Fingerprint Identification Keyless Entry System

Nowadays, keyless entry systems are widely adopted for vehicle immobilizer systems due to both advantages of security and convenience. Keyless entry systems could overcome brute-force key guessing attack, statistics attack and masquerade attack, however, they can't prevent from thieves stealing behavior. In this paper, we proposed a new architecture try to improve the existent flaws. The integration of the keyless entry system and the fingerprint identification technology is more suitable to implement on the portable transponder to achieve higher security needs. We also adopt and modify AES security protocol for life expectancy and security of the portable transponder. In addition, the identification of a driver's fingerprint makes the service of automatic reinstatement of a driver's preferences become possible. Our design can satisfy not only the three kinds of previous illegal attacks, but also the stealing situation. Furthermore, many practical factors, such as costs, life expectancy and performance, have been well considered in the design of portable transponder.

On The Comparison of Fuzzy Logic and State Space Averaging based Sliding Control Methods Applied onan Arc Welding Machine

In this study, the performance of a high-frequency arc welding machine including a two-switch inverter is analyzed. The control of the system is achieved using two different control techniques i- fuzzy logic control (FLC) ii- state space averaging based sliding control. Fuzzy logic control does not need accurate mathematical model of a plant and can be used in nonlinear applications. The second method needs the mathematical model of the system. In this method the state space equations of the system are derived for two different “on" and “off" states of the switches. The derived state equations are combined with the sliding control rule considering the duty-cycle of the converter. The performance of the system is analyzed by simulating the system using SIMULINK tool box of MATLAB. The simulation results show that fuzzy logic controller is more robust and less sensitive to parameter variations.

Application of Extruded Maize Flour in Gluten-free Bread Formulations

Celiac disease is an immune-mediated disease, triggered in genetically susceptible individuals by ingested gluten from wheat, rye, barley and other closely related cereal grains. The only effective treatment is a strict gluten free diet for life. Latvian producers do not offer gluten-free products. In this research, use of extruded maize flour was tested for substituting rice, maize or buckwheat flour in gluten-free bread formulations at different ratios. Also the influence of extruded maize flour on the quality parameters of gluten-free bread was investigated. The aim of research was to study the influence of extruded maize flour on gluten-free bread quality. Addition of extruded maize flour affect gluten-free bread crumb color, structure of crumb, weight loss and dry off of bread.

Study of Water Relations, Chlorophyll and their Correlations with Grain Yield in Wheat(Triticum aestivum L.) Genotypes

The objective of this experiment was to study of water relations and chlorophyll in different wheat genotypes and their correlations with grain and biological yields. 21 genotypes of bread wheat were compared in a field experiment as randomized complete blocks design with four replications. The results showed that relative water deficit, relative water loss, excised leaf water retention, cell membrane stability, chlorophyll-a, chlorophyll-b, total chlorophyll, grain yield and biological yield were different significantly among wheat genotypes, but SPAD-chlorophyll index, relative water content and chlorophyll florescence were not. Significant correlations were not observed among above mentioned water relations and chlorophyll characteristics with grain yield, but there was a positive and significant correlation between biological yield and grain yield.

Description of Kinetics of Propane Fragmentation with a Support of Ab Initio Simulation

Using ab initio theoretical calculations, we present analysis of fragmentation process. The analysis is performed in two steps. The first step is calculation of fragmentation energies by ab initio calculations. The second step is application of the energies to kinetic description of process. The energies of fragments are presented in this paper. The kinetics of fragmentation process can be described by numerical models. The method for kinetic analysis is described in this paper. The result - composition of fragmentation products - will be calculated in future. The results from model can be compared to the concentrations of fragments from mass spectrum.

Lean Thinking Process in the Determination of Design Suggestions to Optimize Treatment of WEEE

This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results- evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented.

Measuring Risk Levels and Efficacy of Risk Management Strategies in Vietnamese Catfish Farming

Although the Vietnamese catfish farming has grown at very high rates in recent years, the industry has also faced many problems affecting its sustainability. This paper studies the perceptions of catfish farmers regarding risk and risk management strategies in their production activities. Specifically, the study aims to measure the consequences, likelihoods, and levels of risks as well as the efficacy of risk management in Vietnamese catfish farming. Data for the study were collected through a sample of 261 catfish farmers in the Mekong Delta, Vietnam using a questionnaire survey in 2008. Results show that, in general, price and production risks were perceived as the most important risks. Farm management and technical measures were perceived more effective than other kinds of risk management strategies in risk reduction. Although price risks were rated as important risks, price risk management strategies were not perceived as important measures for risk mitigation. The results of the study are discussed to provide implications for various industry stakeholders, including policy makers, processors, advisors, and developers of new risk management strategies.

Investigations on Some Operations of Soft Sets

Soft set theory was initiated by Molodtsov in 1999. In the past years, this theory had been applied to many branches of mathematics, information science and computer science. In 2003, Maji et al. introduced some operations of soft sets and gave some operational rules. Recently, some of these operational rules are pointed out to be not true. Furthermore, Ali et al., in their paper, introduced and discussed some new operations of soft sets. In this paper, we further investigate these operational rules given by Maji et al. and Ali et al.. We obtain some sufficient-necessary conditions such that corresponding operational rules hold and give correct forms for some operational rules. These results will be help for us to use rightly operational rules of soft sets in research and application of soft set theory.

An Experimental Study of a Self-Supervised Classifier Ensemble

Learning using labeled and unlabelled data has received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of features. Classifiers are initially trained using some labeled samples. The trained classifiers learn further through labeling the unknown patterns using a teaching signals that is generated using the decision of the classifier ensemble, i.e. the classifiers self-supervise each other. Experiments on a set of object images are presented. Our experiments investigate different classifier models, different fusing techniques, different training sizes and different input features. Experimental results reveal that the proposed self-supervised ensemble learning approach reduces classification error over the single classifier and the traditional ensemble classifier approachs.

Polyisoprene-coated Silica/Natural Rubber Composite

The commercial white tyres are usually used for forklifts in food and medicine industries. Conventionally, silica is used as reinforcement in the tyres. However, the adhesion between silica particles and rubber is remarkably poor. To improve the problem of adhesion and hence enhance wear resistance, modification of silica surface is one of the solutions. In this work, the natural rubber compound blending with polyisoprene-coated silica prepared by admicellar polymerization technique was studied to compare with the natural rubber compound of unmodified silica. The surface characterization of modified silica was also examined by SEM, FTIR, and TGA. The results show that polyisoprene-coated silica/natural rubber compound gave better overall mechanical properties, especially wear resistance with the improvement of the adhesion between silica and natural rubber matrix that can be seen in the SEM micrograph.

Improving Water Productivity of Chickpea by the Use of Deficit Irrigation with Treated Domestic Wastewater

An experiment was performed in the south of Morocco in order to evaluate the effect of deficit irrigation by treated wastewater on chickpea production. We applied six irrigation treatments on a local variety of chickpea by supplying alternatively 50 or 100% of ETm in a completely randomized design. We found a highly significant difference between treatments in terms of biomass production. Drought stress during the vegetative period showed highest yield with 6.5 t/ha which was more than the yield obtained for the control (4.9 t/ha). The optimal crop stage in which deficit irrigation can be applied is the vegetative growth stage, as the crop has a chance to develop its root system, to be able to cover the plant needs for water and nutrient supply during the rest of cycle, and non stress conditions during the flowering and seed filling stages allow the plant to optimize its photosynthesis and carbon translocation, therefore increase its productivity.

Web-Based Architecture of a System for Design Assessment of Night Vision Devices

Nowadays the devices of night vision are widely used both for military and civil applications. The variety of night vision applications require a variety of the night vision devices designs. A web-based architecture of a software system for design assessment before producing of night vision devices is developed. The proposed architecture of the web-based system is based on the application of a mathematical model for designing of night vision devices. An algorithm with two components – for iterative design and for intelligent design is developed and integrated into system architecture. The iterative component suggests compatible modules combinations to choose from. The intelligent component provides compatible combinations of modules  satisfying given user requirements to device parameters. The proposed web-based architecture of a system for design assessment of night vision devices is tested via a prototype of the system. The testing showed the applicability of both iterative and intelligent components of algorithm. 

Dynamics in Tangible Chemical Reactions

Spatial understanding and the understanding of dynamic change in the spatial structure of molecules during a reaction is essential for designing new molecules. Knowing the physical processes in the reactions helps to speed up the designing process. To support the designer with the correct representation of the designed molecule as well as showing the dynamic behavior of the whole reacting system is the goal of our application. Our system shows the spatial deformation of the molecules at every time interval by minimizing the energy level of the molecules. The position and orientation of the molecules can be intuitively controlled by manipulating objects of the real world using Augmented Reality techniques. Our approach has the potential to speed up the design of new molecules and help students to understand the chemical processes better.

Ohmic Quality Factor and Efficiency Estimation for a Gyrotron Cavity

Operating a device at high power and high frequency is a major problem because wall losses greatly reduce the efficiency of the device. In the present communication, authors analytically analyzed the dependence of ohmic/RF efficiency, the fraction of output power with respect to the total power generated, of gyrotron cavity structure on the conductivity of copper for the second harmonic TE0,6 mode. This study shows a rapid fall in the RF efficiency as the quality (conductivity) of copper degrades. Starting with an RF efficiency near 40% at the conductivity of ideal copper (5.8 x 107 S/m), the RF efficiency decreases (upto 8%) as the copper quality degrades. Assuming conductivity half that of ideal copper the RF efficiency as a function of diffractive quality factor, Qdiff, has been studied. Here the RF efficiency decreases rapidly with increasing diffractive Q. Ohmic wall losses as a function of frequency for 460 GHz gyrotron cavity excited in TE0,6 mode has also been analyzed. For 460 GHz cavity, the extracted power is reduced to 32% of the generated power due to ohmic losses in the walls of the cavity.

Material Handling Equipment Selection using Hybrid Monte Carlo Simulation and Analytic Hierarchy Process

The many feasible alternatives and conflicting objectives make equipment selection in materials handling a complicated task. This paper presents utilizing Monte Carlo (MC) simulation combined with the Analytic Hierarchy Process (AHP) to evaluate and select the most appropriate Material Handling Equipment (MHE). The proposed hybrid model was built on the base of material handling equation to identify main and sub criteria critical to MHE selection. The criteria illustrate the properties of the material to be moved, characteristics of the move, and the means by which the materials will be moved. The use of MC simulation beside the AHP is very powerful where it allows the decision maker to represent his/her possible preference judgments as random variables. This will reduce the uncertainty of single point judgment at conventional AHP, and provide more confidence in the decision problem results. A small business pharmaceutical company is used as an example to illustrate the development and application of the proposed model.

LumaCert: Conception and Creation of New Digital Certificate for Online User Authentication in e-Banking Systems

Electronic banking must be secure and easy to use and many banks heavily advertise an apparent of 100% secure system which is contestable in many points. In this work, an alternative approach to the design of e-banking system, through a new solution for user authentication and security with digital certificate called LumaCert is introduced. The certificate applies new algorithm for asymmetric encryption by utilizing two mathematical operators called Pentors and UltraPentors. The public and private key in this algorithm represent a quadruple of parameters which are directly dependent from the above mentioned operators. The strength of the algorithm resides in the inability to find the respective Pentor and UltraPentor operator from the mentioned parameters.

Automated Optic Disc Detection in Retinal Images of Patients with Diabetic Retinopathy and Risk of Macular Edema

In this paper, a new automated methodology to detect the optic disc (OD) automatically in retinal images from patients with risk of being affected by Diabetic Retinopathy (DR) and Macular Edema (ME) is presented. The detection procedure comprises two independent methodologies. On one hand, a location methodology obtains a pixel that belongs to the OD using image contrast analysis and structure filtering techniques and, on the other hand, a boundary segmentation methodology estimates a circular approximation of the OD boundary by applying mathematical morphology, edge detection techniques and the Circular Hough Transform. The methodologies were tested on a set of 1200 images composed of 229 retinographies from patients affected by DR with risk of ME, 431 with DR and no risk of ME and 540 images of healthy retinas. The location methodology obtained 98.83% success rate, whereas the OD boundary segmentation methodology obtained good circular OD boundary approximation in 94.58% of cases. The average computational time measured over the total set was 1.67 seconds for OD location and 5.78 seconds for OD boundary segmentation.

Analysis and Design Business Directory for Micro, Small and Medium Enterprises using Google Maps API and Multimedia

This paper explain about analysis and design a business directory for micro-scale businesses, small and medium enterprises (SMEs). Business Directory, if implemented will facilitate and optimize the access of SMEs to ease suppliers access to marketing. Business Directory will be equipped with the power of geocoding, so each location can be easily viewed SMEs on the map. The map will be constructed by using the functionality of a webbased Google Maps API. The information presented in the form of multimedia that can be more interesting and interactive. The method used to achieve the goal are: observation; interviews; modeling and classifying business directory for SMEs.

Dynamics and Control of a Chaotic Electromagnetic System

In this paper, different nonlinear dynamics analysis techniques are employed to unveil the rich nonlinear phenomena of the electromagnetic system. In particular, bifurcation diagrams, time responses, phase portraits, Poincare maps, power spectrum analysis, and the construction of basins of attraction are all powerful and effective tools for nonlinear dynamics problems. We also employ the method of Lyapunov exponents to show the occurrence of chaotic motion and to verify those numerical simulation results. Finally, two cases of a chaotic electromagnetic system being effectively controlled by a reference signal or being synchronized to another nonlinear electromagnetic system are presented.

Recent Advances on Computational Proteomics

In this work we report the recent progresses that have been achieved by our group in the last half decade on the field of computational proteomics. Specifically, we discuss the application of Molecular Dynamics Simulations and Electronic Structure Calculations in drug design, in the clarification of the structural and dynamic properties of proteins and enzymes and in the understanding of the catalytic and inhibition mechanism of cancer-related enzymes. A set of examples illustrate the concepts and help to introduce the reader into this important and fast moving field.