Application of l1-Norm Minimization Technique to Image Retrieval

Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.

Integrate Communication Modeling into the Design Modeling at Early Stages of the Design Flow Case Study: Unmanned Aerial Vehicle (UAV)

This paper shows how we can integrate communication modeling into the design modeling at early stages of the design flow. We consider effect of incorporating noise such as impulsive noise on system stability. We show that with change of the system model and investigate the system performance under the different communication effects. We modeled a unmanned aerial vehicle (UAV) as a demonstration using SystemC methodology. Moreover the system is modeled by joining the capabilities of UML and SystemC to operate at system level.

The Determination of Rating Points of Objects with Qualitative Characteristics and their Usagein Decision Making Problems

The paper presents the method developed to assess rating points of objects with qualitative indexes. The novelty of the method lies in the fact that the authors use linguistic scales that allow to formalize the values of the indexes with the help of fuzzy sets. As a result it is possible to operate correctly with dissimilar indexes on the unified basis and to get stable final results. The obtained rating points are used in decision making based on fuzzy expert opinions.

Three Computational Mathematics Techniques: Comparative Determination of Area under Curve

The objective of this manuscript is to find area under the plasma concentration- time curve (AUC) for multiple doses of salbutamol sulphate sustained release tablets (Ventolin® oral tablets SR 8 mg, GSK, Pakistan) in the group of 18 healthy adults by using computational mathematics techniques. Following the administration of 4 doses of Ventolin® tablets 12 hourly to 24 healthy human subjects and bioanalysis of obtained plasma samples, plasma drug concentration-time profile was constructed. AUC, an important pharmacokinetic parameter, was measured using integrated equation of multiple oral dose regimens. The approximated AUC was also calculated by using computational mathematics techniques such as repeated rectangular, repeated trapezium and repeated Simpson's rule and compared with exact value of AUC calculated by using integrated equation of multiple oral dose regimens to find best computational mathematics method that gives AUC values closest to exact. The exact values of AUC for four consecutive doses of Ventolin® oral tablets were 150.5819473, 157.8131756, 164.4178231 and 162.78 ng.h/ml while the closest values approximated AUC values were 149.245962, 157.336171, 164.2585768 and 162.289224 ng.h/ml, respectively as found by repeated rectangular rule. The errors in the approximated values of AUC were negligible. It is concluded that all computational tools approximated values of AUC accurately but the repeated rectangular rule gives slightly better approximated values of AUC as compared to repeated trapezium and repeated Simpson's rules.

Design, Modeling and Fabrication of a Tactile Sensor and Display System for Application in Laparoscopic Surgery

One of the major disadvantages of the minimally invasive surgery (MIS) is the lack of tactile feedback to the surgeon. In order to identify and avoid any damage to the grasped complex tissue by endoscopic graspers, it is important to measure the local softness of tissue during MIS. One way to display the measured softness to the surgeon is a graphical method. In this paper, a new tactile sensor has been reported. The tactile sensor consists of an array of four softness sensors, which are integrated into the jaws of a modified commercial endoscopic grasper. Each individual softness sensor consists of two piezoelectric polymer Polyvinylidene Fluoride (PVDF) films, which are positioned below a rigid and a compliant cylinder. The compliant cylinder is fabricated using a micro molding technique. The combination of output voltages from PVDF films is used to determine the softness of the grasped object. The theoretical analysis of the sensor is also presented. A method has been developed with the aim of reproducing the tactile softness to the surgeon by using a graphical method. In this approach, the proposed system, including the interfacing and the data acquisition card, receives signals from the array of softness sensors. After the signals are processed, the tactile information is displayed by means of a color coding method. It is shown that the degrees of softness of the grasped objects/tissues can be visually differentiated and displayed on a monitor.

Performance Analysis of Adaptive LMS Filter through Regression Analysis using SystemC

The LMS adaptive filter has several parameters which can affect their performance. From among these parameters, most papers handle the step size parameter for controlling the performance. In this paper, we approach three parameters: step-size, filter tap-size and filter form. The regression analysis is used for defining the relation between parameters and performance of LMS adaptive filter with using the system level simulation results. The results present that all parameters have performance trends in each own particular form, which can be estimated from equations drawn by regression analysis.

Effects of Winter and Spring Sowing on Yield Components of Safflower Genotypes

The research was conducted with three replications as “Randomized Block Design” in Konya-Turkey ecological conditions. In the study, 16 of promising safflower lines (A8, E1, F4, F6, G16, H14, I1), and 1 cultivar (Dinçer) were evaluated in 2008-09 growing season. Some of the yield components such as plant height (cm), first branch height (cm), number of branches per plant, 1000 seed weight (g), seed yield (kg ha-1), oil content (%), oil yield (kg ha-1) were determined. Winter sowing showed higher values than spring sowing. The highest values were taken from Dinçer for plant height (86.7 cm), E1 (37.5 cm) for first branch height, F6 for number of branch (11.6 per plant), I1 for number of head (24.9 per plant), A8 for 1000 seed weight (51.75 g), Dinçer for seed yield (2927.1 kg ha-1), oil content (28.79 %) and also for oil yield (87.44 kg ha-1) respectively.

Position Control of an AC Servo Motor Using VHDL and FPGA

In this paper, a new method of controlling position of AC Servomotor using Field Programmable Gate Array (FPGA). FPGA controller is used to generate direction and the number of pulses required to rotate for a given angle. Pulses are sent as a square wave, the number of pulses determines the angle of rotation and frequency of square wave determines the speed of rotation. The proposed control scheme has been realized using XILINX FPGA SPARTAN XC3S400 and tested using MUMA012PIS model Alternating Current (AC) servomotor. Experimental results show that the position of the AC Servo motor can be controlled effectively. KeywordsAlternating Current (AC), Field Programmable Gate Array (FPGA), Liquid Crystal Display (LCD).

Eye Gesture Analysis with Head Movement for Advanced Driver Assistance Systems

Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.

A New Heuristic Approach to Solving U-shape Assembly Line Balancing Problems Type-1

Assembly line balancing is a very important issue in mass production systems due to production cost. Although many studies have been done on this topic, but because assembly line balancing problems are so complex they are categorized as NP-hard problems and researchers strongly recommend using heuristic methods. This paper presents a new heuristic approach called the critical task method (CTM) for solving U-shape assembly line balancing problems. The performance of the proposed heuristic method is tested by solving a number of test problems and comparing them with 12 other heuristics available in the literature to confirm the superior performance of the proposed heuristic. Furthermore, to prove the efficiency of the proposed CTM, the objectives are increased to minimize the number of workstation (or equivalently maximize line efficiency), and minimizing the smoothness index. Finally, it is proven that the proposed heuristic is more efficient than the others to solve the U-shape assembly line balancing problem.

Adaptive Digital Watermarking Integrating Fuzzy Inference HVS Perceptual Model

An adaptive Fuzzy Inference Perceptual model has been proposed for watermarking of digital images. The model depends on the human visual characteristics of image sub-regions in the frequency multi-resolution wavelet domain. In the proposed model, a multi-variable fuzzy based architecture has been designed to produce a perceptual membership degree for both candidate embedding sub-regions and strength watermark embedding factor. Different sizes of benchmark images with different sizes of watermarks have been applied on the model. Several experimental attacks have been applied such as JPEG compression, noises and rotation, to ensure the robustness of the scheme. In addition, the model has been compared with different watermarking schemes. The proposed model showed its robustness to attacks and at the same time achieved a high level of imperceptibility.

LAYMOD; A Layered and Modular Platform for CAx Collaboration Management and Supporting Product data Integration based on STEP Standard

Nowadays companies strive to survive in a competitive global environment. To speed up product development/modifications, it is suggested to adopt a collaborative product development approach. However, despite the advantages of new IT improvements still many CAx systems work separately and locally. Collaborative design and manufacture requires a product information model that supports related CAx product data models. To solve this problem many solutions are proposed, which the most successful one is adopting the STEP standard as a product data model to develop a collaborative CAx platform. However, the improvement of the STEP-s Application Protocols (APs) over the time, huge number of STEP AP-s and cc-s, the high costs of implementation, costly process for conversion of older CAx software files to the STEP neutral file format; and lack of STEP knowledge, that usually slows down the implementation of the STEP standard in collaborative data exchange, management and integration should be considered. In this paper the requirements for a successful collaborative CAx system is discussed. The STEP standard capability for product data integration and its shortcomings as well as the dominant platforms for supporting CAx collaboration management and product data integration are reviewed. Finally a platform named LAYMOD to fulfil the requirements of CAx collaborative environment and integrating the product data is proposed. The platform is a layered platform to enable global collaboration among different CAx software packages/developers. It also adopts the STEP modular architecture and the XML data structures to enable collaboration between CAx software packages as well as overcoming the STEP standard limitations. The architecture and procedures of LAYMOD platform to manage collaboration and avoid contradicts in product data integration are introduced.

Langmuir–Blodgett Films of Polyaniline for Efficient Detection of Uric Acid

Langmuir–Blodgett (LB) films of polyaniline (PANI) grown onto ITO coated glass substrates were utilized for the fabrication of Uric acid biosensor for efficient detection of uric acid by immobilizing Uricase via EDC–NHS coupling. The modified electrodes were characterized by atomic force microscopy (AFM). The response characteristics after immobilization of uricase were studied using cyclic voltammetry and electrochemical impedance spectroscopy techniques. The uricase/PANI/ITO/glass bioelectrode studied by CV and EIS techniques revealed detection of uric acid in a wide range of 0.05 mM to 1.0 mM, covering the physiological range in blood. A low Michaelis–Menten constant (Km) of 0.21 mM indicates the higher affinity of immobilized Uricase towards its analyte (uric acid). The fabricated uric acid biosensor based on PANI LB films exhibits excellent sensitivity of 0.21 mA/mM with a response time of 4 s, good reproducibility, long shelf life (8 weeks) and high selectivity.

Sensory Evaluation of Meatballs with Jerusalem Artichoke (Helianthus tuberosus L.)

Meat and meat products for human consumption are one of main sources of protein, amino acids, fatty acids, vitamins, and minerals. Popular variety of meat product is meatballs, which can be enriched with valuable product – Jerusalem artichoke powder, made from dried and grinded Jerusalem artichoke tubers, it is raw material with low-calorie, low fat, rich in dietary fibres, minerals, and vitamins. The results of this study indicate that that people could accept the new product - meatballs with Jerusalem artichoke powder and Jerusalem artichoke powder is suitable for meatballs preparation, in result them is possible to improve meatballs sensory and physical properties.

A Comprehensive Survey on RAT Selection Algorithms for Heterogeneous Networks

Due to the coexistence of different Radio Access Technologies (RATs), Next Generation Wireless Networks (NGWN) are predicted to be heterogeneous in nature. The coexistence of different RATs requires a need for Common Radio Resource Management (CRRM) to support the provision of Quality of Service (QoS) and the efficient utilization of radio resources. RAT selection algorithms are part of the CRRM algorithms. Simply, their role is to verify if an incoming call will be suitable to fit into a heterogeneous wireless network, and to decide which of the available RATs is most suitable to fit the need of the incoming call and admit it. Guaranteeing the requirements of QoS for all accepted calls and at the same time being able to provide the most efficient utilization of the available radio resources is the goal of RAT selection algorithm. The normal call admission control algorithms are designed for homogeneous wireless networks and they do not provide a solution to fit a heterogeneous wireless network which represents the NGWN. Therefore, there is a need to develop RAT selection algorithm for heterogeneous wireless network. In this paper, we propose an approach for RAT selection which includes receiving different criteria, assessing and making decisions, then selecting the most suitable RAT for incoming calls. A comprehensive survey of different RAT selection algorithms for a heterogeneous wireless network is studied.

Artificial Visual Percepts for Image Understanding

Visual inputs are one of the key sources from which humans perceive the environment and 'understand' what is happening. Artificial systems perceive the visual inputs as digital images. The images need to be processed and analysed. Within the human brain, processing of visual inputs and subsequent development of perception is one of its major functionalities. In this paper we present part of our research project, which aims at the development of an artificial model for visual perception (or 'understanding') based on the human perceptive and cognitive systems. We propose a new model for perception from visual inputs and a way of understaning or interpreting images using the model. We demonstrate the implementation and use of the model with a real image data set.

Recovering the Clipped OFDM Figurebased on the Conic Function

In Orthogonal Frequency Division Multiplexing (OFDM) systems, the peak to average power ratio (PAR) is much high. The clipping signal scheme is a useful method to reduce PAR. Clipping the OFDM signal, however, increases the overall noise level by introducing clipping noise. It is necessary to recover the figure of the original signal at receiver in order to reduce the clipping noise. Considering the continuity of the signal and the figure of the peak, we obtain a certain conic function curve to replace the clipped signal module within the clipping time. The results of simulation show that the proposed scheme can reduce the systems? BER (bit-error rate) 10 times when signal-to-interference-and noise-ratio (SINR) equals to 12dB. And the BER performance of the proposed scheme is superior to that of kim's scheme, too.

OCR for Script Identification of Hindi (Devnagari) Numerals using Error Diffusion Halftoning Algorithm with Neural Classifier

The applications on numbers are across-the-board that there is much scope for study. The chic of writing numbers is diverse and comes in a variety of form, size and fonts. Identification of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. There are plentiful approaches that deal with problem of detection of numerals/character depending on the sort of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent our work focused on a technique in feature extraction i.e. Local-based approach, a method using 16-segment display concept, which is extracted from halftoned images & Binary images of isolated numerals. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. Experimentation result shows that recognition rate of halftoned images is 98 % compared to binary images (95%).

Role and Effect of Temperature on LPG Sweetening Process

In the gas refineries of Iran-s South Pars Gas Complex, Sulfrex demercaptanization process is used to remove volatile and corrosive mercaptans from liquefied petroleum gases by caustic solution. This process consists of two steps. Removing low molecular weight mercaptans and regeneration exhaust caustic. Some parameters such as LPG feed temperature, caustic concentration and feed-s mercaptan in extraction step and sodium mercaptide content in caustic, catalyst concentration, caustic temperature, air injection rate in regeneration step are effective factors. In this paper was focused on temperature factor that play key role in mercaptans extraction and caustic regeneration. The experimental results demonstrated by optimization of temperature, sodium mercaptide content in caustic because of good oxidation minimized and sulfur impurities in product reduced.

On Symmetry Analysis and Exact Wave Solutions of New Modified Novikov Equation

In this paper, we study a new modified Novikov equation for its classical and nonclassical symmetries and use the symmetries to reduce it to a nonlinear ordinary differential equation (ODE). With the aid of solutions of the nonlinear ODE by using the modified (G/G)-expansion method proposed recently, multiple exact traveling wave solutions are obtained and the traveling wave solutions are expressed by the hyperbolic functions, trigonometric functions and rational functions.