Hybrid information technology

Intelligence is the process of supporting the policymakers in making their decisions by providing them with the specific information they need. Intelligence analysis is the effort of extracting the nature of intelligence issue with the policy goal in mind. It is performed by intelligence analysts who form judgments that add value to the collected material. With the increased open source collection capabilities, there has emerged a need for a model of intelligence analysis that covers the basic elements of valuable information: relevancy, accuracy, and timeliness. There exist models such as vector space model of information retrieval which only addresses the relevancy aspect of information and cannot cope with nonlinear document spaces. In this paper, we discuss the requirements of an integrated model of intelligence analysis along with its peculiar characteristics.

Metamaterial is the arrangement of "artificial" elements in a periodic manner providing unusual electromagnetic properties. This unusual property has made it an area of interest for last few decades. It has wide applications in antennas. Gain, directivity, bandwidth, efficiency, and many other parameters of microstrip patch antenna can be improved using metamaterials. In this review paper, we first overview the metamaterials, its types and then the application of metamaterials in Microstrip patch antennas over the last 13-15 years.

Fog is a combination of two components airlight and direct attenuation, degrades the picture quality and creates a lot of problem in video surveillance, tracking and navigation. Thus, to remove it from an image, various defogging methods have been proposed in literature. Defogging can achieved using multiple images and single image fog removal method. One of the prominent methods in literature for defogging is Dark Channel Prior (DCP). This method though quite effective in removing fog from images has very high time complexity. In addition, it does not preserve edges and has halo effect. Therefore, this paper proposes a new technique which overcomes the disadvantage of DCP and at the same time preserves the picture quality. The proposed method is implemented in MATLAB-09 and the simulation results show the proposed method is quite good.

Spectrum sensing is one of the vital functions, plays an important role in cognitive radio networks (CRN). This paper discuss to enrich the sensing performance of propose estimated signal to noise ratio (SNR) based detector. Estimated SNR detector consists two detectors, energy detector (ED) & ED with ADT detector, out of these two detectors only one will perform sensing operation at a time. Which detector will be work, selection will be done on condition between estimated SNR value (S e) and threshold (γ). Results show that proposed ESNR_ADT scheme outperforms the cyclostationary based sensing method by 30.5 % at-10 dB SNR. It is also shown that the proposed scheme takes smaller detection time period as compare to cyclostationary detection in the order of 5.2 ms at-20 dB SNR. Furthermore, the scheme was associated with cooperative spectrum sensing (CSS) where each CRs work together in order to take final decision. Finally, it was analyzed that proposed ESNR_ADT sensing scheme with CSS improves detection performance in the order of 0.9 at low SNR value of-18.5 dB approximately.

Most of the synchronization techniques belong to the master-slave (drive-response) system configurations in which the two chaotic systems are coupled in such a manner that the performance of the second (slave /response) system is influenced by the first (drive/master) system and the first system is not disturbed by the exertion of the second (slave / response) system. In this research paper, the synchronization problem of two widely used techniques, the Linear Active Control and Nonlinear Control Algorithms have been studied to achieve chaos synchronization of a new chaotic system. In this study, using the Linear Active Control and the Nonlinear Control algorithms and based on the Lyapunov Stability Theory, it has been shown that the two techniques have excellent transient performance and that analytically as well as graphically, the synchronization is asymptotically globally stable. Numerical simulations are furnished to show the efficiency and effectiveness of the two methods.

The detection of faces is one of the most requesting fields of research in image processing and Visual estimation of head pose is desirable for computer vision applications such as face recognition, human computer interaction, and affective computing. In this paper, we propose completed method for face pose estimation, face and face parts detection, feature extraction, tracking. This paper proposes using an improved AdaBoost algorithm, which is much better than normal AdaBoost. We use the de-facto Viola-Jones method for face and face part detection. From the robustness property of Haar-like feature, we first construct the strong classifier more effective to detect rotated face, and then we propose a novel method that can reduce the training time. We adopt affine motion model estimation as a tracking method. The combination enables efficient detection around the search area limited by tracking. Experimental results demonstrated its effectiveness and robustness against different types of detection and pose estimation in the input face images, including faces that appear in a wide range of image positions and scales, and also complex backgrounds, occlusions, illumination variations and multi-pose head images.

In this study, the removal of sunset yellow dye from aqueous solutions using low-cost materials as adsorbents such as modified Rice husk (MRH) and sugarcane bagasse (SB) by a batch system were investigated. Experiments were carried out as a function of contact time, initial concentration, pH and adsorbent dosages. The equilibrium adsorption of sunset yellow dye on adsorbents was analyzed by Langmuir, Freundlich and Temkin models. The results indicate that the Freundlich model provides the best correlation for sunset yellow-MRH system and the Langmuir model provide the best correlation for sunset yellow-SB system and also pseudo-second-order model was best applicable to the sorption data. The results revealed that the sunset yellow is considerably adsorbed on modified rice husk and sugarcane bagasse and it could be an economical method for the removal of sunset yellow from aqueous systems.

This paper presents a high performance chopper-Stabilized Two-stage operational amplifier for biomedical applications. This Two-stage is designed for low noise, low power, high PSRR and high CMRR. The Miller compensation technique (Cc) is used with a nulling active resistance (Rz) implemented using Transmission gate (TG) transistors for stable operation in feedback mode. Chopper stabilization technique has been widely used in amplifiers for flicker (1/f) noise and offsets reduction purposes using the principles of modulation and demodulation. Thus, the functionality and performance of modulation and demodulation circuits determines the realization and attainment of chopper stabilization. The operational amplifier was manufactured in a SPECTRE using GPDK 90nm CMOS technology with threshold voltages of a 0.17 V and - 0.14 V achieve a low power 2.6uW,

Kalman filtering is a well-established methodology used in various multi-sensor data fusion applications. In our experiment, we first obtain measurements from the accelerometer and gyroscope and fuse them using Kalman filter in an inertial measurement unit (IMU). We estimate Kalman filter output and estimation error. The affect of process noise and measurement noise on estimation error is tested. It is explored that the measurement noise has significant role to increase estimation error in the data fusion process.

In this paper, a new epidemic model, known as the SLBQRS model, is proposed in a computer network with Latent and Breaking-out periods of a virus in its life cycle. Furthermore, an infected computer will be referred to as latent or breaking-out depending on whether all viruses staying in it are in their respective latent periods or at least one virus staying in it is in its breaking-out period. In the real world there exists no infected computer at all that has no infectivity. A breaking-out computer can get treated with a higher probability, because it usually suffers from a marked performance degradation or even breaks down, which can be perceived evidently by the user. The quarantine is a method of isolating the most infected nodes from the network and reduce the spreading virus till they get recovered. The qualitative properties of this model are investigated. The result shows that the dynamic behavior of the model is determined by a threshold R 0. Specially, virus-free equilibrium is globally asymptotically stable if R 0 ≤ 1. Next, the sensitivity analysis of R 0 to six system parameters is also analyzed. On this basis, a collection of strategies are advised for eradicating viruses spreading across the Internet effectively. Threshold R 0 , equilibrium and their stability are discussed in terms of the Jacobian of the system. Numerical methods and MATLAB are employed to solve and simulate the system of equations developed and analysis of the model gives remarkable exposure.

In this paper, we propose a new version of FP-Growth algorithm to find association rules. In this version, we vary the minsup value from one level to another. This variation is made in two cases: increasing and decreasing the minsup value. We performed a set of experiments to validate the usefulness of our proposition in the generation of association rules process.

Protection system is used to protect components against fault as fast as possible and also to minimize the area around it from fault. Nowadays because of the existence of Distributed Generation in power system, a change is needed to be implemented for protection system at distribution network in order to ensure the electricity can be supplied to the consumer safely. With the presence of distributed generation (DG) units in distribution systems, the function of relay protection is generally going to be changed. In this paper the impact of installing Distributed Generation in radial system on the directional over-current protection relay, in presence of a Thyristor Controlled Series Capacitor on fault courant is investigated. The relays coordination scheme was developed through analysis for three fault location scenarios. A realistic feeder system for a case study with its scheme protection is developed in Matlab software environment.

In this paper, a new version of non-ideal model 08-bit current mode pipeline ADC has been developed. It is based on Matlab and Simulink environment with special focus given to the analog building blocks. Those blocks are current Sample-and-Hold(S/H), current Sub-ADC and current Sub-DAC. In this model, the sub-ADC is implemented by two current comparators and encoder logic circuit. For the current S/H and sub-DAC, they are implemented by using a switch current and current source. The main advantage of current mode approach is its low power dissipation, low cost and high speed. However, there are some technical limitations; using the model and running the simulation with the introduction of the main non idealities components such as a current offset, clock feed through, charge injection, clock jitter, switching noise, mismatch errors and non idealities in current amplifier, demonstrated clear degradation of the performance of the ADC.

Errors in the scanning procedures lead to uncertainties when trying to segment the scanned images. Fuzzy c-means is a clustering method that can be applied to segment images with uncertainty estimates. Bias-corrected fuzzy c-means (BCFCM) clustering compensates for two sources of uncertainty by modeling noise and bias fields during the segmentation process. In this paper, we present an approach to improve BCFCM clustering and apply it to magnetic resonance imaging (MRI) data of the human brain. Our approach is based on two variants of BCFCM clustering, the classical one and the one with distance-based weights. We improve both variants by slightly modifying their main algorithms for better bias field estimation. To evaluate the improved algorithms, we apply the algorithms to synthetic data, simulated MRI brain data, and real MRI brain data with ground truth in form of manual segmentation. All experiment results show that our improved methods outperform the original methods in both the segmentation accuracy and efficiency (the number of iterations).

Computer game is a vibrant research area in artificial intelligence. Chinese chess game is an important part of computer game and it has become an important study area after chess game had reached its culmination when Deep Blue and its successors beat Kasparov. Some achievements acquired in Chinese chess game have applied into fields of medicine, economics and military. This paper presented a new method of optimizing evaluation function in Chinese-chess programming by particle swarm optimization. The process of training evaluation function is to automatically adjust these parameters in the evaluation function by self-optimizing method accomplished through competition, which is a Chinese-chess system plays against itself with different evaluation functions. The results show that the particle swarm optimization is successfully applied to optimize the evaluation function in Chinese chess and the performance of the presented program is effectively improved after many trains. We also examined the importance of the place control in the evaluation function by the comparison the optimizing results with and without the control of the place and showed the comparison result.

In the present study, the linear attenuation coefficient and mass attenuation coefficient have been calculated at energy range of 0.8MeV, 1MeV, 3Mev, 5MeV and 7MeV. The mass attenuation Coefficient µm has been calculated analytically for Iron material Fe (ρ= 7.87 g/cm 3) and developed material lead Pb (ρ= 11.3 g/cm 3) at photon energies [0.8 MeV to 7 MeV] using X-Com computer code. The obtained results were compared with the calculated values. The linear attenuation Coefficient µ has been calculated, its variations with photon energy were plotting. The Comparison between two materials Iron and Lead were also studied. The obtained result shows that µ and µm depends on the photon energy, density of the materials and atomic number. From this study we notice that the values of µm and µ of Lead material is greater than Iron material and also the values are decreasing with increasing the photon energy. The half value layer (HVL) and tenth value layer (TVL) of two studied materials were calculated at photon energy range of 0.8 MeV, 1MeV, 5MeV and 7MeV. The relation between this equation Ln (Io/I) and the thickness of material were calculated, so the curves show that the relation of Ln (Io/I) of Iron and Lead materials is increasing with the increasing of material thickness and the relation gives the straight line, also the comparison of this relation for Lead material is higher than Iron material. This study can also be utilized to improve the effectiveness of radiation shielding by using the developed shielding material.

Olfactory display devices have become a recent demand and trend in human computer interaction, providing a new member in the human computer interaction peripheral devices family. These devices enrich the olfactory sense for the user stimulating him/her by means of scent stimuli in correspondence to an object or an event shown on the visual display. Some researches have been done to cover the design, usage and delivery for the scent to the users, other works covered some analysis on the scent categorization and grouping. In this paper a focus is on the controlled atomization of a liquid based scent material while guaranteeing: speed, intensity, durability, compactness and scalability, these important factors are crucial to build a commercial grade olfactory displays containing a universal, interchangeable and versatile but yet durable scent disparity component to facilitate the realization of olfactory display devices.

This research contains the simulation and designing of Quadcopter using Adaptive Neuro Fuzzy Controller to control the altitude of quadcopter and obstacle detection. Now a day's advancement in technology has made it possible to develop low power and lightweight with accurate sensors which are used with controllers for controlling, which have high processing power but small power consumption. This has been allowed for the development of complex and difficult control systems that can be implemented onboard UAV. With this combination of high precision and light weight, real-time onboard navigation or guidance and autonomous flights are now practical. This research work used a Fuzzy controller to control the pitch angle of quadcopter and avoiding obstacles. The fuzzy controller receives the sensory data and adjust the pitch accordingly until unless it finds the clear path. For detecting obstacles the IR sensors are used. For designing a fuzzy inference system used Sugeno model and used mat lab commands to design ANFIS as we have another method for designing by using a Simulink as well. ANFIS designed is based on kinematics and dynamics equation of quadcopter that will be able to control the pitch of quadcopter. Simulations results in mat lab show that by using ANFIS the performance of Quadcopter will be improved significantly.

The connecting rod in four stroke reciprocating diesel engine is subjected to variable loading when Engine is in operating condition. The design of connecting rod is critical for the engine Performance, fatigue life, linear vibration & durability of engine. The fatigue failure is occurred due to alternating compressive & tensile stresses during its two revolutions. The fuel combustion inside cylinder generates a huge compressive force at power stroke. The 3D model is prepared and CAE analysis is done to predict the maximum Stresses and check whether it is safe for fatigue failure. The modification in design is done to make it safe for fatigue life. The experimental Fatigue testing is carried out to validate the predicted & Actual fatigue life of connecting rod.

At present, the voltage stability assessment experiences sizeable agitation in the safe operation of power systems. This is due to the blow of a strain power system. With the accretion of power demand by the consumers and also the ambit amount of power sources, therefore, the system has to perform at its maximum accuracy. Consequently, the cardinally to discover the maximum ability boundary prior to voltage collapse should be undertaken. A preliminary warning can be perceived to avoid accost capacity of power system. This has necessitated the employment of techniques for determination of critical point of voltage stability. In this paper some important aspects related to voltage stability indices use in electric power system are discussed. The line indices are used for estimation of the maximum loadability and in other words indices are used to identify the weak bus in the system. The effectiveness of the analyzed methods are demonstrated through numerical studies in IEEE 14 test bus system, IEEE 30 test bus system and IEEE 118 test bus system, using Fast Voltage Stability Index (FVSI) and Line stability index (L mn) at base loading and heavy reactive loading. This will be very useful in placement of optimal FACTS devices for enhancement the margin of voltage stability.

Seaports are among the vital requirements of a country’s trade. The service capacity of a seaport is important to maintain seaport operations. Determining the number of the berthing places is a major decision for planning a seaport by considering the future port capacity. Queuing theory is used to determine the optimum berth number in a seaport. In this study, optimum number of berths of Izmir seaport in Turkey was determined by implementing the queuing theory. Likewise, the ship traffic was predicted using two forecasting models: Linear Regression Analysis and Artificial Neural Networks. Model results were candidates of input variables for the queueing model for estimating the feasible berth numbers between 2015 and 2023. For 2015, feasible number of berthing places was found as 14 and for 2023 it was found as 16 by the queuing theory.

Genomic repositories gradually increase individual and reference sequences, which shares long identical and near-identical strings of nucleotides. In this paper a lossless DNA data compression technique called Optimized Base Repeat Length DNA Compression (OBRLDNAComp) has been proposed, based upon redundancy of DNA sequences. For easy storage, retrieval time reducing and to find similarity within and between sequences compression is mandatory. OBRLDNAComp searches long identical and near-identical strings of nucleotides which are overlooked by other DNA specific compression algorithms. This technique is an optimal solution of longest possible exact repeat benefits towards compression ratio. It scans a sequence horizontally from left to right to find statistic of repeats then follow substitution technique to compress those repeats. The algorithm is straightforward and does not need any external reference file; it scans the individual file for compression and decompression. The achieved compression ratio 1.673 bpb outperforms many non-reference based compression methods.

Time-varying channel estimation is an important activity in next generation wireless communication. Channel estimation is required mainly for the significant signal processing operation in multiple input multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems such as precoder designing at transmitter & relay and relay selection scheme in cooperative communication system. In this paper we investigate and compare various efficient channel estimation schemes for OFDM system. In this paper the channel estimation techniques based on block type Pilot arrangement for OFDM system are investigated. Finally, the discrete Fourier transform (DFT) based channel estimation technique is performed which gives better performance over least square(LS) and minimum mean square error(MMSE) based channel estimation. The bit error rate (BER) of DFT based channel estimation is less than the BER of LS and MMSE based channel estimation with same signal to noise ratio (SNR).

Cloud computing is a computing paradigm where applications, resources and services are provided over the internet. Software and hardware can be used to pay as service basis, without buying them. The key role of scheduling is to manage different tasks in different cloud environment. Cloud computing service providers use the available resources efficiently to achieve maximum profit. This makes task scheduling as a challenging issue for cloud service providers. This paper gives an introduction about cloud computing, various existing scheduling algorithms in different task scheduling environments, existing problem and the future suggestions in existing algorithms.

Online product reviews have become the major source of information for the end users to make purchasing decisions. Companies/individuals often hire people for writing fake reviews to increase the sale of their products. These individuals are known as opinion spammers and their activities are known as opinion spamming. Manually it is difficult for a human being to detect these deceptive reviews. Features play a major role to build effective deceptive reviews detection classifiers. We have observed human behavior through reviews, blogs datasets, and transferred these observations into features.Towards the end, we have built automated deceptive reviews classifiers using document level and aspect level domain independent features. We have performed our experiments in hotels domain. We achieved around 93 percent accuracy on Myle Ott's gold standard dataset [1] and up to 86 percent accuracy on the self-crawled Yelp 1 dataset.

Bad weather conditions including haze, fog, rain etc. degrade the picture quality which causes poor visualizations. Various methods have been proposed to eradicate the effects of above conditions. Initially, polarization filters were used to restore the foggy image. Though this method estimates airlight to quite good an extent but at the same time uses multiple images therefore, cannot be applied on dynamic scenes. In addition, it has very high time complexity. To overcome the use of multiple images Dark channel prior technique was used that effectively calculates the transmission map to restore the foggy image. For this purpose it requires usage of soft matting technique that causes halo effect and has high time complexity. We are of the opinion that if transmission map is calculated using dark channel prior and airlight is estimated using polarisation filters, the resultant process will not only have lower time complexity but at the same time overcomes the drawback of multiple images. The above mentioned technique is implemented in MATLAB-9 and analysed in this paper. The results shows that usage of this hybrid approach gives quite better results.

This paper presents a comprehensive comparative review of existing floating-point multiplier systems. The study focuses on single, double, quadruple and multi-precision floatingpoint multiplier architectures and seeks to identify engineering techniques involved in their development. A comparison of the performance of these systems in terms of metrics such as path delay, hardware utilization and even power consumption in some cases are carried out. Weaknesses in the systems reviewed along with possible gaps in the area of research are identified. This paper also serves to identify several recommendations and considerations for the development of a multi-precision floating-point multiplier system capable of treating the weaknesses of multiplier systems identified.

This study developed a real-time remote monitoring system (RTRMS) to receive the vibration frequency of bridge pier. The system included a front station and a middle station. A multi-hop wireless routing is employed to transmit the data from the front to the middle station. The front station includes a receiver equipped to receive the vibration frequency, and a wireless sensor network to transmit the data. The middle station is designed by an embedded system for storing the data. The pressure test shows that the loss rate of received data is less than 0.6%. The consuming power of one day is 3 ampere hours in the front station and 30 ampere hours in the middle station if the 12 voltage battery is used.

Design a delay free FPGA-based Proportional-Integral-Derivative (PID) controller to control of first order delay system is the main objective in this research. In order to provide high performance micro-based controller, FPGA-based PID controller based on design Derivative and Integral algorithm is selected. Conventional PID controller is a stable linear type model-free controller that reduces the delay time in first order delay system. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12). In this research, linear controller need real time mobility operation, and one of the most important devices which can be used to solve this challenge is Field Programmable Gate Array (FPGA). FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In HDL based derivative algorithm the minimum input arrival time before clock is 16.466 ns and the maximum frequency is 60.73 MHz, but in the best design action, the maximum frequency to design this single chip algorithm should be 63.629 MHz. In HDL integral algorithm the minimum input arrival time before clock is 15.599 ns and the maximum frequency is 64.1 MHz, but in the best design action, the maximum frequency to design this single chip algorithm should be 178.190 MHz.

Over a period of time, there are different types of multipliers used to minimize cost of constructive parameters in digital FIR filter design in different forms. In these multipliers truncated multiplier design play’s an essential role. Due to multiple adders and delay elements the circuit in transpose form occupies more area and consumes power. In the proposed method effectiveness in different parameters are achieved with low cost, high speed and effective results are done by faithfully rounded truncated multipliers with operations of carry save adder. Direct form of FIR filter utilizes based on MCMAT for multiplication and accumulation operations; it will reduce the area by decreasing the number of different components like structural adders and registers. By using MCMAT operation in the digital FIR filters, optimal results can be obtained in terms of power and area specifications. The proposed 12 bit Arithmetic and Logic Unit is designed along with MCMAT based digital FIR filter ...

A detailed analysis of scientific work done in tracking an embedded object with special reference to telemetry capsules in the gastro-intestinal (GI) tract using radio frequency (RF) signals is presented in this paper. We fully discuss the mathematical analysis of our tracking procedure as well as experimental validation of our tracking concept. Experimental validation is accomplished by using a radio frequency (RF) signals at 433MHz (Free Industrial Scientific and Medical centre frequency in EMEA regions), Analog Devices 8052 based microcontroller with ADC capability and a means of transferring the received signal strength intensity (RSSI) voltage converted to digital, from the microcontroller to the personal computer (PC). The primary focus of this paper is practical way of achieving these tasks using basic mathematical and computing principles. Consequently, our algorithm-based tracking results for experiments in a liquid medium yielded an average error of less than 21%. These results were validated with the Bland-Altman plots using semi-automated manual measurements as gold standard.

For decades, Image enhancement techniques have been pushing the envelope of image processing applications. The aim of image enhancement is to recover the information perception contained in the image for human eyes besides delivering the best input for image processing systems. Fingerprint system is one of the most popular image processing system, The performance of any fingerprint system highly depends on the fingerprint image quality; therefore, fingerprint image enhancement is an essential stage in fingerprint systems. Gabor filtering has been widely used to facilitate various fingerprint applications. Meanwhile, enhancement using Gabor filter still has several drawbacks. In the present enhancement approach, we propose an active hybrid contextual module used for image enhancement. In order to prove the efficiency and effectiveness the proposed algorithm applied to fingerprint image. The proposed filter methodology includes eight stages, each one designed for a particular image defect, which can much improve the clarity and continuity of ridge structures, link broken ridges and reduce the false minutia. The experimental results show that the enhanced image quality by using our algorithm has higher performance, robustness and versatility. Presented approach might be useful for many applications related to digital image processing, computer vision.

The purpose of this paper is to provide a model for communication in large scale projects in Big Data environment. Given the fact that Big Data is going to be part of every business organization very soon, this study aims to present a new communication management strategy in order to accommodate the change in technology of data base storage systems. The complex large projects always emerge with different modes and have different attributes for processing the data. In this model different data sources of a large scale project are connected to the enterprise data ware house using Information Inference Framework (IIF). This new approach may provide an enhanced way of communication management for activities in large scale projects.

Considering the cutting stock problem and lot sizing problem for tower transmission industry, we present the new effective mathematical simulation for One-Dimensional Cutting Stock Problem (1D-CSP) by applying heuristic approach. This approach works within pre-defined trim except at the end of cutting process. The pre-defined trim is called the sustainable trim which is based on average order lengths and given stock lengths. By considering the constraints like space, manpower etc., the main objective of this study is to minimize the trim loss.

This thesis examine and compares the efficiency of DSSC sensitized with natural dye extracted from Euphorbia amygdaloides and opuntia Ficus indica plant and pure ZnO, ZnO-Fe 2 O 3 and pure Fe 2 O 3 nanocomposite. The study starts by selecting natural dyes that they have good absorption spectra in the visible range using the UV-Vis spectrophotometer the selected natural dyes were Euphorbia amygdaloides and opuntia Ficus indica. Nanocomposites semiconductor oxide starting from pure ZnO, 95%ZnO-5% Fe 2 O 3 , 90% ZnO-10% Fe 2 O 3 , 80% ZnO-20% Fe 2 O 3 , and pure Fe 2 O 3 were prepared using co-precipitation method. Then the prepared semiconductor oxide particle sizes were estimated using XRD. The estimated size of the prepared nanoparticles were ZnO =39.84nm, 95%ZnO-5% Fe 2 O 3 =23.22nm, 90% ZnO-10% Fe 2 O 3 =32.44nm, 80% ZnO-20% Fe 2 O 3 =38.38nm and pure Fe2O3=35.47nm. Finally dye sensitized solar cells (DSSCs) had been assembled and characterized from each dye extracted, Euphorbia amygdaloides. (Using Ethanol) and opuntia Ficus indica (using water) and the prepared semiconductor metallic oxide. The current density-voltage characteristics in the dark and under white light illumination and also IPCE under monochromatic illuminations have been studied. Solar energy conversion efficiency (η) of the as-synthesized semiconductors sensitized by the natural dye (Euphorbia amygdaloides. and opuntia Ficus indica) was obtained in the following order ZnO>80% ZnO-20% Fe 2 O 3 >95%ZnO-5% Fe 2 O 3 >90% ZnO-10% Fe 2 O 3 > Fe 2 O 3. From the ten devices assembled best device parameter was achieved by the ethanol extract of Euphorbia amygdaloides. and pure ZnO nanoparticle semiconductor. The result was JSC=0.3696mAcm-2, VOC =0.33V, FF = 0.31 and η=0.038.

Today, an effective website design has emerged as a thing of main concern for online shopping businesses and thus the companies involved in the online shopping businesses are aspiring for well-designed websites. In the past, several methods have been reported but they proved unproductive as they failed to handle the decision making involved in the process to evaluate the customer needs efficiently. Thus to cope up with the issue, the paper considers QFD approach as it a customer driven process that strongly assists in guiding the design decisions. The purpose of this paper is to explore the issues that have resulted in the decrease of satisfaction rate of users, analyze the problems with the methods used and propose effective solution through the literature review. The contribution of this paper is manifold. First, it explores QFD at length and evaluates its applicability for effective design of online shopping websites. This helps users understand the decision making capabilities of QFD. Second, it highlights the limitations of QFD approach in handling the vague and imprecise data that arise due to the inherent crisp approach and subjectivity involved in the QFD approach. Finally, the paper proposes fuzzy integration with QFD to deal with the uncertainty and vagueness involved in the QFD process for improved decision making and more precise results leading to effective design of online shopping websites. The literature review is based on information from various research papers, tools and web sources.

In this article we described the channel capacity of random MIMO channel when CSI is not available at transmitter side. The channel correlation is directly related to capacity of MIMO channel. Also we consider the capacity of MIMO channel when the channel gain between transmitter and receiver is correlated. We compute mathematical equation for calculation of ergodic channel capacity of random MIMO system. MIMO system have very large impact on channel capacity, so it is very necessary to analyze all parameter which are responsible for very high speed data transmission. Because day by day there is very high need of technologies which provide high data transmission. All the simulation in this article are done with the help of MATLAB/Simulink software.

In this article, we modelled and simulated Carbon Nanotube Field Effect Transistors (CNTFET); this transistor has a carbon nanotube channel. An Artificial Neural Networks (ANN) model was developed to reproduce accurately the behavior of CNTFET to predict its response for a wide range of temperature and voltage with focusing on the experimental data. The neural model is tested and validated; hence the ANN model is able to predict the CNTFET behavior with good accuracy. Finally, the proposed ANN model is integrated as a component in the library of simulation software of PSPICE electronic components.

Software reliability testing plays a vital role to identify many flaws in software design as well as functional aspects. Reliability testing encompasses the analysis of the software's capacity to carry out intended tasks, particular environmental conditions within the given time instance. So, reliability estimation should be carried out within the initial stage of the software development. Through this paper we have shown the importance of the testing time and testing coverage in the analysis of software reliability. Testing time is the time interim required to carry out testing mechanism. Testing coverage includes the amount of tests exercised by the test set or batch. In order to enhance the efficiency of the proposed system we have applied the non-homogeneous Poisson process.

Retrieval of information from the database and web log files is a very time consuming process. There are many techniques and models to retrieve data from the web. There are two types of data available on the web i.e. structured and unstructured. If data is structured then retrieval of information is an easy task. Otherwise, firstly apply the algorithm to unstructured data and then models will be applied. Vector space and Boolean models are used for IR. In this paper, we compare both Boolean model & Vector Space model techniques to retrieve data from the web (log files) and proposed a new algorithm based on time, frequency, memory consumption, etc.

Brain tumour is the largest problem in the world. Few researchers have worked in that area. In the paper brain tumour is detected by the three different parameter of the proposed antenna namely return-loss of the antenna, current density of the brain phantom model with tumour and without tumour and specific absorption rate (SAR) with and without tumour. None of the previous work detects a tumour by three different parameter simultaneously. Initially the proposed antenna is designed at 2.45GHz and then applies different technology to make it ultra wide band. Antenna frequency is shifted and it become the ultra wide band and gives a bandwidth of 2.89GHz.S 11 parameter of antenna achieved maximum at 7.624GHz that is 45.76dB. Found current density of the antenna is 770.6A/m 2 , SAR of the antenna is 2.67*10 6 Watt/m 3 .Brain is assumed as a single layer Brain Phantom model in which brain is considered as centre radius of sphere of 10mm radius and placed in contact with upper part of the antenna, dielectric constant of brain is assumed as 45.8.it gives a return loss with brain model is 31.89dB at 7.61GHz and current density is 801.24A/m 2 , SAR of the brain phantom model with antenna is 3.15*10 6 Watt/m 3 .Now triangular shape tumor is assumed with dielectric constant of the tumor is 52.06 and it gives a return loss with tumor 32.26 at 7.544GHz.current density with tumor is 960.3A/m 2 , SAR of the phantom model with tumor and antenna is 3.069*10 6 A/m 2 .The paper detect tumors by three different parameter simultaneously that is very important aspect.

Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This research focuses on the design, and analysis of a model-reference sliding mode controller for first order delay system, in presence of uncertainties. In order to provide high performance nonlinear methodology, model-reference sliding mode controller is selected. Pure sliding mode controller can be used to control of partly known nonlinear dynamic parameters. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon. To attenuation the chattering, new filter based high speed control technique is introduced. In this technique, two type derivative techniques are used to improve the rate of delay as well stability, robustness and chattering attenuation. This technique cased to improve the rate of delay compare with conventional PID controller and conventional sliding mode controller.

This paper presents a design and simulation of a new structure having simultaneous negative permeability and permittivity which called double negative metamaterial (DNM) or left handed material (LHM). The LHM structure consists of five circular split ring resonators on one side of dielectric substrate and a set of wire couples on other side. CST Microwave Studio is used to model the LHM structure to calculate the scattering parameters (S11 and S21) from which the complex permittivity, permeability and refractive index can be extracted. MATLAB is used for verification of obtained negative values of structure's parameter. The circuit was manufactured and measured. The experimental results well agree with the simulated ones.

Software testing can be stated as the process of validating and verifying that a computer program, application and product [1]. Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Software testing, depending on the testing method employed, can be implemented at any time in the development process. Traditionally most of the test effort occurs after the requirements have been defined and the coding process has been completed. Testing can never completely identify all the defects within software. A primary purpose of testing is to detect software failures so that defects may be discovered and corrected. Testing cannot establish that a product functions properly under all conditions but can only establish that it does not function properly under specific conditions. There are many approaches to software testing. Reviews, walkthroughs, or inspections are referred to as static testing, whereas actually executing programmed code with a given set of test cases is referred to as dynamic testing. Regression testing is an important but expensive software maintenance activity performed with the aim of providing confidence in modified software. Regression test selection techniques reduce the cost of regression testing by selecting test cases for a modified program from a previously existing test suite. Regression testing is done every time when a program is modified to ensure that the modifications do not introduce new bugs into previously validated code. Regressions Testing can be done by collectively perform Regression Test Selection, Test Minimization and Test Case Priotrization Technique. An important research problem, in this context, is the selection of a relevant subset of test cases from the initial test suite. Regression test selection (RTS) techniques minimize both the regression testing time and effort. Regression test selection (RTS) techniques select a subset of valid test cases from an initial test suite (T) to test that the affected but unmodified parts of a program continue to work correctly. Use of an effective regression test selection technique can help to reduce the testing costs in environments in which a program undergoes frequent modifications. D is a new programming language. This is an object-oriented, imperative, multiparadigm system programming language. Regression testing on D programming language still untouched by researchers. Our research attempts to bridge this gap by introducing a techniques to revalidate D programs. A framework is proposed which automates both the regression test selection and regression testing processes for D programming language. As part of this approach, special consideration is given to the analysis of the source code of D language. In our approach system dependence graph representation will be used for regression test selection for analyzing and comparing the

In computer science, one of the fundamental issue is to arrange the elements in some logical order. Various algorithms have been developed over the years to handle this process of ordering the elements (sorting) having their own running time, efficiency and simplicity. Sorting problem has attracted a great deal of research because efficient sorting is important to optimize the use of other algorithms. This report presents a new sorting algorithm, using the data structure Binomial Heap, called Binomial Heap sort algorithm which will give an innovative sorting scheme through which we can arrange the given elements in some specific order either in increasing order or in decreasing order. Binomial Heap sort results in minimum complexity over Binary Heap sort as far as frequency of inbuilt operations is concerned. In this report, we consider all the cases whether the input elements given in an array are in descending order, ascending order or randomly distributed. Through this paper, we are proposing a new sorting algorithm called Binomial Heap sort. Its time complexity is

Multi-carrier phenomenon Orthogonal Frequency Division Multiplexing (OFDM) is considered to be one of the most significant developments in wireless communication. It is now becoming somewhat a critical important standard. However, high Peak Average Power Ratio (PAPR) is a key issue in OFDM systems. It resulted the lowering of power efficiency. Conventionally OFDM can be implemented using Discrete Fourier Transform (DFT) technique that usually adopts modulation either Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK) or Quadrature Amplitude Modulation (QAM). In the study, OFDM systems employing DFT, Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) had been investigated by means of computer simulation. The main aim is to assess the enactment of the Bit Error Rate (BER) and PAPR in OFDM system. The performance of the system was assessed in the occurrence of Additive white Gaussian noise (AWGN) as well as incorporating multipath fading as the channel impairments. The acquired preliminary findings show that the DWT technique outperforms DFT and DCT. It is therefore deemed that DWT based OFDM has the potential to significantly reduce PAPR.

A novel approach for the efficient weighted association rule mining proposed in this present paper. The proposed approach reducts the transactional dataset (weighted) by utilizing the power of Rough Set theory. Furthermore, proposed approach acquires the benefit for weighted measures (w-support, w-confidence) for obtaining the most profitable weighted frequent itemsets and the Genetic Algorithm for the extracting the desired set of optimized weighted association rules. Experimental analysis of proposed approach has been done and observed that the approach works well and will be helpful in situation when there is a requirement for the consideration of extracting the best weighted association rules in decision-making process.

It seems quite interesting to reconstruct the destroyed documents. On the other hand it is possible that documents might be mistakenly destroyed by someone. Another useful application of this type is in the field of forensics and archeology for the restoring of the ancient documents. To reduce the availability of information documents are shredded. The advent of new and effective ways has developed a convenient way for the people to get rid of important information so that it could not get into the hands of others. It includes the use of shredder to render the information on the pages useless and usually eliminating of proof is been practiced. The same scenario has been dealt hereby and an efficient way of rearranging those strips, known as shreds, to recreate the original document is been designed. This paper presents an efficient way of reconstructing the documents by genetic algorithm which is an extended version of memetic algorithm by emerging the variable neighborhood search (VNS). This computer based algorithm deals with an input of multiple shreds of a single page, which are to be rearranged in order to make the text on it understandable. A few Image Processing techniques are been used to get back what was intended to be destroyed. This consumes less time as compared to manual rearranging with promising results in a form of Image. Recommendations are also indicated to improve the algorithm.

Defect probabilities in embedded memories have been increased by the scaling reduction in advanced VLSI technology. Built-In Self Repair (BIRA) circuit design is a solution to improve the yield drop and get to a high reliability. This paper will present an at-speed optimal algorithm to repair Word-Oriented memories. In spite of parallel structure in our analyzer to get high analysis speed, the area consumption of the circuit has decreased considerably due to the optimal algorithm. The repair rate of the proposed method is also 100% because of applying the binary search three as its foundation. Simulation results and comparison with other methods show the efficiency of the Wordy-R-CRESTA analyzer method.