Search results for: Digital social networks

Authors: Zhenyu Zhang, Qingbin Gao

Abstract:

Low-resolution digital encoder (LRDE) is commonly adopted as a position sensor in low-cost and resource-constraint applications. Traditionally, a digital encoder is modeled as a quantizer without considering the initial position of the LRDE. However, it cannot be applied to extreme LRDE for which stroke of angular motion is only a few times of resolution of the encoder. Besides, the actual angular motion is substantially distorted by this extreme LRDE so that the encoder reading does not faithfully represent the actual angular motion. This paper presents a modeling method for extreme LRDE by taking into account the initial position of the LRDE. For a control system with sinusoidal reference signal and extreme LRDE, this paper analyzes the characteristics of angular motion. Specifically, two descriptors of sinusoidal angular motion are studied, which essentially sheds light on the actual angular motion from extreme LRDE.

Keywords: Low resolution digital encoder, resource-constraint control system, sinusoidal reference signal, servo motion control.

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Authors: L. Parisi

Abstract:

In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: Kinemic gait data, Neural networks, Hip joint implant, Hip arthroplasty, Rehabilitation Engineering.

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Authors: Meenakshi Bansal, Iqbal Singh, Parvinder S. Sandhu

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In over deployed sensor networks, one approach to Conserve energy is to keep only a small subset of sensors active at Any instant. For the coverage problems, the monitoring area in a set of points that require sensing, called demand points, and consider that the node coverage area is a circle of range R, where R is the sensing range, If the Distance between a demand point and a sensor node is less than R, the node is able to cover this point. We consider a wireless sensor network consisting of a set of sensors deployed randomly. A point in the monitored area is covered if it is within the sensing range of a sensor. In some applications, when the network is sufficiently dense, area coverage can be approximated by guaranteeing point coverage. In this case, all the points of wireless devices could be used to represent the whole area, and the working sensors are supposed to cover all the sensors. We also introduce Hybrid Algorithm and challenges related to coverage in sensor networks.

Keywords: Wireless sensor networks, network coverage, Energy conservation, Hybrid Algorithms.

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Authors: Hiba Hasan, Khalid Raza

Abstract:

Reverse engineering of genetic regulatory network involves the modeling of the given gene expression data into a form of the network. Computationally it is possible to have the relationships between genes, so called gene regulatory networks (GRNs), that can help to find the genomics and proteomics based diagnostic approach for any disease. In this paper, clustering based method has been used to reconstruct genetic regulatory network from time series gene expression data. Supercoiled data set from Escherichia coli has been taken to demonstrate the proposed method.

Keywords: Gene expression, gene regulatory networks (GRNs), clustering, data preprocessing, network visualization.

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Authors: Abhishek Bansal, G. N. Pillai

Abstract:

This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.

Keywords: Fault identification, distribution networks, high impedance arc-faults, feature vector, LVQ networks.

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Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

Abstract:

Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: Heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry.

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Authors: Artan Luma, Betim Prevalla, Besart Qoku, Bujar Raufi

Abstract:

Electronic banking must be secure and easy to use and many banks heavily advertise an apparent of 100% secure system which is contestable in many points. In this work, an alternative approach to the design of e-banking system, through a new solution for user authentication and security with digital certificate called LumaCert is introduced. The certificate applies new algorithm for asymmetric encryption by utilizing two mathematical operators called Pentors and UltraPentors. The public and private key in this algorithm represent a quadruple of parameters which are directly dependent from the above mentioned operators. The strength of the algorithm resides in the inability to find the respective Pentor and UltraPentor operator from the mentioned parameters.

Keywords: Security, Digital Certificate, Cryptography.

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Authors: Magnus Eriksson, Arif Mahmud

Abstract:

A novel idea presented in this paper is to combine multihop routing with single-frequency networks (SFNs) for a broadcasting scenario. An SFN is a set of multiple nodes that transmit the same data simultaneously, resulting in transmitter macrodiversity. Two of the most important performance factors of multihop networks, node reachability and routing robustness, are analyzed. Simulation results show that our proposed SFN-D routing algorithm improves the node reachability by 37 percentage points as compared to non-SFN multihop routing. It shows a diversity gain of 3.7 dB, meaning that 3.7 dB lower transmission powers are required for the same reachability. Even better results are possible for larger networks. If an important node becomes inactive, this algorithm can find new routes that a non-SFN scheme would not be able to find. Thus, two of the major problems in multihopping are addressed; achieving robust routing as well as improving node reachability or reducing transmission power.

Keywords: OFDM, single-frequency networks (SFN), DSFN, MANET; multihop routing, transmitter macrodiversity, broadcasting.

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

Abstract:

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: Metaphor detection, deep learning, representation learning, embeddings.

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Authors: Kelvin Rozier, Vladimir E. Bondarenko

Abstract:

It is known that an analog Hopfield neural network with time delay can generate the outputs which are similar to the human electroencephalogram. To gain deeper insights into the mechanisms of rhythm generation by the Hopfield neural networks and to study the effects of noise on their activities, we investigated the behaviors of the networks with symmetric and asymmetric interneuron connections. The neural network under the study consists of 10 identical neurons. For symmetric (fully connected) networks all interneuron connections aij = +1; the interneuron connections for asymmetric networks form an upper triangular matrix with non-zero entries aij = +1. The behavior of the network is described by 10 differential equations, which are solved numerically. The results of simulations demonstrate some remarkable properties of a Hopfield neural network, such as linear growth of outputs, dependence of synchronization properties on the connection type, huge amplification of oscillation by the external uniform noise, and the capability of the neural network to transform one type of noise to another.

Keywords: Chaos, Hopfield neural network, noise, synchronization

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Authors: Joohee Kim

Abstract:

This paper presents a video transmission system using layered multiple description (coding (MDC) and multi-path transport for reliable video communications in wireless ad-hoc networks. The proposed MDC extends a quality-scalable H.264/AVC video coding algorithm to generate two independent descriptions. The two descriptions are transmitted over different paths to a receiver in order to alleviate the effect of unstable channel conditions of wireless adhoc networks. If one description is lost due to transmission erros, then the correctly received description is used to estimate the lost information of the corrupted description. The proposed MD coder maintains an adequate video quality as long as both description are not simultaneously lost. Simulation results show that the proposed MD coding combined with multi-path transport system is largely immune to packet losses, and therefore, can be a promising solution for robust video communications over wireless ad-hoc networks.

Keywords: Multiple description coding, wireless video streaming, rate control.

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Authors: I. R. Farah, I. B. Ismail, M. B. Ahmed

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The huge development of new technologies and the apparition of open communication system more and more sophisticated create a new challenge to protect digital content from piracy. Digital watermarking is a recent research axis and a new technique suggested as a solution to these problems. This technique consists in inserting identification information (watermark) into digital data (audio, video, image, databases...) in an invisible and indelible manner and in such a way not to degrade original medium-s quality. Moreover, we must be able to correctly extract the watermark despite the deterioration of the watermarked medium (i.e attacks). In this paper we propose a system for watermarking satellite images. We chose to embed the watermark into frequency domain, precisely the discrete wavelet transform (DWT). We applied our algorithm on satellite images of Tunisian center. The experiments show satisfying results. In addition, our algorithm showed an important resistance facing different attacks, notably the compression (JEPG, JPEG2000), the filtering, the histogram-s manipulation and geometric distortions such as rotation, cropping, scaling.

Keywords: Digital data watermarking, Spatial Database, Satellite images, Discrete Wavelets Transform (DWT).

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Authors: Chris Landorf, Stephen Ward

Abstract:

This paper addresses a virtual environment approach to work integrated learning for students in construction-related disciplines. The virtual approach provides a safe and pedagogically rigorous environment where students can apply theoretical knowledge in a simulated real-world context. The paper describes the development of a 4-dimensional digital construction environment and associated learning activities funded by the Australian Office for Learning and Teaching. The environment was trialled with over 1,300 students and evaluated through questionnaires, observational studies and coursework analysis. Results demonstrate a positive impact on students’ technical learning and collaboration skills, but there is need for further research in relation to critical thinking skills and work-readiness.

Keywords: Architectural education, construction industry, digital learning environments, immersive learning.

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Authors: Rahul Malhotra

Abstract:

The field of wireless sensor networks (WSN) engages a lot of associates in the research community as an interdisciplinary field of interest. This type of network is inexpensive, multifunctionally attributable to advances in micro-electromechanical systems and conjointly the explosion and expansion of wireless communications. A mobile ad hoc network is a wireless network without fastened infrastructure or federal management. Due to the infrastructure-less mode of operation, mobile ad-hoc networks are gaining quality. During this work, we have performed an efficient performance study of the two major routing protocols: Ad hoc On-Demand Distance Vector Routing (AODV) and Dynamic Source Routing (DSR) protocols. We have used an accurate simulation model supported NS2 for this purpose. Our simulation results showed that AODV mitigates the drawbacks of the DSDV and provides better performance as compared to DSDV.

Keywords: Routing protocols, mobility, Mobile Ad-hoc Networks, Ad-hoc On-demand Distance Vector, Dynamic Source Routing, Destination Sequence Distance Vector, Quality of Service.

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Authors: R. Byler

Abstract:

Innovation, particularly in technology development, is a crucial aspect of nanotechnology R&D and, although several approaches to effective innovation management exist, organizational structures that promote knowledge exchange have been found to be most effect in supporting new and emerging technologies. This paper discusses Integrated Knowledge Networks (IKNs) and evaluates its use within nanotechnology R&D to increase technology innovation. Specifically, this paper reviews the role of IKNs in bolstering national and international nanotechnology development and in enhancing nanotechnology innovation. Both physical and virtual IKNs, particularly IT-based network platforms for community-based innovation, offer strategies for enhanced technology innovation, interdisciplinary cooperation, and enterprise development. Effectively creating and managing technology R&D networks can facilitate successful knowledge exchange, enhanced innovation, commercialization, and technology transfer. As such, IKNs are crucial to technology development processes and, thus, in increasing the quality and access to new, innovative nanoscience and technologies worldwide.

Keywords: Community-based innovation, integrated knowledge networks, nanotechnology, technology innovation.

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Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

Abstract:

In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished though the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: Analog to digital conversion, digitization, sampling rate, ultrasonic sensors.

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Authors: J. Bolzan, C. Marden

Abstract:

The article proposed intends to analyze the possibility (and conditions) of a media regulation law in a democratic rule of law in the twenty-first century. To do so, will be presented initially the idea of the public sphere (by Jürgen Habermas), showing how it is presented as an interface between the citizen and the state (or the private and public) and how important is it in a deliberative democracy. Based on this paradigm, the traditional perception of the role of public information (such as system functional element) and on the possibility of media regulation will be exposed, due to the public nature of their activity. A critical argument will then be displayed from two different perspectives: a) the formal function of the current media information, considering that the digital age has fragmented the information access; b) the concept of a constructive democracy, which reduces the need for representation, changing the strategic importance of the public sphere. The question to be addressed (based on the comparative law) is if the regulation is justified in a polycentric democracy, especially when it operates under the digital age (with immediate and virtual communication). The proposal is to be presented in the sense that even in a twenty-first century the media in a democratic rule of law still has an extremely important role and may be subject to regulation, but this should be on terms very different (and narrower) from those usually defended.

Keywords: Media regulation, public sphere, digital age, constructive democracy.

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Authors: Varun Gupta, Ankit Pandey

Abstract:

Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.

Keywords: Crude oil price prediction, deep learning, LSTM, recurrent neural networks.

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Authors: Min Kyung An, Hyuk Cho

Abstract:

In this paper, we study the Minimum Latency Broadcast Scheduling (MLBS) problem in wireless sensor networks (WSNs). The main issue of the MLBS problem is to compute schedules with the minimum number of timeslots such that a base station can broadcast data to all other sensor nodes with no collisions. Unlike existing works that utilize the traditional omni-directional WSNs, we target the directional WSNs where nodes can collaboratively determine and orientate their antenna directions. We first develop a 7-approximation algorithm, adopting directional WSNs. Our ratio is currently the best, to the best of our knowledge. We then validate the performance of the proposed algorithm through simulation.

Keywords: Broadcast, collision-free, directional antenna, approximation, wireless sensor networks.

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Authors: Yaping Ren, Yongkun Li

Abstract:

In this paper, by using the continuation theorem of coincidence degree theory, M-matrix theory and constructing some suitable Lyapunov functions, some sufficient conditions are obtained for the existence and global exponential stability of periodic solutions of recurrent neural networks with distributed delays and impulses on time scales. Without assuming the boundedness of the activation functions gj, hj , these results are less restrictive than those given in the earlier references.

Keywords: Recurrent neural networks, global exponential stability, periodic solutions, distributed delays, impulses, time scales.

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Authors: Amir Reza Saffari Azar Alamdari

Abstract:

In this paper, a model of self-organizing spiking neural networks is introduced and applied to mobile robot environment representation and path planning problem. A network of spike-response-model neurons with a recurrent architecture is used to create robot-s internal representation from surrounding environment. The overall activity of network simulates a self-organizing system with unsupervised learning. A modified A* algorithm is used to find the best path using this internal representation between starting and goal points. This method can be used with good performance for both known and unknown environments.

Keywords: Mobile Robot, Path Planning, Self-organization, Spiking Neural Networks.

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Authors: Bharadwaj Kadiyala, Sunitha V

Abstract:

Most routing protocols (DSR, AODV etc.) that have been designed for wireless adhoc networks incorporate the broadcasting operation in their route discovery scheme. Probabilistic broadcasting techniques have been developed to optimize the broadcast operation which is otherwise very expensive in terms of the redundancy and the traffic it generates. In this paper we have explored percolation theory to gain a different perspective on probabilistic broadcasting schemes which have been actively researched in the recent years. This theory has helped us estimate the value of broadcast probability in a wireless adhoc network as a function of the size of the network. We also show that, operating at those optimal values of broadcast probability there is at least 25-30% reduction in packet regeneration during successful broadcasting.

Keywords: Crossover length, Percolation, Probabilistic broadcast, Wireless adhoc networks

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

In many data mining 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. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. 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: Heejin Lee, Yeonjoo Kim, Kyungrak Sohn

Abstract:

We present a white LED-based optical wireless communication systems for indoor ubiquitous sensor networks. Each sensor node could access to the server through the PLC (Power Line Communication)-Ethernet interface. The proposed system offers a full-duplex wireless link by using different wavelengths to reduce the inter-symbol interference between uplink and downlink. Through the 1-to-n optical wireless sensor network and PLC modem, the mobile terminals send a temperature data to server. The data transmission speed and distance are 115.2kbps and about 60cm, respectively.

Keywords: Visible light communications, LED lighting, powerline communications, ubiquitous sensor networks, full-duplex links

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Authors: Yongzhi Liao

Abstract:

By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of positive almost periodic solution in a delayed Lotka-Volterra recurrent neural networks with harvesting terms. To a certain extent, our work in this paper corrects some result in recent years. Finally, an example is given to illustrate the feasibility and effectiveness of the main result.

Keywords: positive almost periodic solution, Lotka-Volterra, neural networks, Banach fixed point theorem, harvesting

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Authors: Dai Miyamoto

Abstract:

This paper examines the factors, which determine R&D outsourcing behaviour at Japanese firms, from the viewpoints of transaction cost and strategic management, since the latter half of the 1990s. This study uses empirical analysis, which involves the application of large-sample data. The principal findings of this paper are listed below. Firms that belong to a wider corporate group are more active in executing R&D outsourcing activities. Diversification strategies such as the expansion of product and sales markets have a positive effect on the R&D outsourcing behaviour of firms. Moreover, while quantitative R&D resources have positive influences on R&D outsourcing, qualitative indices have no effect. These facts suggest that R&D outsourcing behaviour of Japanese firms are consistent with the two perspectives of transaction cost and strategic management. Specifically, a conventional corporate group network plays an important role in R&D outsourcing behaviour. Firms that execute R&D outsourcing leverage 'old' networks to construct 'new' networks and use both networks properly.

Keywords: Corporate Group Networks, R&D Outsourcing, Strategic Management Perspective, Transaction Cost Perspective.

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Authors: Ching-Sheng Hsu, Young-Chang Hou

Abstract:

In this paper, a novel copyright protection scheme for digital images based on Visual Cryptography and Statistics is proposed. In our scheme, the theories and properties of sampling distribution of means and visual cryptography are employed to achieve the requirements of robustness and security. Our method does not need to alter the original image and can identify the ownership without resorting to the original image. Besides, our method allows multiple watermarks to be registered for a single host image without causing any damage to other hidden watermarks. Moreover, it is also possible for our scheme to cast a larger watermark into a smaller host image. Finally, experimental results will show the robustness of our scheme against several common attacks.

Keywords: Copyright protection, digital watermarking, samplingdistribution, visual cryptography.

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Authors: N. Nacereddine, M. Zelmat, S. S. Belaïfa, M. Tridi

Abstract:

Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.

Keywords: Digital image processing, global and localapproaches, radiographic film, weld defect.

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Authors: Amandeep Singh Dhaliwal

Abstract:

Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN.

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Authors: Rade M. Ciric

Abstract:

The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: Engineering education, power distribution network, syllabus implementation, outcome evaluation.

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