Comparison of FAHP and TOPSIS for Evacuation Capability Assessment of High-rise Buildings

A lot of computer-based methods have been developed to assess the evacuation capability (EC) of high-rise buildings. Because softwares are time-consuming and not proper for on scene applications, we adopted two methods, fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to an ideal solution (TOPSIS), for EC assessment of a high-rise building in Jinan. The EC scores obtained with the two methods and the evacuation time acquired with Pathfinder 2009 for floors 47-60 of the building were compared with each other. The results show that FAHP performs better than TOPSIS for EC assessment of high-rise buildings, especially in the aspect of dealing with the effect of occupant type and distance to exit on EC, tackling complex problem with multi-level structure of criteria, and requiring less amount of computation. However, both FAHP and TOPSIS failed to appropriately handle the situation where the exit width changes while occupants are few.

In Search of New Laws for a Gluten Kingdom

The enthusiasm for gluten avoidance in a growing market is met by improvements in sensitive detection methods for analysing gluten content. Paradoxically, manufacturers employ no such systems in the production process but continue to market their product as gluten free, a significant risk posed to an undetermined coeliac population. This paper resonates with an immunological response that causes gastrointestinal scarring and villous atrophy with the conventional description of personal injury. This thesis divulges into evaluating potential inadequacies of gluten labelling laws which not only present a diagnostic challenge for general practitioners in the UK but it also exposes a less than adequate form of available legal protection to those who suffer adverse reactions as a result of gluten digestion. Central to this discussion is whether a claim brought in misrepresentation, negligence and/or under the Consumer Protection Act 1987 could be sustained. An interesting comparison is then made with the legal regimes of neighboring jurisdictions furthering the theme of a legally un-catered for gluten kingdom.

Productive Design and Calculation of Intermittent Mechanisms with Radial Parallel Cams

The paper deals with the kinematics and automated calculation of intermittent mechanisms with radial cams. Currently, electronic cams are increasingly applied in the drives of working link mechanisms. Despite a huge advantage of electronic cams in their reprogrammability or instantaneous change of displacement diagrams, conventional cam mechanisms have an irreplaceable role in production and handling machines. With high frequency of working cycle periods, the dynamic load of the proper servomotor rotor increases and efficiency of electronic cams strongly decreases. Though conventional intermittent mechanisms with radial cams are representatives of fixed automation, they have distinct advantages in their high speed (high dynamics), positional accuracy and relatively easy manufacture. We try to remove the disadvantage of firm displacement diagram by reducing costs for simple design and automated calculation that leads reliably to high-quality and inexpensive manufacture.

Simulation of Lightning Surge Propagation in Transmission Lines Using the FDTD Method

This paper describes a finite-difference time-domainFDTD) method to analyze lightning surge propagation in electric transmission lines. Numerical computation of solving the Telegraphist-s equations is determined and investigated its effectiveness. A source of lightning surge wave on power transmission lines is modeled by using Heidler-s surge model. The proposed method was tested against medium-voltage power transmission lines in comparison with the solution obtained by using lattice diagram. As a result, the calculation showed that the method is one of accurate methods to analyze transient lightning wave in power transmission lines.

Parallel Multisplitting Methods for Singular Linear Systems

In this paper, we discuss convergence of the extrapolated iterative methods for linear systems with the coefficient matrices are singular H-matrices. And we present the sufficient and necessary conditions for convergence of the extrapolated iterative methods. Moreover, we apply the results to the GMAOR methods. Finally, we give one numerical example.

A Comprehensive and Integrated Framework for Formal Specification of Concurrent Systems

Due to important issues, such as deadlock, starvation, communication, non-deterministic behavior and synchronization, concurrent systems are very complex, sensitive, and error-prone. Thus ensuring reliability and accuracy of these systems is very essential. Therefore, there has been a big interest in the formal specification of concurrent programs in recent years. Nevertheless, some features of concurrent systems, such as dynamic process creation, scheduling and starvation have not been specified formally yet. Also, some other features have been specified partially and/or have been described using a combination of several different formalisms and methods whose integration needs too much effort. In other words, a comprehensive and integrated specification that could cover all aspects of concurrent systems has not been provided yet. Thus, this paper makes two major contributions: firstly, it provides a comprehensive formal framework to specify all well-known features of concurrent systems. Secondly, it provides an integrated specification of these features by using just a single formal notation, i.e., the Z language.

Effect of Indole-3-Acetic Acid on Arsenic Translocation in Agricultural Crops

The problem of agricultural-soil pollution is closely linked to the production of ecologically pure foodstuffs and to human health. An important task, therefore, is to rehabilitate agricultural soils with the help of state-of-the-art biotechnologies, based on the use of metal-accumulating plants. In this work, on the basis of literature data and the results of prior research from this laboratory, plants were selected for which the growing technology is well developed and which are widespread locally: sugar sorghum (Sorghum saccharatum), sudangrass (Sorghum sudanense (Piper.) Stapf.), and sunflower (Helianthus annuus L.). I report on laboratory experiments designed to study the influence of synthetic indole-3- acetic acid and the extracellular indole-3-acetic acid released by the plant-growth-promoting rhizobacterium Azospirillum brasilense Sp245 on growth of and arsenic accumulation by these plants.

Feature Selection Methods for an Improved SVM Classifier

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Constructing a Simple Polygonalizations

We consider the methods of construction simple polygons for a set S of n points and applying them for searching the minimal area polygon. In this paper we propose the approximate algorithm, which generates the simple polygonalizations of a fixed set of points and finds the minimal area polygon, in O (n3) time and using O(n2) memory.

The Role of Human Resource System on Crisis Resolve

Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.

Improvement of Blood Detection Accuracy using Image Processing Techniques suitable for Capsule Endoscopy

Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.

Machine Learning Techniques for Short-Term Rain Forecasting System in the Northeastern Part of Thailand

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Effects of Drought on Yield and Some Yield Components of Chickpea

This research was conducted to determine responses of chickpeas to drought in different periods (early period, late period, no-irrigation, two times irrigation as control). The trial was made in “Randomized Complete Block Design" with three replications on 2010 and 2011 years in Konya-Turkey. Genotypes were consisted from 7 lines of ICARDA, 2 certified lines and 1 local population. The results showed that; as means of years and genotypes, early period stress showed highest (207.47 kg da-1) seed yield and it was followed by control (202.33 kg da-1), late period (144.64 kg da-1) and normal (106.93 kg da-1) stress applications. The genotypes were affected too much by drought and, the lowest seed was taken from non-irrigated plots. As the means of years and stress applications, the highest (196.01 kg da-1) yield was taken from genotype 22255. The reason of yield variation could be derived from different responses of genotypes to drought.

Verification of a Locked CFD Approach to Cool Down Modeling

Increasing demand on the performance of Subsea Production Systems (SPS) suggests a need for more detailed investigation of fluid behavior taking place in subsea equipment. Complete CFD cool down analyses of subsea equipment are very time demanding. The objective of this paper is to investigate a Locked CFD approach, which enables significant reduction of the computational time and at the same time maintains sufficient accuracy during thermal cool down simulations. The result comparison of a dead leg simulation using the Full CFD and the three LCFD-methods confirms the validity of the locked flow field assumption for the selected case. For the tested case the LCFD simulation speed up by factor of 200 results in the absolute thermal error of 0.5 °C (3% relative error), speed up by factor of 10 keeps the LCFD results within 0.1 °C (0.5 % relative error) comparing to the Full CFD.

Assessment of the Influence of External Earth Terrain at Construction of the Physicmathematical Models or Finding the Dynamics of Pollutants' Distribution in Urban Atmosphere

There is a complex situation on the transport environment in the cities of the world. For the analysis and prevention of environmental problems an accurate calculation hazardous substances concentrations at each point of the investigated area is required. In the turbulent atmosphere of the city the wellknown methods of mathematical statistics for these tasks cannot be applied with a satisfactory level of accuracy. Therefore, to solve this class of problems apparatus of mathematical physics is more appropriate. In such models, because of the difficulty as a rule the influence of uneven land surface on streams of air masses in the turbulent atmosphere of the city are not taken into account. In this paper the influence of the surface roughness, which can be quite large, is mathematically shown. The analysis of this problem under certain conditions identified the possibility of areas appearing in the atmosphere with pressure tending to infinity, i.e. so-called "wall effect".

Trispectral Analysis of Voiced Sounds Defective Audition and Tracheotomisian Cases

This paper presents the cepstral and trispectral analysis of a speech signal produced by normal men, men with defective audition (deaf, deep deaf) and others affected by tracheotomy, the trispectral analysis based on parametric methods (Autoregressive AR) using the fourth order cumulant. These analyses are used to detect and compare the pitches and the formants of corresponding voiced sounds (vowel \a\, \i\ and \u\). The first results appear promising, since- it seems after several experimentsthere is no deformation of the spectrum as one could have supposed it at the beginning, however these pathologies influenced the two characteristics: The defective audition influences to the formants contrary to the tracheotomy, which influences the fundamental frequency (pitch).

Investigation of Various PWM Techniques for Shunt Active Filter

Pulse width modulation (PWM) techniques have been the subject of intensive research for different industrial and power sector applications. A large variety of methods, different in concept and performance, have been newly developed and described. This paper analyzes the comparative merits of Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM) techniques and the suitability of these techniques in a Shunt Active Filter (SAF). The objective is to select the scheme that offers effective utilization of DC bus voltage and also harmonic reduction at the input side. The effectiveness of the PWM techniques is tested in the SAF configuration with a non linear load. The performance of the SAF with the SPWM and (SVPWM) techniques are compared with respect to the THD in source current. The study reveals that in the context of closed loop SAF control with the SVPWM technique there is only a minor improvement in THD. The utilization of the DC bus with SVPWM is also not significant compared to that with SPWM because of the non sinusoidal modulating signal from the controller in SAF configuration.

Predicting Dietary Practice Behavior among Type 2 Diabetics Using the Theory of Planned Behavior and Mixed Methods Design

This study applied the Theory of Planned Behavior model in predicting dietary behavior among Type 2 diabetics in a Kenyan environment. The study was conducted for three months within the diabetic clinic at Kisii Hospital in Nyanza Province in Kenya and adopted sequential mixed methods design combing both qualitative and quantitative phases. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The results based on the common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within dietary behavior {χ2 = 223.3, df = 77, p = .02, χ2/df = 2.9, n=237; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)}. This implies that the Theory of Planned Behavior holds and forms a framework for promoting dietary practice among Type 2 diabetics.

A Decision Boundary based Discretization Technique using Resampling

Many supervised induction algorithms require discrete data, even while real data often comes in a discrete and continuous formats. Quality discretization of continuous attributes is an important problem that has effects on speed, accuracy and understandability of the induction models. Usually, discretization and other types of statistical processes are applied to subsets of the population as the entire population is practically inaccessible. For this reason we argue that the discretization performed on a sample of the population is only an estimate of the entire population. Most of the existing discretization methods, partition the attribute range into two or several intervals using a single or a set of cut points. In this paper, we introduce a technique by using resampling (such as bootstrap) to generate a set of candidate discretization points and thus, improving the discretization quality by providing a better estimation towards the entire population. Thus, the goal of this paper is to observe whether the resampling technique can lead to better discretization points, which opens up a new paradigm to construction of soft decision trees.

Methods for Data Selection in Medical Databases: The Binary Logistic Regression -Relations with the Calculated Risks

The medical studies often require different methods for parameters selection, as a second step of processing, after the database-s designing and filling with information. One common task is the selection of fields that act as risk factors using wellknown methods, in order to find the most relevant risk factors and to establish a possible hierarchy between them. Different methods are available in this purpose, one of the most known being the binary logistic regression. We will present the mathematical principles of this method and a practical example of using it in the analysis of the influence of 10 different psychiatric diagnostics over 4 different types of offences (in a database made from 289 psychiatric patients involved in different types of offences). Finally, we will make some observations about the relation between the risk factors hierarchy established through binary logistic regression and the individual risks, as well as the results of Chi-squared test. We will show that the hierarchy built using the binary logistic regression doesn-t agree with the direct order of risk factors, even if it was naturally to assume this hypothesis as being always true.