Search results for: Social networks
2618 Study Regarding Effect of Isolation on Social Behaviour in Mice
Authors: Ritu Shitak
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Humans are social mammals, of the primate order. Our biology, our behaviour and our pathologies are unique to us. In our desire to understand, reduce solitary confinement one source of information is the many reports of social isolation of other social mammals, especially primates. A behavioural study was conducted in the department of pharmacology at Indira Gandhi Medical College, Shimla in Himachalpradesh province in India using white albino mice. Different behavioural parameters were observed by using open field, tail suspension, tests for aggressive behaviour and social interactions and the effect of isolation was studied. The results were evaluated and the standard statistics were applied. The said study was done to establish facts that isolation itself impairs social behaviour and can lead to alcohol dependence as well as related drug dependence.
Keywords: Albino Mice, Drug Dependence, Social isolation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21552617 Performance of Total Vector Error of an Estimated Phasor within Local Area Networks
Authors: Ahmed Abdolkhalig, Rastko Zivanovic
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This paper evaluates the Total Vector Error of an estimated Phasor as define in IEEE C37.118 standard within different medium access in Local Area Networks (LAN). Three different LAN models (CSMA/CD, CSMA/AMP and Switched Ethernet) are evaluated. The Total Vector Error of the estimated Phasor has been evaluated for the effect of Nodes Number under the standardized network Band-width values defined in IEC 61850-9-2 communication standard (i.e. 0.1, 1 and 10 Gbps).
Keywords: Phasor, Local Area Network, Total Vector Error, IEEE C37.118, IEC 61850.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41342616 Generalization of Clustering Coefficient on Lattice Networks Applied to Criminal Networks
Authors: Christian H. Sanabria-Montaña, Rodrigo Huerta-Quintanilla
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A lattice network is a special type of network in which all nodes have the same number of links, and its boundary conditions are periodic. The most basic lattice network is the ring, a one-dimensional network with periodic border conditions. In contrast, the Cartesian product of d rings forms a d-dimensional lattice network. An analytical expression currently exists for the clustering coefficient in this type of network, but the theoretical value is valid only up to certain connectivity value; in other words, the analytical expression is incomplete. Here we obtain analytically the clustering coefficient expression in d-dimensional lattice networks for any link density. Our analytical results show that the clustering coefficient for a lattice network with density of links that tend to 1, leads to the value of the clustering coefficient of a fully connected network. We developed a model on criminology in which the generalized clustering coefficient expression is applied. The model states that delinquents learn the know-how of crime business by sharing knowledge, directly or indirectly, with their friends of the gang. This generalization shed light on the network properties, which is important to develop new models in different fields where network structure plays an important role in the system dynamic, such as criminology, evolutionary game theory, econophysics, among others.Keywords: Clustering coefficient, criminology, generalized, regular network d-dimensional.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16132615 PTH Moment Exponential Stability of Stochastic Recurrent Neural Networks with Distributed Delays
Authors: Zixin Liu, Jianjun Jiao Wanping Bai
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In this paper, the issue of pth moment exponential stability of stochastic recurrent neural network with distributed time delays is investigated. By using the method of variation parameters, inequality techniques, and stochastic analysis, some sufficient conditions ensuring pth moment exponential stability are obtained. The method used in this paper does not resort to any Lyapunov function, and the results derived in this paper generalize some earlier criteria reported in the literature. One numerical example is given to illustrate the main results.
Keywords: Stochastic recurrent neural networks, pth moment exponential stability, distributed time delays.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12422614 Using Neural Network for Execution of Programmed Pulse Width Modulation (PPWM) Method
Authors: M. Tarafdar Haque, A. Taheri
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Application of neural networks in execution of programmed pulse width modulation (PPWM) of a voltage source inverter (VSI) is studied in this paper. Using the proposed method it is possible to cancel out the desired harmonics in output of VSI in addition to control the magnitude of fundamental harmonic, contineously. By checking the non-trained values and a performance index, the most appropriate neural network is proposed. It is shown that neural networks may solve the custom difficulties of practical utilization of PPWM such as large size of memory, complex digital circuits and controlling the magnitude of output voltage in a discrete manner.Keywords: Neural Network, Inverter, PPWM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16792613 Allocation of Mobile Units in an Urban Emergency Service System
Authors: Dimitra Alexiou
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In an urban area the location allocation of emergency services mobile units, such as ambulances, police patrol cars must be designed so as to achieve a prompt response to demand locations. In this paper the partition of a given urban network into distinct sub-networks is performed such that the vertices in each component are close and simultaneously the sums of the corresponding population in the sub-networks are almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.
Keywords: Distances, Emergency Service, Graph Partition, location.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19272612 A Virtual Grid Based Energy Efficient Data Gathering Scheme for Heterogeneous Sensor Networks
Authors: Siddhartha Chauhan, Nitin Kumar Kotania
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Traditional Wireless Sensor Networks (WSNs) generally use static sinks to collect data from the sensor nodes via multiple forwarding. Therefore, network suffers with some problems like long message relay time, bottle neck problem which reduces the performance of the network.
Many approaches have been proposed to prevent this problem with the help of mobile sink to collect the data from the sensor nodes, but these approaches still suffer from the buffer overflow problem due to limited memory size of sensor nodes. This paper proposes an energy efficient scheme for data gathering which overcomes the buffer overflow problem. The proposed scheme creates virtual grid structure of heterogeneous nodes. Scheme has been designed for sensor nodes having variable sensing rate. Every node finds out its buffer overflow time and on the basis of this cluster heads are elected. A controlled traversing approach is used by the proposed scheme in order to transmit data to sink. The effectiveness of the proposed scheme is verified by simulation.
Keywords: Buffer overflow problem, Mobile sink, Virtual grid, Wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18182611 Neural Network Learning Based on Chaos
Authors: Truong Quang Dang Khoa, Masahiro Nakagawa
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Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.
Keywords: learning and evolutionary computing, Chaos Optimization Algorithm, Artificial Neural Networks, nonlinear optimization, intelligent computational technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17672610 Pose Normalization Network for Object Classification
Authors: Bingquan Shen
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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.Keywords: Convolutional neural networks, object classification, pose normalization, viewpoint invariant.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11072609 Stop Texting While Learning: A Meta-Analysis of Social Networks Use and Academic Performances
Authors: Proud Arunrangsiwed, Sarinya Kongtieng
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Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.
Keywords: Meta-regression analysis, social networking site use, academic performance, multitasking, motivation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16592608 Blind Image Deconvolution by Neural Recursive Function Approximation
Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu
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This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.
Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20452607 Prediction of Slump in Concrete using Artificial Neural Networks
Authors: V. Agrawal, A. Sharma
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High Strength Concrete (HSC) is defined as concrete that meets special combination of performance and uniformity requirements that cannot be achieved routinely using conventional constituents and normal mixing, placing, and curing procedures. It is a highly complex material, which makes modeling its behavior a very difficult task. This paper aimed to show possible applicability of Neural Networks (NN) to predict the slump in High Strength Concrete (HSC). Neural Network models is constructed, trained and tested using the available test data of 349 different concrete mix designs of High Strength Concrete (HSC) gathered from a particular Ready Mix Concrete (RMC) batching plant. The most versatile Neural Network model is selected to predict the slump in concrete. The data used in the Neural Network models are arranged in a format of eight input parameters that cover the Cement, Fly Ash, Sand, Coarse Aggregate (10 mm), Coarse Aggregate (20 mm), Water, Super-Plasticizer and Water/Binder ratio. Furthermore, to test the accuracy for predicting slump in concrete, the final selected model is further used to test the data of 40 different concrete mix designs of High Strength Concrete (HSC) taken from the other batching plant. The results are compared on the basis of error function (or performance function).Keywords: Artificial Neural Networks, Concrete, prediction ofslump, slump in concrete
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35822606 Detection of Leaks in Water Mains Using Ground Penetrating Radar
Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi
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Ground Penetrating Radar (GPR) is one of the most effective electromagnetic techniques for non-destructive non-invasive subsurface features investigation. Water leak from pipelines is the most common undesirable reason of potable water losses. Rapid detection of such losses is going to enhance the use of the Water Distribution Networks (WDN) and decrease threatens associated with water mains leaks. In this study, GPR approach was developed to detect leaks by implementing an appropriate imaging analyzing strategy based on image refinement, reflection polarity and reflection amplitude that would ease the process of interpreting the collected raw radargram image.Keywords: Water Networks, Leakage, Water pipelines, Ground Penetrating Radar.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22962605 Adaptive Routing Protocol for Dynamic Wireless Sensor Networks
Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali
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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several subnetworks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.Keywords: Wireless sensor networks, routing protocols, ad hoc topology, cluster, sub-network, WSN design requirements.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19472604 New Delay-Dependent Stability Criteria for Neural Networks With Two Additive Time-varying Delay Components
Authors: Xingyuan Qu, Shouming Zhong
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In this paper, the problem of stability criteria of neural networks (NNs) with two-additive time-varying delay compenents is investigated. The relationship between the time-varying delay and its lower and upper bounds is taken into account when estimating the upper bound of the derivative of Lyapunov functional. As a result, some improved delay stability criteria for NNs with two-additive time-varying delay components are proposed. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
Keywords: Delay-dependent stability, time-varying delays, Lyapunov functional, linear matrix inequality (LMI).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16002603 Existence and Global Exponential Stability of Periodic Solutions of Cellular Neural Networks with Distributed Delays and Impulses on Time Scales
Authors: Daiming Wang
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In this paper, by using Mawhin-s continuation theorem of coincidence degree and a method based on delay differential inequality, some sufficient conditions are obtained for the existence and global exponential stability of periodic solutions of cellular neural networks with distributed delays and impulses on time scales. The results of this paper generalized previously known results.
Keywords: Periodic solutions, global exponential stability, coincidence degree, M-matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14532602 Unsupervised Classification of DNA Barcodes Species Using Multi-Library Wavelet Networks
Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar
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DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19552601 Improvements in Navy Data Networks and Tactical Communication Systems
Authors: Laurent Enel, Franck Guillem
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This paper considers the benefits gained by using an efficient quality of service management such as DiffServ technique to improve the performance of military communications. Low delay and no blockage must be achieved especially for real time tactical data. All traffic flows generated by different applications do not need same bandwidth, same latency, same error ratio and this scalable technique of packet management based on priority levels is analysed. End to end architectures supporting various traffic flows and including lowbandwidth and high-delay HF or SHF military links as well as unprotected Internet sub domains are studied. A tuning of Diffserv parameters is proposed in accordance with different loads of various traffic and different operational situations.Keywords: Military data networks, Quality of service, Tacticalsystems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20572600 Analyzing the Usage of Social Media: A Study on Elderly in Malaysia
Authors: Chan Eang Teng, Tang Mui Joo
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In the beginning of the prevalence of social media, it would be an obvious trend that the young adult age group has the highest population among the users on social media. However, apart from the age group of the users are becoming younger and younger, the elderly group has become a new force on social media, and this age group has increased rapidly. On top of that, the influence of social media towards the elderly is becoming more significant and it is even trending among them. This is because basic computer knowledge is not instilled into their life when they were young. This age group tends to be engrossed more than the young as this is something new for them, and they have the mindset that it is a new platform to approach things, and they tend to be more engrossed when they start getting in touch with the social media. Generally, most of the social media has been accepted and accessed by teenagers and young adult, but it is reasonable to believe that the social media is not really accepted among the elderly. Surprisingly, the elderlies are more addicted to the social media than the teenagers. Therefore, this study is to determine and understand the relationship between the elderly and social media, and how they employ social media in their lives. An online survey on 200 elderly aged 45-80 and an interview with a media expert are conducted to answer the main questions in the research paper. Uses and Gratification Approach is employed in theoretical framework. Finding revealed that majority of the respondents use social media to connect with family, friends, and for leisure purposes. The finding concluded that the elderly use social media differently according to their needs and wants which is in par with the highlight of Uses and Gratification theory. Considering the significantly large role social media plays in our culture and daily life today, the finding will shed some light on the effect of social media on the elderly or senior citizens who are usually relegated into a minority group in today’s age where the internet and social media are of great importance to our society and humanity in general. This may also serve to be useful in understanding behavioral patterns and preference in terms of social media usage among the elderly.
Keywords: Elderly, Facebook, Malaysia, social media.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 54572599 Sensitivity of Small Disturbance Angle Stability to the System Parameters of Future Power Networks
Authors: Nima Farkhondeh Jahromi, George Papaefthymiou, Lou van der Sluis
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The incorporation of renewable energy sources for the sustainable electricity production is undertaking a more prominent role in electric power systems. Thus, it will be an indispensable incident that the characteristics of future power networks, their prospective stability for instance, get influenced by the imposed features of sustainable energy sources. One of the distinctive attributes of the sustainable energy sources is exhibiting the stochastic behavior. This paper investigates the impacts of this stochastic behavior on the small disturbance rotor angle stability in the upcoming electric power networks. Considering the various types of renewable energy sources and the vast variety of system configurations, the sensitivity analysis can be an efficient breakthrough towards generalizing the effects of new energy sources on the concept of stability. In this paper, the definition of small disturbance angle stability for future power systems and the iterative-stochastic way of its analysis are presented. Also, the effects of system parameters on this type of stability are described by performing a sensitivity analysis for an electric power test system.
Keywords: Power systems stability, Renewable energy sources, Stochastic behavior, Small disturbance rotor angle stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20682598 Artificial Neurons Based on Memristors for Spiking Neural Networks
Authors: Yan Yu, Wang Yu, Chen Xintong, Liu Yi, Zhang Yanzhong, Wang Yanji, Chen Xingyu, Zhang Miaocheng, Tong Yi
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Neuromorphic computing based on spiking neural networks (SNNs) has emerged as a promising avenue for building the next generation of intelligent computing systems. Owing to their high-density integration, low power, and outstanding nonlinearity, memristors have attracted emerging attention on achieving SNNs. However, fabricating a low-power and robust memristor-based spiking neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a TiO2-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, used to realize single layer fully connected (FC) SNNs. Moreover, our TiO2-based resistive switching (RS) memristors realize spiking-time-dependent-plasticity (STDP), originating from the Ag diffusion-based filamentary mechanism. This work demonstrates that TiO2-based memristors may provide an efficient method to construct hardware neuromorphic computing systems.
Keywords: Leaky integrate-and-fire, memristor, spiking neural networks, spiking-time-dependent-plasticity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6632597 Advanced Hybrid Particle Swarm Optimization for Congestion and Power Loss Reduction in Distribution Networks with High Distributed Generation Penetration through Network Reconfiguration
Authors: C. Iraklis, G. Evmiridis, A. Iraklis
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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.
Keywords: Congestion, distribution networks, loss reduction, particle swarm optimization, smart grid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7262596 Forms of Social Quality Mobilization in Suburban Communities of a Changing World
Authors: Supannee Chaiumporn
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This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social qualitymaking. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party which is concerned (4) self-reliance.Keywords: Social quality, form of social quality moving process, happiness, different social and cultural context.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15812595 Effective Implementation of Burst SegmentationTechniques in OBS Networks
Authors: A. Abid, F. M. Abbou, H. T. Ewe
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Optical Bursts Switching (OBS) is a relatively new optical switching paradigm. Contention and burst loss in OBS networks are major concerns. To resolve contentions, an interesting alternative to discarding the entire data burst is to partially drop the burst. Partial burst dropping is based on burst segmentation concept that its implementation is constrained by some technical challenges, besides the complexity added to the algorithms and protocols on both edge and core nodes. In this paper, the burst segmentation concept is investigated, and an implementation scheme is proposed and evaluated. An appropriate dropping policy that effectively manages the size of the segmented data bursts is presented. The dropping policy is further supported by a new control packet format that provides constant transmission overhead.Keywords: Burst length, Burst Segmentation, Optical BurstSwitching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14222594 Practice of Social Audit in Hotel Companies: Case Study of Agadir, Morocco
Authors: M. El Mousadik, F. Elkandoussi
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The concern for increased rigor in social management has led more and more Moroccan business leaders to question the value of applying social audit as an essential tool in the management of human resources. Hotel companies are not excluded; in fact, they are expected to implement such an audit to develop sound and credible human resources management (HRM) policies. The main objective of this paper is to establish the relationship between the practice of social audit as a tool, and its impact on the tourism sector, especially on hotels at one of the Morocco’s first and most popular city for tourism, Agadir. This exploratory study of properties in Agadir has revealed that hotel executives are aware of the importance of social auditing to hone their decisions in the field of HRM.
Keywords: Social audit, hotel companies, human resources management, social piloting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17942593 Tidal Data Analysis using ANN
Authors: Ritu Vijay, Rekha Govil
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The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.Keywords: ANN, RBF, Tidal Data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16432592 Design and Social Innovation: A Systemic Approach
Authors: Marco Ogê Muniz, Luiz Fernando Gonçalves De Figueiredo
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Design, as an area of knowledge, is subject to changes that affect it through different approaches, both theoretical and practical; its include matters related with responsibility, environment, social worries, and things alike. Commensurately, such contemporary aspects open room for social initiatives. This scenario begins to be looked at, especially in creative communities. Such proposal for a systemic approach of design is seen as a way to involve the stakeholders in the processes of investigation and of social innovation, which can decisively contribute for the development of traditional local communities. As a theoretical basis for the research, this paper outlines some especial features of design and social innovation, in their particular and in their complementary aspects, as well as in the way they relate with each other.
Keywords: Responsible design, social innovation, creative community, systemic approach, network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16242591 Artificial Neural Networks for Classifying Magnetic Measurements in Tokamak Reactors
Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci
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This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.
Keywords: Tokamak, sensors, artificial neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18102590 An Efficient and Optimized Multi Constrained Path Computation for Real Time Interactive Applications in Packet Switched Networks
Authors: P.S. Prakash, S. Selvan
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Quality of Service (QoS) Routing aims to find path between source and destination satisfying the QoS requirements which efficiently using the network resources and underlying routing algorithm and to fmd low-cost paths that satisfy given QoS constraints. One of the key issues in providing end-to-end QoS guarantees in packet networks is determining feasible path that satisfies a number of QoS constraints. We present a Optimized Multi- Constrained Routing (OMCR) algorithm for the computation of constrained paths for QoS routing in computer networks. OMCR applies distance vector to construct a shortest path for each destination with reference to a given optimization metric, from which a set of feasible paths are derived at each node. OMCR is able to fmd feasible paths as well as optimize the utilization of network resources. OMCR operates with the hop-by-hop, connectionless routing model in IP Internet and does not create any loops while fmding the feasible paths. Nodes running OMCR not necessarily maintaining global view of network state such as topology, resource information and routing updates are sent only to neighboring nodes whereas its counterpart link-state routing method depend on complete network state for constrained path computation and that incurs excessive communication overhead.
Keywords: QoS Routing, Optimization, feasible path, multiple constraints.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11142589 Factorial Design Analysis for Quality of Video on MANET
Authors: Hyoup-Sang Yoon
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The quality of video transmitted by mobile ad hoc networks (MANETs) can be influenced by several factors, including protocol layers; parameter settings of each protocol. In this paper, we are concerned with understanding the functional relationship between these influential factors and objective video quality in MANETs. We illustrate a systematic statistical design of experiments (DOE) strategy can be used to analyze MANET parameters and performance. Using a 2k factorial design, we quantify the main and interactive effects of 7 factors on a response metric (i.e., mean opinion score (MOS) calculated by PSNR with Evalvid package) we then develop a first-order linear regression model between the influential factors and the performance metric.
Keywords: Evalvid, full factorial design, mobile ad hoc networks, ns-2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2078