Search results for: sensor networks.

Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova

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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterise a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: Complexity, hypergraphs, reciprocity, metabolism.

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Authors: Rajendra Prasad Mahapatra, K. Vimal Kumar

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There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..

Keywords: Panoramic sensors, Blind spot, Convex lens, Computer Vision, Sonar.

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Authors: K. Chethana, A. S. Guru Prasad, S. N. Omkar, B. Vadiraj, S. Asokan

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This paper describes an ab-initio design, development and calibration results of an Optical Sensor Ground Reaction Force Measurement Platform (OSGRFP) for gait and geriatric studies. The developed system employs an array of FBG sensors to measure the respective ground reaction forces from all three axes (X, Y and Z), which are perpendicular to each other. The novelty of this work is two folded. One is in its uniqueness to resolve the tri axial resultant forces during the stance in to the respective pure axis loads and the other is the applicability of inherently advantageous FBG sensors which are most suitable for biomechanical instrumentation. To validate the response of the FBG sensors installed in OSGRFP and to measure the cross sensitivity of the force applied in other directions, load sensors with indicators are used. Further in this work, relevant mathematical formulations are presented for extracting respective ground reaction forces from wavelength shifts/strain of FBG sensors on the OSGRFP. The result of this device has implications in understanding the foot function, identifying issues in gait cycle and measuring discrepancies between left and right foot. The device also provides a method to quantify and compare relative postural stability of different subjects under test, which has implications in post-surgical rehabilitation, geriatrics and optimizing training protocols for sports personnel.

Keywords: Balance, stability, Gait analysis, FBG applications, optical sensor ground reaction force platform.

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: Artificial Neural Network, Decision Support System, drug abuse, drug addiction, Multilayer Perceptron.

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Authors: Felix Dobslaw

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In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

Keywords: Parameter-Tuning, Metaheuristics, Design of Experiments, Artificial Neural Networks.

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Authors: Kah-Hyong Chang, Xin Liu, Jia Hao Cheong, Saisundar Sankaranarayanan, Dexing Pang, Hongzhao Zheng

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A digital baseband Application-Specific Integrated Circuit (ASIC) (yclic Redundancy Checkis developed for a microchip transponder to transmit signals and temperature levels from biomedical monitoring devices. The transmission protocol is adapted from the ISO/IEC 11784/85 standard. The module has a decimation filter that employs only a single adder-subtractor in its datapath. The filtered output is coded with cyclic redundancy check and transmitted through backscattering Load Shift Keying (LSK) modulation to a reader. Fabricated using the 0.18-μm CMOS technology, the module occupies 0.116 mm² in chip area (digital baseband: 0.060 mm², decimation filter: 0.056 mm²), and consumes a total of less than 0.9 μW of power (digital baseband: 0.75 μW, decimation filter: 0.14 μW).

Keywords: Biomedical sensor, decimation filter, Radio Frequency Integrated Circuit (RFIC) baseband, temperature sensor.

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Authors: Maidul Islam, Dibakar Roy Chowdhury, Gagan Kumar

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We investigate sensing capabilities of a planar plasmonic THz waveguide. The waveguide is comprised of one dimensional array of periodically arranged sub wavelength scale corrugations in the form of rectangular dimples in order to ensure the plasmonic response. The THz waveguide transmission is observed for polyimide (as thin film) substance filling the dimples. The refractive index of the polyimide film is varied to examine various sensing parameters such as frequency shift, sensitivity and Figure of Merit (FoM) of the fundamental plasmonic resonance supported by the waveguide. In efforts to improve sensing characteristics, we also examine sensing capabilities of a plasmonic waveguide having V shaped corrugations and compare results with that of rectangular dimples. The proposed study could be significant in developing new terahertz sensors with improved sensitivity utilizing the plasmonic waveguides.

Keywords: Terahertz, plasmonic, sensor, sub-wavelength structures.

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Authors: Rani Astya, S.C. Sharma

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The wireless adhoc network is comprised of wireless node which can move freely and are connected among themselves without central infrastructure. Due to the limited transmission range of wireless interfaces, in most cases communication has to be relayed over intermediate nodes. Thus, in such multihop network each node (also called router) is independent, self-reliant and capable to route the messages over the dynamic network topology. Various protocols are reported in this field and it is very difficult to decide the best one. A key issue in deciding which type of routing protocol is best for adhoc networks is the communication overhead incurred by the protocol. In this paper STAR a table driven and DSR on demand protocols based on IEEE 802.11 are analyzed for their performance on different performance measuring metrics versus varying traffic CBR load using QualNet 5.0.2 network simulator.

Keywords: Adhoc networks, wireless networks, CBR, routingprotocols, route discovery, simulation, performance evaluation, MAC, IEEE 802.11, STAR, DSR

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Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs – Sigmoid, ReLU, and Tanh – have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment on multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLU-ReLU) combination. Our results show that on using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: Activation Function, Universal Approximation function, Neural Networks, convergence.

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Authors: Eman S. El-Din, Hesham M. El-Badawy, Salwa H. Elramly

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Whereas cellular wireless communication systems are subject to short-and long-term fading. The effect of wireless channel has largely been ignored in most of the teletraffic assessment researches. In this paper, a mathematical teletraffic model is proposed to estimate blocking and forced termination probabilities of cellular wireless networks as a result of teletraffic behavior as well as the outage of the propagation channel. To evaluate the proposed teletraffic model, gamma inter-arrival and general service time distributions have been considered based on wireless channel fading effect. The performance is evaluated and compared with the classical model. The proposed model is dedicated and investigated in different operational conditions. These conditions will consider not only the arrival rate process, but also, the different faded channels models.

Keywords: Cellular wireless networks, outage probability, traffic model, gamma inter-arrival distribution.

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Authors: Rajoo Pandey

Abstract:

Most of the commonly used blind equalization algorithms are based on the minimization of a nonconvex and nonlinear cost function and a neural network gives smaller residual error as compared to a linear structure. The efficacy of complex valued feedforward neural networks for blind equalization of linear and nonlinear communication channels has been confirmed by many studies. In this paper we present two neural network models for blind equalization of time-varying channels, for M-ary QAM and PSK signals. The complex valued activation functions, suitable for these signal constellations in time-varying environment, are introduced and the learning algorithms based on the CMA cost function are derived. The improved performance of the proposed models is confirmed through computer simulations.

Keywords: Blind Equalization, Neural Networks, Constant Modulus Algorithm, Time-varying channels.

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Authors: Omar Gaci, Stefan Balev

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In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we identify a number of properties of these networks. We compare them to the general small-world network model and we analyze their hierarchical structure.

Keywords: interaction network, protein structure, small-world network.

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Authors: Widodo Budiharto, Michael Yoseph Ricky, Ro'fah Nur Rachmawati

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The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform

Keywords: Adaptive games, neural networks, mobile games, BlackBerry

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Authors: Y. Shpungin

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Estimating the lifetime distribution of computer networks in which nodes and links exist in time and are bound for failure is very useful in various applications. This problem is known to be NP-hard. In this paper we present efficient combinatorial approaches to Monte Carlo estimation of network lifetime distribution. We also present some simulation results.

Keywords: Combinatorial spectrum, Monte Carlo, Networklifetime, Unreliable nodes and edges.

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Authors: Hamdi. A. Awad, Mohamed A. Al-Zorkany

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Developing techniques for mobile robot navigation constitutes one of the major trends in the current research on mobile robotics. This paper develops a local model network (LMN) for mobile robot navigation. The LMN represents the mobile robot by a set of locally valid submodels that are Multi-Layer Perceptrons (MLPs). Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular region. The submodels then are combined in a unified structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the proposed LMN reflect the soundness of the proposed scheme.

Keywords: Mobile Robot Navigation, Neural Networks, Local Model Networks

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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Short-Term Load Forecasting (STLF) plays an important role for the economic and secure operation of power systems. In this paper, Continuous Genetic Algorithm (CGA) is employed to evolve the optimum large neural networks structure and connecting weights for one-day ahead electric load forecasting problem. This study describes the process of developing three layer feed-forward large neural networks for load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. We find good performance for the large neural networks. The proposed methodology gives lower percent errors all the time. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Feed-forward Large Neural Network, Short-TermLoad Forecasting, Continuous Genetic Algorithm.

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Authors: Ebadollah Zohrevandi, Rasoul Roustaei, Omid Moradtalab

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In this paper, we first consider the quality of service problems in heterogeneous wireless networks for sending the video data, which their problem of being real-time is pronounced. At last, we present a method for ensuring the end-to-end quality of service at application layer level for adaptable sending of the video data at heterogeneous wireless networks. To do this, mechanism in different layers has been used. We have used the stop mechanism, the adaptation mechanism and the graceful degrade at the application layer, the multi-level congestion feedback mechanism in the network layer and connection cutting off decision mechanism in the link layer. At the end, the presented method and the achieved improvement is simulated and presented in the NS-2 software.

Keywords: Congestion, Handoff, Heterogeneous wireless networks, Adaptation mechanism, Stop mechanism, Graceful degrade.

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Authors: A. Bahrampour, A. Iadicicco, G. De Luca, M. Giordano, A. Cutolo, L. Monsù Scolaro, A. Cusano

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In this work we report on preliminary analysis of a novel optoelectronic gas sensor based on an optical fiber integrated with a tetrakis(4-sulfonatophenyl)porphyrin (TPPS) thin film. The sensitive materials are selectively deposited on the core region of a fiber tip by UV light induced deposition technique. A simple and cheap process which can be easily extended to different porphyrin derivatives. When the TPPS film on the fiber tip is exposed to acid and/or base vapors, dramatic changes occur in the aggregation structure of the dye molecules in the film, from J- to H-type, resulting in a profound modification of their corresponding reflectance spectra. From the achieved experimental results it is evident that the presence of intense and narrow band peaks in the reflected spectra could be monitored to detect hazardous vapors.

Keywords: Optical fiber sensor, Porphyrins, Thin films UV induced deposition, TPPS.

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Authors: Majid Tolouei-Rad, Peter Kalivitis

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Industrial robots become useless without end-effectors that for many instances are in the form of friction grippers. Commonly friction grippers apply frictional forces to different objects on the basis of programmers- experiences. This puts a limitation on the effectiveness of gripping force that may result in damaging the object. This paper describes various stages of design and development of a low cost sensor-based robotic gripper that would facilitate the task of applying right gripping forces to different objects. The gripper is also equipped with range sensors in order to avoid collisions of the gripper with objects. It is a fully functional automated pick and place gripper which can be used in many industrial applications. Yet it can also be altered or further developed in order to suit a larger number of industrial activities. The current design of gripper could lead to designing completely automated robot grippers able to improve the efficiency and productivity of industrial robots.

Keywords: Control system, end-effector, robot, sensor

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Authors: Marco Bötel, Tobias Gelau, Wendelin Gross

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Supply chain networks are frequently hit by unplanned events which lead to disruptions and cause operational and financial consequences. It is neither possible to avoid disruption risk entirely, nor are network members able to prepare for every possible disruptive event. Therefore a continuity planning should be set up which supports effective operational responses in supply chain networks in times of emergencies. In this research network related degrees of freedom which determine the options for responsive actions are derived from interview data. The findings are further embedded into a common risk management process. The paper provides support for researchers and practitioners to identify the network related options for responsive actions and to determine the need for improving the reaction capabilities.

Keywords: Supply Chain Risk Management, Business Continuity Planning, Degrees of Freedom, Risk Management Process, Mitigation Measures.

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Authors: Motonobu Hattori

Abstract:

In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.

Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network

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Authors: H. Unger, H. Coltzau

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In Peer-to-Peer service networks, where peers offer any kind of publicly available services or applications, intuitive navigation through all services in the network becomes more difficult as the number of services increases. In this article, a concept is discussed that enables users to intuitively browse and use large scale P2P service networks. The concept extends the idea of creating virtual 3D-environments solely based on Peer-to-Peer technologies. Aside from browsing, users shall have the possibility to emphasize services of interest using their own semantic criteria. The appearance of the virtual world shall intuitively reflect network properties that may be of interest for the user. Additionally, the concept comprises options for load- and traffic-balancing. In this article, the requirements concerning the underlying infrastructure and the graphical user interface are defined. First impressions of the appearance of future systems are presented and the next steps towards a prototypical implementation are discussed.

Keywords: Internet Operating System, Peer-To-Peer, Service Exploration

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Authors: Usha Chouhan, K. R. Pardasani

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Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. The process of gene transfer in bacteria and hybridization in plants lead to reticulate networks, therefore, the methods of constructing trees fail in constructing reticulate networks. In this paper a model has been employed to reconstruct phylogenetic network in honey bee. This network represents reticulate evolution in honey bee. The maximum parsimony approach has been used to obtain this reticulate network.

Keywords: Hybridization, HGT, Reticulate networks, Recombination, Species, Parsimony.

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Authors: F. O. Aron, T. O. Olwal, A. Kurien, M. O. Odhiambo

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A considerable amount of energy is consumed during transmission and reception of messages in a wireless mesh network (WMN). Reducing per-node transmission power would greatly increase the network lifetime via power conservation in addition to increasing the network capacity via better spatial bandwidth reuse. In this work, the problem of topology control in a hybrid WMN of heterogeneous wireless devices with varying maximum transmission ranges is considered. A localized distributed topology control algorithm is presented which calculates the optimal transmission power so that (1) network connectivity is maintained (2) node transmission power is reduced to cover only the nearest neighbours (3) networks lifetime is extended. Simulations and analysis of results are carried out in the NS-2 environment to demonstrate the correctness and effectiveness of the proposed algorithm.

Keywords: Topology Control, Wireless Mesh Networks, Backbone, Energy Efficiency, Localized Algorithm.

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Authors: Michal Bidlo, Radek Bidlo, Lukas Sekanina

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A method is presented for the construction of arbitrary even-input sorting networks exhibiting better properties than the networks created using a conventional technique of the same type. The method was discovered by means of a genetic algorithm combined with an application-specific development. Similarly to human inventions in the area of theoretical computer science, the evolved invention was analyzed: its generality was proven and area and time complexities were determined.

Keywords: Development, genetic algorithm, program, sorting network.

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Authors: Ahmed S. Fayed, Umima M. Mansour

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Three polyvinyl chloride membrane sensors were developed for the electrochemical evaluation of ferrous, manganese and zinc ions. The sensors were used for assaying metal ions in cervical mucus (CM) of Egyptian river buffalo-cows (Bubalus bubalis) as their levels vary dependent on cyclical hormone variation during different phases of estrus cycle. The presented sensors are based on using ionophores, β-cyclodextrin (β-CD), hydroxypropyl β-cyclodextrin (HP-β-CD) and sulfocalix-4-arene (SCAL) for sensors 1, 2 and 3 for Fe²⁺, Mn²⁺ and Zn²⁺, respectively. Dioctyl phthalate (DOP) was used as the plasticizer in a polymeric matrix of polyvinylchloride (PVC). For increasing the selectivity and sensitivity of the sensors, each sensor was enriched with a suitable complexing agent, which enhanced the sensor’s response. For sensor 1, β-CD was mixed with bathophenanthroline; for sensor 2, porphyrin was incorporated with HP-β-CD; while for sensor 3, oxine was the used complexing agent with SCAL. Linear responses of 10^-7-10^-2 M with cationic slopes of 53.46, 45.01 and 50.96 over pH range 4-8 were obtained using coated graphite sensors for ferrous, manganese and zinc ionic solutions, respectively. The three sensors were validated, according to the IUPAC guidelines. The obtained results by the presented potentiometric procedures were statistically analyzed and compared with those obtained by atomic absorption spectrophotometric method (AAS). No significant differences for either accuracy or precision were observed between the two techniques. Successful application for the determination of the three studied cations in CM, for the purpose to determine the proper time for artificial insemination (AI) was achieved. The results were compared with those obtained upon analyzing the samples by AAS. Proper detection of estrus and correct time of AI was necessary to maximize the production of buffaloes. In this experiment, 30 multi-parous buffalo-cows were in second to third lactation and weighting 415-530 kg, and were synchronized with OVSynch protocol. Samples were taken in three times around ovulation, on day 8 of OVSynch protocol, on day 9 (20 h before AI) and on day 10 (1 h before AI). Beside analysis of trace elements (Fe²⁺, Mn²⁺ and Zn²⁺) in CM using the three sensors, the samples were analyzed for the three cations and also Cu²⁺ by AAS in the CM samples and blood samples. The results obtained were correlated with hormonal analysis of serum samples and ultrasonography for the purpose of determining of the optimum time of AI. The results showed significant differences and powerful correlation with Zn²⁺ composition of CM during heat phase and the ovulation time, indicating that the parameter could be used as a tool to decide optimal time of AI in buffalo-cows.

Keywords: PVC sensors, buffalo-cows, cyclodextrins, atomic absorption spectrophotometry, artificial insemination, OVSynch protocol.

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimize the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain). To this end, a flight with this type of sensors has been planned, developed and analyzed. It has been applied to the archaeological site of Juliobriga (Cantabria, Spain). A strong dependence of the thermal sensor on the GSD, and the capability of this technique to interpret underground materials. This research allows to state that the thermal nature of the site does not provide main information about the site itself, but with combination with other types of information, such as the DEM, the typology of materials, etc., can produce very positive results with respect to the exploration and knowledge of the site. 

Keywords: process optimization, RGB models, thermal models, UAV, workflow

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Authors: Daniel Padilla, Edward Guillen

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Several wireless networks security standards have been proposed and widely implemented in both business and home environments in order to protect the network from unauthorized access. However, the implementation of such standards is usually achieved by network administrators without even knowing the standards- weaknesses and strengths. The intention of this paper is to evaluate and analyze the impact over the network-s security due to the implementation of the wireless networks security standards WEP, WPA and WLAN 802.1X.

Keywords: 802.1X, vulnerabilities analysis, WEP, wireless security, WPA.

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Authors: C. M. A. Robles G., R. A. Hernandez-Becerril

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We board the problem of creating a seismic alert system, based upon artificial neural networks, trained by using the well-known back-propagation and genetic algorithms, in order to emit the alarm for the population located into a specific city, about an eminent earthquake greater than 4.5 Richter degrees, and avoiding disasters and human loses. In lieu of using the propagation wave, we employed the magnitude of the earthquake, to establish a correlation between the recorded magnitudes from a controlled area and the city, where we want to emit the alarm. To measure the accuracy of the posed method, we use a database provided by CIRES, which contains the records of 2500 quakes incoming from the State of Guerrero and Mexico City. Particularly, we performed the proposed method to generate an issue warning in Mexico City, employing the magnitudes recorded in the State of Guerrero.

Keywords: Seismic Alert System, Artificial Neural Networks, Genetic Algorithms.

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Authors: Mousavian, M. Moghimi Mofrad, M. H. Vakili, D. Ashouri, R. Alizadeh

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The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.

Keywords: Neural Network, Net Heating Value, Crude Oil, Experimental, Modeling.

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