Search results for: small cell networks.

Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: Mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi

Abstract:

This paper proposes a comparison between wavelet neural networks (WNN), RBF neural network and polynomial approximation in term of 1-D and 2-D functions approximation. We present a novel wavelet neural network, based on Beta wavelets, for 1-D and 2-D functions approximation. Our purpose is to approximate an unknown function f: Rn - R from scattered samples (xi; y = f(xi)) i=1....n, where first, we have little a priori knowledge on the unknown function f: it lives in some infinite dimensional smooth function space and second the function approximation process is performed iteratively: each new measure on the function (xi; f(xi)) is used to compute a new estimate f as an approximation of the function f. Simulation results are demonstrated to validate the generalization ability and efficiency of the proposed Beta wavelet network.

Keywords: Beta wavelets networks, RBF neural network, training algorithms, MSE, 1-D, 2D function approximation.

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Authors: Engin Eyceyurt, Josko Zec

Abstract:

The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: Drive test, LTE, machine learning, uplink throughput prediction.

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Authors: Zhanli Zhang, Wei Chen, Xin Jiang, Lili Ma, Shaoting Tang, Zhiming Zheng

Abstract:

A new class of percolation model in complex networks, in which nodes are characterized by hidden variables reflecting the properties of nodes and the occupied probability of each link is determined by the hidden variables of the end nodes, is studied in this paper. By the mean field theory, the analytical expressions for the phase of percolation transition is deduced. It is determined by the distribution of the hidden variables for the nodes and the occupied probability between pairs of them. Moreover, the analytical expressions obtained are checked by means of numerical simulations on a particular model. Besides, the general model can be applied to describe and control practical diffusion models, such as disease diffusion model, scientists cooperation networks, and so on.

Keywords: complex networks, percolation transition, hidden variable, occupied probability.

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Authors: Xinhua Zhang, Kelin Li

Abstract:

In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural networks with timevarying delays and reaction-diffusion is considered. By utilizing suitable Lyapunov-Krasovskii funcational, the inequality technique and stochastic analysis technique, some sufficient conditions ensuring global exponential stability of equilibrium point for impulsive stochastic fuzzy cellular neural networks with time-varying delays and diffusion are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of fuzzy neural networks. An example is given to show the effectiveness of the obtained results.

Keywords: Exponential stability, stochastic fuzzy cellular neural networks, time-varying delays, impulses, reaction-diffusion terms.

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Authors: N. David, H. O. Gao

Abstract:

Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: Air pollution, commercial microwave links, rainfall.

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Authors: Anna Vildová, H. Hendrychová, J. Kubeš, L. Tůmová

Abstract:

The abiotic elicitation is one of the methods for increasing the secondary metabolites production in plant tissue cultures and it seems to be more effective than traditional strategies. This study verified the use of silver nitrate as elicitor to enhance flavonolignans and flavonoid taxifolin production in suspension culture of Sylibum marianum (L.) Gaertn. Silver nitrate in various concentrations (5.887.10-3 mol/L, 5.887.10-4 mol/L, 5.887.10-5 mol/L) was used as elicitor. The content of secondary metabolites in cell suspension cultures was determined by high performance liquid chromatography. The samples were taken after 6, 12, 24, 48, 72 and 168 hours of treatment. The highest content of taxifolin production (2.2 mg.g-1) in cell suspension culture of Silybum marianum (L.) Gaertn. was detected after silver nitrate (5.887.10-4 mol/L) treatment and 72 h application. Flavonolignans such as silybinA, silybin B, silydianin, silychristin, isosilybin A, isosilybin B were not produced by cell suspension culture of S. marianum after elicitor treatment. Our results show that the secondarymetabolites could be released from S. marianum cells into the nutrient medium by changed permeability of cell wall.

Keywords: Silybum marianum (L.) Gaertn., elicitation, silver nitrate, taxifolin.

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Authors: Ahmed K. Hasan, A. A. Zaidan, Anas Majeed, B. B. Zaidan, Rosli Salleh, Omar Zakaria, Ali Zuheir

Abstract:

Wireless mesh networks based on IEEE 802.11 technology are a scalable and efficient solution for next generation wireless networking to provide wide-area wideband internet access to a significant number of users. The deployment of these wireless mesh networks may be within different authorities and without any planning, they are potentially overlapped partially or completely in the same service area. The aim of the proposed model is design a new model to Enhancement Throughput of Unplanned Wireless Mesh Networks Deployment Using Partitioning Hierarchical Cluster (PHC), the unplanned deployment of WMNs are determinates there performance. We use throughput optimization approach to model the unplanned WMNs deployment problem based on partitioning hierarchical cluster (PHC) based architecture, in this paper the researcher used bridge node by allowing interworking traffic between these WMNs as solution for performance degradation.

Keywords: Wireless Mesh Networks, 802.11s Internetworking, partitioning Hierarchical Cluste.

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Authors: Samir Osman M., Mohammed Hassan S.

Abstract:

Sample of CsAg2I3 was prepared by solid state reaction. Then, microstructure parameters of this sample have been determined using wide angle X-ray scattering WAXS method. As well as, Cell parameters of crystal structure have been refined using CHEKCELL program. This analysis states that the lattice intrinsic strainof the sample is so small and the crystal size is on the order of 559Å.

Keywords: WAXS, Microstructure parameters, super-ionic conductor.

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Authors: Zixin Liu, Huawei Yang, Fangwei Chen

Abstract:

This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis and inequality technique. These conditions are expressed in the form of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. The feedback controller used in this paper is more general than those used in previous literatures. One simulation example is presented to demonstrate the effectiveness of the derived results.

Keywords: Exponential synchronization, stochastic analysis, chaotic neural networks, neutral type system.

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Authors: Benedek Kovacs, Janos Toth

Abstract:

Solutions are proposed for the central problem of estimating the reaction rate coefficients in homogeneous kinetics. The first is based upon the fact that the right hand side of a kinetic differential equation is linear in the rate constants, whereas the second one uses the technique of neural networks. This second one is discussed deeply and its advantages, disadvantages and conditions of applicability are analyzed in the mirror of the first one. Numerical analysis carried out on practical models using simulated data, and our programs written in Mathematica.

Keywords: Neural networks, parameter estimation, linear regression, kinetic models, reaction rate coefficients.

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Authors: Vinay Chandwani, Vinay Agrawal, Ravindra Nagar

Abstract:

Artificial Neural Networks (ANN) trained using backpropagation (BP) algorithm are commonly used for modeling material behavior associated with non-linear, complex or unknown interactions among the material constituents. Despite multidisciplinary applications of back-propagation neural networks (BPNN), the BP algorithm possesses the inherent drawback of getting trapped in local minima and slowly converging to a global optimum. The paper present a hybrid artificial neural networks and genetic algorithm approach for modeling slump of ready mix concrete based on its design mix constituents. Genetic algorithms (GA) global search is employed for evolving the initial weights and biases for training of neural networks, which are further fine tuned using the BP algorithm. The study showed that, hybrid ANN-GA model provided consistent predictions in comparison to commonly used BPNN model. In comparison to BPNN model, the hybrid ANNGA model was able to reach the desired performance goal quickly. Apart from the modeling slump of ready mix concrete, the synaptic weights of neural networks were harnessed for analyzing the relative importance of concrete design mix constituents on the slump value. The sand and water constituents of the concrete design mix were found to exhibit maximum importance on the concrete slump value.

Keywords: Artificial neural networks, Genetic algorithms, Back-propagation algorithm, Ready Mix Concrete, Slump value.

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Authors: C. N. Vanitha, M. Usha

Abstract:

In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: Neural networks, pattern learning, security, wireless sensor networks.

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Authors: Aytekin A.O., Morimura S.

Abstract:

Chitosan is a biopolymer composed of glucosamine and N-acetyl glucosamine. Solubility and viscosity pose problems in some applications. These problems can be overcome with unique modifications. In this study, firstly, chitosan was modified by caffeic acid and thioglycolic acid, separately. Then, growing effects of these modified polymers was observed in U937 cell line. Caffeic acid is a phenolic compound and its modifications act carcinogenic inhibitors in drugs. Thiolated chitosans are commonly being used for drugdelivery systems in various routes, because of enhancing mucoadhesiveness property. U937 cell line was used model cell for leukaemia. Modifications were achieved by 1 – 15 % binding range. Increasing binding ratios showed higher radical-scavenging activity and reducing cell growth, in compared to native chitosan. Caffeic acid modifications showed higher radical-scavenging activity than thiolated chitosans at the same concentrations. Caffeic acid and thioglycolic acid modifications inhibited growth of U937, effectively.

Keywords: Chitosan, U937 cell, caffeic acid, thioglycolic acid

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Authors: M. S. Kilic, S. Korkut, B. Hazer

Abstract:

Newly synthesized Polypropylene-g-Polyethylene glycol polymer was first time used for a compartment-less enzymatic fuel cell. Working electrodes based on Polypropylene-g-Polyethylene glycol were operated as unmediated and mediated system (with ferrocene and gold/cobalt oxide nanoparticles). Glucose oxidase and bilirubin oxidase was selected as anodic and cathodic enzyme, respectively. Glucose was used as fuel in a single-compartment and membrane-less cell. Maximum power density was obtained as 0.65 nW cm-2, 65 nW cm-2 and 23500 nW cm-2 from the unmediated, ferrocene and gold/cobalt oxide modified polymeric film, respectively. Power density was calculated to be ~16000 nW cm-2 for undiluted wastewater sample with gold/cobalt oxide nanoparticles including system.

Keywords: Bilirubin oxidase, Enzymatic fuel cell, Glucose oxidase, Nanoparticles.

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Authors: Razvan Bocu, Dr Sabin Tabirca

Abstract:

The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents the latest authors- achievements regarding the analysis of the networks of proteins (interactome networks), by computing more efficiently the betweenness centrality measure. The paper introduces the concept of betweenness centrality, and then describes how betweenness computation can help the interactome net- work analysis. Current sequential implementations for the between- ness computation do not perform satisfactory in terms of execution times. The paper-s main contribution is centered towards introducing a speedup technique for the betweenness computation, based on modified shortest path algorithms for sparse graphs. Three optimized generic algorithms for betweenness computation are described and implemented, and their performance tested against real biological data, which is part of the IntAct dataset.

Keywords: Betweenness centrality, interactome networks, protein-protein interactions, sub-communities, sparse networks, speedup tech-nique, IntAct.

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Authors: Joo-Han Kim, Jung-Moo Seo, Ha Gyeong Sung, Se Hyun Rhyu

Abstract:

This study presents a blower for air management system of fuel cell modules. A blower is composed of BLDC motor and impeller. Magnetic equivalent circuit model and finite element analysis are used to design the motor, and an improved structure is considered to reduce a mechanical loss induced from bearing units. Finally, air blower system combined with the motor and an impeller is manufactured and output properties, such as an air pressure and an amount of flowing air, are measured. Through the experimental results, a validity of the simulated one is confirmed.

Keywords: Fuel cell modules, BLDC motor, Impeller, Air management

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Authors: S. H. Oudjana, A. Hellal, I. Hadj Mahammed

Abstract:

Photovoltaic power generation forecasting is an important task in renewable energy power system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic power generation forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic power generation forecasting error.

Keywords: Photovoltaic Power Forecasting, Regression, Neural Networks.

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Authors: Mohammadreza Amini, Omid Moradtalab, Ebadollah Zohrevandi

Abstract:

In real-time networks a large number of application programs are relying on video data and heterogeneous data transmission techniques. The aim of this research is presenting a method for end-to-end vouch quality service in surface applicationlayer for sending video data in comparison form in wireless heterogeneous networks. This method tries to improve the video sending over the wireless heterogeneous networks with used techniques in surface layer, link and application. The offered method is showing a considerable improvement in quality observing by user. In addition to this, other specifications such as shortage of data load that had require to resending and limited the relation period length to require time for second data sending, help to be used the offered method in the wireless devices that have a limited energy. The presented method and the achieved improvement is simulated and presented in the NS-2 software.

Keywords: Heterogeneous wireless networks, adaptation mechanism, multi-level, Handoff, stop mechanism, graceful degrades, application layer.

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Authors: M. Sangeetha, A. Sabari, T. Shanthi Priya

Abstract:

Recent advances in wireless networking technologies introduce several energy aware routing protocols in sensor networks. Such protocols aim to extend the lifetime of network by reducing the energy consumption of nodes. Many researchers are looking for certain challenges that are predominant in the grounds of energy consumption. One such protocol that addresses this energy consumption issue is ‘Cluster based hierarchical routing protocol’. In this paper, we intend to discuss some of the major hierarchical routing protocols adhering towards sensor networks. Furthermore, we examine and compare several aspects and characteristics of few widely explored hierarchical clustering protocols, and its operations in wireless sensor networks (WSN). This paper also presents a discussion on the future research topics and the challenges of hierarchical clustering in WSNs.

Keywords: Clustering, Energy Efficiency, Hierarchical routing, Wireless sensor networks.

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Authors: Chun Wen, Tingzhu Huang

Abstract:

We present a new numerical method for the computation of the steady-state solution of Markov chains. Theoretical analyses show that the proposed method, with a contraction factor α, converges to the one-dimensional null space of singular linear systems of the form Ax = 0. Numerical experiments are used to illustrate the effectiveness of the proposed method, with applications to a class of interesting models in the domain of tandem queueing networks.

Keywords: Markov chains, tandem queueing networks, convergence, effectiveness.

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Authors: U. Bottigli, M.Carpinelli, P.L. Fiori, B. Golosio, A. Marras, G. L. Masala, P. Oliva

Abstract:

The counting process of cell colonies is always a long and laborious process that is dependent on the judgment and ability of the operator. The judgment of the operator in counting can vary in relation to fatigue. Moreover, since this activity is time consuming it can limit the usable number of dishes for each experiment. For these purposes, it is necessary that an automatic system of cell colony counting is used. This article introduces a new automatic system of counting based on the elaboration of the digital images of cellular colonies grown on petri dishes. This system is mainly based on the algorithms of region-growing for the recognition of the regions of interest (ROI) in the image and a Sanger neural net for the characterization of such regions. The better final classification is supplied from a Feed-Forward Neural Net (FF-NN) and confronted with the K-Nearest Neighbour (K-NN) and a Linear Discriminative Function (LDF). The preliminary results are shown.

Keywords: Automatic cell counting, neural network, region growing, Sanger net.

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Authors: Qingqing Wang, Shouming Zhong

Abstract:

This paper deals with the problem of delay-dependent stability for neural networks with distributed delays. Some new sufficient condition are derived by constructing a novel Lyapunov-Krasovskii functional approach. The criteria are formulated in terms of a set of linear matrix inequalities, this is convenient for numerically checking the system stability using the powerful MATLAB LMI Toolbox. Moreover, in order to show the stability condition in this paper gives much less conservative results than those in the literature, numerical examples are considered.

Keywords: Neural networks, Globally asymptotic stability , LMI approach, Distributed delays.

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Authors: Ružarovský, Roman, Danišová, Nina, Velíšek, Karol

Abstract:

In this contribution is presented a complex design of individual objects identification in the workplace of intelligent assembly cell. Intelligent assembly cell is situated at Institute of Manufacturing Systems and Applied Mechanics and is used for pneumatic actuator assembly. Pneumatic actuator components are pneumatic roller, cover, piston and spring. Two identification objects alternatives for assembly are designed in the workplace of industrial robot. In the contribution is evaluated and selected suitable alternative for identification – 2D codes reader. The complex design of individual object identification is going out of intelligent manufacturing systems knowledge. Intelligent assembly and manufacturing systems as systems of new generation are gradually loaded in to the mechanical production, when they are removeing human operation out of production process and they also short production times.

Keywords: system, cell, intelligent, mechanics, device

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Authors: Tae-Yeong Lee, Eun-Ju Yoo, Won-Yeong Choi, Young-Woo Park

Abstract:

This paper presents a 24 watts SEPIC converter design and control using microprocessor. SEPIC converter has advantages of a wide input range and miniaturization caused by the low stress at elements. There is also an advantage that the input and output are isolated in MOSFET-off state. This paper presents the PID control through the SEPIC converter transfer function using a DSP and the protective circuit for fuel cell from the over-current and inverse-voltage by using the characteristic of SEPIC converter. Then it derives them through the experiments.

Keywords: DC-DC Converter, Fuel-Cell, Microprocessor Control, Military Converter, SEPIC Converter

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Authors: A. Sokołowska

Abstract:

The study presents a brief and synthetic discussion of selected conclusions resulting from multidimensional and in-depth empirical studies. Its theoretical part presents the assumptions referring to social responsibility management from the perspective of the specific nature of small enterprise functioning, while the empirical part presents the selected dysfunctions and paradoxes in social responsibility management referring to this group of enterprises. The paper is summarized by a short list of the resulting recommendations.

Keywords: Small enterprise, social responsibility management, social responsibility of small enterprise.

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Authors: Lina Paola Orozco-Marín, Yuliet Montoya, John Bustamante

Abstract:

Ischemic events can culminate in acute myocardial infarction with irreversible cardiac lesions that cannot be restored due to the limited regenerative capacity of the heart. Tissue engineering proposes therapeutic alternatives by using biomaterials to resemble the native extracellular medium combined with healthy and functional cells. This research focused on developing a natural thermosensitive hydrogel, its physical-chemical characterization and in vitro biocompatibility determination. Hydrogels’ morphological characterization was carried out through scanning electron microscopy and its chemical characterization by employing Infrared Spectroscopy technic. In addition, the biocompatibility was determined using fetal human ventricular cardiomyocytes cell line RL-14 and the MTT cytotoxicity test according to the ISO 10993-5 standard. Four biocompatible and thermosensitive hydrogels were obtained with a three-dimensional internal structure and two gelation times. The results show the potential of the hydrogel to increase the cell survival rate to the cardiac cell therapies under investigation and lay the foundations to continue with its characterization and biological evaluation both in vitro and in vivo models.

Keywords: cardiac cell therapy, cardiac ischemia, natural polymers, thermosensitive hydrogel

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Authors: Sanjeev Gupta, Mayank Dave

Abstract:

The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.

Keywords: Cluster head, data reliability, real time communication, wireless sensor networks.

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Authors: Hazem M. El-Bakry

Abstract:

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.

Keywords: Fast Character Detection, Neural Processors, Cross Correlation, Image Normalization, Parallel Processing.

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Authors: Jiraporn Rojtinnakorn

Abstract:

ICAM-2 (intercellular adhesion molecule 2) or CD102 (Cluster of Differentiation 102) is type I transmembrane glycoproteins, composing 2-9 immunoglobulin-like C2-type domains. ICAM-2 plays the particular role in immune response and cell surveillance. It is concerned in innate and specific immunity, cell survival signal, apoptosis, and anticancer. EST clone of ICAM-2, from P. gigas blood cell EST libraries, showed high identity to human ICAM-2 (92%) with conserve region of ICAM N-terminal domain and part of Ig superfamily. Gene and protein of ICAM-2 has been founded in mammals. This is the first report of ICAM-2 in fish

Keywords: ICAM-2, CD102, Pangasianodon gigas, antitumor.

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