Mixed Convection Boundary Layer Flow from a Vertical Cone in a Porous Medium Filled with a Nanofluid

The steady mixed convection boundary layer flow from a vertical cone in a porous medium filled with a nanofluid is numerically investigated using different types of nanoparticles as Cu (copper), Al2O3 (alumina) and TiO2 (titania). The boundary value problem is solved by using the shooting technique by reducing it into an ordinary differential equation. Results of interest for the local Nusselt number with various values of the constant mixed convection parameter and nanoparticle volume fraction parameter are evaluated. It is found that dual solutions exist for a certain range of mixed convection parameter.

Secondary Effects on Water Vapor Transport Properties Measured by Cup Method

The cup method is applied for the measurement of water vapor transport properties of porous materials worldwide. However, in practical applications the experimental results are often used without taking into account some secondary effects which can play an important role under specific conditions. In this paper, the effect of temperature on water vapor transport properties of cellular concrete is studied, together with the influence of sample thickness. At first, the bulk density, matrix density, total open porosity and sorption and desorption isotherms are measured for material characterization purposes. Then, the steady state cup method is used for determination of water vapor transport properties, whereas the measurements are performed at several temperatures and for three different sample thicknesses.

Increase of Peroxidase Activity of Haptoglobin (2-2)-Hemoglobin at Pathologic Temperature and Presence of Antibiotics

Free Hemoglobin promotes the accumulation of hydroxyl radicals by the heme iron, which can react with endogenous hydrogen peroxide to produce free radicals which may cause severe oxidative cell damage. Haptoglobin binds to Hemoglobin strongly and Haptoglobin-Hemoglobin binding is irreversible. Peroxidase activity of Haptoglobin(2-2)-Hemoglobin complex was assayed by following increase of absorption of produced tetraguaiacol as the second substrate of Haptoglobin-Hemoglobin complex at 470 nm and 42°C by UV-Vis spectrophotometer. The results have shown that peroxidase activity of Haptoglobin(2-2)-Hemoglobin complex is modulated via homotropic effect of hydrogen peroxide as allostric substrate. On the other hand antioxidant property of Haptoglobin(2- 2)-Hemoglobin was increased via heterotropic effect of the two drugs (especially ampicillin) on peroxidase activity of the complex. Both drugs also have mild effect on quality of homotropic property of peroxidase activity of Haptoglobin(2-2)-Hemoglobin complex. Therefore, in vitro studies show that the two drugs may help Hp-Hb complex to remove hydrogen peroxide from serum at pathologic temperature ature (42 C).

Modeling Peer-to-Peer Networks with Interest-Based Clusters

In the world of Peer-to-Peer (P2P) networking different protocols have been developed to make the resource sharing or information retrieval more efficient. The SemPeer protocol is a new layer on Gnutella that transforms the connections of the nodes based on semantic information to make information retrieval more efficient. However, this transformation causes high clustering in the network that decreases the number of nodes reached, therefore the probability of finding a document is also decreased. In this paper we describe a mathematical model for the Gnutella and SemPeer protocols that captures clustering-related issues, followed by a proposition to modify the SemPeer protocol to achieve moderate clustering. This modification is a sort of link management for the individual nodes that allows the SemPeer protocol to be more efficient, because the probability of a successful query in the P2P network is reasonably increased. For the validation of the models, we evaluated a series of simulations that supported our results.

A Metric-Set and Model Suggestion for Better Software Project Cost Estimation

Software project effort estimation is frequently seen as complex and expensive for individual software engineers. Software production is in a crisis. It suffers from excessive costs. Software production is often out of control. It has been suggested that software production is out of control because we do not measure. You cannot control what you cannot measure. During last decade, a number of researches on cost estimation have been conducted. The metric-set selection has a vital role in software cost estimation studies; its importance has been ignored especially in neural network based studies. In this study we have explored the reasons of those disappointing results and implemented different neural network models using augmented new metrics. The results obtained are compared with previous studies using traditional metrics. To be able to make comparisons, two types of data have been used. The first part of the data is taken from the Constructive Cost Model (COCOMO'81) which is commonly used in previous studies and the second part is collected according to new metrics in a leading international company in Turkey. The accuracy of the selected metrics and the data samples are verified using statistical techniques. The model presented here is based on Multi-Layer Perceptron (MLP). Another difficulty associated with the cost estimation studies is the fact that the data collection requires time and care. To make a more thorough use of the samples collected, k-fold, cross validation method is also implemented. It is concluded that, as long as an accurate and quantifiable set of metrics are defined and measured correctly, neural networks can be applied in software cost estimation studies with success

Real-Time Testing of Steel Strip Welds based on Bayesian Decision Theory

One of the main trouble in a steel strip manufacturing line is the breakage of whatever weld carried out between steel coils, that are used to produce the continuous strip to be processed. A weld breakage results in a several hours stop of the manufacturing line. In this process the damages caused by the breakage must be repaired. After the reparation and in order to go on with the production it will be necessary a restarting process of the line. For minimizing this problem, a human operator must inspect visually and manually each weld in order to avoid its breakage during the manufacturing process. The work presented in this paper is based on the Bayesian decision theory and it presents an approach to detect, on real-time, steel strip defective welds. This approach is based on quantifying the tradeoffs between various classification decisions using probability and the costs that accompany such decisions.

An Approach for Blind Source Separation using the Sliding DFT and Time Domain Independent Component Analysis

''Cocktail party problem'' is well known as one of the human auditory abilities. We can recognize the specific sound that we want to listen by this ability even if a lot of undesirable sounds or noises are mixed. Blind source separation (BSS) based on independent component analysis (ICA) is one of the methods by which we can separate only a special signal from their mixed signals with simple hypothesis. In this paper, we propose an online approach for blind source separation using the sliding DFT and the time domain independent component analysis. The proposed method can reduce calculation complexity in comparison with conventional methods, and can be applied to parallel processing by using digital signal processors (DSPs) and so on. We evaluate this method and show its availability.

Understanding E-Learning Satisfaction in the Context of University Teachers

The present study was designed to test the influence of confirmed expectations, perceived usefulness and perceived competence on e-learning satisfaction among university teachers. A questionnaire was completed by 125 university teachers from 12 different universities in Norway. We found that 51% of the variance in university teachers- satisfaction with e-learning could be explained by the three proposed antecedents. Perceived usefulness seems to be the most important predictor of teachers- satisfaction with e-learning.

Simulating the Dynamics of Distribution of Hazardous Substances Emitted by Motor Engines in a Residential Quarter

This article is dedicated to development of mathematical models for determining the dynamics of concentration of hazardous substances in urban turbulent atmosphere. Development of the mathematical models implied taking into account the time-space variability of the fields of meteorological items and such turbulent atmosphere data as vortex nature, nonlinear nature, dissipativity and diffusivity. Knowing the turbulent airflow velocity is not assumed when developing the model. However, a simplified model implies that the turbulent and molecular diffusion ratio is a piecewise constant function that changes depending on vertical distance from the earth surface. Thereby an important assumption of vertical stratification of urban air due to atmospheric accumulation of hazardous substances emitted by motor vehicles is introduced into the mathematical model. The suggested simplified non-linear mathematical model of determining the sought exhaust concentration at a priori unknown turbulent flow velocity through non-degenerate transformation is reduced to the model which is subsequently solved analytically.

Laser Excited Nuclear γ -Source of High Spectral Brightness

This paper considers various channels of gammaquantum generation via an ultra-short high-power laser pulse interaction with different targets.We analyse the possibilities to create a pulsed gamma-radiation source using laser triggering of some nuclear reactions and isomer targets. It is shown that sub-MeV monochromatic short pulse of gamma-radiation can be obtained with pulse energy of sub-mJ level from isomer target irradiated by intense laser pulse. For nuclear reaction channel in light- atom materials, it is shown that sub-PW laser pulse gives rise to formation about million gamma-photons of multi-MeV energy.

A Review on Soft Computing Technique in Intrusion Detection System

Intrusion Detection System is significant in network security. It detects and identifies intrusion behavior or intrusion attempts in a computer system by monitoring and analyzing the network packets in real time. In the recent year, intelligent algorithms applied in the intrusion detection system (IDS) have been an increasing concern with the rapid growth of the network security. IDS data deals with a huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. Since the amount of audit data that an IDS needs to examine is very large even for a small network, classification by hand is impossible. Hence, the primary objective of this review is to review the techniques prior to classification process suit to IDS data.

Performance Evaluation of a Limited Round-Robin System

Performance of a limited Round-Robin (RR) rule is studied in order to clarify the characteristics of a realistic sharing model of a processor. Under the limited RR rule, the processor allocates to each request a fixed amount of time, called a quantum, in a fixed order. The sum of the requests being allocated these quanta is kept below a fixed value. Arriving requests that cannot be allocated quanta because of such a restriction are queued or rejected. Practical performance measures, such as the relationship between the mean sojourn time, the mean number of requests, or the loss probability and the quantum size are evaluated via simulation. In the evaluation, the requested service time of an arriving request is converted into a quantum number. One of these quanta is included in an RR cycle, which means a series of quanta allocated to each request in a fixed order. The service time of the arriving request can be evaluated using the number of RR cycles required to complete the service, the number of requests receiving service, and the quantum size. Then an increase or decrease in the number of quanta that are necessary before service is completed is reevaluated at the arrival or departure of other requests. Tracking these events and calculations enables us to analyze the performance of our limited RR rule. In particular, we obtain the most suitable quantum size, which minimizes the mean sojourn time, for the case in which the switching time for each quantum is considered.

A Study of Touching Characters in Degraded Gurmukhi Text

Character segmentation is an important preprocessing step for text recognition. In degraded documents, existence of touching characters decreases recognition rate drastically, for any optical character recognition (OCR) system. In this paper a study of touching Gurmukhi characters is carried out and these characters have been divided into various categories after a careful analysis.Structural properties of the Gurmukhi characters are used for defining the categories. New algorithms have been proposed to segment the touching characters in middle zone. These algorithms have shown a reasonable improvement in segmenting the touching characters in degraded Gurmukhi script. The algorithms proposed in this paper are applicable only to machine printed text.

Automated Stereophotogrammetry Data Cleansing

The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.

Effect of Dietary Linseed Oil Soap on Lamb Meat

Theexperiment was carried out with 2x5 male Merino lambs raised under intensive conditions to investigate the effect of dietary calcium soap of linseed oil on the color and fatty acid composition of longissimusdorsi muscle. Control lambs fed a basal diet and the experimental lambs consumed a diet supplemented with 3% calcium soap of linseed oil. The color values (L*, a*, b* a*/b* and chroma) were not influenced by dietary treatment. The MUFA proportion reduced, SFA and PUFA content did not alter. As expected, the linolenic (C18:3 n3) and thusthe n-3 content significantly improved by linseed supplement (0.47 and 0.81; 0.78 and 1.16 in control and in experimental samples, respectively). Other n-3 and n-6 fatty acids had similar valuestocontrol samples. The n- 6/n-3 ratio was significantly narrower in the experimental group (6.31 vs. 9.38) but the P/S ratio did not differ betweenthe two groups.In conclusion calcium soap of linseed oil seems to be a suitable supplement form of n-3 fatty acids to improve the nutritive value of lamb meat.

Application of a Modified BCR Approach to Investigate the Mobility and Availability of Trace Elements (As, Ba, Cd, Co, Cr, Cu, Mo,Ni, Pb, Zn, and Hg) from a Solid Residue Matrix Designed for Soil Amendment

Trace element speciation of an integrated soil amendment matrix was studied with a modified BCR sequential extraction procedure. The analysis included pseudo-total concentration determinations according to USEPA 3051A and relevant physicochemical properties by standardized methods. Based on the results, the soil amendment matrix possessed neutralization capacity comparable to commercial fertilizers. Additionally, the pseudo-total concentrations of all trace elements included in the Finnish regulation for agricultural fertilizers were lower than the respective statutory limit values. According to chemical speciation, the lability of trace elements increased in the following order: Hg < Cr < Co < Cu < As < Zn < Ni < Pb < Cd < V < Mo < Ba. The validity of the BCR approach as a tool for chemical speciation was confirmed by the additional acid digestion phase. Recovery of trace elements during the procedure assured the validity of the approach and indicated good quality of the analytical work.

Application-Specific Instruction Sets Processor with Implicit Registers to Improve Register Bandwidth

Application-Specific Instruction (ASI ) set Processors (ASIP) have become an important design choice for embedded systems due to runtime flexibility, which cannot be provided by custom ASIC solutions. One major bottleneck in maximizing ASIP performance is the limitation on the data bandwidth between the General Purpose Register File (GPRF) and ASIs. This paper presents the Implicit Registers (IRs) to provide the desirable data bandwidth. An ASI Input/Output model is proposed to formulate the overheads of the additional data transfer between the GPRF and IRs, therefore, an IRs allocation algorithm is used to achieve the better performance by minimizing the number of extra data transfer instructions. The experiment results show an up to 3.33x speedup compared to the results without using IRs.

Comments on He et al.’s Robust Biometric-based User Authentication Scheme for WSNs

In order to guarantee secure communication for wireless sensor networks (WSNs), many user authentication schemes have successfully drawn researchers- attention and been studied widely. In 2012, He et al. proposed a robust biometric-based user authentication scheme for WSNs. However, this paper demonstrates that He et al.-s scheme has some drawbacks: poor reparability problem, user impersonation attack, and sensor node impersonate attack.

Evaluation of Antiglycation Effects of Extracts Obtained from Canarium album Raeusch Fruit and Beneficial Activity on Advanced Glycation Endproduct-Mediated Oxidative Stress and Inflammation in Monocytes and Vascular Endothelial Cells

Hyperglycemia-mediated accumulation of advanced glycation end-products (AGEs) play a pivotal role in the development of diabetic complications by inducing inflammation. In the present study, we evaluated the possible effects of water/ethanol (1/1, v/v) extracts (WEE) and its fractions from Canarium album Raeusch. (Chinese olive) which is a fruit used on AGEs-stimulated oxidative stress and inflammation in monocytes and vascular endothelial cells. Co-incubation of EA.hy926 endothelial cells with WEE and its fractions for 24h resulted in a significant decrease of monocyte–endothelial cell adhesion, the expression of ICAM-1, generation of intracellular ROS and depletion of GSH induced by AGEs. Chinese olive fruit extracts also reduced the expression of pro-inflammatory mediates, such as TNF-α, IL-1β and IL-6 in THP-1 cells. These findings suggested that Chinese olive fruit was able to protect vascular endothelium from dysfunction induced by AGEs. 

Endogenous Fantasy – Based Serious Games: Intrinsic Motivation and Learning

Current technological advances pale in comparison to the changes in social behaviors and 'sense of place' that is being empowered since the Internet made it on the scene. Today-s students view the Internet as both a source of entertainment and an educational tool. The development of virtual environments is a conceptual framework that needs to be addressed by educators and it is important that they become familiar with who these virtual learners are and how they are motivated to learn. Massively multiplayer online role playing games (MMORPGs), if well designed, could become the vehicle of choice to deliver learning content. We suggest that these games, in order to accomplish these goals, must begin with well-established instructional design principles that are co-aligned with established principles of video game design. And have the opportunity to provide an instructional model of significant prescriptive power. The authors believe that game designers need to take advantage of the natural motivation player-learners have for playing games by developing them in such a way so as to promote, intrinsic motivation, content learning, transfer of knowledge, and naturalization.