrinsic and intrinsic EHW. Each of these solutions has a real interest. Nevertheless, although the extrinsic evolution generates some excellent results, the intrinsic systems are not so advanced. This paper suggests 3 possible solutions to implement the run-time configuration intrinsic EHW system: FPGA-based Run-Time Configuration system, JBits-based Run-Time Configuration system and Multi-board functional-level Run-Time Configuration system. The main characteristic of the proposed architectures is that they are implemented on Field Programmable Gate Array. A comparison of proposed solutions demonstrates that multi-board functional-level run-time configuration is superior in terms of scalability, flexibility and the implementation easiness.

Keywords: Evolvable hardware, evolutionary computation, FPGA systems.

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1144 Artificial Neural Network-Based Short-Term Load Forecasting for Mymensingh Area of Bangladesh

Authors: S. M. Anowarul Haque, Md. Asiful Islam

Abstract:

Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: Load forecasting, artificial neural network, particle swarm optimization.

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1143 High-Efficiency Comparator for Low-Power Application

Authors: M. Yousefi, N. Nasirzadeh

Abstract:

In this paper, dynamic comparator structure employing two methods for power consumption reduction with applications in low-power high-speed analog-to-digital converters have been presented. The proposed comparator has low consumption thanks to power reduction methods. They have the ability for offset adjustment. The comparator consumes 14.3 μW at 100 MHz which is equal to 11.8 fJ. The comparator has been designed and simulated in 180 nm CMOS. Layouts occupy 210 μm2.

Keywords: Comparator, low, power, efficiency.

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1142 Comparison between the Conventional Methods and PSO Based MPPT Algorithm for Photovoltaic Systems

Authors: Ramdan B. A. Koad, Ahmed. F. Zobaa

Abstract:

Since the output characteristics of photovoltaic (PV) system depends on the ambient temperature, solar radiation and load impedance, its maximum power point (MPP) is not constant. Under each condition PV module has a point at which it can produce its MPP. Therefore, a maximum power point tracking (MPPT) method is needed to uphold the PV panel operating at its MPP. This paper presents comparative study between the conventional MPPT methods used in (PV) system: Perturb and Observe (P&O), Incremental Conductance (IncCond), andParticle Swarm Optimization (PSO) algorithmfor (MPPT) of (PV) system. To evaluate the study, the proposed PSO MPPT is implemented on a DC-DC cuk converter and has been compared with P&O and INcond methods in terms of their tracking speed, accuracy and performance by using the Matlab tool Simulink. The simulation result shows that the proposed algorithm is simple, and is superior to the P&O and IncCond methods.

Keywords: Incremental Conductance (IncCond) Method, Perturb and Observe (P&O) Method, Photovoltaic Systems (PV) and Practical Swarm Optimization Algorithm (PSO).

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1141 A Novel Genetic Algorithm Designed for Hardware Implementation

Authors: Zhenhuan Zhu, David Mulvaney, Vassilios Chouliaras

Abstract:

A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.

Keywords: Genetic algorithms, genetic hardware, machinelearning.

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1140 Biometric Steganography Using Variable Length Embedding

Authors: Souvik Bhattacharyya, Indradip Banerjee, Anumoy Chakraborty, Gautam Sanyal

Abstract:

Recent growth in digital multimedia technologies has presented a lot of facilities in information transmission, reproduction and manipulation. Therefore, the concept of information security is one of the superior articles in the present day situation. The biometric information security is one of the information security mechanisms. It has the advantages as well as disadvantages. The biometric system is at risk to a range of attacks. These attacks are anticipated to bypass the security system or to suspend the normal functioning. Various hazards have been discovered while using biometric system. Proper use of steganography greatly reduces the risks in biometric systems from the hackers. Steganography is one of the fashionable information hiding technique. The goal of steganography is to hide information inside a cover medium like text, image, audio, video etc. through which it is not possible to detect the existence of the secret information. Here in this paper a new security concept has been established by making the system more secure with the help of steganography along with biometric security. Here the biometric information has been embedded to a skin tone portion of an image with the help of proposed steganographic technique.

Keywords: Biometrics, Skin tone detection, Series, Polynomial, Cover Image, Stego Image.

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1139 Enhancing Multi-Frame Images Using Self-Delaying Dynamic Networks

Authors: Lewis E. Hibell, Honghai Liu, David J. Brown

Abstract:

This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN) to create a high resolution image from a set of time stepped input frames. These SDNs are non-recurrent temporal neural networks which can process time sampled data. SDNs can store input data for a lifecycle and feature dynamic logic based connections between layers. Several low resolution images and one high resolution image of a scene were presented to the SDN during training by a Genetic Algorithm. The SDN was trained to process the input frames in order to recreate the high resolution image. The trained SDN was then used to enhance a number of unseen noisy image sets. The quality of high resolution images produced by the SDN is compared to that of high resolution images generated using Bi-Cubic interpolation. The SDN produced images are superior in several ways to the images produced using Bi-Cubic interpolation.

Keywords: Image Enhancement, Neural Networks, Multi-Frame.

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1138 The Effects of Immersion on Visual Attention and Detection of Signals Performance for Virtual Reality Training Systems

Authors: Shiau-Feng Lin, Chiuhsiang Joe Lin, Rou-Wen Wang, Wei-Jung Shiang

Abstract:

The Virtual Reality (VR) is becoming increasingly important for business, education, and entertainment, therefore VR technology have been applied for training purposes in the areas of military, safety training and flying simulators. In particular, the superior and high reliability VR training system is very important in immersion. Manipulation training in immersive virtual environments is difficult partly because users must do without the hap contact with real objects they rely on in the real world to orient themselves and their manipulated. In this paper, we create a convincing questionnaire of immersion and an experiment to assess the influence of immersion on performance in VR training system. The Immersion Questionnaire (IQ) included spatial immersion, Psychological immersion, and Sensory immersion. We show that users with a training system complete visual attention and detection of signals. Twenty subjects were allocated to a factorial design consisting of two different VR systems (Desktop VR and Projector VR). The results indicated that different VR representation methods significantly affected the participants- Immersion dimensions.

Keywords: Virtual Reality, Training, Immersion, Visual Attention, Visual Detection

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1137 Laboratory Evaluation of the Airborne Sound Insulation of Plasterboard Sandwich Panels Filled with Recycled Textile Material

Authors: Svetlana T. Djambova, Natalia B. Ivanova, Roumiana A. Zaharieva

Abstract:

Small size acoustic chamber test method has been applied to experimentally evaluate and compare the airborne sound insulation provided by plasterboard sandwich panels filled with mineral wool and with its alternative from recycled textile material (produced by two different technologies). An original small-size acoustic chamber is used as a sound source room. It has been specially built in a real-size room, which is utilized as a sound receiving room. The experimental results of one of the recycled textile material specimens have demonstrated sound insulation properties similar to those of the mineral wool specimen and even superior in the 1600-3150 Hz frequency range. This study contributes to the improvement of recycled textile material production, as well as to the synergy of heat insulation and sound insulation performances of building materials.

Keywords: Airborne sound insulation, heat insulation products, mineral wool, recycled textile material.

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1136 Identification of High Stress and Strain Regions in Proximal Femur during Single-Leg Stance and Sideways Fall Using QCT-Based Finite Element Model

Authors: H. Kheirollahi, Y. Luo

Abstract:

Studying stress and strain trends in the femur and recognizing femur failure mechanism is very important for preventing hip fracture in the elderly. The aim of this study was to identify high stress and strain regions in the femur during normal walking and falling to find the mechanical behavior and failure mechanism of the femur. We developed a finite element model of the femur from the subject’s quantitative computed tomography (QCT) image and used it to identify potentially high stress and strain regions during the single-leg stance and the sideways fall. It was found that fracture may initiate from the superior region of femoral neck and propagate to the inferior region during a high impact force such as sideways fall. The results of this study showed that the femur bone is more sensitive to strain than stress which indicates the effect of strain, in addition to effect of stress, should be considered for failure analysis.

Keywords: Finite element analysis, hip fracture, strain, stress.

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1135 Automatic Vehicle Identification by Plate Recognition

Authors: Serkan Ozbay, Ergun Ercelebi

Abstract:

Automatic Vehicle Identification (AVI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.). License Plate Recognition is an effective form of AVI systems. In this study, a smart and simple algorithm is presented for vehicle-s license plate recognition system. The proposed algorithm consists of three major parts: Extraction of plate region, segmentation of characters and recognition of plate characters. For extracting the plate region, edge detection algorithms and smearing algorithms are used. In segmentation part, smearing algorithms, filtering and some morphological algorithms are used. And finally statistical based template matching is used for recognition of plate characters. The performance of the proposed algorithm has been tested on real images. Based on the experimental results, we noted that our algorithm shows superior performance in car license plate recognition.

Keywords: Character recognizer, license plate recognition, plate region extraction, segmentation, smearing, template matching.

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1134 Denoising by Spatial Domain Averaging for Wireless Local Area Network Terminal Localization

Authors: Diego Felix, Eugene Hyun, Michael McGuire, Mihai Sima

Abstract:

Terminal localization for indoor Wireless Local Area Networks (WLANs) is critical for the deployment of location-aware computing inside of buildings. A major challenge is obtaining high localization accuracy in presence of fluctuations of the received signal strength (RSS) measurements caused by multipath fading. This paper focuses on reducing the effect of the distance-varying noise by spatial filtering of the measured RSS. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of clusters and survey points uniformly distributed over the network area. The results show that the location accuracy improves by 16% when the filter is used and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. The estimated locations are within 2 m of the true location, which indicates that clustering the survey points provides better localization accuracy due to superior noise removal.

Keywords: Position measurement, Wireless LAN, Radio navigation, Filtering

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1133 Variable Step-Size Affine Projection Algorithm With a Weighted and Regularized Projection Matrix

Authors: Tao Dai, Andy Adler, Behnam Shahrrava

Abstract:

This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Keywords: Adaptive signal processing, affine projection algorithms, variable step-size adaptive algorithms, regularization.

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1132 Numerical Analysis on Triceratops Restraining System: Failure Conditions of Tethers

Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

Abstract:

Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: Fatigue life, Failure analysis, PM spectrum, rain flow counting, triceratops.

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1131 The New Effective Biostimulator for Agroecological Engineering

Authors: Saniyam A. Ibragimova, Zhandos M. Basygarayev, Almagul R. Kerimkulova, E. A. Bukenova, Murat K. Gilmanov

Abstract:

New biostimulator from wheat seeds which by its chemical composition relates to fusicoccin is presented in this article. New biostimulator could be used as powerful hormonal substance that has ability to increase productivity and salt tolerance of agricultural plants. Also on the basis of biostimulator we have developed vegetative method for fast reproduction of perennial plants as desert plant - Tamarix gracilis.

Keywords: Biostimulator, crop productivity, ecology, fussicoccin, salt tolerance.

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1130 Effects of Additives on Thermal Decompositions of Carbon Black/High Density Polyethylene Compounds

Authors: Orathai Pornsunthorntawee, Wareerom Polrut, Nopphawan Phonthammachai

Abstract:

In the present work, the effects of additives, including contents of the added antioxidants and type of the selected metallic stearates (either calcium stearate (CaSt) or zinc stearate (ZnSt)), on the thermal stabilities of carbon black (CB)/high density polyethylene (HDPE) compounds were studied. The results showed that the AO contents played a key role in the thermal stabilities of the CB/HDPE compounds — the higher the AO content, the higher the thermal stabilities. Although the CaSt-containing compounds were slightly superior to those with ZnSt in terms of the thermal stabilities, the remaining solid residue of CaSt after heated to the temperature of 600 °C (mainly calcium carbonate (CaCO3) as characterized by the X-ray diffraction (XRD) technique) seemed to catalyze the decomposition of CB in the HDPE-based compounds. Hence, the quantification of CB in the CaSt-containing compounds with a muffle furnace gave an inaccurate CB content — much lower than actual value. However, this phenomenon was negligible in the ZnSt-containing system.

Keywords: Antioxidant, Stearate, Carbon black, Polyethylene.

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1129 Evaluation of Anti-Varroa Bottom Boards to Control Small Hive Beetle (Aethina tumida)

Authors: M. Keshlaf, R. Spooner-Hart

Abstract:

Australia does not have varroa mite. However, we investigated the efficacy of modified hive bottom boards used for varroa mite management in honeybee colonies to control small hive beetle, Aethina tumida. We assessed infestation levels between hives fitted with tube, mesh and conventional (solid) bottom boards in Richmond, NSW eastern Australian. Colonies housed in hives with tube bottom boards were significantly superior to those in hives with conventional and mesh bottom boards. Even though in-hive beetle populations were generally low during the trial period, hives fitted with tube bottom boards however, had fewer small hive beetles than other hives. Although the trial was conducted over only one season, it suggests that there may be benefit in Australian beekeepers changing from using conventional bottom boards even with the absence of varroa mite, when small hive beetle is present.

Keywords: Aethina tumida, Apis mellifera, mesh bottom boards, tube bottom boards.

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1128 Use of Fuzzy Edge Image in Block Truncation Coding for Image Compression

Authors: Amarunnishad T.M., Govindan V.K., Abraham T. Mathew

Abstract:

An image compression method has been developed using fuzzy edge image utilizing the basic Block Truncation Coding (BTC) algorithm. The fuzzy edge image has been validated with classical edge detectors on the basis of the results of the well-known Canny edge detector prior to applying to the proposed method. The bit plane generated by the conventional BTC method is replaced with the fuzzy bit plane generated by the logical OR operation between the fuzzy edge image and the corresponding conventional BTC bit plane. The input image is encoded with the block mean and standard deviation and the fuzzy bit plane. The proposed method has been tested with test images of 8 bits/pixel and size 512×512 and found to be superior with better Peak Signal to Noise Ratio (PSNR) when compared to the conventional BTC, and adaptive bit plane selection BTC (ABTC) methods. The raggedness and jagged appearance, and the ringing artifacts at sharp edges are greatly reduced in reconstructed images by the proposed method with the fuzzy bit plane.

Keywords: Image compression, Edge detection, Ground truth image, Peak signal to noise ratio

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1127 Examining Organizational Improvisation: The Role of Strategic Reasoning and Managerial Factors

Authors: Darwina Arshad, Paul Hughes

Abstract:

Recent environmental turbulence including financial crisis, intensified competitive forces, rapid technological change and high market turbulence have dramatically changed the current business climate. The managers firms have to plan and decide what the best approaches that best fit their firms in order to pursue superior performance. This research aims to examine the influence of strategic reasoning and top level managers- individual characteristics on the effectiveness of organizational improvisation and firm performance. Given the lack of studies on these relationships in the previous literature, there is significant contribution to the body of knowledge as well as for managerial practices. 128 responses from top management of technology-based companies in Malaysia were used as a sample. Three hypotheses were examined and the findings confirm that (a) there is no relationship between intuitive reasoning and organizational improvisation but there is a link between rational reasoning and organizational improvisation, (b) top level managers- individual characteristics as a whole affect organizational improvisation; and (c) organizational improvisation positively affects firm performance. The theoretical and managerial implications were discussed in the conclusions.

Keywords: Organizational improvisation, strategic reasoning, firm performance.

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1126 The Effects of Aggregate Sizes and Fiber Volume Fraction on Bending Toughness and Direct Tension of Steel Fiber Reinforced Concrete

Authors: Hyun-Woo Cho, Jae-Heum Moon, Jang-Hwa Lee

Abstract:

In order to supplement the brittle property of concrete, fibers are added into concrete mixtures. Compared to general concrete, various characteristics such as tensile strength, bending strength, bending toughness, and resistance to crack are superior, and even when cracks occur, improvements on toughness as well as resistance to shock are excellent due to the growth of fracture energy. Increased function of steel fiber reinforced concrete can be differentiated depending on the fiber dispersion, and sand percentage can be an important influence on the fiber dispersion. Therefore, in this research, experiments were planned on sand percentage in order to apprehend the influence of sand percentage on the bending properties and direct tension of SFRC and basic experiments were conducted on bending and direct tension in order to recognize the properties of bending properties and direct tension following the size of the aggregates and sand percentage.

Keywords: Steel Fiber Reinforced Concrete, Bending Toughness, Direct tension.

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1125 Multi Switched Split Vector Quantization of Narrowband Speech Signals

Authors: M. Satya Sai Ram, P. Siddaiah, M. Madhavi Latha

Abstract:

Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization (MSSVQ), which is a hybrid of Multi, switched, split vector quantization techniques. The spectral distortion performance, computational complexity, and memory requirements of MSSVQ are compared to split vector quantization (SVQ), multi stage vector quantization(MSVQ) and switched split vector quantization (SSVQ) techniques. It has been proved from results that MSSVQ has better spectral distortion performance, lower computational complexity and lower memory requirements when compared to all the above mentioned product code vector quantization techniques. Computational complexity is measured in floating point operations (flops), and memory requirements is measured in (floats).

Keywords: Linear predictive Coding, Multi stage vectorquantization, Switched Split vector quantization, Split vectorquantization, Line Spectral Frequencies (LSF).

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1124 Potential of Henna Leaves as Dye and Its Fastness Properties on Fabric

Authors: Nkem Angela Udeani

Abstract:

Despite the wide spread use of synthetic dyes, natural dyes are still exploited and used to enhance its inherent aesthetic qualities as a major material for beautification of the body. Centuries before the discovery of synthetic dyes, natural dyes were the only source of dye open to mankind. Dyes are extracted from plant - leaves, roots and barks, insect secretions, and minerals. However, research findings have made it clear that of all, plants- leaves, roots, barks or flowers are the most explored and exploited in which henna (Lawsonia innermis L.) is one of those plants. Experiment has also shown that henna is used in body painting in conjunction with an alkaline (Ammonium Sulphate) as a fixing agent. This of course gives a clue that if colour derived from henna is properly investigated, it may not only be used for body decoration but possibly, may have affinity to fiber substrate. This paper investigates the dyeing potentials – dye ability and fastness qualities of henna dye extracts on cotton and linen fibers using mordants like ammonium sulphate and other alkalis (hydrosulphate and caustic soda, potash, common salt, potassium alum). Hot and cold water and ethanol solvent were used in the extraction of the dye to investigate the most effective method, dye ability, and fastness qualities of these extracts under room temperature. The results of the experiment show that cotton have a high rate of dye intake than other fiber. On a similar note, the colours obtained depend most on the solvent used. In conclusion, hot water extraction appears more effective. While the colours obtained from ethanol and both cold hot methods of extraction range from light to dark yellow, light green to army green and to some extent shades of brown hues.

Keywords: Dye, fabrics, henna leaves, potential.

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1123 The Importance of Raising Awareness of Collocational Knowledge in ESL/EFL Classrooms

Authors: Mohammad ALAmro

Abstract:

The most crucial aspect that is closely related to vocabulary and the one that needs to be emphasized and investigated more than it has been up until now, is the ability to combine words that co-occur frequently in the language. Pedagogically, collocation is one of the error-provoking aspects in foreign language learning. This is indicative of the dire need to provide L2 learners with tools to help them improve their collocational knowledge. This paper pinpoints the role that collocations play in the English language. Furthermore, it presents pedagogical implications for ESL/EFL learners.

Keywords: Collocation, pedagogy, vocabulary knowledge.

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1122 Performences of Type-2 Fuzzy Logic Control and Neuro-Fuzzy Control Based on DPC for Grid Connected DFIG with Fixed Switching Frequency

Authors: Fayssal Amrane, Azeddine Chaiba

Abstract:

In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.

Keywords: Doubly fed induction generetor, direct power control, space vector modulation, type-2 fuzzy logic control, neuro-fuzzy control, maximum power point tracking.

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