Vibration Analysis of the Gas Turbine Considering Dependency of Stiffness and Damping on Frequency

In this paper the complete rotor system including elastic shaft with distributed mass, allowing for the effects of oil film in bearings. Also, flexibility of foundation is modeled. As a whole this article is a relatively complete research in modeling and vibration analysis of rotor considering gyroscopic effect, damping, dependency of stiffness and damping coefficients on frequency and solving the vibration equations including these parameters. On the basis of finite element method and utilizing four element types including element of shaft, disk, bearing and foundation and using MATLAB, a computer program is written. So the responses in several cases and considering different effects are obtained. Then the results are compared with each other, with exact solutions and results of other papers.

Effects of Annealing Treatment on Optical Properties of Anatase TiO2 Thin Films

In this investigation, anatase TiO2 thin films were grown by radio frequency magnetron sputtering on glass substrates at a high sputtering pressure and room temperature. The anatase films were then annealed at 300-600 °C in air for a period of 1 hour. To examine the structure and morphology of the films, X-ray diffraction (XRD) and atomic force microscopy (AFM) methods were used respectively. From X-ray diffraction patterns of the TiO2 films, it was found that the as-deposited film showed some differences compared with the annealed films and the intensities of the peaks of the crystalline phase increased with the increase of annealing temperature. From AFM images, the distinct variations in the morphology of the thin films were also observed. The optical constants were characterized using the transmission spectra of the films obtained by UV-VIS-IR spectrophotometer. Besides, optical thickness of the film deposited at room temperature was calculated and cross-checked by taking a cross-sectional image through SEM. The optical band gaps were evaluated through Tauc model. It was observed that TiO2 films produced at room temperatures exhibited high visible transmittance and transmittance decreased slightly with the increase of annealing temperatures. The films were found to be crystalline having anatase phase. The refractive index of the films was found from 2.31-2.35 in the visible range. The extinction coefficient was nearly zero in the visible range and was found to increase with annealing temperature. The allowed indirect optical band gap of the films was estimated to be in the range from 3.39 to 3.42 eV which showed a small variation. The allowed direct band gap was found to increase from 3.67 to 3.72 eV. The porosity was also found to decrease at a higher annealing temperature making the film compact and dense.

EML-Estimation of Multivariate t Copulas with Heuristic Optimization

In recent years, copulas have become very popular in financial research and actuarial science as they are more flexible in modelling the co-movements and relationships of risk factors as compared to the conventional linear correlation coefficient by Pearson. However, a precise estimation of the copula parameters is vital in order to correctly capture the (possibly nonlinear) dependence structure and joint tail events. In this study, we employ two optimization heuristics, namely Differential Evolution and Threshold Accepting to tackle the parameter estimation of multivariate t distribution models in the EML approach. Since the evolutionary optimizer does not rely on gradient search, the EML approach can be applied to estimation of more complicated copula models such as high-dimensional copulas. Our experimental study shows that the proposed method provides more robust and more accurate estimates as compared to the IFM approach.

Effect of Different Fertilization Methods on Soil Biological Indexes

Fertilization plays an important role in crop growth and soil improvement. This study was conducted to determine the best fertilization system for wheat production. Experiments were arranged in a complete block design with three replications in two years. Main plots consisted of six methods of fertilization including (N1): farmyard manure; (N2): compost; (N3): chemical fertilizers; (N4): farmyard manure + compost; (N5): farmyard manure + compost + chemical fertilizers and (N6): control were arranged in sub plots. The addition of compost or farm yard manure significantly increased the soil microbial biomass carbon in comparison to the chemical fertilizer. The dehydrogenase, phosphatase and urease activities in the N3 treatment were significantly lower than in the farm yard manure and compost treatments.

The Investigation of Motor Cooling Performance

This study experimentally and numerically investigates motor cooling performance. The motor consists of a centrifugal fan, two axial fans, a shaft, a stator, a rotor and a heat exchanger with 637 cooling tubes. The pressure rise-flow rate (P-Q) performance curves of the cooling fans at 1800 rpm are tested using a test apparatus complying with the Chinese National Standard (CNS) 2726. Compared with the experimental measurements, the numerical analysis results show that the P-Q performance curves of the axial fan and centrifugal fan can be estimated within about 2% and 6%, respectively. By using the simplified model, setting up the heat exchanger and stator as porous media, the flow field in the motor is calculated. By using the results of the flow field near the rotor and stator, and subjecting the heat generation rate as a boundary condition, the temperature distributions of the stator and rotor are also calculated. The simulation results show that the calculated temperature of the stator winding near the axial fans is lower by about 5% than the measured value, and the calculated temperature of the stator core located at the center of the stator is about 1% higher than the measured value. Besides, discussion is made to improve the motor cooling performance.

A Comparative Study of Page Ranking Algorithms for Information Retrieval

This paper gives an introduction to Web mining, then describes Web Structure mining in detail, and explores the data structure used by the Web. This paper also explores different Page Rank algorithms and compare those algorithms used for Information Retrieval. In Web Mining, the basics of Web mining and the Web mining categories are explained. Different Page Rank based algorithms like PageRank (PR), WPR (Weighted PageRank), HITS (Hyperlink-Induced Topic Search), DistanceRank and DirichletRank algorithms are discussed and compared. PageRanks are calculated for PageRank and Weighted PageRank algorithms for a given hyperlink structure. Simulation Program is developed for PageRank algorithm because PageRank is the only ranking algorithm implemented in the search engine (Google). The outputs are shown in a table and chart format.

A New Measurable Definition of Knowledge in New Growth Theory

New Growth Theory helps us make sense of the ongoing shift from a resource-based economy to a knowledge-based economy. It underscores the point that the economic processes which create and diffuse new knowledge are critical to shaping the growth of nations, communities and individual firms. In all too many contributions to New (Endogenous) Growth Theory – though not in all – central reference is made to 'a stock of knowledge', a 'stock of ideas', etc., this variable featuring centre-stage in the analysis. Yet it is immediately apparent that this is far from being a crystal clear concept. The difficulty and uncertainty of being able to capture the value associated with knowledge is a real problem. The intent of this paper is introducing new thinking and theorizing about the knowledge and its measurability in new growth theory. Moreover the study aims to synthesize various strain of the literature with a practical bearing on knowledge concept. By contribution of institution framework which is found within NGT, we can indirectly measure the knowledge concept. Institutions matter because they shape the environment for production and employment of new knowledge

“The Social Destination“: How Social Media Influences the Organisational Structure and Leadership of DMOs

The paper deals with the most important changes that have occurred in business because of social media and its impact on organisations and leadership in recent years. It seeks to synthesize existing research, theories and concepts, in order to understand "social destinations", and to provide a bridge from past research to future success. Becoming a "social destination" is a strategic and tactical leadership and management issue and the paper will present the importance of destination leadership in choosing the way towards a social destination and some organisational models. It also presents some social media tools that can be used in transforming a destination into a social one. Adapting organisations to the twentyfirst century means adopting social media as a way of life and a way of business.

AudioMine: Medical Data Mining in Heterogeneous Audiology Records

We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, category and textual data. The tools developed are designed to observe associations between any field in the records and any other field. The techniques employed were the statistical chi-squared test, and the use of self-organizing maps, an unsupervised neural learning approach.

Earth Grid Safety Consideration: Civil Upgrade Works for an Energised Substation

The demand on High voltage (HV) infrastructures is growing due to the corresponding growth in industries and population. Many areas are being developed and therefore require additional electrical power to comply with the demand. Substation upgrade is one of the rapid solutions to ensure the continuous supply of power to customers. This upgrade requires civil modifications to structures and fences. The civil work requires excavation and steel works that may create unsafe touch conditions. This paper presents a brief theoretical overview of the touch voltage inside and around substations and uses CDEGS software to simulate a case study.

A Parameter-Tuning Framework for Metaheuristics Based on Design of Experiments and Artificial Neural Networks

In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

Prediction of Dissolved Oxygen in Rivers Using a Wang-Mendel Method – Case Study of Au Sable River

Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.

Sterility Examination and Comparative Analyses of Inhibitory Effect of Honey on Some Gram Negative and Gram Positive Food Borne Pathogens in South West Nigeria

Food borne illnesses have been reported to be a global health challenge. Annual incidences of food–related diseases involve 76 million cases, of which only 14 million can be traced to known pathogens. Poor hygienic practices have contributed greatly to this. It has been reported that in the year 2000 about 2.1 million people died from diarrheal diseases, hence, there is a need to ensure food safety at all level. This study focused on the sterility examination and inhibitory effect of honey samples on selected gram negative and gram positive food borne pathogen from South West Nigeria. The laboratory examinations revealed the presence of some bacterial and fungal contaminations of honey samples and that inhibitory activity of the honey sample was more pronounced on the gram negative bacteria than the gram positive bacterial isolates. Antibiotic sensitivity test conducted on the different bacterial isolates also showed that honey was able to inhibit the proliferation of the tested bacteria than the employed antibiotics.

The Optimization of an Intelligent Traffic Congestion Level Classification from Motorists- Judgments on Vehicle's Moving Patterns

We proposed a technique to identify road traffic congestion levels from velocity of mobile sensors with high accuracy and consistent with motorists- judgments. The data collection utilized a GPS device, a webcam, and an opinion survey. Human perceptions were used to rate the traffic congestion levels into three levels: light, heavy, and jam. Then the ratings and velocity were fed into a decision tree learning model (J48). We successfully extracted vehicle movement patterns to feed into the learning model using a sliding windows technique. The parameters capturing the vehicle moving patterns and the windows size were heuristically optimized. The model achieved accuracy as high as 99.68%. By implementing the model on the existing traffic report systems, the reports will cover comprehensive areas. The proposed method can be applied to any parts of the world.

Automated Thickness Measurement of Retinal Blood Vessels for Implementation of Clinical Decision Support Systems in Diagnostic Diabetic Retinopathy

The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

The Model of Blended Learning and Its Use at Foreign Language Teaching

In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroom) with a teacher and additionally at home at a convenient time; student himself sets the optimal speed and intensity of the learning process; this method helps student to discipline himself and learn to work independently.

A DEA Model for Performance Evaluation in The Presence of Time Lag Effect

Data Envelopment Analysis (DEA) is a methodology that computes efficiency values for decision making units (DMU) in a given period by comparing the outputs with the inputs. In many cases, there are some time lag between the consumption of inputs and the production of outputs. For a long-term research project, it is hard to avoid the production lead time phenomenon. This time lag effect should be considered in evaluating the performance of organizations. This paper suggests a model to calculate efficiency values for the performance evaluation problem with time lag. In the experimental part, the proposed methods are compared with the CCR and an existing time lag model using the data set of the 21st century frontier R&D program which is a long-term national R&D program of Korea.

The Interaction between Accounting Students- Preference, Teaching Methodology and Performance

This paper examined the influence of matching students- learning preferences with the teaching methodology adopted, on their academic performance in an accounting course in two types of learning environment in one university in Lebanon: classes with PowerPoint (PPT) vs. conventional classes. Learning preferences were either for PPT or for Conventional methodology. A statistically significant increase in academic achievement is found in the conventionally instructed group as compared to the group taught with PPT. This low effectiveness of PPT might be attributed to the learning preferences of Lebanese students. In the PPT group, better academic performance was found among students with learning/teaching match as compared with students with learning/teaching mismatch. Since the majority of students display a preference for the conventional methodology, the result might suggest that Lebanese students- performance is not optimized by PPT in the accounting classrooms, not because of PPT itself, but because it is not matching the Lebanese students- learning preferences in such a quantitative course.

Improvement of Short Channel Effects in Cylindrical Strained Silicon Nanowire Transistor

In this paper we investigate the electrical characteristics of a new structure of gate all around strained silicon nanowire field effect transistors (FETs) with dual dielectrics by changing the radius (RSiGe) of silicon-germanium (SiGe) wire and gate dielectric. Indeed the effect of high-κ dielectric on Field Induced Barrier Lowering (FIBL) has been studied. Due to the higher electron mobility in tensile strained silicon, the n-type FETs with strained silicon channel have better drain current compare with the pure Si one. In this structure gate dielectric divided in two parts, we have used high-κ dielectric near the source and low-κ dielectric near the drain to reduce the short channel effects. By this structure short channel effects such as FIBL will be reduced indeed by increasing the RSiGe, ID-VD characteristics will be improved. The leakage current and transfer characteristics, the threshold-voltage (Vt), the drain induced barrier height lowering (DIBL), are estimated with respect to, gate bias (VG), RSiGe and different gate dielectrics. For short channel effects, such as DIBL, gate all around strained silicon nanowire FET have similar characteristics with the pure Si one while dual dielectrics can improve short channel effects in this structure.

A Text Mining Technique Using Association Rules Extraction

This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TFIDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.