Search results for: Long Short-Term Memory Network

Authors: M. Saravanan, M. Madheswaran

Abstract:

Wireless Sensor Network (WSN) clustering architecture enables features like network scalability, communication overhead reduction, and fault tolerance. After clustering, aggregated data is transferred to data sink and reducing unnecessary, redundant data transfer. It reduces nodes transmitting, and so saves energy consumption. Also, it allows scalability for many nodes, reduces communication overhead, and allows efficient use of WSN resources. Clustering based routing methods manage network energy consumption efficiently. Building spanning trees for data collection rooted at a sink node is a fundamental data aggregation method in sensor networks. The problem of determining Cluster Head (CH) optimal number is an NP-Hard problem. In this paper, we combine cluster based routing features for cluster formation and CH selection and use Minimum Spanning Tree (MST) for intra-cluster communication. The proposed method is based on optimizing MST using Simulated Annealing (SA). In this work, normalized values of mobility, delay, and remaining energy are considered for finding optimal MST. Simulation results demonstrate the effectiveness of the proposed method in improving the packet delivery ratio and reducing the end to end delay.

Keywords: Wireless sensor network, clustering, minimum spanning tree, genetic algorithm, low energy adaptive clustering hierarchy, simulated annealing.

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Authors: Panchalee Sukjit, Herwig Unger

Abstract:

IT infrastructures are becoming more and more difficult. Therefore, in the first industrial IT systems, the P2P paradigm has replaced the traditional client server and methods of self-organization are gaining more and more importance. From the past it is known that especially regular structures like grids may significantly improve the system behavior and performance. This contribution introduces a new algorithm based on a biologic analogue, which may provide the growth of several regular structures on top of anarchic grown P2P- or social network structures.

Keywords: P2P, Pattern generation, Grid, Social network, Inheritance, Reproduction

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Authors: Haider K. Raad

Abstract:

In this paper, a compact wide-band, ultra-thin and flexible slot antenna intended for wearable applications is presented. The presented antenna is designed to provide Wireless Local Area Network (WLAN) and Long Term Evolution (LTE) connectivity. The presented design exhibits a relatively wide bandwidth (1600-3500 MHz below -6 dB impedance bandwidth limit). The antenna is positioned on a 33 mm x 30 mm flexible substrate with a thickness of 50 µm. Antenna properties, such as the far-field radiation patterns, scattering parameter S₁₁ are provided. The presented compact, thin and flexible design along with excellent radiation characteristics are deemed suitable for integration into flexible and wearable devices.

Keywords: Wearable Electronics, Slot Antenna, LTE, WLAN.

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Authors: M. Ghalambaz, A.R. Noghrehabadi, M.A. Behrang, E. Assareh, A. Ghanbarzadeh, N.Hedayat

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This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.

Keywords: Neural Networks, Gravitational Search Algorithm (GSR), Wessinger's Equation.

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Authors: Seyed Ali Sadat Noori, Elham Sahebi Bazaz

Abstract:

Topological changes in mobile ad hoc networks frequently render routing paths unusable. Such recurrent path failures have detrimental effects on quality of service. A suitable technique for eliminating this problem is to use multiple backup paths between the source and the destination in the network. This paper proposes an effective and efficient protocol for backup and disjoint path set in ad hoc wireless network. This protocol converges to a highly reliable path set very fast with no message exchange overhead. The paths selection according to this algorithm is beneficial for mobile ad hoc networks, since it produce a set of backup paths with more high reliability. Simulation experiments are conducted to evaluate the performance of our algorithm in terms of route numbers in the path set and its reliability. In order to acquire link reliability estimates, we use link expiration time (LET) between two nodes.

Keywords: Wireless Ad Hoc Networks, Reliability, Routing, Disjoint Path

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Authors: Nhon Do, Hien Nguyen

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Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: educational software, artificial intelligence, knowledge base system, knowledge representation.

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Authors: Vahid Parvaresh, Zohre Kassaian, Saeed Ketabi, Masoud Saeedi

Abstract:

This case study investigates the effects of reactive focus on form through negotiation on the linguistic development of an adult EFL learner in an exclusive private EFL classroom. The findings revealed that in this classroom negotiated feedback occurred significantly more often than non-negotiated feedback. However, it was also found that in the long run the learner was significantly more successful in correcting his own errors when he had received nonnegotiated feedback than negotiated feedback. This study, therefore, argues that although negotiated feedback seems to be effective for some learners in the short run, it is non-negotiated feedback which seems to be more effective in the long run. This long lasting effect might be attributed to the impact of schooling system which is itself indicative of the dominant culture, or to the absence of other interlocutors in the course of interaction.

Keywords: error, feedback, focus on form, interaction, schooling.

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Authors: Tlili-Guiassa Yamina

Abstract:

Many natural language expressions are ambiguous, and need to draw on other sources of information to be interpreted. Interpretation of the e word تعاون to be considered as a noun or a verb depends on the presence of contextual cues. To interpret words we need to be able to discriminate between different usages. This paper proposes a hybrid of based- rules and a machine learning method for tagging Arabic words. The particularity of Arabic word that may be composed of stem, plus affixes and clitics, a small number of rules dominate the performance (affixes include inflexional markers for tense, gender and number/ clitics include some prepositions, conjunctions and others). Tagging is closely related to the notion of word class used in syntax. This method is based firstly on rules (that considered the post-position, ending of a word, and patterns), and then the anomaly are corrected by adopting a memory-based learning method (MBL). The memory_based learning is an efficient method to integrate various sources of information, and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run, and in order, to improve the importance of the various information in learning.

Keywords: Arabic language, Based-rules, exceptions, Memorybased learning, Tagging.

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Authors: Chutima Prommak, Airisa Jantaweetip

Abstract:

In wireless networks, bandwidth is scare resource and it is essential to utilize it effectively. This paper analyses effects of using different bandwidth management techniques on the network performances of the Wireless Local Area Networks (WLANs) that use hybrid load balancing scheme. In particular, we study three bandwidth management schemes, namely Complete Sharing (CS), Complete Partitioning (CP), and Partial Sharing (PS). Performances of these schemes are evaluated by simulation experiments in term of percentage of network association blocking. Our results show that the CS scheme can provide relatively low blocking percentage in various network traffic scenarios whereas the PS scheme can enhance quality of services of the multimedia traffic with rather small expenses on the blocking percentage of the best effort traffic.

Keywords: Bandwidth management, Load Balancing, WLANs.

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Authors: Amit Sachan

Abstract:

The network designing and data modeling developments which are the two significant research tasks in direction to tolerate power control of Microgrid concluded using IEC 61850 data models and facilities. The current casing areas of IEC 61580 include infrastructures in substation automation systems, among substations and to DERs. So, for LV microgrid power control, previously using the IEC 61850 amenities to control the smart electrical devices, we have to model those devices as IEC 61850 data models and design a network topology to maintenance all-in-one communiqué amid those devices. In adding, though IEC 61850 assists modeling a portion by open-handed several object models for common functions similar measurement, metering, monitoring…etc., there are motionless certain missing smithereens for building a multiplicity of functions for household appliances like tuning the temperature of an electric heater or refrigerator.

Keywords: IEC 61850, RCMC, HCMC, DER Unit Controller.

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Authors: C. N. Okafor, M. Maaza, T. A. E. Mokrani

Abstract:

A proton exchange membrane has been developed for direct methanol fuel cell (DMFC). The nanofiber network composite membranes were prepared by interconnected network of Nafion (perfuorosulfonic acid) nanofibers that have been embedded in an uncharged and inert polymer matrix, by electro-spinning. The spinning solution of Nafion with a low concentration (1 wt% compared to Nafion) of high molecular weight poly(ethylene oxide), as a carrier polymer. The interconnected network of Nafion nanofibers with average fiber diameter in the range of 160-700nm, were used to make the membranes, with the nanofiber occupying up to 85% of the membrane volume. The matrix polymer was crosslinked with Norland Optical Adhesive 63 under UV. The resulting membranes showed proton conductivity of 0.10 S/cm at 25°C and 80% RH; and methanol permeability of 3.6 x 10-6 cm2/s.

Keywords: Composite membrane, electrospinning, fuel cell, nanofibers.

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Authors: M. Nekri, A. Khelladi

Abstract:

The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: Clustering coefficient, preferential attachment, small world, Web community.

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces  high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: Activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss.

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Authors: Pia I. Hautamäki

Abstract:

Selling has changed. Selling has taken on aspects of relationship marketing and sales force play a critical role in developing long-term relationships between buyers and sellers which is seen to serve the company’s targets and create success for a long run. The purpose of this study was to examine what really matters in buyer-seller encounters and determine what expectations business buyers have. We studied 17 business buyers by a qualitative interview. We found that buyers appreciate encounters where the salesperson face the buyer as a way he or she is as a person, map the real needs to improve buyers’ business and build up cooperation for long-term relationship. This study show that personality matters are a key elements when satisfying business buyers’ expectations.

Keywords: Business-to-Business, Business buyer-seller encounters, Business buyer, Expectations, Perceived similarity, Personal selling, Personality types.

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Authors: Valeri Arghutashvili, Mari Gogochuri

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Tourism industry development is one of the key priorities in Georgia, as it has positive influence on economic activities. Its contribution is very important for the different regions, as well as for the national economy. Benefits of the tourism industry include new jobs, service development, and increasing tax revenues, etc. The main aim of this research is to review and analyze the potential of the Georgian tourism industry with its long-term strategy and current challenges. To plan activities in a long-term development, it is required to evaluate several factors on the regional and on the national level. Factors include activities, transportation, services, lodging facilities, infrastructure and institutions. The major research contributions are practical estimates about regional tourism development which plays an important role in the integration process with global markets.

Keywords: Regional tourism, tourism industry, tourism in Georgia, tourism benefits.

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Authors: Nazif Çalış, Murat Erişoğlu, Hamza Erol, Tayfun Servi

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In the recent works related with mixture discriminant analysis (MDA), expectation and maximization (EM) algorithm is used to estimate parameters of Gaussian mixtures. But, initial values of EM algorithm affect the final parameters- estimates. Also, when EM algorithm is applied two times, for the same data set, it can be give different results for the estimate of parameters and this affect the classification accuracy of MDA. Forthcoming this problem, we use Self Organizing Mixture Network (SOMN) algorithm to estimate parameters of Gaussians mixtures in MDA that SOMN is more robust when random the initial values of the parameters are used [5]. We show effectiveness of this method on popular simulated waveform datasets and real glass data set.

Keywords: Self Organizing Mixture Network, MixtureDiscriminant Analysis, Waveform Datasets, Glass Identification, Mixture of Multivariate Normal Distributions

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Authors: Myagmarsuren Soronzonjav, N. Togtokhbayar, L. Davaahuu, B. Minjigdorj, Seong Gu Hwang

Abstract:

The number of natural or organic product consumers is increased in recent years and this healthy demand pushes to increase usage of healthy meat. At the same time, consumers pay more attention on the healthy fat, especially on unsaturated fatty acids. These long chain carbohydrates reduce heart diseases, improve memory and eye sight and activate the immune system. One of the important issues to be solved for our Mongolia’s food security is to provide healthy, fresh, widely available and cheap meat for the population. Thus, an importance of the Selenge breed meat production is increasing in order to supply the quality meat food security since the Selenge breed cattle are rapidly multiplied, beneficial in term of income, the same quality as Mongolian breed, and well digested for human body. We researched the lipid, unsaturated and saturated fatty acid contents of meat of Selenge breed younger cattle by their muscle types. Result of our research reveals that 11 saturated fatty acids are detected. For the content of palmitic acid among saturated fatty acids, 23.61% was in the sirloin meat, 24.01% was in the round and chuck meat, and 24.83% was in the short loin meat.

Keywords: Chromatogram, gas chromatography, organic resolving, saturated and unsaturated fatty acids.

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Authors: Ghassan A. Abed, Akbal O. Salman, Bayan M. Sabbar

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Transmission Control Protocol (TCP) among the wired and wireless networks, it still has a practical problem; where the congestion control mechanism does not permit the data stream to get complete bandwidth over the existing network links. To solve this problem, many TCP protocols have been introduced with high speed performance. Therefore, an enhanced congestion window (cwnd) for the congestion control mechanism is proposed in this article to improve the performance of TCP by increasing the number of cycles of the new window to improve the transmitted packet number. The proposed algorithm used a new mechanism based on the available bandwidth of the connection to detect the capacity of network path in order to improve the regular clocking of congestion avoidance mechanism. The work in this paper based on using Network Simulator 2 (NS-2) to simulate the proposed algorithm.

Keywords: TCP, cwnd, Congestion Control, NS-2.

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Authors: Fei Hao, Hai Wang

Abstract:

One of research issues in social network analysis is to evaluate the position/importance of users in social networks. As the information diffusion in social network is evolving, it seems difficult to evaluate the importance of users using traditional approaches. In this paper, we propose an evaluation approach for user importance with fractal view in social networks. In this approach, the global importance (Fractal Importance) and the local importance (Topological Importance) of nodes are considered. The basic idea is that the bigger the product of fractal importance and topological importance of a node is, the more important of the node is. We devise the algorithm called TFRank corresponding to the proposed approach. Finally, we evaluate TFRank by experiments. Experimental results demonstrate our TFRank has the high correlations with PageRank algorithm and potential ranking algorithm, and it shows the effectiveness and advantages of our approach.

Keywords: TFRank, Fractal Importance, Topological Importance, Social Network

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Authors: Salwa M. Salah Eldeen, Fathi A. Farag, Abd Allah M. Moselhy

Abstract:

This paper proposed a new CAD tools for microwave amplifier design. The proposed tool is based on survey about the broadband amplifier design methods, such as the Feedback amplifiers, balanced amplifiers and Compensated Matching Network The proposed tool is developed for broadband amplifier using a compensated matching network "unconditional stability amplifier". The developed program is based on analytical procedures with ability of smith chart explanation. The C# software is used for the proposed tools implementation. The program is applied on broadband amplifier as an example for testing. The designed amplifier is considered as a broadband amplifier at the range 300-700 MHz. The results are highly agreement with the expected results. Finally, these methods can be extended for wide band amplifier design.

Keywords: Broadband amplifier (BBA), Compensated Matching Network, Microwave Amplifier.

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Authors: Saeid Nahi, Seyed Mohammad Hossein Nabavi

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Nowadays, power systems, energy generation by wind has been very important. Noting that the production of electrical energy by wind turbines on site to several factors (such as wind speed and profile site for the turbines, especially off the wind input speed, wind rated speed and wind output speed disconnect) is dependent. On the other hand, several different types of turbines in the market there. Therefore, selecting a turbine that its capacity could also answer the need for electric consumers the efficiency is high something is important and necessary. In this context, calculating the amount of wind power to help optimize overall network, system operation, in determining the parameters of wind power is very important. In this article, to help calculate the amount of wind power plant, connected to the national network in the region Manjil wind, selecting the best type of turbine and power delivery profile appropriate to the network using Monte Carlo method has been. In this paper, wind speed data from the wind site in Manjil, as minute and during the year has been. Necessary simulations based on Random Numbers Simulation method and repeat, using the software MATLAB and Excel has been done.

Keywords: wind turbine, efficiency, wind turbine work points, Random Numbers, reliability

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Authors: Jae Chul Cha, Sandeep K. Gupta

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The demand for higher performance graphics continues to grow because of the incessant desire towards realism. And, rapid advances in fabrication technology have enabled us to build several processor cores on a single die. Hence, it is important to develop single chip parallel architectures for such data-intensive applications. In this paper, we propose an efficient PIM architectures tailored for computer graphics which requires a large number of memory accesses. We then address the two important tasks necessary for maximally exploiting the parallelism provided by the architecture, namely, partitioning and placement of graphic data, which affect respectively load balances and communication costs. Under the constraints of uniform partitioning, we develop approaches for optimal partitioning and placement, which significantly reduce search space. We also present heuristics for identifying near-optimal placement, since the search space for placement is impractically large despite our optimization. We then demonstrate the effectiveness of our partitioning and placement approaches via analysis of example scenes; simulation results show considerable search space reductions, and our heuristics for placement performs close to optimal – the average ratio of communication overheads between our heuristics and the optimal was 1.05. Our uniform partitioning showed average load-balance ratio of 1.47 for geometry processing and 1.44 for rasterization, which is reasonable.

Keywords: Data Partitioning and Placement, Graphics, PIM, Search Space Reduction.

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Authors: Mohammad Rakibul Islam

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Link reliability and transmitted power are two important design constraints in wireless network design. Error control coding (ECC) is a classic approach used to increase link reliability and to lower the required transmitted power. It provides coding gain, resulting in transmitter energy savings at the cost of added decoder power consumption. But the choice of ECC is very critical in the case of wireless sensor network (WSN). Since the WSNs are energy constraint in nature, both the BER and power consumption has to be taken into count. This paper develops a step by step approach in finding suitable error control codes for WSNs. Several simulations are taken considering different error control codes and the result shows that the RS(31,21) fits both in BER and power consumption criteria.

Keywords: Error correcting code, RS, BCH, wireless sensor networks.

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Authors: Karin Kandananond

Abstract:

The nature of consumer products causes the difficulty in forecasting the future demands and the accuracy of the forecasts significantly affects the overall performance of the supply chain system. In this study, two data mining methods, artificial neural network (ANN) and support vector machine (SVM), were utilized to predict the demand of consumer products. The training data used was the actual demand of six different products from a consumer product company in Thailand. The results indicated that SVM had a better forecast quality (in term of MAPE) than ANN in every category of products. Moreover, another important finding was the margin difference of MAPE from these two methods was significantly high when the data was highly correlated.

Keywords: Artificial neural network (ANN), Bullwhip effect, Consumer products, Demand forecasting, Supply chain, Support vector machine (SVM).

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Authors: Zöhre Kara Kayikci, Günther Palm

Abstract:

A word recognition architecture based on a network of neural associative memories and hidden Markov models has been developed. The input stream, composed of subword-units like wordinternal triphones consisting of diphones and triphones, is provided to the network of neural associative memories by hidden Markov models. The word recognition network derives words from this input stream. The architecture has the ability to handle ambiguities on subword-unit level and is also able to add new words to the vocabulary during performance. The architecture is implemented to perform the word recognition task in a language processing system for understanding simple command sentences like “bot show apple".

Keywords: Hebbian learning, hidden Markov models, neuralassociative memories, word recognition.

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Authors: Kyi Lin Lin Kyaw

Abstract:

Nowadays, we are facing with network threats that cause enormous damage to the Internet community day by day. In this situation, more and more people try to prevent their network security using some traditional mechanisms including firewall, Intrusion Detection System, etc. Among them honeypot is a versatile tool for a security practitioner, of course, they are tools that are meant to be attacked or interacted with to more information about attackers, their motives and tools. In this paper, we will describe usefulness of low-interaction honeypot and high-interaction honeypot and comparison between them. And then we propose hybrid honeypot architecture that combines low and high -interaction honeypot to mitigate the drawback. In this architecture, low-interaction honeypot is used as a traffic filter. Activities like port scanning can be effectively detected by low-interaction honeypot and stop there. Traffic that cannot be handled by low-interaction honeypot is handed over to high-interaction honeypot. In this case, low-interaction honeypot is used as proxy whereas high-interaction honeypot offers the optimal level realism. To prevent the high-interaction honeypot from infections, containment environment (VMware) is used.

Keywords: Low-interaction honeypot, High-interactionhoneypot, VMware, Proxy

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Authors: Nerguè Kassahan Kone, Souleymane Oumtanaga

Abstract:

The third generation (3G) of cellular system adopted the spread spectrum as solution for the transmission of the data in the physical layer. Contrary to systems IS-95 or CDMAOne (systems with spread spectrum of the preceding generation), the new standard, called Universal Mobil Telecommunications System (UMTS), uses long codes in the down link. The system is conceived for the vocal communication and the transmission of the data. In particular, the down link is very important, because of the asymmetrical request of the data, i.e., more remote loading towards the mobiles than towards the basic station. Moreover, the UMTS uses for the down link an orthogonal spreading out with a variable factor of spreading out (OVSF for Orthogonal Variable Spreading Factor). This characteristic makes it possible to increase the flow of data of one or more users by reducing their factor of spreading out without changing the factor of spreading out of other users. In the current standard of the UMTS, two techniques to increase the performances of the down link were proposed, the diversity of sending antenna and the codes space-time. These two techniques fight only fainding. The receiver proposed for the mobil station is the RAKE, but one can imagine a receiver more sophisticated, able to reduce the interference between users and the impact of the coloured noise and interferences to narrow band. In this context, where the users have long codes synchronized with variable factor of spreading out and ignorance by the mobile of the other active codes/users, the use of the sequences of code pseudo-noises different lengths is presented in the form of one of the most appropriate solutions.

Keywords: DS-CDMA, multiple access interference, ratio Signal / interference + Noise.

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Authors: Badar Muneer, Waseem Shabir, Faisal Karim Shaikh

Abstract:

Substrate Integrated waveguide based 6-element array of Planar Inverted F antenna (PIFA) has been presented and analyzed parametrically in this paper. The antenna is fed with coupled transverse slots on a plate laminated waveguide cavity to ensure wide bandwidth and simplicity of feeding network. The two-layer structure has one layer dedicated for feeding network and the top layer dedicated for radiating elements. It has been demonstrated that the presented feeding technique for feeding such class of array antennas can be far simple in structure and miniaturized in size when it comes to designing large phased array antenna systems. A good return loss and standing wave ratio of 2:1 has been achieved while maintaining properties of typical PIFA.

Keywords: Feeding network, laminated waveguide, PIFA, transverse slots.

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Authors: Savita Sindhu, Shruti Vashist

Abstract:

A wireless body area sensor network (WBASN) is composed of a central node and heterogeneous sensors to supervise the physiological signals and functions of the human body. This overwhelmimg area has stimulated new research and calibration processes, especially in the area of WBASN’s attainment and fidelity. In the era of mobility or imbricated WBASN’s, system performance incomparably degrades because of unstable signal integrity. Hence, it is mandatory to define mitigation techniques in the design to avoid interference. There are various mitigation methods available e.g. diversity techniques, equalization, viterbi decoder etc. This paper presents equalization mitigation scheme in WBASNs to improve the signal integrity. Eye diagrams are also given to represent accuracy of the signal. Maximum no. of symbols is taken to authenticate the signal which in turn results in accuracy and increases the overall performance of the system.

Keywords: Wireless body area network, equalizer, RLS, LMS.

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Authors: Baeza S. Roberto

Abstract:

The knitted fabric suffers a deformation in its dimensions due to stretching and tension factors, transverse and longitudinal respectively, during the process in rectilinear knitting machines so it performs a dry relaxation shrinkage procedure and thermal action of prefixed to obtain stable conditions in the knitting. This paper presents a dry relaxation shrinkage prediction of Bordeaux fiber using a feed forward neural network and linear regression models. Six operational alternatives of shrinkage were predicted. A comparison of the results was performed finding neural network models with higher levels of explanation of the variability and prediction. The presence of different reposes is included. The models were obtained through a neural toolbox of Matlab and Minitab software with real data in a knitting company of Southern Guanajuato. The results allow predicting dry relaxation shrinkage of each alternative operation.

Keywords: Neural network, dry relaxation, knitting, linear regression.

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