Search results for: small cell networks.

Authors: Rajesh Joseph Abraham, D. Das, Amit Patra

Abstract:

This paper is concerned with the application of small rating Capacitive Energy Storage units for the improvement of Automatic Generation Control of a multiunit multiarea power system. Generation Rate Constraints are also considered in the investigations. Integral Squared Error technique is used to obtain the optimal integral gain settings by minimizing a quadratic performance index. Simulation studies reveal that with CES units, the deviations in area frequencies and inter-area tie-power are considerably improved in terms of peak deviations and settling time as compared to that obtained without CES units.

Keywords: Automatic Generation Control, Capacitive EnergyStorage, Integral Squared Error.

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Authors: Dimitra Sygkridou, Dimitrios Karageorgopoulos, Elias Stathatos, Evangelos Vitoratos

Abstract:

Transparent nickel doped cobalt sulfide was fabricated on a SnO2:F electrode and tested as an efficient electrocatalyst and as an alternative to the expensive platinum counter electrode. In order to investigate how this electrode could affect the electrical characteristics of a dye-sensitized solar cell, we manufactured cells with the same TiO2 photoanode sensitized with dye (N719) and employing the same quasi-solid electrolyte, altering only the counter electrode used. The cells were electrically and electrochemically characterized and it was observed that the ones with the Ni doped CoS2 outperformed the efficiency of the cells with the Pt counter electrode (3.76% and 3.44% respectively). Particularly, the higher efficiency of the cells with the Ni doped CoS2 counter electrode (CE) is mainly because of the enhanced photocurrent density which is attributed to the enhanced electrocatalytic ability of the CE and the low charge transfer resistance at the CE/electrolyte interface.

Keywords: Counter electrodes, dye-sensitized solar cells, quasisolid state electrolyte, transparency.

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Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad

Abstract:

As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.

Keywords: Artificial Neural Networks (ANN); Computational Intelligence (CI); Connectionist Text Summarizer ECTS (ECTS); Evolving Connectionist systems; Evolving systems; Fuzzy systems (FS); Part of Speech (POS) disambiguation.

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Authors: João Paulo Teixeira, Paula Odete Fernandes

Abstract:

The authors have been developing several models based on artificial neural networks, linear regression models, Box- Jenkins methodology and ARIMA models to predict the time series of tourism. The time series consist in the “Monthly Number of Guest Nights in the Hotels" of one region. Several comparisons between the different type models have been experimented as well as the features used at the entrance of the models. The Artificial Neural Network (ANN) models have always had their performance at the top of the best models. Usually the feed-forward architecture was used due to their huge application and results. In this paper the author made a comparison between different architectures of the ANNs using simply the same input. Therefore, the traditional feed-forward architecture, the cascade forwards, a recurrent Elman architecture and a radial based architecture were discussed and compared based on the task of predicting the mentioned time series.

Keywords: Artificial Neural Network Architectures, time series forecast, tourism.

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Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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Authors: А. Pashayev, C. Ardil, D. Askerov, R. Sadiqov, A. Samedov

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Keywords: Mathematical Modeling, Gas Turbine Blade Cooling, Neural Networks, BIEM and FDM.

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

Abstract:

This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: Data mining, textile production, decision trees, classification.

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Authors: L. Dzierzbicka-Głowacka, M. Janecki

Abstract:

Dynamic of phytoplankton blooms in the Baltic Sea has been analyzed applying the numerical ecosystem model 3D CEMBS. The model consists of the hydrodynamic model (POP, version 2.1) and the ice model (CICE, version 4.0), which are imposed by the atmospheric data model (DATM7). The 3D model has an ecosystem module, activated in 2012 in the operational mode. The ecosystem model consists of 11 main variables: biomass of small-size phytoplankton and large-size phytoplankton and cyanobacteria, zooplankton biomass, dissolved and molecular detritus, dissolved oxygen concentration, as well as concentrations of nutrients, including: nitrates, ammonia, phosphates and silicates. The 3D-CEMBS model is an effective tool for solving problems related to phytoplankton blooms dynamic in the Baltic Sea

Keywords: Ecosystem model, phytoplankton, Baltic Sea

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Authors: Supriya Pal, Kalyan Adhikari, Somnath Mukherjee, Sudipta Ghosh

Abstract:

This study presents the application of artificial neural network for modeling the phenolic compound migration through vertical soil column. A three layered feed forward neural network with back propagation training algorithm was developed using forty eight experimental data sets obtained from laboratory fixed bed vertical column tests. The input parameters used in the model were the influent concentration of phenol(mg/L) on the top end of the soil column, depth of the soil column (cm), elapsed time after phenol injection (hr), percentage of clay (%), percentage of silt (%) in soils. The output of the ANN was the effluent phenol concentration (mg/L) from the bottom end of the soil columns. The ANN predicted results were compared with the experimental results of the laboratory tests and the accuracy of the ANN model was evaluated.

Keywords: Modeling, Neural Networks, Phenol, Soil media

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Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedigheh Fabriki Ourang

Abstract:

GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: Domain, Gene Family, GRF, Motif.

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

Abstract:

Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: Criminal digital evidence, social media, ontologies, reasoning.

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Authors: P. Jomsri

Abstract:

Currently, web usage make a huge data from a lot of user attention. In general, proxy server is a system to support web usage from user and can manage system by using hit rates. This research tries to improve hit rates in proxy system by applying data mining technique. The data set are collected from proxy servers in the university and are investigated relationship based on several features. The model is used to predict the future access websites. Association rule technique is applied to get the relation among Date, Time, Main Group web, Sub Group web, and Domain name for created model. The results showed that this technique can predict web content for the next day, moreover the future accesses of websites increased from 38.15% to 85.57 %. This model can predict web page access which tends to increase the efficient of proxy servers as a result. In additional, the performance of internet access will be improved and help to reduce traffic in networks.

Keywords: Association rule, proxy server, data mining.

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Authors: Sushil Sarwa, Rajeev Kumar

Abstract:

The wireless mesh networks (WMNs) are emerging technology in wireless networking as they can serve large scale high speed internet access. Due to its wireless multi-hop feature, wireless mesh network is prone to suffer from many attacks, such as denial of service attack (DoS). We consider a special case of DoS attack which is selective forwarding attack (a.k.a. gray hole attack). In such attack, a misbehaving mesh router selectively drops the packets it receives rom its predecessor mesh router. It is very hard to detect that packet loss is due to medium access collision, bad channel quality or because of selective forwarding attack. In this paper, we present a review of detection algorithms of selective forwarding attack and discuss their advantage & disadvantage. Finally we conclude this paper with open research issues and challenges.

Keywords: CAD algorithm, CHEMAS, selective forwarding attack, watchdog & pathrater, wireless mesh network.

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Authors: Marcelo R. G. Duarte, Marcilio Alves

Abstract:

Pedestrians are the fourth group among road traffic users that most suffer accidents. Their death rate is even higher than the motorcyclists group. This gives motivation for the development of an urban vehicle capable of complying with the United Nations Economic Commission for Europe pedestrian regulations. The conceptual vehicle is capable of transporting two passengers and small parcels for 100 km at a maximum speed of 90 km/h. This paper presents the design of this vehicle using the finite element method specially in connection with frontal crash test and car to pedestrian collision. The simulation is based in a human body FE.

Keywords: Electric urban vehicle, finite element method, global human body model, pedestrian safety, road safety.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

Abstract:

Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: Payam Nabhani, Sima Radmanesh

Abstract:

Opportunistic network is a kind of Delay Tolerant Networks (DTN) where the nodes in this network come into contact with each other opportunistically and communicate wirelessly and, an end-to-end path between source and destination may have never existed, and disconnection and reconnection is common in the network. In such a network, because of the nature of opportunistic network, perhaps there is no a complete path from source to destination for most of the time and even if there is a path; the path can be very unstable and may change or break quickly. Therefore, routing is one of the main challenges in this environment and, in order to make communication possible in an opportunistic network, the intermediate nodes have to play important role in the opportunistic routing protocols. In this paper we proposed an Adaptive Fuzzy Routing in opportunistic network (AFRON). This protocol is using the simple parameters as input parameters to find the path to the destination node. Using Message Transmission Count, Message Size and Time To Live parameters as input fuzzy to increase delivery ratio and decrease the buffer consumption in the all nodes of network.

Keywords: Opportunistic Routing, Fuzzy Routing, Opportunistic Network, Message Routing.

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Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie

Abstract:

Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.

Keywords: Human motion analysis, biometrics, gait recognition, principal component analysis, MLP neural network.

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Authors: Sonia Manhas, Parvinder S. Sandhu, Vinay Chopra, Nirvair Neeru

Abstract:

The cost of developing the software from scratch can be saved by identifying and extracting the reusable components from already developed and existing software systems or legacy systems [6]. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. We have used metric based approach for characterizing a software module. In this present work, the metrics McCabe-s Cyclometric Complexity Measure for Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling Metric values of the software component are used as input attributes to the different types of Neural Network system and reusability of the software component is calculated. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE).

Keywords: Software reusability, Neural Networks, MAE, RMSE, Accuracy.

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Authors: R. Mousli, A. Tazerouti

Abstract:

This work deals with the synthesis and the determination of some surface properties of a new anionic surfactant belonging to sulfonamide derivatives. The interest in this new surfactant is that its behavior in aqueous solution is interesting both from a fundamental and a practice point of view. Indeed, it is well known that this kind of surfactant leads to the formation of bilayer structures, and the microstructures obtained have applications in various fields, ranging from cosmetics to detergents, to biological systems such as cell membranes and bioreactors. The surfactant synthesized from pure n-alkane by photosulfochlorination and derivatized using N-ethanol amine is a mixture of position isomers. These compounds have been analyzed by Gas Chromatography coupled to Mass Spectrometry by Electron Impact mode (GC -MS/IE), and IR. The surface tension measurements were carried out, leading to the determination of the critical micelle concentration (CMC), surface excess and the area occupied per molecule at the interface. The foaming power has also been determined by Bartsch method, and the results have been compared to those of commercial surfactants. The stability of the foam formed has also been evaluated. These compounds show good foaming power characterized in most cases by dry foam.

Keywords: Non ionic surfactants, GC-MS, surface properties, CMC, foam power.

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Authors: Jianbo Hu, Hongbao Wang

Abstract:

The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to control the amount of de-noising in any region of image, according to relative information of local feature scale. Experimental results demonstrate the efficient of the proposed algorithm. Compared with standard Total Variation, our algorithm can better preserve smaller-scaled features and show better performance.

Keywords: Adaptive, de-noising, feature scale, regularizationparameter, Total Variation.

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Authors: M. R. Martinez-Torres, S. L. Toral, M. Olmedilla

Abstract:

Typically, virtual communities exhibit the well-known phenomenon of participation inequality, which means that only a small percentage of users is responsible of the majority of contributions. However, the sustainability of the community requires that the group of active users must be continuously nurtured with new users that gain expertise through a participation process. This paper analyzes the time evolution of Open Source Software (OSS) communities, considering users that join/abandon the community over time and several topological properties of the network when modeled as a social network. More specifically, the paper analyzes the role of those users rejoining the community and their influence in the global characteristics of the network.

Keywords: Open source communities, social network analysis, time series, virtual communities.

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Authors: K. Rattanachan

Abstract:

In sheet metal forming process, raw material mechanical properties are important parameters. This paper is to compare the wall’s incline angle or formability of SS 400 steel and SUS 304 stainless steel in single point incremental forming. The two materials are ferrous base alloyed, which have the different unit cell, mechanical property and chemical composition. They were forming into cone shape specimens having 100 mm diameter with different wall’s incline angle: 90o, 75o and 60o. The investigation was continued until the specimens formed surface facture. The experimental result showed that the smaller the wall incline angle higher the formability with the both materials. The formability limit of the ferrous base alloy was approx. 60o wall’s incline angle. By nature, SS 400 has higher formability than SUS 304. This result can be used as the initial data in designing the single point incremental forming parts.

Keywords: NC incremental forming, Single point incremental forming, Wall incline angle, Formability.

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Authors: Xiaolai Zhang, Haitao Zhang, Qiwen Sun, Weixin Qian, Weiyong Ying

Abstract:

High temperature Fischer-Tropsch synthesis process use fixed fluidized bed as a reactor. In order to understand the flow behavior in the fluidized bed better, the research of how the radial velocity affects the entire flow field is necessary. Laser Doppler Velocimetry (LDV) was used to study the radial velocity distribution along the diameter direction of the cross-section of the particle in a fixed fluidized bed. The velocity in the cross-section is fluctuating within a small range. The direction of the speed is a random phenomenon. In addition to r/R is 1, the axial velocity are more than 6 times of the radial velocity, the radial velocity has little impact on the axial velocity in a fixed fluidized bed.

Keywords: LDV, fixed fluidized bed, velocity, Fischer-Tropsch synthesis.

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Authors: Peyman Shadman Heidari, Mohammad Khorasani

Abstract:

The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive Neural Network Fuzzy Inference System, Wavelet Packet Transform, Response Spectrum.

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Authors: Kati Kõrbe Kaare, Ott Koppel

Abstract:

Transport and logistics are the lifeblood of societies. There is a strong correlation between overall growth in economic activity and growth of transport. The movement of people and goods has the potential for creating wealth and prosperity, therefore the state of transportation infrastructure and especially the condition of road networks is often a governmental priority. The design, building and maintenance of national roads constitute a substantial share of government budgets. Taking into account the magnitude and importance of these investments, the expedience, efficiency and sustainability of these projects are of great public interest. This paper provides an overview of supply chain management principles applied to road construction. In addition, road construction performance measurement systems and ICT solutions are discussed. Road construction in Estonia is analyzed. The authors propose the development of a national performance measurement system for road construction.

Keywords: ICT in road construction, key performance indicators, quality performance measurement, road construction supply chain.

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Authors: Ki-Jin Kim, Sanghoon Park, K. H. Ahn

Abstract:

This paper presents the 20-GHz fractional PLL (Phase Locked Loop) circuit for the next generation Wi-Fi by using 90 nm TSMC process. The newly suggested millimeter wave 16/17 pre-scalar is designed and verified by measurement to make the fractional PLL having a low quantization noise. The operational bandwidth of the 60 GHz system is 15 % of the carrier frequency which requires large value of Kv (VCO control gain) resulting in degradation of phase noise. To solve this problem, this paper adopts AFC (Automatic Frequency Controller) controlled 4-bit millimeter wave VCO with small value of Kv. Also constant Kv is implemented using 4-bit varactor bank. The measured operational bandwidth is 18.2 ~ 23.2 GHz which is 25 % of the carrier frequency. The phase noise of -58 and -96.2 dBc/Hz at 100 KHz and 1 MHz offset is measured respectively. The total power consumption of the PLL is only 30 mW.

Keywords: Millimeter Wave Fractional PLL, Wide band VCO, WPAN Transceiver.

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Authors: Sunmyeng Kim

Abstract:

IEEE 802.11a/b/g standards support multiple transmission rates. Even though the use of multiple transmission rates increase the WLAN capacity, this feature leads to the performance anomaly problem. Cooperative communication was introduced to relieve the performance anomaly problem. Data packets are delivered to the destination much faster through a relay node with high rate than through direct transmission to the destination at low rate. In the legacy cooperative protocols, a source node chooses a relay node only based on the transmission rate. Therefore, they are not so feasible in multi-flow environments since they do not consider the effect of other flows. To alleviate the effect, we propose a new relay node selection algorithm based on the transmission rate and channel contention level. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and delay.

Keywords: Cooperative communications, MAC protocol, Relay node, WLAN.

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Authors: Shweta Kumari, Parmjit S. Panesar, Manab B. Bera

Abstract:

The hydrolysis of lactose using β-galactosidase is one of the most promising biotechnological applications, which has wide range of potential applications in food processing industries. However, due to intracellular location of the yeast enzyme, and expensive extraction methods, the industrial applications of enzymatic hydrolysis processes are being hampered. The use of permeabilization technique can help to overcome the problems associated with enzyme extraction and purification of yeast cells and to develop the economically viable process for the utilization of whole cell biocatalysts in food industries. In the present investigation, standardization of permeabilization process of novel yeast isolate was carried out using a statistical model approach known as Response Surface Methodology (RSM) to achieve maximal b-galactosidase activity. The optimum operating conditions for permeabilization process for optimal β-galactosidase activity obtained by RSM were 1:1 ratio of toluene (25%, v/v) and ethanol (50%, v/v), 25.0 ^oC temperature and treatment time of 12 min, which displayed enzyme activity of 1.71 IU /mg DW.

Keywords: β-galactosidase, optimization, permeabilization, response surface methodology, yeast.

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Authors: A. Pashayev, D. Askerov, R.Sadiqov, A. Samedov, C. Ardil

Abstract:

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade

Keywords: multiconnected systems, method of the boundary integrated equations, splines, neural networks.

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