Identification of an Unstable Nonlinear System: Quadrotor

In the following article we begin from a multi-parameter unstable nonlinear model of a Quadrotor. We design a control to stabilize and assure the attitude of the device, starting off a linearized system at the equilibrium point of the null angles of Euler (hover), which provides us a control with limited capacities at small angles of rotation of the vehicle in three dimensions. In order to clear this obstacle, we propose the identification of models in different angles by means of simulations and the design of a controller specifically implemented for the identification task, that in future works will allow the development of controllers according to fast and agile angles of Euler for Quadrotor.

Impact Behavior of Cryogenically Treated En 52 and 21-4N Valve Steels

Cryogenic treatment is the process of cooling a material to extremely low temperatures to generate enhanced mechanical and physical properties. The purpose of this study is to examine the effect of cryogenic treatment on the impact behavior of En 52 and 21-4N valve steels. The valve steels are subjected to shallow (193 K) and deep cryogenic treatment (85 K), and the impact behavior is compared with the valve steel materials subjected to conventional heat treatment. The impact test is carried out in accordance with the ASTM E 23-02a standard. The results show an improvement of 23 % in the impact energy for the En 52 deep cryo-treated samples when compared to that of the conventionally heat treated samples. It is revealed that during cryogenic treatment fine platelets of martensite are formed from the retained austenite, and these platelets promote the precipitation of fine carbides by a diffusion mechanism during tempering.

Physical Parameter Based Compact Expression for Propagation Constant of SWCNT Interconnects

Novel compact expressions for propagation constant (γ) of SWCNT and bundled SWCNTs interconnect, in terms of physical parameters such as length, operating frequency and diameter of CNTs is proposed in this work. These simplified expressions enable physical insight and accurate estimation of signal attenuation level and its phase change at any length for a particular frequency. The proposed expressions are validated against SPICE simulated results of lumped as well as distributed equivalent electrical RLC nets of CNT interconnect. These expressions also help us to evaluate the cut off frequencies of SWCNTs for different interconnect lengths.

Evolutionary Algorithm Based Centralized Congestion Management for Multilateral Transactions

This work presents an approach for AC load flow based centralized model for congestion management in the forward markets. In this model, transaction maximizes its profit under the limits of transmission line capacities allocated by Independent System Operator (ISO). The voltage and reactive power impact of the system are also incorporated in this model. Genetic algorithm is used to solve centralized congestion management problem for multilateral transactions. Results obtained for centralized model using genetic algorithm is compared with Sequential Quadratic Programming (SQP) technique. The statistical performances of various algorithms such as best, worst, mean and standard deviations of social welfare are given. Simulation results clearly demonstrate the better performance of genetic algorithm over SQP.

Vibration Characteristics of Functionally Graded Material Skew Plate in Thermal Environment

In the present investigation, free vibration of functionally graded material (FGM) skew plates under thermal environment is studied. Kinematics equations are based on the Reddy’s higher order shear deformation theory and a nine noded isoparametric Lagrangian element is adopted to mesh the plate geometry. The issue of C1 continuity requirement related to the assumed displacement field has been circumvented effectively to develop C0 finite element formulation. Effective mechanical properties of the constituents of the plate are considered to be as position and temperature dependent and assumed to vary in the thickness direction according to a simple power law distribution. The displacement components of a rectangular plate are mapped into skew plate geometry by means of suitable transformation rule. One dimensional Fourier heat conduction equation is used to ascertain the temperature profile of the plate along thickness direction. Influence of different parameters such as volume fraction index, boundary condition, aspect ratio, thickness ratio and temperature field on frequency parameter of the FGM skew plate is demonstrated by performing various examples and the related findings are discussed briefly. New results are generated for vibration of the FGM skew plate under thermal environment, for the first time, which may be implemented in the future research involving similar kind of problems.

Web–Based Tools and Databases for Micro-RNA Analysis: A Review

MicroRNAs (miRNAs), a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into a flawed stem-loop structure. Mature micro RNAs are involved in many cellular processes that encompass development, proliferation, stress response, apoptosis, and fat metabolism by gene regulation. Resent finding reveals that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicate that cellular microRNA can target the genetic material of invading viruses. Cellular microRNA can be used in the virus life cycle; either to up regulate or down regulate viral gene expression Computational tools use in miRNA target prediction has been changing drastically in recent years. Many of the methods have been made available on the web and can be used by experimental researcher and scientist without expert knowledge of bioinformatics. With the development and ease of use of genomic technologies and computational tools in the field of microRNA biology has superior tremendously over the previous decade. This review attempts to give an overview over the genome wide approaches that have allow for the discovery of new miRNAs and development of new miRNA target prediction tools and databases.

Ahiska Turks in Philadelphia: Keeping Cultural Identity and Religion in a Multicultural Environment

Ahiska Turks in the Philadelphia area maintain a very complex, cultural heritage which they have carried with them for centuries from Georgia to Uzbekistan then Russia and lastly to the USA. While facing very severe conditions in the last half of the last century, their passion for their language, religion and tradition allowed them to keep their cultural identity. In the paper, the Ahiska Turks’ sorrowful story is reviewed and their struggle with keeping their identity in a multicultural environment of the USA is examined in the context of the Philadelphia area.

An Anonymity-Based Secure On-Demand Routing for Mobile Ad Hoc Networks

Privacy and Security have emerged as an important research issue in Mobile Ad Hoc Networks (MANET) due to its unique nature such as scarce of resources and absence of centralized authority. There are number of protocols have been proposed to provide privacy and security for data communication in an adverse environment, but those protocols are compromised in many ways by the attackers. The concept of anonymity (in terms of unlinkability and unobservability) and pseudonymity has been introduced in this paper to ensure privacy and security. In this paper, a Secure Onion Throat (SOT) protocol is proposed to provide complete anonymity in an adverse environment. The SOT protocol is designed based on the combination of group signature and onion routing with ID-based encryption for route discovery. The security analysis demonstrates the performance of SOT protocol against all categories of attacks. The simulation results ensure the necessity and importance of the proposed SOT protocol in achieving such anonymity.

Public Attachment to Religious Places: A Study of Place Attachment to Mosques in Malaysia

Religious place attachment is an affective bond that develops between people and their religious settings. The published literature shows that although religion has a significant impact on the public ‘place attachment’, the architectural features and attributes of the places could still play an influencing role in strengthening this attachment. However, the role of architectural characteristics and features of the religious places, as the components that give them meaning(s), has not been adequately explored. This paper reports the impacts of factors influencing the physical and ambience quality of different styles of Malaysian mosques from the Muslim public perspective. Thereby, a survey was conducted to investigate Malaysian public attachment to selected five Malaysian state mosques with respect to their architectural characteristics and features. The survey employed the results of series of interviews as its theoretical basis. The finding proved that Malaysian ‘Muslim’ society has equally strong attachment to all selected mosques in spite of their different architectural styles. The findings also confirmed that the emotional attachment to the impressive aspects of architectural features (e.g. dome, minaret etc.) and the unique identity of the studied mosques is irrespective of the architectural styles, e.g. Modern vs. Postmodern. The paper also argued that religious activities and pleasant architectural characteristic of the studied places including the functional facilities are equally important factors in forming place attachment. This is a new approach to the study of physical and ambience quality of mosques, hence providing sufficient theoretical basis for further investigations and improvements.

A Model for Test Case Selection in the Software-Development Life Cycle

Software maintenance is one of the essential processes of Software-Development Life Cycle. The main philosophies of retaining software concern the improvement of errors, the revision of codes, the inhibition of future errors, and the development in piece and capacity. While the adjustment has been employing, the software structure has to be retested to an upsurge a level of assurance that it will be prepared due to the requirements. According to this state, the test cases must be considered for challenging the revised modules and the whole software. A concept of resolving this problem is ongoing by regression test selection such as the retest-all selections, random/ad-hoc selection and the safe regression test selection. Particularly, the traditional techniques concern a mapping between the test cases in a test suite and the lines of code it executes. However, there are not only the lines of code as one of the requirements that can affect the size of test suite but including the number of functions and faulty versions. Therefore, a model for test case selection is developed to cover those three requirements by the integral technique which can produce the smaller size of the test cases when compared with the traditional regression selection techniques.

Statistical Analysis and Predictive Learning of Mechanical Parameters for TiO2 Filled GFRP Composite

The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L9 orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.

Prediction of Research Topics Using Ensemble of Best Predictors from Similar Dataset

Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar validation dataset. The dataset used in the experiment is time series derived from research report in Garuda, which is an online sites belongs to the Ministry of Education in Indonesia, over the past 20 years. The experimental result demonstrates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, we can forecast emerging research topics for the next few years.

Statistical Analysis for Overdispersed Medical Count Data

Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling overdispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling overdispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling overdispered medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling overdispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling overdispersed medical count data when ZIP and ZINB are inadequate.

Review of Various Designs and Development in Hydropower Turbines

The growth of population, rising fossil fuel prices (limited and decreasing day by day), pollution problem due to use of fossil fuels and increasing electrical demand are important factors that encourage the use of green and renewable energy technologies. Among the different renewable energy technologies, hydro power generation (large and small scale) is the prime choice in terms of contribution to the world's electricity generation by using water current turbines. Currently, researchers mainly focused on design and development of different kind of turbines to capture hydropower to generate electricity as clean and reliable energy. This paper is a review of the status of research on water current turbines carried out to generate electricity from hydrokinetic energy especially in places where there is no electricity, but there is access to flowing water.

Big Data Strategy for Telco: Network Transformation

Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Modelling Sudden Deaths from Myocardial Infarction and Stroke

Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, myocardial infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a myocardial infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a generalized linear model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.

The Impact of System Cascading Collapse and Transmission Line Outages to the Transfer Capability Assessment

Uncertainty of system operating conditions is one of the causative reasons which may render to the instability of a transmission system. For that reason, accurate assessment of transmission reliability margin (TRM) is essential to ensure effective power transfer between areas during the occurrence of system uncertainties. The power transfer is also called as the available transfer capability (ATC) which is the information required by the utilities and marketers to instigate selling and buying the electric energy. This paper proposes a computationally effective approach to estimate TRM and ATC by considering the uncertainties of system cascading collapse and transmission line outages. In accordance to the results that have been obtained, the proposed method is essential for the transmission providers which could help the power marketers and planning sectors in the operation and reserving transmission services based on the ATC calculated.

Evaluation of Transfer Capability Considering Uncertainties of System Operating Condition and System Cascading Collapse

Over the past few decades, power system industry in many developing and developed countries has gone through a restructuring process of the industry where they are moving towards deregulated power industry. This situation will lead to competition among the generation and distribution companies to provide quality and efficient production of electric energy, which will reduce the price of electricity. Therefore it is important to obtain an accurate value of the available transfer capability (ATC) and transmission reliability margin (TRM) in order to ensure the effective power transfer between areas during the occurrence of uncertainties in the system. In this paper, the TRM and ATC is determined by taking into consideration the uncertainties of the system operating condition and system cascading collapse by applying the bootstrap technique. A case study of the IEEE RTS-79 is employed to verify the robustness of the technique proposed in the determination of TRM and ATC.

A Structural Equation Model of Knowledge Management Based On Organizational Climate in Universities

The purpose of the present study was to provide a structural model of knowledge management in universities based on organizational climate. The population of the research included all employees of Islamic Azad University (IAU). The sample consisted of 1590 employees selected using stratified and cluster random sampling method. The research instruments were two questionnaires which were administered in 78 IAU branches and education centers: Sallis and Jones’s (2002) Knowledge Management Questionnaire (α= 0.97); and Latwin & Stringer’s (1968) Organizational Climate Questionnaire (α= 0.83). The results of path analysis using LISREL software indicated that dimensions of organizational climate had a direct effect on knowledge management with the indices of 0.94. The model also showed that the factor of support in organizational climate had the highest direct effect on the knowledge management.

Enhanced Thermal, Mechanical and Morphological Properties of CNT/HDPE Nanocomposite Using MMT as Secondary Filler

This study explains the influence of secondary filler on the dispersion of carbon nanotube (CNT) reinforced high density polyethylene (HDPE) nanocomposites (CNT/HDPE). In order to understand the mixed-fillers system, Montmorillonite (MMT) was added to CNT/HDPE nanocomposites. It was followed by investigating their effect on the thermal, mechanical and morphological properties of the aforesaid nanocomposite. Incorporation of 3 wt% each of MMT into CNT/HDPE nanocomposite resulted to the increased values for the tensile and flexural strength, as compared to the pure HDPE matrix. The thermal analysis result showed improved thermal stability of the formulated nanocomposites. Transmission electron microscopy (TEM) images revealed that larger aggregates of CNTs were disappeared upon addition of these two components leading to the enhancement of thermo-mechanical properties for such composites.