Robust Fuzzy Control of Nonlinear Fuzzy Impulsive Singular Perturbed Systems with Time-varying Delay

The problem of robust fuzzy control for a class of nonlinear fuzzy impulsive singular perturbed systems with time-varying delay is investigated by employing Lyapunov functions. The nonlinear delay system is built based on the well-known T–S fuzzy model. The so-called parallel distributed compensation idea is employed to design the state feedback controller. Sufficient conditions for global exponential stability of the closed-loop system are derived in terms of linear matrix inequalities (LMIs), which can be easily solved by LMI technique. Some simulations illustrate the effectiveness of the proposed method.

Aligning IS Development with Users- Work Habits

As a primitive assumption, if a new information system is able to remind users their old work habits, it should have a better opportunity to be accepted, adopted and finally, utilized. In this paper some theoretical concepts borrowed from psychodynamic theory e.g. ego defenses are discussed to show how such resemblance can be made without necessarily affecting the performance of the new system. The main assertion is a new system should somehow imitate old work habits, not literally, but through following their paces in terms of the order of habitual tensional states including stimulation, defensive actions and satisfactions.

Genome-Wide Analysis of BES1/BZR1 Gene Family in Five Plant Species

Brassinosteroids (BRs) regulate cell elongation, vascular differentiation, senescence, and stress responses. BRs signal through the BES1/BZR1 family of transcription factors, which regulate hundreds of target genes involved in this pathway. In this research a comprehensive genome-wide analysis was carried out in BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus, Vitis vinifera, Glycin max and Brachypodium distachyon. Specifications of the desired sequences, dot plot and hydropathy plot were analyzed in the protein and genome sequences of five plant species. The maximum amino acid length was attributed to protein sequence Brdic3g with 374aa and the minimum amino acid length was attributed to protein sequence Gm7g with 163aa. The maximum Instability index was attributed to protein sequence AT1G19350 equal with 79.99 and the minimum Instability index was attributed to protein sequence Gm5g equal with 33.22. Aliphatic index of these protein sequences ranged from 47.82 to 78.79 in Arabidopsis thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in Cucumis sativus. Overall, data obtained from our investigation contributes a better understanding of the complexity of the BES1/BZR1 gene family and provides the first step towards directing future experimental designs to perform systematic analysis of the functions of the BES1/BZR1 gene family.

Automatic Segmentation of Lung Areas in Magnetic Resonance Images

Segmenting the lungs in medical images is a challenging and important task for many applications. In particular, automatic segmentation of lung cavities from multiple magnetic resonance (MR) images is very useful for oncological applications such as radiotherapy treatment planning. However, distinguishing of the lung areas is not trivial due to largely changing lung shapes, low contrast and poorly defined boundaries. In this paper, we address lung segmentation problem from pulmonary magnetic resonance images and propose an automated method based on a robust regionaided geometric snake with a modified diffused region force into the standard geometric model definition. The extra region force gives the snake a global complementary view of the lung boundary information within the image which along with the local gradient flow, helps detect fuzzy boundaries. The proposed method has been successful in segmenting the lungs in every slice of 30 magnetic resonance images with 80 consecutive slices in each image. We present results by comparing our automatic method to manually segmented lung cavities provided by an expert radiologist and with those of previous works, showing encouraging results and high robustness of our approach.

Investigation on Feature Extraction and Classification of Medical Images

In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Computing Entropy for Ortholog Detection

Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.

A Competitive Replica Placement Methodology for Ad Hoc Networks

In this paper, a mathematical model for data object replication in ad hoc networks is formulated. The derived model is general, flexible and adaptable to cater for various applications in ad hoc networks. We propose a game theoretical technique in which players (mobile hosts) continuously compete in a non-cooperative environment to improve data accessibility by replicating data objects. The technique incorporates the access frequency from mobile hosts to each data object, the status of the network connectivity, and communication costs. The proposed technique is extensively evaluated against four well-known ad hoc network replica allocation methods. The experimental results reveal that the proposed approach outperforms the four techniques in both the execution time and solution quality

Crystalline Graphene Nanoribbons with Atomically Smooth Edges via a Novel Physico- Chemical Route

A novel physico-chemical route to produce few layer graphene nanoribbons with atomically smooth edges is reported, via acid treatment (H2SO4:HNO3) followed by characteristic thermal shock processes involving extremely cold substances. Samples were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy. This method demonstrates the importance of having the nanotubes open ended for an efficient uniform unzipping along the nanotube axis. The average dimensions of these nanoribbons are approximately ca. 210 nm wide and consist of few layers, as observed by transmission electron microscopy. The produced nanoribbons exhibit different chiralities, as observed by high resolution transmission electron microscopy. This method is able to provide graphene nanoribbons with atomically smooth edges which could be used in various applications including sensors, gas adsorption materials, composite fillers, among others.

A New High Speed Neural Model for Fast Character Recognition Using Cross Correlation and Matrix Decomposition

Neural processors have shown good results for detecting a certain character in a given input matrix. In this paper, a new idead to speed up the operation of neural processors for character detection is presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single faster neural processor. Furthermore, faster character detection is obtained by using parallel processing techniques to test the resulting sub-images at the same time using the same number of faster neural networks. In contrast to using only faster neural processors, the speed up ratio is increased with the size of the input image when using faster neural processors and image decomposition. Moreover, the problem of local subimage normalization in the frequency domain is solved. The effect of image normalization on the speed up ratio of character detection is discussed. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.

Environmental Impact Assessment of Gotv and Hydro-Electric Dam on the Karoon River Using ICOLD Technique

Today Environmental Impact Assessment (EIA) is known as one of the most important tools for decision makers in the construction of civil and industrial projects towards sustainable development. In the past, projects were evaluated based on cost and benefit analysis regardless of the physical and biological environmental effects and its socio-economical impacts. According to the Department of Environment (DOE) of Iran's regulations, the construction of hydroelectric dams is an activity that requires an EIA report. In this paper the environmental impact assessment of the Gotvand hydro-electrical dam has been evaluated in the three environment elements, biological, Physical-chemical and cultural units. This dam is one of the largest dams in Iran with a volume of 4500 MCM and is going to be the last dam on the Karoon River in the south of Iran. In this paper the ICOLD (International Commission on Large Dams) technique was employed for the environmental impact assessment of the dam. The research includes all socio economical and environmental effects of the dam during the construction and operation of the hydro electric dam and Environmental management, monitoring and mitigation of negative impacts were analyzed. In this project the results led to using some techniques to protect the destructive impacts on biological aspects beside the effective long time period impacts on the biological aspects. The impacts on physical aspects are temporary and negative commonly that could be restored and rehabilitated in natural process in the long time in operation period.

Preservation of Natural and Historical Values in Sustainable Architecture of Creative Tourism Complex of Aab-Ask, Iran

Studying literature theme in the fields of tourism and sustainable development and its importance in today world and their criteria in architecture, here in this article we will also study the area where the selected site is located; beside the Aab-Ask Village located in Larijan region in Mazandaran province on the way to Haraz – one of the tourism routes of Iran. After these studies by analyzing the site, its strong potentials – such as mineral water springs (hot springs), geothermal, landscapes and ideal climate - as a tourist attraction spot in the region, and considering sustainable development criteria – with regard to limits and available facilities – a plan was offered that could change the region to provide the needs of local people and in addition change it to a place where tourism services is offered to the visitors and make it an acceptable sample of stable building in Iran. Finally the reason to make design for this complex is recovery of natural and historical values of Aab-Ask area regarding development and sustainable architecture criteria in the form of a functional sample which can be a suitable place to fulfill this goal for having lots of strong points in attracting cultural and sustainable tourist.

Effects of Allelochemical Gramine on Photosynthetic Pigments of Cyanobacterium Microcystis aeruginosa

Toxic and bloom-forming cyanobacterium Microcystis aeruginosa was exposed to antialgal allelochemical gramine (0, 0.5, 1, 2, 4, 8 mg·L-1), The effects of gramine on photosynthetic pigments (lipid soluble: chlorophyll a and β-carotene; water soluble: phycocyanin, allophycocyanin, phycoerythrin, and total phycobilins) and absorption spectra were studied in order to identify the most sensitive pigment probe implicating the crucial suppression site on photosynthetic apparatus. The results obtained indicated that all pigment parameters were decreased with gramine concentration increasing and exposure time extending. The above serious bleaching of pigments was also reflected on the scanning results of absorption spectra. Phycoerytherin exhibited the highest sensitivity to gramine added, following by the largest relative decrease. It was concluded that gramine seriously influenced algal photosynthetic activity by destroying photosynthetic pigments and phycoerythrin most sensitive to gramine might be contributed to its placing the outside of phycobilins.

An Analysis of Abortion Laws and Sex Selective Abortion in India: A Case Study of Rajasthan

A son in every Hindu society pays his own father the debt and he owes him for his own life whereas a girl child is treated as a burden mainly in case of first child. Even today in India we have many societies which does not welcome girl child. Although there is an increase in overall sex ratio, there is a continuous decline in child sex ratio. This paper focuses on issues of sex selective abortion in Rajasthan based on secondary data. It is found that 90.0 percentages of women in Rajasthan wants at least one son. Around 34.3 percentages of women wants more sons than daughters and only 1.5 percentages of women wants more daughters than sons. It is very common among the rich and educated people.

Virtual E-Medic: A Cloud Based Medical Aid

This paper discusses about an intelligent system to be installed in ambulances providing professional support to the paramedics on board. A video conferencing device over mobile 4G services enables specialists virtually attending the patient being transferred to the hospital. The data centre holds detailed databases on the patients past medical history and hospitals with the specialists. It also hosts various software modules that compute the shortest traffic –less path to the closest hospital with the required facilities, on inputting the symptoms of the patient, on a real time basis.

Determining of Threshold Levels of Burst by Burst AQAM/CDMA in Slow Rayleigh Fading Environments

In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.

Comparison of Three Versions of Conjugate Gradient Method in Predicting an Unknown Irregular Boundary Profile

An inverse geometry problem is solved to predict an unknown irregular boundary profile. The aim is to minimize the objective function, which is the difference between real and computed temperatures, using three different versions of Conjugate Gradient Method. The gradient of the objective function, considered necessary in this method, obtained as a result of solving the adjoint equation. The abilities of three versions of Conjugate Gradient Method in predicting the boundary profile are compared using a numerical algorithm based on the method. The predicted shapes show that due to its convergence rate and accuracy of predicted values, the Powell-Beale version of the method is more effective than the Fletcher-Reeves and Polak –Ribiere versions.

Numerical Analysis of the SIR-SI Differential Equations with Application to Dengue Disease Mapping in Kuala Lumpur, Malaysia

The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease. 

Users- Motivation and Satisfaction with IS

To motivate users to adopt and use information systems effectively, the nature of motivation should be carefully investigated. People are usually motivated within ongoing processes which include a chain of states such as perception, stimulation, motivation, actions and reactions and finally, satisfaction. This study assumes that the relevant motivation processes should be executed in a proper and continuous manner to be able to persistently motivate and re-motivate people in organizational settings and towards information systems. On this basis, the study attempts to propose possible relationships between this process-nature view of motivation in terms of the common chain of states and the nearly unique properties of information systems as is perceived by users in the sense of a knowledgeable and authoritative entity. In the conclusion section, some guidelines for practitioners are suggested to ease their tasks for motivating people to adopt and use information systems.

Controller Synthesis of Switched Positive Systems with Bounded Time-Varying Delays

This paper addresses the controller synthesis problem of discrete-time switched positive systems with bounded time-varying delays. Based on the switched copositive Lyapunov function approach, some necessary and sufficient conditions for the existence of state-feedback controller are presented as a set of linear programming and linear matrix inequality problems, hence easy to be verified. Another advantage is that the state-feedback law is independent on time-varying delays and initial conditions. A numerical example is provided to illustrate the effectiveness and feasibility of the developed controller.

LMI Approach to Regularization and Stabilization of Linear Singular Systems: The Discrete-time Case

Sufficient linear matrix inequalities (LMI) conditions for regularization of discrete-time singular systems are given. Then a new class of regularizing stabilizing controllers is discussed. The proposed controllers are the sum of predictive and memoryless state feedbacks. The predictive controller aims to regularizing the singular system while the memoryless state feedback is designed to stabilize the resulting regularized system. A systematic procedure is given to calculate the controller gains through linear matrix inequalities.