Sentiment Analysis: Popularity of Candidates for the President of the United States

This article deals with the popularity of candidates for the president of the United States of America. The popularity is assessed according to public comments on the Web 2.0. Social networking, blogging and online forums (collectively Web 2.0) are for common Internet users the easiest way to share their personal opinions, thoughts, and ideas with the entire world. However, the web content diversity, variety of technologies and website structure differences, all of these make the Web 2.0 a network of heterogeneous data, where things are difficult to find for common users. The introductory part of the article describes methodology for gathering and processing data from Web 2.0. The next part of the article is focused on the evaluation and content analysis of obtained information, which write about presidential candidates.

Synthesis of Analogue to Camptothecine

Camptothecin (CPT) is a cytotoxic quinoline alkaloid, which inhibits the DNA enzyme topoisomerase I (topo I). It was discovered in 1966 by M. E. Wall and M. C. Wani in systematic screening of natural products for anticancer drugs. It was isolated from the bark and stem of Camptotheca acuminata (Camptotheca, Happy tree), a tree native in China. CPT showed remarkable anticancer activity in preliminary clinical trials but also low solubility and (high) adverse drug reaction. Because of these disadvantages synthetic and medicinal chemists have developed numerous syntheses of Camptothecine [1][2][3] and various derivatives to increase the benefits of the chemical, with good results. In our method CPT analogues has be six steps starting from available material DL Malic acid.

On SNR Estimation by the Likelihood of near Pitch for Speech Detection

People have the habitual pitch level which is used when people say something generally. However this pitch should be changed irregularly in the presence of noise. So it is useful to estimate SNR of speech signal by pitch. In this paper, we obtain the energy of input speech signal and then we detect a stationary region on voiced speech. And we get the pitch period by NAMDF for the stationary region that is not varied pitch rapidly. After getting pitch, each frame is divided by pitch period and the likelihood of closed pitch is estimated. In this paper, we proposed new parameter, NLF, to estimate the SNR of received speech signal. The NLF is derived from the correlation of near pitch periods. The NLF is obtained for each stationary region in voiced speech. Finally we confirmed good performance of the estimation of the SNR of received input speech in the presence of noise.

A Study of Neuro-Fuzzy Inference System for Gross Domestic Product Growth Forecasting

In this paper we present a Adaptive Neuro-Fuzzy System (ANFIS) with inputs the lagged dependent variable for the prediction of Gross domestic Product growth rate in six countries. We compare the results with those of Autoregressive (AR) model. We conclude that the forecasting performance of neuro-fuzzy-system in the out-of-sample period is much more superior and can be a very useful alternative tool used by the national statistical services and the banking and finance industry.

A Confucianism Observed in Disaster Films of East Asia

Hollywood has produced various blockbusters on the subject of disasters. Entering the 2000s, disaster films began to be produced in the East Asian region as well, and as most of them were successful, disaster films have settled as a popular genre in the region. East Asian disaster films utilize a plot structure similar to Hollywood films but, at the same time, represent East Asian people-s unique value system. East Asian people-s social behavior pattern defined as collectivism is a characteristic that distinguishes this region from other cultural regions. In order to examine Confucian culture in disaster films on the premise of the difference, the author conducts this research as follows.This study first reviews the concepts disaster and disaster film, and understands the genre through analyzing the narrative structure and style. In addition, it discusses collectivism, a characteristic of the East Asian region distinguished from the West, and investigates Confucian culture in films and examines differences among Korean, Chinese and Japanese Confucianism. Films selected for this study are Tidal Wave (Korea, 2009), After Shock (China, 2006), and The Sinking of Japan (Japan, 2006). Using the characters in these films, we analyze how Confucian thought is described and reproduced.

A Socio-Ecological Study of Sacred Groves and Memorial Parks: Cases from USA and India

The concept of sacred and nature have long been interlinked. Various cultural aspects such as religion, faith, traditions bring people closer to nature and the natural environment. Memorial Parks and Sacred Groves are examples of two such cultural landscapes that exist today. The project mainly deals with the significance of such sites to the environment and the deep rooted significance it has to the people. These parks and groves play an important role in biodiversity conservation and environmental protection. There are many differences between the establishment of memorial parks and sacred groves, but the underlying significance is the same. Sentiments, emotions play an important role in landscape planning and management. Hence the people and communities living at these sites need to be involved in any planning activity or decisions. The conservation of the environment should appeal to the sentiments of the people; the need to be 'with nature' should be used in the setting up of memorial forests and in the preservation of sacred groves.

Automatic Microaneurysm Quantification for Diabetic Retinopathy Screening

Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.

Numerical and Experimental Study of Flow from a Leaking Buried Pipe in an Unsaturated Porous Media

Considering the numerous applications of the study of the flow due to leakage in a buried pipe in unsaturated porous media, finding a proper model to explain the influence of the effective factors is of great importance.There are various important factors involved in this type of flow such as: pipe leakage size and location, burial depth, the degree of the saturation of the surrounding porous medium, characteristics of the porous medium, fluid type and pressure of the upstream.In this study, the flow through unsaturated porous media due to leakage of a buried pipe for up and down leakage location is studied experimentally and numerically and their results are compared. Study results show that Darcy equation together with BCM method (for calculating the relative permeability) have suitable ability for predicting the flow due to leakage of buried pipes in unsaturated porous media.

A Numerical Framework to Investigate Intake Aerodynamics Behavior in Icing Conditions

One of the major parts of a jet engine is air intake, which provides proper and required amount of air for the engine to operate. There are several aerodynamic parameters which should be considered in design, such as distortion, pressure recovery, etc. In this research, the effects of lip ice accretion on pitot intake performance are investigated. For ice accretion phenomenon, two supervised multilayer neural networks (ANN) are designed, one for ice shape prediction and another one for ice roughness estimation based on experimental data. The Fourier coefficients of transformed ice shape and parameters include velocity, liquid water content (LWC), median volumetric diameter (MVD), spray time and temperature are used in neural network training. Then, the subsonic intake flow field is simulated numerically using 2D Navier-Stokes equations and Finite Volume approach with Hybrid mesh includes structured and unstructured meshes. The results are obtained in different angles of attack and the variations of intake aerodynamic parameters due to icing phenomenon are discussed. The results show noticeable effects of ice accretion phenomenon on intake behavior.

Analysis of Take-off Phase of Somersaults with Twisting along the Longitudinal Body Axis

The contribution deals with problem of take-off phase of back somersault with twisting with various numbers of twists along longitudinal body axis. The aim was to evaluate the changes in angles during transition phase from back handspring to back somersault using 3D kinematic analysis of the somersaults. We used Simi Motion System for the 3D kinematic analysis of the observed gymnastic element performed by Czech Republic female representative and 2008 Summer Olympic Games participant. The results showed that the higher the number of twists, the smaller the touchdown angle in which the gymnasts lands on the pad in the beginning of take-off phase. In back somersault with one twist (180°) the average angle is 54°, in 1080° back somersault the average angle is 45.9°. These results may help to improve technical training of sports gymnasts.

On the Central Limit Theorems for Forward and Backward Martingales

Let {Xi}i≥1 be a martingale difference sequence with Xi = Si - Si-1. Under some regularity conditions, we show that (X2 1+· · ·+X2N n)-1/2SNn is asymptotically normal, where {Ni}i≥1 is a sequence of positive integer-valued random variables tending to infinity. In a similar manner, a backward (or reverse) martingale central limit theorem with random indices is provided.

Fuzzy Processing of Uncertain Data

In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity measure with of the requirements of the selection with stored data, where both the select query and the data itself may contain vague terms, for example in the form of linguistic qualifiers. In this paper, we focus on the processing of uncertain data in databases and demonstrate it on the example multi-criteria decision making in the selection of variants, specified by higher number of technical parameters.

Real-Coded Genetic Algorithm for Robust Power System Stabilizer Design

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.

Multiple-Points Fault Signature's Dynamics Modeling for Bearing Defect Frequencies

Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.

Production of Milk Clotting Protease by Rhizopus Stolonifer through Optimization of Culture Conditions

The present study describes the biosynthesis of a milkclotting protease by solid state fermentation (SSF) of a locally isolated mould, Rhizopus stolonifer. The production medium was prepared using wheat bran at 50% (w/v). The production conditions are optimized by varying 7 parameters: carbon and nitrogen sources, medium moisture, temperature, pH, fermentation time and inoculum-s size. The maximum enzyme synthesis was measured after 96 h of incubation time at temperature of 28°C. The optimum pH determined was 6 and the inoculum size was 3.106spores/ml. The optimum initial moisture content is comprised between 50 to 70%. The formation of milk clotting protease is enhanced when galactose and peptone are used at 10% (w/v) and 1% (w/v) concentrations respectively. The maximum production of milk clotting protease is 120 US/ml.

Analysis of Genotype Size for an Evolvable Hardware System

The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.

Operational Analysis of Urban Intelligent Transportation System and Strategies for Future Development - Taking Calling Service of Taxi in Wuhan as an Example

Intelligent Transportation System integrates various modern advanced technologies into the ground transportation system, and it will be the goal of urban transport system in the future because of its comprehensive effects. However, it also brings some problems, such as project performance assessment, fairness of benefiting groups, fund management, which are directly related to its operation and implementation. Wuhan has difficulties in organizing transportation because of its nature feature (river and lake), therefore, calling Service of Taxi plays an important role in transportation. This paper researches on calling Service of Taxi in Wuhan, based on quantitative and qualitative analysis. It analyzes its operations management systematically, including business model, finance, usage analysis and users evaluation. As for business model, it is that the government leads the operation at the initial stage, and the third part dominates the operation at the mature stage, which not only eases the pressure of the third part and benefits the spread of the calling service at the initial stage, but also alleviates financial pressure of government and improve the efficiency of the operation at the mature stage. As for finance, it draws that this service will bring heavy financial burden of equipments, but it will be alleviated in the future because of its spread. As for usage analysis, through data comparison, this service can bring some benefits for taxi drivers, and time and spatial distribution of usage have certain features. As for user evaluation, it analyzes using group and the reason why choosing it. At last, according to the analysis above, the paper puts forward the potentials, limitations, and future development strategies for it.

Business Intelligence for N=1 Analytics using Hybrid Intelligent System Approach

The future of business intelligence (BI) is to integrate intelligence into operational systems that works in real-time analyzing small chunks of data based on requirements on continuous basis. This is moving away from traditional approach of doing analysis on ad-hoc basis or sporadically in passive and off-line mode analyzing huge amount data. Various AI techniques such as expert systems, case-based reasoning, neural-networks play important role in building business intelligent systems. Since BI involves various tasks and models various types of problems, hybrid intelligent techniques can be better choice. Intelligent systems accessible through web services make it easier to integrate them into existing operational systems to add intelligence in every business processes. These can be built to be invoked in modular and distributed way to work in real time. Functionality of such systems can be extended to get external inputs compatible with formats like RSS. In this paper, we describe a framework that use effective combinations of these techniques, accessible through web services and work in real-time. We have successfully developed various prototype systems and done few commercial deployments in the area of personalization and recommendation on mobile and websites.

Effects of Drought on Microbial Activity in Rhizosphere, Soil Hydrophobicity and Leaching of Mineral Nitrogen from Arable Soil Depending on Method of Fertilization

This work presents the first results from the long-term laboratory experiment dealing with impact of drought on soil properties. Three groups of the treatment (A, B and C) with different regime of irrigation were prepared. The soil water content was maintained at 70 % of soil water holding capacity in group A, at 40 % in group B. In group C, soil water regime was maintained in the range of wilting point. Each group of the experiment was divided into three variants (A1 = B1, C1; A2 = B2, C2 etc.) with three repetitions: Variants A1 (B1, C1) were a controls without addition of another fertilizer. Variants A2 (B2, C2) were fertilized with mineral nitrogen fertilizer DAM 390 (0.140 Mg of N per ha) and variants A3 (B3, C3) contained 45 g of Cp per a pot. The significant differences (ANOVA, P