Search results for: passive optical networks (PON)

Authors: Danilo López, Nelson Vera, Luis Pedraza

Abstract:

This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Keywords: Neural networks, multilayer perceptron, long short-term memory, recurrent neuronal network, mathematical analysis.

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Authors: Ouadoudi Zytoune, Youssef Fakhri, Driss Aboutajdine

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This paper focuses on reducing the power consumption of wireless sensor networks. Therefore, a communication protocol named LEACH (Low-Energy Adaptive Clustering Hierarchy) is modified. We extend LEACHs stochastic cluster-head selection algorithm by a modifying the probability of each node to become cluster-head based on its required energy to transmit to the sink. We present an efficient energy aware routing algorithm for the wireless sensor networks. Our contribution consists in rotation selection of clusterheads considering the remoteness of the nodes to the sink, and then, the network nodes residual energy. This choice allows a best distribution of the transmission energy in the network. The cluster-heads selection algorithm is completely decentralized. Simulation results show that the energy is significantly reduced compared with the previous clustering based routing algorithm for the sensor networks.

Keywords: Wireless Sensor Networks, Energy efficiency, WirelessCommunications, Clustering-based algorithm.

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Authors: H. El Fadili, K. Zenkouar, H. Qjidaa

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This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.

Keywords: Genetic algorithm, Legendre Moments, MEP, Neural Network.

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Authors: Sepehr Aslani, Homayoun Mahdavi-Nasab

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Automated motion detection and tracking is a challenging task in traffic surveillance. In this paper, a system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and image processing techniques to enhance the process. To remove noises, median filter is used and the unwanted objects are removed by applying thresholding algorithms in morphological operations. Also the object type restrictions are set using blob analysis. The results show that the proposed system successfully detects and tracks moving objects in urban videos.

Keywords: Optical flow estimation, moving object detection, tracking, morphological operation, blob analysis.

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Authors: Aiswaria Ramachandran, Balaji Haiharan

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The importance of our country-s communication system is noticeable when a disaster occurs. The communication system in our country includes wired and wireless telephone networks, radio, satellite system and more increasingly internet. Even though our communication system is most extensive and dependable, extreme conditions can put a strain on them. Interoperability between heterogeneous wireless networks can be used to provide efficient communication for emergency first response. IEEE 802.21 specifies Media Independent Handover (MIH) services to enhance the mobile user experience by optimizing handovers between heterogeneous access networks. This paper presents an algorithm to improve congestion control in MIH framework. It is analytically shown that by including time factor in network selection we can optimize congestion in the network.

Keywords: Vertical Handoff, Heterogeneous Networks, MIH

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Authors: Anjana Choudhary

Abstract:

The ad hoc networks are the future of wireless technology as everyone wants fast and accurate error free information so keeping this in mind Bit Error Rate (BER) and power is optimized in this research paper by using the Genetic Algorithm (GA). The digital modulation techniques used for this paper are Binary Phase Shift Keying (BPSK), M-ary Phase Shift Keying (M-ary PSK), and Quadrature Amplitude Modulation (QAM). This work is implemented on Wireless Ad Hoc Networks (WLAN). Then it is analyze which modulation technique is performing well to optimize the BER and power of WLAN.

Keywords: Bit Error Rate, Genetic Algorithm, Power, Phase Shift Keying, Quadrature Amplitude Modulation, Signal to Noise Ratio, Wireless Ad Hoc Networks.

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Authors: Adnene Arbi, Chaouki Aouiti, Abderrahmane Touati

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In this paper, we consider the global exponential stability of the equilibrium point of Hopfield neural networks with delays and impulsive perturbation. Some new exponential stability criteria of the system are derived by using the Lyapunov functional method and the linear matrix inequality approach for estimating the upper bound of the derivative of Lyapunov functional. Finally, we illustrate two numerical examples showing the effectiveness of our theoretical results.

Keywords: Hopfield Neural Networks, Exponential stability.

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Authors: Pierre Abou-Haila, Richard Hall, Mark Dawes

Abstract:

Instead of representing individual cognition only, population cognition is represented using artificial neural networks whilst maintaining individuality. This population network trains continuously, simulating adaptation. An implementation of two coexisting populations is compared to the Lotka-Volterra model of predator-prey interaction. Applications include multi-agent systems such as artificial life or computer games.

Keywords: Collective unconsciousness, neural networks, adaptation, predator-prey simulation.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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Wireless sensor network can be applied to both abominable and military environments. A primary goal in the design of wireless sensor networks is lifetime maximization, constrained by the energy capacity of batteries. One well-known method to reduce energy consumption in such networks is data aggregation. Providing efcient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present privacy-preserving data aggregation scheme for additive aggregation functions. The Cluster-based Private Data Aggregation (CPDA)leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes.

Keywords: Aggregation, Clustering, Query Processing.

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Authors: Barbara Kilosanidze, George Kakauridze, Levan Nadareishvili, Yuri Mshvenieradze

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A new method for determining the distribution of birefringence and linear dichroism in optical polymer materials is presented. The method is based on the use of polarizationholographic diffraction grating that forms an orthogonal circular basis in the process of diffraction of probing laser beam on the grating. The intensities ratio of the orders of diffraction on this grating enables the value of birefringence and linear dichroism in the sample to be determined. The distribution of birefringence in the sample is determined by scanning with a circularly polarized beam with a wavelength far from the absorption band of the material. If the scanning is carried out by probing beam with the wavelength near to a maximum of the absorption band of the chromophore then the distribution of linear dichroism can be determined. An appropriate theoretical model of this method is presented. A laboratory setup was created for the proposed method. An optical scheme of the laboratory setup is presented. The results of measurement in polymer films with two-dimensional gradient distribution of birefringence and linear dichroism are discussed.

Keywords: Birefringence, graded oriented polymers, linear dichroism, optical polymers, optical anisotropy, polarization-holographic grating,

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Authors: H.-G. Herrmann, M. Schwarz, J. Summa, F. Grossmann

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In this work, different non-destructive testing methods for the characterization of defects and interfaces are presented. It is shown that, by means of active thermography, defects in the interface and in the carbon fiber reinforced polymer (CFRP) itself can be detected and determined. The bonding of metal and thermoplastic can be characterized very well by ultrasonic testing with electromagnetic acoustic transducers (EMAT). Mechanical testing is combined with passive thermography to correlate mechanical values with the defect-size. There is also a comparison between active and passive thermography. Mechanical testing shows the influence of different defects. Furthermore, a correlation of defect-size and loading to rupture was performed.

 

Keywords: Defect evaluation, EMAT, mechanical testing, thermography.

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Authors: V. Prasannavenkadesan, A. Elango, S. Chockalingam

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During machining process, chatter is an unavoidable phenomenon. Boring bars possess the cantilever shape and due to this, it is subjected to chatter. The adverse effect of chatter includes the increase in temperature which will leads to excess tool wear. To overcome these problems, in this investigation, Cartridge brass (Cu – 70% and Zn – 30%) is passively fixed on the boring bar and also clearance is provided in order to reduce the displacement, tool wear and cutting temperature. A conventional all geared lathe is attached with vibrometer and pyrometer is used to measure the displacement and temperature. The influence of input parameters such as cutting speed, depth of cut and clearance on temperature, tool wear and displacement are investigated for various cutting conditions. From the result, the optimum conditions to obtain better damping in boring process for chatter reduction is identified.

Keywords: Boring, chatter, mass damping, passive damping.

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Authors: Kavi K. Khedo, R. K. Subramanian

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Wireless sensor networks (WSN) are currently receiving significant attention due to their unlimited potential. These networks are used for various applications, such as habitat monitoring, automation, agriculture, and security. The efficient nodeenergy utilization is one of important performance factors in wireless sensor networks because sensor nodes operate with limited battery power. In this paper, we proposed the MiSense hierarchical cluster based routing algorithm (MiCRA) to extend the lifetime of sensor networks and to maintain a balanced energy consumption of nodes. MiCRA is an extension of the HEED algorithm with two levels of cluster heads. The performance of the proposed protocol has been examined and evaluated through a simulation study. The simulation results clearly show that MiCRA has a better performance in terms of lifetime than HEED. Indeed, MiCRA our proposed protocol can effectively extend the network lifetime without other critical overheads and performance degradation. It has been noted that there is about 35% of energy saving for MiCRA during the clustering process and 65% energy savings during the routing process compared to the HEED algorithm.

Keywords: Clustering algorithm, energy consumption, hierarchical model, sensor networks.

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Authors: A. Melka, N. Slater, A. Mualem, Y. Louzoun

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Networks are often presented as containing a “core” and a “periphery.” The existence of a core suggests that some vertices are central and form the skeleton of the network, to which all other vertices are connected. An alternative view of graphs is through communities. Multiple measures have been proposed for dense communities in graphs, the most classical being k-cliques, k-cores, and k-plexes, all presenting groups of tightly connected vertices. We here show that the edge number thresholds for such communities to emerge and for their percolation into a single dense connectivity component are very close, in all networks studied. These percolating cliques produce a natural core and periphery structure. This result is generic and is tested in configuration models and in real-world networks. This is also true for k-cores and k-plexes. Thus, the emergence of this connectedness among communities leading to a core is not dependent on some specific mechanism but a direct result of the natural percolation of dense communities.

Keywords: Networks, cliques, percolation, core structure, phase transition.

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Authors: Seyed Fazel Ziaei Asl, Ali Karami, Gholamreza Ashari, Azam Behrang, Arezoo Assareh, N.Hedayat

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Predict daily global solar radiation (GSR) based on meteorological variables, using Multi-layer perceptron (MLP) neural networks is the main objective of this study. Daily mean air temperature, relative humidity, sunshine hours, evaporation, wind speed, and soil temperature values between 2002 and 2006 for Dezful city in Iran (32° 16' N, 48° 25' E), are used in this study. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data.

Keywords: Multi-layer Perceptron (MLP) Neural Networks;Global Solar Radiation (GSR), Meteorological Parameters, Prediction.

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Authors: Tolga Yazici

Abstract:

As a matter of the fact that online social networks like Twitter, Facebook and MySpace have experienced an extensive growth in recent years. Social media offers individuals with a tool for communicating and interacting with one another. These social networks enable people to stay in touch with other people and express themselves. This process makes the users of online social networks active creators of content rather than being only consumers of traditional media. That’s why millions of people show strong desire to learn the methods and tools of digital content production and necessary communication skills. However, the booming interest in communication and interaction through online social networks and high level of eagerness to invent and implement the ways to participate in content production raise some privacy and security concerns. This presentation aims to open the assumed revolutionary, democratic and liberating nature of the online social media up for discussion by reviewing some recent political developments in Turkey. Firstly, the role of Internet and online social networks in mobilizing collective movements through social interactions and communications will be questioned. Secondly, some cases from Gezi and Okmeydanı Protests and also December 17-25 period will be presented in order to illustrate misinformation and manipulation in social media and violation of individual privacy through online social networks in order to damage social unity and stability contradictory to democratic nature of online social networking.

Keywords: Online, social media networks, democratic participation, social polarization, privacy of individuals, Turkey.

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Authors: Sikder Mohammad Faruk, Mir Mofajjal Hossain, Muhibul Haque Bhuyan

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In this investigative research paper, we have presented the simulation results of a three-phase rectifier circuit to improve the input side current using the passive filters, such as capacitors and inductors at the output and input terminals of the rectifier circuit respectively. All simulation works were performed in a personal computer using the PSPICE simulator software, which is a virtual circuit design and simulation software package. The output voltages and currents were measured across a resistive load of 1 k. We observed that the output voltage levels, input current wave shapes, harmonic contents through the harmonic spectrum, and total harmonic distortion improved due to the use of such filters.

Keywords: input current wave, three-phase rectifier, passive filter, PSPICE Simulation

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Authors: Ramin Yousefi, Muhamad. Rasat. Muhamad

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We investigated a modified thermal evaporation method in the growth process of ZnO nanowires. ZnO nanowires were fabricated on p-type silicon substrates without using a metal catalyst. A simple horizontal double-tube system along with chemical vapor diffusion of the precursor was used to grow the ZnO nanowires. The substrates were placed in different temperature zones, and ZnO nanowires with different diameters were obtained for the different substrate temperatures. In addition to the nanowires, ZnO microdiscs with different diameters were obtained on another substrate, which was placed at a lower temperature than the other substrates. The optical properties and crystalline quality of the ZnO nanowires and microdiscs were characterized by room temperature photoluminescence (PL) and Raman spectrometers. The PL and Raman studies demonstrated that the ZnO nanowires and microdiscs grown using such set-up had good crystallinity with excellent optical properties. Rectifying behavior of ZnO/Si heterostructures was characterized by a simple DC circuit.

Keywords: ZnO nano and microstructures, Photoluminescence, Raman, Rectifying behavior.

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Authors: Rio G. L. D'Souza, K. Chandra Sekaran, A. Kandasamy

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The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.

Keywords: Evolutionary computing, gene expression analysis, gene networks, microarray data analysis, phenomic algorithms.

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Authors: Naveen Chauhan, L.K. Awasthi, Narottam chand, Vivek Katiyar, Ankit Chug

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Mobile ad-hoc networks (MANETs) are a form of wireless networks which do not require a base station for providing network connectivity. Mobile ad-hoc networks have many characteristics which distinguish them from other wireless networks which make routing in such networks a challenging task. Cluster based routing is one of the routing schemes for MANETs in which various clusters of mobile nodes are formed with each cluster having its own clusterhead which is responsible for routing among clusters. In this paper we have proposed and implemented a distributed weighted clustering algorithm for MANETs. This approach is based on combined weight metric that takes into account several system parameters like the node degree, transmission range, energy and mobility of the nodes. We have evaluated the performance of proposed scheme through simulation in various network situations. Simulation results show that proposed scheme outperforms the original distributed weighted clustering algorithm (DWCA).

Keywords: MANETs, Clustering, Routing, WirelessCommunication, Distributed Clustering

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Authors: Bhavneet Sidhu, Hardeep Singh

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Cellular networks provide voice and data services to the users with mobility. To deliver services to the mobile users, the cellular network is capable of tracking the locations of the users, and allowing user movement during the conversations. These capabilities are achieved by the location management. Location management in mobile communication systems is concerned with those network functions necessary to allow the users to be reached wherever they are in the network coverage area. In a cellular network, a service coverage area is divided into smaller areas of hexagonal shape, referred to as cells. The cellular concept was introduced to reuse the radio frequency. Continued expansion of cellular networks, coupled with an increasingly restricted mobile spectrum, has established the reduction of communication overhead as a highly important issue. Much of this traffic is used in determining the precise location of individual users when relaying calls, with the field of location management aiming to reduce this overhead through prediction of user location. This paper describes and compares various location management schemes in the cellular networks.

Keywords: Cellular Networks, Location Area, MobilityManagement, Paging.

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: Cognitive radio, neural network, prediction, primary user.

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Authors: Ankita Gaur, Mouli Karmakar, Shyam

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In this study, a silicon solar cell has been modeled and analyzed to enhance its performance by improving the optical properties using an anti-reflecting coating (ARC). The dynamic optical reflectance, transmittance along with the net transmissivity absorptivity product of each layer are assessed as per the diurnal variation of the angle of incidence using MATLAB 2019. The model is tested with various anti-reflective coatings and the performance has also been compared with uncoated cells. ARC improves the optical transmittance of the photon. Higher transmittance of ⁓96.57% with lowest reflectance of ⁓ 1.74% at 12.00 hours was obtained with MgF2 coated silicon cells. The electrical efficiency of the configured solar cell was evaluated for a composite climate of New Delhi, India, for all weather conditions. The annual electricity generation for anti-reflective coated and uncoated crystalline silicon PV Module was observed to be 103.14 KWh and 99.51 KWh, respectively.

Keywords: Anti-reflecting coating, electrical efficiency, reflectance, solar cell, transmittance.

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Authors: S. Balaji, N. Revathi

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Connected dominating set (CDS) problem in unit disk graph has signi£cant impact on an ef£cient design of routing protocols in wireless sensor networks, where the searching space for a route is reduced to nodes in the set. A set is dominating if all the nodes in the system are either in the set or neighbors of nodes in the set. In this paper, a simple and ef£cient heuristic method is proposed for £nding a minimum connected dominating set (MCDS) in ad hoc wireless networks based on the new parameter support of vertices. With this parameter the proposed heuristic approach effectively £nds the MCDS of a graph. Extensive computational experiments show that the proposed approach outperforms the recently proposed heuristics found in the literature for the MCD

Keywords: ad hoc wireless networks, dominating sets, unit disk graphs, heuristic.

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Authors: Marwan Ihsan Shukur, Lee Sheng Chyan, Vooi Voon Yap

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Wireless sensor networks is an emerging technology that serves as environment monitors in many applications. Yet these miniatures suffer from constrained resources in terms of computation capabilities and energy resources. Limited energy resource in these nodes demands an efficient consumption of that resource either by developing the modules itself or by providing an efficient communication protocols. This paper presents a comprehensive summarization and a comparative study of the available MAC protocols proposed for Wireless Sensor Networks showing their capabilities and efficiency in terms of energy consumption and delay guarantee.

Keywords: MAC (Medium Access Control), SEA (Simple EnergyAware), WSNs (Wireless Sensor Nodes or Networks) RTS (RequestTo Send), CTS (Clear To Send), SYNCH (Synchronize), NS2(Network Simulator 2).

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Authors: Mahmood Q.K. Ghaznavi, Martin Perry, Paul Toulson, Keri Logan

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The importance of nurturing, accumulating, and efficiently deploying knowledge resources through formal structures and organisational mechanisms is well understood. Recent trends in knowledge management (KM) highlight that the effective creation and transfer of knowledge can also rely upon extra-organisational channels, such as, informal networks. The perception exists that the role of informal networks in knowledge creation and performance has been underestimated in the organisational context. Literature indicates that many managers fail to comprehend and successfully exploit the potential role of informal networks to create value for their organisations. This paper investigates: 1) whether managers share work-specific knowledge with informal contacts within and outside organisational boundaries; and 2) what do they think is the importance of this knowledge collaboration in their learning and work outcomes.

Keywords: Informal network, knowledge management, knowledge sharing, performance.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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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

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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: Chokri Baccouch, Chayma Bahhar, Hedi Sakli, Nizar Sakli, Taoufik Aguili

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This paper presents a hybrid system solar cell antenna for 5G mobile communications networks. We propose here a solar cell antenna with either a front face collection grid or mesh patch. The solar cell antenna of our contribution combines both optical and radiofrequency signals. Thus, we propose two solar cell antenna structures in the frequency bands of future 5G standard respectively in both 2.6 and 3.5 GHz bands. Simulation using the Advanced Design System (ADS) software allows us to analyze and determine the antenna parameters proposed in this work such as the reflection coefficient (S11), gain, directivity and radiated power.

Keywords: Patch antenna, solar cell, DC, RF, 5G.

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Authors: Engin Eyceyurt, Josko Zec

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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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