Abstract: 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.
Abstract: The purpose of this paper is to present the design and
instrumentation of a new benchmark multivariable nonlinear control
laboratory. The mathematical model of this system may be used to
test the applicability and performance of various nonlinear control
procedures. The system is a two degree-of-freedom robotic arm with
soft and hard (discontinuous) nonlinear terms. Two novel
mechanisms are designed to allow the implementation of adjustable
Coulomb friction and backlash.
Abstract: Peer-to-Peer (P2P) is a self-organizing resource sharing network with no centralized authority or infrastructure, which makes it unpredictable and vulnerable. In this paper, we propose architecture to make the peer-to-peer network more centralized, predictable, and safer to use by implementing trust and stopping free riding.
Abstract: 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.
Abstract: This paper predicts the effect of the user-s hand-hold
position on the Total Isotropic Sensitivity (TIS) of GSM900/1800
mobile phone antennas of realistic in-use conditions, where different
semi-realistic mobile phone models, i.e., candy bar and clamshell, as
well as different antenna types, i.e., external and internal, are
simulated using a FDTD-based platform. A semi-realistic hand model
consisting of three tissues and the SAM head are used in simulations.
The results show a considerable impact on TIS of the adopted mobile
phone models owing to the user-s hand presence at different
positions, where a maximum level of TIS is obtained while grasping
the upper part of the mobile phone against head. Maximum TIS
levels are recorded in talk position for mobile phones with external
antenna and maximum differences in TIS levels due to the hand-hold
alteration are recorded for clamshell-type phones.
Abstract: Dehydration behavior gives a hint about thermal properties of materials. It is important for the usage areas and transportation of minerals. Magnesium borates can be used as additive materials in areas such as in the production of superconducting materials, in the composition of detergents, due to the content of boron in the friction-reducing additives in oils and insulating coating compositions due to their good mechanic and thermal properties.
In this study, thermal dehydration behavior of admontite (MgO(B2O3)3.7(H2O)), which is a kind of magnesium borate mineral, is experimented by microwave energy at 360W. Structure of admontite is suitable for the investigation of dehydration behavior by microwave because of its seven moles of crystal water. It is seen that admontite lost its 28.7% of weight at the end of the 120 minutes heating in microwave furnace.
Abstract: This paper presents a new approach in the identification of the quadrotor dynamic model using a black-box system for identification. Also the paper considers the problems which appear during the identification in the closed-loop and offers a technical solution for overcoming the correlation between the input noise present in the output
Abstract: The characterization and modeling of the dynamic
behavior of many built-up structures under vibration conditions is still
a subject of current research. The present study emphasizes the
theoretical investigation of slip damping in layered and jointed
welded cantilever structures using finite element approach.
Application of finite element method in damping analysis is relatively
recent, as such, some problems particularly slip damping analysis has
not received enough attention. To validate the finite element model
developed, experiments have been conducted on a number of mild
steel specimens under different initial conditions of vibration. Finite
element model developed affirms that the damping capacity of such
structures is influenced by a number of vital parameters such as;
pressure distribution, kinematic coefficient of friction and micro-slip
at the interfaces, amplitude, frequency of vibration, length and
thickness of the specimen. Finite element model developed can be
utilized effectively in the design of machine tools, automobiles,
aerodynamic and space structures, frames and machine members for
enhancing their damping capacity.
Abstract: The prediction of meteorological parameters at a
meteorological station is an interesting and open problem. A firstorder
linear dynamic model GM(1,1) is the main component of the
grey system theory. The grey model requires only a few previous data
points in order to make a real-time forecast. In this paper, we
consider the daily average ambient temperature as a time series and
the grey model GM(1,1) applied to local prediction (short-term
prediction) of the temperature. In the same case study we use a fuzzy
predictive model for global prediction. We conclude the paper with a
comparison between local and global prediction schemes.
Abstract: Language Reforms and potential use of ICTs has been a focal area of Higher Education Commission of Pakistan. Efforts are being accelerated to incorporate fast expanding ICTs to bring qualitative improvement in language instruction in higher education. This paper explores how university teachers are benefitting from ICTs to make their English class effective and what type of problems they face in practicing ICTs during their lectures. An in-depth qualitative study was employed to understand why language teachers tend to use ICTs in their instruction and how they are practicing it. A sample of twenty teachers from five universities located in Islamabad, three from public sector and two from private sector, was selected on non-random (Snowball) sampling basis. An interview with 15 semi-structured items was used as research instruments to collect data. The findings reveal that business English teaching is facilitated and improved through the use of ICTs. The language teachers need special training regarding the practices and implementation of ICTs. It is recommended that initiatives might be taken to equip university language teachers with modern methodology incorporating ICTs as focal area and efforts might be made to remove barriers regarding the training of language teachers and proper usage of ICTs.
Abstract: In wireless and mobile communications, this progress
provides opportunities for introducing new standards and improving
existing services. Supporting multimedia traffic with wireless networks
quality of service (QoS). In this paper, a grey-fuzzy controller for radio
resource management (GF-RRM) is presented to maximize the number
of the served calls and QoS provision in wireless networks. In a
wireless network, the call arrival rate, the call duration and the
communication overhead between the base stations and the control
center are vague and uncertain. In this paper, we develop a method to
predict the cell load and to solve the RRM problem based on the
GF-RRM, and support the present facility has been built on the
application-level of the wireless networks. The GF-RRM exhibits the
better adaptability, fault-tolerant capability and performance than other
algorithms. Through simulations, we evaluate the blocking rate, update
overhead, and channel acquisition delay time of the proposed method.
The results demonstrate our algorithm has the lower blocking rate, less
updated overhead, and shorter channel acquisition delay.
Abstract: In this paper, we consider a two-neuron system with time-delayed connections between neurons. By analyzing the associated characteristic transcendental equation, its linear stability is investigated and Hopf bifurcation is demonstrated. Some explicit formulae for determining the stability and the direction of the Hopf bifurcation periodic solutions bifurcating from Hopf bifurcations are obtained by using the normal form theory and center manifold theory. Some numerical simulation results are given to support the theoretical predictions. Finally, main conclusions are given.
Abstract: At present, dictionary attack has been the basic tool for
recovering key passwords. In order to avoid dictionary attack, users
purposely choose another character strings as passwords. According to
statistics, about 14% of users choose keys on a keyboard (Kkey, for
short) as passwords. This paper develops a framework system to attack
the password chosen from Kkeys and analyzes its efficiency. Within
this system, we build up keyboard rules using the adjacent and parallel
relationship among Kkeys and then use these Kkey rules to generate
password databases by depth-first search method. According to the
experiment results, we find the key space of databases derived from
these Kkey rules that could be far smaller than the password databases
generated within brute-force attack, thus effectively narrowing down
the scope of attack research. Taking one general Kkey rule, the
combinations in all printable characters (94 types) with Kkey adjacent
and parallel relationship, as an example, the derived key space is about
240 smaller than those in brute-force attack. In addition, we
demonstrate the method's practicality and value by successfully
cracking the access password to UNIX and PC using the password
databases created
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: This paper presents a cold flow simulation study of a small gas turbine combustor performed using laboratory scale test rig. The main objective of this investigation is to obtain physical insight of the main vortex, responsible for the efficient mixing of fuel and air. Such models are necessary for predictions and optimization of real gas turbine combustors. Air swirler can control the combustor performance by assisting in the fuel-air mixing process and by producing recirculation region which can act as flame holders and influences residence time. Thus, proper selection of a swirler is needed to enhance combustor performance and to reduce NOx emissions. Three different axial air swirlers were used based on their vane angles i.e., 30°, 45°, and 60°. Three-dimensional, viscous, turbulent, isothermal flow characteristics of the combustor model operating at room temperature were simulated via Reynolds- Averaged Navier-Stokes (RANS) code. The model geometry has been created using solid model, and the meshing has been done using GAMBIT preprocessing package. Finally, the solution and analysis were carried out in a FLUENT solver. This serves to demonstrate the capability of the code for design and analysis of real combustor. The effects of swirlers and mass flow rate were examined. Details of the complex flow structure such as vortices and recirculation zones were obtained by the simulation model. The computational model predicts a major recirculation zone in the central region immediately downstream of the fuel nozzle and a second recirculation zone in the upstream corner of the combustion chamber. It is also shown that swirler angles changes have significant effects on the combustor flowfield as well as pressure losses.
Abstract: In this treatise we will study the capability of static
compensator for reactive power to stabilize sheen voltage with motor
loading on power networks system. We also explain the structure and main function of STATCOM and the method to control it using STATCOM transformer current to simultaneously predict after
telling about the necessity of FACTS tools to compensate in power networks. Then we study topology and controlling system to stabilize
voltage during start of inductive motor. The outcome of stimulat by MATLAB software supports presented controlling idea and
system in the treatise.
Abstract: In this study, an inland metropolitan area, Gwangju, in Korea was selected to assess the amplification potential of earthquake motion and provide the information for regional seismic countermeasure. A geographic information system-based expert system was implemented for reliably predicting the spatial geotechnical layers in the entire region of interesting by building a geo-knowledge database. Particularly, the database consists of the existing boring data gathered from the prior geotechnical projects and the surface geo-knowledge data acquired from the site visit. For practical application of the geo-knowledge database to estimate the earthquake hazard potential related to site amplification effects at the study area, seismic zoning maps on geotechnical parameters, such as the bedrock depth and the site period, were created within GIS framework. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site in the study area. KeywordsEarthquake hazard, geo-knowledge, geographic information system, seismic zonation, site period.
Abstract: In recent years, new product development became more and more competitive and globalized, and the designing phase is critical for the product success. The concept of modularity can provide the necessary foundation for organizations to design products that can respond rapidly to market needs. The paper describes data structures and algorithms of intelligent Web-based system for modular design taking into account modules compatibility relationship and given design requirements. The system intelligence is realized by developed algorithms for choice of modules reflecting all system restrictions and requirements. The proposed data structure and algorithms are illustrated by case study of personal computer configuration. The applicability of the proposed approach is tested through a prototype of Web-based system.
Abstract: In any trust model, the two information sources that a peer relies on to predict trustworthiness of another peer are direct experience as well as reputation. These two vital components evolve over time. Trust evolution is an important issue, where the objective is to observe a sequence of past values of a trust parameter and determine the future estimates. Unfortunately, trust evolution algorithms received little attention and the proposed algorithms in the literature do not comply with the conditions and the nature of trust. This paper contributes to this important problem in the following ways: (a) presents an algorithm that manages and models trust evolution in a P2P environment, (b) devises new mechanisms for effectively maintaining trust values based on the conditions that influence trust evolution , and (c) introduces a new methodology for incorporating trust-nurture incentives into the trust evolution algorithm. Simulation experiments are carried out to evaluate our trust evolution algorithm.
Abstract: In this paper we will develop a sequential life test approach applied to a modified low alloy-high strength steel part used in highway overpasses in Brazil.We will consider two possible underlying sampling distributions: the Normal and theInverse Weibull models. The minimum life will be considered equal to zero. We will use the two underlying models to analyze a fatigue life test situation, comparing the results obtained from both.Since a major chemical component of this low alloy-high strength steel part has been changed, there is little information available about the possible values that the parameters of the corresponding Normal and Inverse Weibull underlying sampling distributions could have. To estimate the shape and the scale parameters of these two sampling models we will use a maximum likelihood approach for censored failure data. We will also develop a truncation mechanism for the Inverse Weibull and Normal models. We will provide rules to truncate a sequential life testing situation making one of the two possible decisions at the moment of truncation; that is, accept or reject the null hypothesis H0. An example will develop the proposed truncated sequential life testing approach for the Inverse Weibull and Normal models.