Search results for: Online Social Network

Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello

Abstract:

Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.

Keywords: Internet of Things, LoRa, LoRaWAN, smart cities.

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Authors: R.N.Pise, S.A.Kulkarni, R.V.Pawar

Abstract:

MultiProtocol Label Switching (MPLS) is an emerging technology that aims to address many of the existing issues associated with packet forwarding in today-s Internetworking environment. It provides a method of forwarding packets at a high rate of speed by combining the speed and performance of Layer 2 with the scalability and IP intelligence of Layer 3. In a traditional IP (Internet Protocol) routing network, a router analyzes the destination IP address contained in the packet header. The router independently determines the next hop for the packet using the destination IP address and the interior gateway protocol. This process is repeated at each hop to deliver the packet to its final destination. In contrast, in the MPLS forwarding paradigm routers on the edge of the network (label edge routers) attach labels to packets based on the forwarding Equivalence class (FEC). Packets are then forwarded through the MPLS domain, based on their associated FECs , through swapping the labels by routers in the core of the network called label switch routers. The act of simply swapping the label instead of referencing the IP header of the packet in the routing table at each hop provides a more efficient manner of forwarding packets, which in turn allows the opportunity for traffic to be forwarded at tremendous speeds and to have granular control over the path taken by a packet. This paper deals with the process of MPLS forwarding mechanism, implementation of MPLS datapath , and test results showing the performance comparison of MPLS and IP routing. The discussion will focus primarily on MPLS IP packet networks – by far the most common application of MPLS today.

Keywords: Forwarding equivalence class, incoming label map, label, next hop label forwarding entry.

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Authors: A. Mirzaaghazadeh, H. Motameni, M. Karshenas, H. Nematzadeh

Abstract:

Learning the gradient of neuron's activity function like the weight of links causes a new specification which is flexibility. In flexible neural networks because of supervising and controlling the operation of neurons, all the burden of the learning is not dedicated to the weight of links, therefore in each period of learning of each neuron, in fact the gradient of their activity function, cooperate in order to achieve the goal of learning thus the number of learning will be decreased considerably. Furthermore, learning neurons parameters immunes them against changing in their inputs and factors which cause such changing. Likewise initial selecting of weights, type of activity function, selecting the initial gradient of activity function and selecting a fixed amount which is multiplied by gradient of error to calculate the weight changes and gradient of activity function, has a direct affect in convergence of network for learning.

Keywords: Back propagation, Flexible, Gradient, Learning, Neural network, Pattern recognition.

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

Abstract:

This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: Visual search, deep learning, convolutional neural network, machine learning.

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Authors: Rustamov Nasim, Roostamov Yunusbek

Abstract:

In this work social stratification is considered as one of significant factor which generate the phenomena “terrorism” and it puts the accent on correlation connection between them, with the object of creation info-logical model generation of phenomena of “terrorism” based on stratification process.

Keywords: Social stratification, stratification process, generation of phenomena “terrorism”, conceptions – “terror”, “terrorize” and “terrorism”, info-logical model of phenomena of “terrorism”.

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Authors: Nor Azuana Ramli, Mohd Tahir Ismail, Hooy Chee Wooi

Abstract:

Developing a stable early warning system (EWS) model that is capable to give an accurate prediction is a challenging task. This paper introduces k-nearest neighbour (k-NN) method which never been applied in predicting currency crisis before with the aim of increasing the prediction accuracy. The proposed k-NN performance depends on the choice of a distance that is used where in our analysis; we take the Euclidean distance and the Manhattan as a consideration. For the comparison, we employ three other methods which are logistic regression analysis (logit), back-propagation neural network (NN) and sequential minimal optimization (SMO). The analysis using datasets from 8 countries and 13 macro-economic indicators for each country shows that the proposed k-NN method with k = 4 and Manhattan distance performs better than the other methods.

Keywords: Currency crisis, k-nearest neighbour method, logit, neural network.

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Authors: Sarah Vuningoma, Maria Rosa Lorini, Wallace Chigona

Abstract:

Mobile phones are one of the main tools for promoting the wellbeing of people and supporting the integration of communities on the margins such as refugees. Information and Communication Technology has the potential to contribute towards reducing isolation, loneliness, and to assist in improving interpersonal relations and fostering acculturation processes. Therefore, the use of mobile phones by refugees might contribute to their social connectedness. This paper aims to demonstrate how existing literature has shown how the use of mobile phones by refugees should engender social connectedness amongst the refugees. Data for the study are drawn from existing literature; we searched a number of electronic databases for papers published between 2010 and 2019. The main findings of the study relate to the use of mobile phones by refugees to (i) create a sense of belonging, (ii) maintain relationships, and (iii) advance the acculturation process. The analysis highlighted a gap in the research over refugees and social connectedness. In particular, further studies should consider evaluating the differences between those who have a refugee permit, those who are waiting for the refugee permit, and those whose request was denied.

Keywords: Belonging, mobile phones, refugees, social connectedness.

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Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.

Keywords: Adaptive filter, distributed estimation, sensor network, diffusion.

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Authors: Sheng-Shih Wang, Wei-Ting Wang

Abstract:

This paper designs an intelligent guidance system, based on wireless sensor networks, for efficient parking in parking lots. The proposed system consists of a parking space allocation subsystem, a parking space monitoring subsystem, a driving guidance subsystem, and a vehicle detection subsystem. In the system, we propose a novel and effective virtual coordinate system for sensing and displaying devices to determine the proper vacant parking space and provide the precise guidance to the driver. This study constructs a ZigBee-based wireless sensor network on Arduino platform and implements the prototype of the proposed system using Arduino-based complements. Experimental results confirm that the proposed prototype can not only work well, but also provide drivers the correct parking information.

Keywords: Arduino, Parking guidance, Wireless sensor network, ZigBee.

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Authors: R. Behmanesh, I. Rahimi

Abstract:

recurrent neural network (RNN) is an efficient tool for modeling production control process as well as modeling services. In this paper one RNN was combined with regression model and were employed in order to be checked whether the obtained data by the model in comparison with actual data, are valid for variable process control chart. Therefore, one maintenance process in workshop of Esfahan Oil Refining Co. (EORC) was taken for illustration of models. First, the regression was made for predicting the response time of process based upon determined factors, and then the error between actual and predicted response time as output and also the same factors as input were used in RNN. Finally, according to predicted data from combined model, it is scrutinized for test values in statistical process control whether forecasting efficiency is acceptable. Meanwhile, in training process of RNN, design of experiments was set so as to optimize the RNN.

Keywords: RNN, DOE, regression, control chart.

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Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

Abstract:

The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: Condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network.

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

Abstract:

In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: Inverse problems, multi-component solutions, neural networks, Raman spectroscopy.

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

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Authors: M. Bouguerra, H. Meglouli, I. Habi

Abstract:

The great majority of the electric installations belong to the first and second category. In order to ensure a high level of reliability of their electric system feeder, two power supply sources are envisaged, one principal, the other of reserve, generally a cold reserve (electric diesel group). The principal source being under operation, its control can be ideal and sure, however for the reserve source being in stop, a preventive maintenance-s which proceeds on time intervals (periodicity) and for well defined lengths of time are envisaged, so that this source will always available in case of the principal source failure. The choice of the periodicity of preventive maintenance of the source of reserve influences directly the reliability of the electric feeder system. On the basis of the semi-markovians processes, the influence of the periodicity of the preventive maintenance of the source of reserve is studied and is given the optimal periodicity.

Keywords: Semi Markovians processes, reliability, optimization, electric network.

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Authors: M. Nageswara Rao

Abstract:

In this paper, a topology for high voltage gain half-bridge z-source inverter with low voltage stress on capacitors is proposed. The proposed inverter has only one impedance network. It can generate symmetric and asymmetric voltages with different magnitudes during both half-cycles. By selecting the duty cycle it can also produce conventional half-bridge inverter characteristics. It is used in special applications like, electrochemical and electro plating applications. Calculations of voltage ripple of capacitors, capacitors voltage stress inductors current ripple are presented. The proposed topology is simulated using PSCAD software and the simulated values are compared with the theoretical values.

Keywords: Half-bridge inverter, impedance network-source inverter, high voltage gain inverter, power system computer aided design.

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Authors: Z. Goosen, E. J. Cilliers

Abstract:

Social sustainability, as an independent perspective of sustainable development, has gained some acknowledgement, becoming an important aspect in sustainable urban planning internationally. However, limited research aiming at promoting social sustainability within urban areas exists within the South African context. This is mainly due to the different perspectives of sustainable development (e.g., Environmental, Economic, and Social) not being equally prioritized by policy makers and supported by implementation strategies, guidelines, and planning frameworks. The enhancement of social sustainability within urban areas relies on urban dweller satisfaction and the quality of urban life. Inclusive cities with high-quality public spaces are proposed within this research through implementing the third place theory. Third places are introduced as any place other than our homes (first place) and work (second place) and have become an integrated part of sustainable urban planning. As Third Places consist of every place 'in between', the approach has taken on a large role of the everyday life of city residents, and the importance of planning for such places can only be measured through identifying and highlighting the social sustainability benefits thereof. The aim of this research paper is to introduce third place planning within the urban area to ultimately enhance social sustainability. Selected background planning approaches influencing the planning of third places will briefly be touched on, as the focus will be placed on the social sustainability benefits provided through third place planning within an urban setting. The study will commence by defining and introducing the concept of third places within urban areas as well as a discussion on social sustainability, acting as one of the three perspectives of sustainable development. This will gain the researcher an improved understanding on social sustainability in order for the study to flow into an integrated discussion of the benefits Third places provide in terms of social sustainability and the impact it has on improved quality of life within urban areas. Finally, a visual case study comparison of local and international examples of third places identified will be illustrated. These international case studies will contribute towards the conclusion of this study where a local gap analysis will be formulated, based on local third place evidence and international best practices in order to formulate a strategic planning framework on improving social sustainability through third place planning within the local South African context.

Keywords: Planning benefits, social sustainability, third places, urban area.

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Authors: Rajoo Pandey

Abstract:

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

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

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Authors: Yung-Chuan Lee, Shahram Rahimi, Bidyut Gupta

Abstract:

In this paper, we introduce an mobile agent framework with proactive load balancing for ambient intelligence (AmI) environments. One of the main obstacles of AmI is the scalability in which the openness of AmI environment introduces dynamic resource requirements on agencies. To mediate this scalability problem, our framework proposes a load balancing module to proactively analyze the resource consumption of network bandwidth and preferred agencies to suggest the optimal communication method to its user. The framework generally formulates an AmI environment that consists of three main components: (1) mobile devices, (2) hosts or agencies, and (3) directory service center (DSC). A preliminary implementation was conducted with NetLogo and the experimental results show that the proposed approach provides enhanced system performance by minimizing the network utilization to provide users with responsive services.

Keywords: Ambient intelligence, load balancing, multiagent systems, ubiquitous computing.

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Authors: Najib Ahmad Marzuki, Che Su Mustaffa, Johana Johari, Nur Hafizza Rahaman

Abstract:

The purpose of this paper is to examine the effects and relationship of stress and social support towards the quality of life among flood victims in Malaysia. A total of 764 respondents took part in the survey via convenience sampling. The Depression, Anxiety and Stress scale (DASS) was utilized to measure stress while The Multidimensional Scale of Perceived Social Support was used to measure social support. To measure quality of life, the combination of WHO Quality of Life – BREF (WHOQOL-BREF) and The Impact of Event Scale – Revised (IES-R) were utilized. The findings of this study indicate that there were significant correlations between variables in the study. The findings showed a significant negative relation between stress and quality of life; and significant positive correlations between support from family as well as support from friends with quality of life. Stress and support from family were found to be significant predictors that influence the quality of life among flood victims.

Keywords: Stress, social support, quality of life, flood victims.

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Authors: Yahya H. Zweiri

Abstract:

The back-propagation algorithm calculates the weight changes of an artificial neural network, and a two-term algorithm with a dynamically optimal learning rate and a momentum factor is commonly used. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third term increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and optimization approaches for evaluating the learning parameters are required to facilitate the application of the three terms BP algorithm. This paper considers the optimization of the new back-propagation algorithm by using derivative information. A family of approaches exploiting the derivatives with respect to the learning rate, momentum factor and proportional factor is presented. These autonomously compute the derivatives in the weight space, by using information gathered from the forward and backward procedures. The three-term BP algorithm and the optimization approaches are evaluated using the benchmark XOR problem.

Keywords: Neural Networks, Backpropagation, Optimization.

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Authors: M. Abbasi Dezfouli, S. Mazraeh, M. H. Yektaie

Abstract:

Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.

Keywords: Wireless Sensor Networks, Security, Concealed Data Aggregation.

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Authors: Tingke Wu, Man Yuan

Abstract:

“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: Driving forces, Hubei, optimizing strategies, spatial pattern, territory.

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Authors: I Putu Eka N. Kencana, I Wayan Mertha

Abstract:

As an entity of the tourism system, local communities were considered have better understanding of their region as well as influenced positively or negatively by the tourism activities in the region. This paper aimed to study role of community involvement in the development of ecotourism at Kintamani Bali from two perspectives of view, i.e. participation in the process of initiatives and participation in the utilizing the economic benefits of tourism. Thorough participation as an antecedent of social capital form, the sustainability of ecotourism at Kintamani could be expected.

Keywords: Community involvement, ecotourism, participation, social capital.

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Authors: Piotr Podlipniak

Abstract:

This paper proposes that in the course of evolution pitch structure became a human specific tool of communication the function of which is to induce emotional states such as uncertainty and cohesion. By the means of eliciting these emotions during collective music performance people are able to unconsciously give cues concerning social acceptance. This is probably one of the reasons why in all cultures people collectively perform tonal music. It is also suggested that tonal pitch structure had been invented socially before it became an evolutionary innovation of hominines. It means that a predisposition to tonally organize pitches evolved by the means of ‘Baldwin effect’ – a process in which natural selection transforms the learned response of an organism into the instinctive response. In the proposed, hypothetical evolutionary scenario of the emergence of tonal pitch structure social forces such as a need for closer cooperation play the crucial role.

Keywords: Emotion, evolution, tonality, social consolidation.

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Authors: Guenther Schuh, Sebastian Woelk

Abstract:

Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. Goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: Interorganizational cooperation, design of network governance, research network.

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Authors: Maria de Nazaré Moraes Soares, Silvia Maria Dias Pedro Rebouças, José Carlos Lázaro

Abstract:

The Solidarity Economy (SE) acts in the re-articulation of the economic field to the other spheres of social action. The significant participation of women in SE resulted in the formation of a national network of self-managed enterprises in Brazil: The Solidarity and Feminist Economy Network (SFEN). The objective of the research is to identify factors of gender justice and feminist self-management practices that adhere to the reality of women in SE enterprises. The conceptual apparatus related to feminist studies in this research covers Nancy Fraser approaches on gender justice, and Patricia Yancey Martin approaches on feminist management practices, and authors of postcolonial feminism such as Mohanty and Maria Lugones, who lead the discussion to peripheral contexts, a necessary perspective when observing the women’s movement in SE. The research has a quantitative nature in the phases of data collection and analysis. The data collection was performed through two data sources: the database mapped in Brazil in 2010-2013 by the National Information System in Solidary Economy and 150 questionnaires with women from 16 enterprises in SFEN, in a state of Brazilian northeast. The data were analyzed using the multivariate statistical technique of Factor Analysis. The results show that the factors that define gender justice and feminist self-management practices in SE are interrelated in several levels, proving statistically the intersectional condition of the issue of women. The evidence from the quantitative analysis allowed us to understand the dimensions of gender justice and feminist management practices intersectionality; in this sense, the non-distribution of domestic work interferes in non-representation of women in public spaces, especially in peripheral contexts. The study contributes with important reflections to the studies of this area and can be complemented in the future with a qualitative research that approaches the perspective of women in the context of the SE self-management paradigm.

Keywords: Feminist management practices, gender justice, self-management, solidarity economy.

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Authors: Mirjana Radman-Funarić, Katarina Potnik Galić

Abstract:

The paper presents an analysis of linkages and structures of co-operation and their intensity like the potential for the establishment of clusters in the Central and Eastern (Pannonian) Croatian. Starting from the theoretical elaboration of the need for entrepreneurs to organize through the cluster model and the terms of their self-actualization, related to the importance of traditional values in terms of benefits, social capital and assess where the company now is, in order to prove the need to create their own identity in terms of clustering. The institutional dimensions of social capital where the public sector has the best role in creating the social structure of clusters, and social dimensions of social capital in terms of trust, cooperation and networking will be analyzed to what extent the trust and coherency are present between companies in the Brod posavina and Pozega slavonia County, expressed through the readiness of inclusion in clusters in the NUTS II region - Central and Eastern (Pannonian) Croatia, as a homogeneous economic entity, with emphasis on limiting factors that stand in the way of greater competitiveness.

Keywords: Analysis of linkages, structures of co-operation, Cluster, Region

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

Abstract:

In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: Distributed control, game theory, multi-agent learning, reinforcement learning.

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Authors: Laveen Sundararaj, Palanisamy Vellaiyan

Abstract:

Delay and Disruption Tolerant Networking is part of the Inter Planetary Internet with primary application being Deep Space Networks. Its Terrestrial form has interesting research applications such as Alagappa University Delay Tolerant Water Monitoring Network which doubles as test beds for improvising its routing scheme. DTNs depend on node mobility to deliver packets using a store-carry-and forward paradigm. Throwboxes are small and inexpensive stationary devices equipped with wireless interfaces and storage. We propose the use of Throwboxes to enhance the contact opportunities of the nodes and hence improve the Throughput. The enhancement is evaluated using Alunivdtnsim, a desktop simulator in C language and the results are graphically presented.

Keywords: Alunivdtnsim – Alagappa University Delay TolerantNetwork Simulator, AUDTWMN- Alagappa University DelayTolerant Water Monitoring Network, DTN - Delay and DisruptionTolerant Networking, LTP – Lick Lider Transmission Protocol.

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Authors: M. Abbasi Dezfouli, S. Mazraeh, M. H. Yektaie

Abstract:

Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.

Keywords: Wireless Sensor Networks, Security, Concealed Data Aggregation.

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