Convection through Light Weight Timber Constructions with Mineral Wool

The major part of light weight timber constructions consists of insulation. Mineral wool is the most commonly used insulation due to its cost efficiency and easy handling. The fiber orientation and porosity of this insulation material enables flowthrough. The air flow resistance is low. If leakage occurs in the insulated bay section, the convective flow may cause energy losses and infiltration of the exterior wall with moisture and particles. In particular the infiltrated moisture may lead to thermal bridges and growth of health endangering mould and mildew. In order to prevent this problem, different numerical calculation models have been developed. All models developed so far have a potential for completion. The implementation of the flow-through properties of mineral wool insulation may help to improve the existing models. Assuming that the real pressure difference between interior and exterior surface is larger than the prescribed pressure difference in the standard test procedure for mineral wool ISO 9053 / EN 29053, measurements were performed using the measurement setup for research on convective moisture transfer “MSRCMT". These measurements show, that structural inhomogeneities of mineral wool effect the permeability only at higher pressure differences, as applied in MSRCMT. Additional microscopic investigations show, that the location of a leak within the construction has a crucial influence on the air flow-through and the infiltration rate. The results clearly indicate that the empirical values for the acoustic resistance of mineral wool should not be used for the calculation of convective transfer mechanisms.

Graphical Password Security Evaluation by Fuzzy AHP

In today's day and age, one of the important topics in information security is authentication. There are several alternatives to text-based authentication of which includes Graphical Password (GP) or Graphical User Authentication (GUA). These methods stems from the fact that humans recognized and remembers images better than alphanumerical text characters. This paper will focus on the security aspect of GP algorithms and what most researchers have been working on trying to define these security features and attributes. The goal of this study is to develop a fuzzy decision model that allows automatic selection of available GP algorithms by taking into considerations the subjective judgments of the decision makers who are more than 50 postgraduate students of computer science. The approach that is being proposed is based on the Fuzzy Analytic Hierarchy Process (FAHP) which determines the criteria weight as a linear formula.

Technical Trading Rules in Emerging Stock Markets

Literature reveals that many investors rely on technical trading rules when making investment decisions. If stock markets are efficient, one cannot achieve superior results by using these trading rules. However, if market inefficiencies are present, profitable opportunities may arise. The aim of this study is to investigate the effectiveness of technical trading rules in 34 emerging stock markets. The performance of the rules is evaluated by utilizing White-s Reality Check and the Superior Predictive Ability test of Hansen, along with an adjustment for transaction costs. These tests are able to evaluate whether the best model performs better than a buy-and-hold benchmark. Further, they provide an answer to data snooping problems, which is essential to obtain unbiased outcomes. Based on our results we conclude that technical trading rules are not able to outperform a naïve buy-and-hold benchmark on a consistent basis. However, we do find significant trading rule profits in 4 of the 34 investigated markets. We also present evidence that technical analysis is more profitable in crisis situations. Nevertheless, this result is relatively weak.

Fracture Location Characterizations of Dissimilar Friction Stir Welds

This paper reports the tensile fracture location characterizations of dissimilar friction stir welds between 5754 aluminium alloy and C11000 copper. The welds were produced using three shoulder diameter tools; namely, 15, 18 and 25 mm by varying the process parameters. The rotational speeds considered were 600, 950 and 1200 rpm while the feed rates employed were 50, 150 and 300 mm/min to represent the low, medium and high settings respectively. The tensile fracture locations were evaluated using the optical microscope to identify the fracture locations and were characterized. It was observed that 70% of the tensile samples failed in the Thermo Mechanically Affected Zone (TMAZ) of copper at the weld joints. Further evaluation of the fracture surfaces of the pulled tensile samples revealed that welds with low Ultimate Tensile Strength either have defects or intermetallics present at their joint interfaces.

Hot-Spot Blob Merging for Real-Time Image Segmentation

One of the major, difficult tasks in automated video surveillance is the segmentation of relevant objects in the scene. Current implementations often yield inconsistent results on average from frame to frame when trying to differentiate partly occluding objects. This paper presents an efficient block-based segmentation algorithm which is capable of separating partly occluding objects and detecting shadows. It has been proven to perform in real time with a maximum duration of 47.48 ms per frame (for 8x8 blocks on a 720x576 image) with a true positive rate of 89.2%. The flexible structure of the algorithm enables adaptations and improvements with little effort. Most of the parameters correspond to relative differences between quantities extracted from the image and should therefore not depend on scene and lighting conditions. Thus presenting a performance oriented segmentation algorithm which is applicable in all critical real time scenarios.

Characterization of Chemically Modified Biomass as a Coating Material for Controlled Released Urea by Contact Angle Measurement

Controlled release urea has become popular in agricultural industry as it helps to solve environmental issues and increase crop yield. Recently biomass was identified to replace the polymer used as a coating material in the conventional coated urea. In this paper spreading and contact angle of biomass droplet (lignin, cellulose and clay) on urea surface are investigated experimentally. There were two tests were conducted, sessile drop for contact angle measurement and pendant drop for contact angle measurement. A different concentration of biomass droplet was released from 30 mm above a substrate. Glass was used as a controlled substrate. Images were recorded as soon as the droplet impacted onto the urea before completely adsorb into the urea. Digitized droplets were then used to identify the droplet-s surface tension and contact angle. There is large difference observed between the low surface tension and high surface tension liquids, where the wetting and spreading diameter is higher for lower surface tension. From the contact angle results, the data showed that the biomass coating films were possible as wetting liquid (θ < 90º). Contact angle of biomass coating material gives good indication for the wettablity of a liquid on urea surface.

The Influence of using Compost Leachate on Soil Reaction

In the area where the high quality water is not available, unconventional water sources are used to irrigate. Household leachate is one of the sources which are used in dry and semi dry areas in order to water the barer trees and plants. It meets the plants needs and also has some effects on the soil, but at the same time it might cause some problems as well. This study in order to evaluate the effect of using Compost leachate on the density of soil iron in form of a statistical pattern called ''Split Plot'' by using two main treatments, one subsidiary treatment and three repetitions of the pattern in a three month period. The main N treatments include: irrigation using well water as a blank treatments and the main I treatments include: irrigation using leachate and well water concurrently. Some subsidiary treatments were DI (Drop Irrigation) and SDI (Sub Drop Irrigation). Then in the established plots, 36 biannual pine and cypress shrubs were randomly grown. Two months later the treatment begins. The results revealed that there was a significant variation between the main treatment and the instance regarding pH decline in the soil which was related to the amount of leachate injected into the soil. After some time and using leachate the pH level fell, as much as 0.46 and also increased due to the great amounts of leachate. The underneath drop irrigation ends in better results than sub drop irrigation since it keeps the soil texture fixed.

Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) Parameters for Propane, Ethylene, and Hydrogen under Supercritical Conditions

Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.

Molecular Epidemiology and Genotyping of Bovine Viral Diarrhea Virus in Xinjiang Uygur Autonomous Region of China

As part of national epidemiological survey on bovine viral diarrhea virus (BVDV), a total of 274 dejecta samples were collected from 14 cattle farms in 8 areas of Xinjiang Uygur Autonomous Region in northwestern China. Total RNA was extracted from each sample, and 5--untranslated region (UTR) of BVDV genome was amplified by using two-step reverse transcriptase-polymerase chain reaction (RT-PCR). The PCR products were subsequently sequenced to study the genetic variations of BVDV in these areas. Among the 274 samples, 33 samples were found virus-positive. According to sequence analysis of the PCR products, the 33 samples could be arranged into 16 groups. All the sequences, however, were highly conserved with BVDV Osloss strains. The virus possessed theses sequences belonged to BVDV-1b subtype by phylogenetic analysis. Based on these data, we established a typing tree for BVDV in these areas. Our results suggested that BVDV-1b was a predominant subgenotype in northwestern China and no correlation between the genetic and geographical distances could be observed above the farm level.

En-Face Optical Coherence Tomography and Fluorescence in Evaluation of Orthodontic Interfaces

Bonding has become a routine procedure in several dental specialties – from prosthodontics to conservative dentistry and even orthodontics. In many of these fields it is important to be able to investigate the bonded interfaces to assess their quality. All currently employed investigative methods are invasive, meaning that samples are destroyed in the testing procedure and cannot be used again. We have investigated the interface between human enamel and bonded ceramic brackets non-invasively, introducing a combination of new investigative methods – optical coherence tomography (OCT), fluorescence OCT and confocal microscopy (CM). Brackets were conventionally bonded on conditioned buccal surfaces of teeth. The bonding was assessed using these methods. Three dimensional reconstructions of the detected material defects were developed using manual and semi-automatic segmentation. The results clearly prove that OCT, fluorescence OCT and CM are useful in orthodontic bonding investigations.

A New Distribution Network Reconfiguration Approach using a Tree Model

Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.

Association of the p53 Codon 72 Polymorphism with Colorectal Cancer in South West of Iran

The p53 tumor suppressor gene plays two important roles in genomic stability: blocking cell proliferation after DNA damage until it has been repaired, and starting apoptosis if the damage is too critical. Codon 72 exon4 polymorphism (Arg72Pro) of the P53 gene has been implicated in cancer risk. Various studies have been done to investigate the status of p53 at codon 72 for arginine (Arg) and proline (Pro) alleles in different populations and also the association of this codon 72 polymorphism with various tumors. Our objective was to investigate the possible association between P53 Arg72Pro polymorphism and susceptibility to colorectal cancer among Isfahan and Chaharmahal Va Bakhtiari (a part of south west of Iran) population. We investigated the status of p53 at codon 72 for Arg/Arg, Arg/Pro and Pro/Pro allele polymorphisms in blood samples from 145 colorectal cancer patients and 140 controls by Nested-PCR of p53 exon 4 and digestion with BstUI restriction enzyme and the DNA fragments were then resolved by electrophoresis in 2% agarose gel. The Pro allele was 279 bp, while the Arg allele was restricted into two fragments of 160 and 119 bp. Among the 145 colorectal cancer cases 49 cases (33.79%) were homozygous for the Arg72 allele (Arg/Arg), 18 cases (12.41%) were homozygous for the Pro72 allele (Pro/Pro) and 78 cases (53.8%) found in heterozygous (Arg/Pro). In conclusion, it can be said that p53Arg/Arg genotype may be correlated with possible increased risk of this kind of cancers in south west of Iran.

Learning Classifier Systems Approach for Automated Discovery of Censored Production Rules

In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Time-Delay Estimation Using Cross-ΨB-Energy Operator

In this paper, a new time-delay estimation technique based on the cross IB-energy operator [5] is introduced. This quadratic energy detector measures how much a signal is present in another one. The location of the peak of the energy operator, corresponding to the maximum of interaction between the two signals, is the estimate of the delay. The method is a fully data-driven approach. The discrete version of the continuous-time form of the cross IBenergy operator, for its implementation, is presented. The effectiveness of the proposed method is demonstrated on real underwater acoustic signals arriving from targets and the results compared to the cross-correlation method.

Multi-View Neural Network Based Gait Recognition

Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.

A Combined Practical Approach to Condition Monitoring of Reciprocating Compressors using IAS and Dynamic Pressure

A Comparison and evaluation of the different condition monitoring (CM) techniques was applied experimentally on RC e.g. Dynamic cylinder pressure and crankshaft Instantaneous Angular Speed (IAS), for the detection and diagnosis of valve faults in a two - stage reciprocating compressor for a programme of condition monitoring which can successfully detect and diagnose a fault in machine. Leakage in the valve plate was introduced experimentally into a two-stage reciprocating compressor. The effect of the faults on compressor performance was monitored and the differences with the normal, healthy performance noted as a fault signature been used for the detection and diagnosis of faults. The paper concludes with what is considered to be a unique approach to condition monitoring. First, each of the two most useful techniques is used to produce a Truth Table which details the circumstances in which each method can be used to detect and diagnose a fault. The two Truth Tables are then combined into a single Decision Table to provide a unique and reliable method of detection and diagnosis of each of the individual faults introduced into the compressor. This gives accurate diagnosis of compressor faults.

Analyzing Methods of the Relation between Concepts based on a Concept Hierarchy

Data objects are usually organized hierarchically, and the relations between them are analyzed based on a corresponding concept hierarchy. The relation between data objects, for example how similar they are, are usually analyzed based on the conceptual distance in the hierarchy. If a node is an ancestor of another node, it is enough to analyze how close they are by calculating the distance vertically. However, if there is not such relation between two nodes, the vertical distance cannot express their relation explicitly. This paper tries to fill this gap by improving the analysis method for data objects based on hierarchy. The contributions of this paper include: (1) proposing an improved method to evaluate the vertical distance between concepts; (2) defining the concept horizontal distance and a method to calculate the horizontal distance; and (3) discussing the methods to confine a range by the horizontal distance and the vertical distance, and evaluating the relation between concepts.

Targeting the Pulmonary Delivery via Optimizing Physicochemical Characteristics of Instilled Liquid and Exploring Distribution of Produced Liquids by Bench-Top Models and Scintigraphy of Rabbits- Lungs

We aimed to investigate how can target and optimize pulmonary delivery distribution by changing physicochemical characteristics of instilled liquid.Therefore, we created a new liquids group: a. eligible for desired distribution within lung because of assorted physicochemical characteristics b. capable of being augmented with a broad range of chemicals inertly c. no interference on respiratory function d. compatible with airway surface liquid We developed forty types of new liquid,were composed of Carboxymethylcellulose sodium,Glycerin and different types of Polysorbates.Viscosity was measured using a Programmable Rheometer and surface tension by KRUSS Tensiometer.We subsequently examined the liquids and delivery protocols by simple and branched glass capillary tube models of airways.Eventually,we explored pulmonary distribution of liquids being augmented with technetium-99m in mechanically ventilated rabbits.We used a single head large field of view gamma camera.Kinematic viscosity between 0.265Stokes and 0.289Stokes,density between 1g/cm3 and 1.5g/cm3 and surface tension between 25dyn/cm and 35dyn/cm were the most acceptable.

n− Strongly Gorenstein Projective, Injective and Flat Modules

Let R be a ring and n a fixed positive integer, we investigate the properties of n-strongly Gorenstein projective, injective and flat modules. Using the homological theory , we prove that the tensor product of an n-strongly Gorenstein projective (flat) right R -module and projective (flat) left R-module is also n-strongly Gorenstein projective (flat). Let R be a coherent ring ,we prove that the character module of an n -strongly Gorenstein flat left R -module is an n-strongly Gorenstein injective right R -module . At last, let R be a commutative ring and S a multiplicatively closed set of R , we establish the relation between n -strongly Gorenstein projective (injective , flat ) R -modules and n-strongly Gorenstein projective (injective , flat ) S−1R-modules. All conclusions in this paper is helpful for the research of Gorenstein dimensions in future.

Hydrogenation of Acetic Acid on Alumina-Supported Pt-Sn Catalysts

Three alumina-supported Pt-Sn catalysts have been prepared by means of co-impregnation and characterized by XRD and N2 adsorption. The influence of catalyst composition and reaction conditions on the conversion and selectivity were investigated in the hydrogenation of acetic acid in an isothermal integral fixed bed reactor. The experiments were performed on the temperature interval 468-548 K, liquid hourly space velocity (LHSV) of 0.3-0.7h-1, pressures between 1.0 and 5.0Mpa. A good compromise of 0.75%Pt-1.5%Sn can act as an optimized acetic acid hydrogenation catalyst, and the conversion and selectivity can be tuned through the variation of reaction conditions.