Use of social networks for academic purposes: a case study

Purpose This paper aims to analyse various aspects of an academic social network: the profile of users, the reasons for its use, its perceived benefits and the use of other social media for scholarly purposes. Design/methodology/approach The authors examined the profiles of the users of an academic social network. The users were affiliated with 12 universities. The following were recorded for each user: sex, the number of documents uploaded, the number of followers, and the number of people being followed. In addition, a survey was sent to the individuals who had an email address in their profile. Findings Half of the users of the social network were academics and a third were PhD students. Social sciences scholars accounted for nearly half of all users. Academics used the service to get in touch with other scholars, disseminate research results and follow other scholars. Other widely employed social media included citation indexes, document creation, edition and sharing tools and communication tools. Users complained about the lack of support for the utilisation of these tools. Research limitations/implications The results are based on a single case study. Originality/value This study provides new insights on the impact of social media in academic contexts by analysing the user profiles and benefits of a social network service that is specifically targeted at the academic community.

The establishment of communication systems depends on the scale of competition

How communication systems emerge and remain stable is an important question in both cognitive science and evolutionary biology. For communication to arise, not only must individuals cooperate by signaling reliable information, but they must also coordinate and perpetuate signals. Most studies on the emergence of communication in humans typically consider scenarios where individuals implicitly share the same interests. Likewise, most studies on human cooperation consider scenarios where shared conventions of signals and meanings cannot be developed de novo. Here, we combined both approaches with an economic experiment where participants could develop a common language, but under different conditions fostering or hindering cooperation. Participants endeavored to acquire a resource through a learning task in a computer-based environment. After this task, participants had the option to transmit a signal (a color) to a fellow group member, who would subsequently play the same learning task. We varied the way participants competed with each other (either global scale or local scale) and the cost of transmitting a signal (either costly or noncostly) and tracked the way in which signals were used as communication among players. Under global competition, players signaled more often and more consistently, scored higher individual payoffs, and established shared associations of signals and meanings. In addition, costly signals were also more likely to be used under global competition; whereas under local competition, fewer signals were sent and no effective communication system was developed. Our results demonstrate that communication involves both a coordination and a cooperative dilemma and show the importance of studying language evolution under different conditions influencing human cooperation.

Characterization of Reward Functions in Networks with Costs

In this paper we study network structures in which the possibilities for cooperation are restricted and can not be described by a cooperative game. The benefits of a group of players depend on how these players are internally connected. One way to represent this type of situations is the so-called reward function, which represents the profits obtainable by the total coalition if links can be used to coordinate agents' actions. The starting point of this paper is the work of Vilaseca et al. where they characterized the reward function. We concentrate on those situations where there exist costs for establishing communication links. Given a reward function and a costs function, our aim is to analyze under what conditions it is possible to associate a cooperative game to it. We characterize the reward function in networks structures with costs for establishing links by means of two conditions, component permanence and component additivity. Finally, an economic application is developed to illustrate the main theoretical result.

A Secure and Anonymous Cooperative Sensing Protocol for Cognitive Radio Networks

Spectrum is an essential resource for the provision of mobile services. In order to control and delimit its use, governmental agencies set up regulatory policies. Unfortunately, such policies have led to a deficiency of spectrum as only few frequency bands are left unlicensed, and these are used for the majority of new emerging wireless applications. One promising way to alleviate the spectrum shortage problem is adopting a spectrum sharing paradigm in which frequency bands are used opportunistically. Cognitive radio is the key technology to enable this shift of paradigm.Cognitive radio networks are self-organized systems in which devices cooperate to use those spectrum ranges that are not occupied by licensed users. They carry out spectrum sensing in order to detect vacant channels that can be used for communication. Even though spectrum sensing is an active area of research, an important issue remains unsolved: the secure authentication of sensing reports. Not providing security enables the input of false data in the system thus empowering false results. This paper presents a distributed protocol based on wireless physical layer security, symmetric cryptography and one-way functions that allows determining a final sensing decision from multiple sources in a quick and secure way, as well as it preserves users¿ privacy.

Reconstruction of networks from their betweenness centrality

In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimization method to generate the network from the values of the betweenness centrality. We compare the performance of this technique when reconstructing different categories of networks –random, regular, small-world, scale-free and clustered–. We show that the method allows an exact reconstruction of small networks and leads to good topological approximations in the case of networks with larger orders. The method can be used to generate a quasi-optimal topology fora communication network from a list with the values of the maximum allowable traffic for each node.

Joint physical-MAC layer design of the broadcast channel protocol in adhoc networks

Broadcast transmission mode in ad hoc networks is critical to manage multihop routing or providing medium accesscontrol (MAC)-layer fairness. In this paper, it is shown that ahigher capacity to exchange information among neighbors may beobtained through a physical-MAC cross-layer design of the broadcastprotocol exploiting signal separation principles. Coherentdetection and separation of contending nodes is possible throughtraining sequences which are selected at random from a reducedset. Guidelines for the design of this set are derived for a lowimpact on the network performance and the receiver complexity.

Secure many-to-one communications in wireless sensor networks

Wireless Sensor Networks (WSN) are formed by nodes with limited computational and power resources. WSNs are finding an increasing number of applications, both civilian and military, most of which require security for the sensed data being collected by the base station from remote sensor nodes. In addition, when many sensor nodes transmit to the base station, the implosion problem arises. Providing security measures and implosion-resistance in a resource-limited environment is a real challenge. This article reviews the aggregation strategies proposed in the literature to handle the bandwidth and security problems related to many-to-one transmission in WSNs. Recent contributions to secure lossless many-to-one communication developed by the authors in the context of several Spanish-funded projects are surveyed. Ongoing work on the secure lossy many-to-one communication is also sketched.

Integrating defeasible argumentation with fuzzy ART neural networks for pattern classification

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that every cluster ci is labelled as positive or negative. Given a new, unlabelled instance enew, the above classification is used to determine to which particular cluster ci this new instance belongs. In such a setting clusters can overlap, and a new unlabelled instance can be assigned to more than one cluster with conflicting labels. In the literature, such a case is usually solved non-deterministically by making a random choice. This paper presents a novel, hybrid approach to solve this situation by combining a neural network for classification along with a defeasible argumentation framework which models preference criteria for performing clustering.

Using Pareto optimality to explore the topology and dynamics of the human connectome.

Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.

Mobility Management in Packet Switched Mobile Networks

Nykyisin matkaviestinverkot ovat osa jokapäiväistä elämää. Merkittävimpiä eroja kiinteiden ja matkaviestinverkkojen välillä on käyttäjän liikkuvuus, joka voidaan määritellä mahdollisuudeksi soittaa ja vastaanottaa puheluita missä ja milloin tahansa. Työ selittää termin liikkuvuus ja määrittää ongelmat, jotka täytyy ratkaista liikkuvuuden aikaansaamiseksi sekä tavat, joilla nämä ongelmat on ratkaistu matkaviestinverkoissa. Työ luo yleiskatsauksen liikkuvuuden aikaansaamisessa käytettäviin menetelmiin, joita ovat haku, sijainnin päivitys, sijainnin seuranta ja kanavan vaihto. Työ keskittyy liikkuvuuteen kolmannen sukupolven matkaviestinverkkojen paketti-kytkentäisessä osassa, esimerkkinä liikkuvuuden hallinta UMTS:ssa (Universal Mobile Telecommunications System). Erot paketti- ja piirikytkentäisen osan välillä tuodaan esille ja selitetään. Jotta käyttäjät ja heidän päätteensä voisivat liikkua, tiedon täytyy kulkea verkon eri osien välillä. Merkinanto verkkoelementtien välillä ja liikkuvuuden mahdollistavien toimenpiteiden suoritus tehdään yhteyskäytännön avulla. Työ kuvaa yhteyskäytännöt, jotka ovat osallisena liikkuvuuden tarjontaan. Painopiste on GPRS:n liikkuvuuden-hallintayhteyskäytännössä, GMM:ssä. GMM protokollan prototyypin toteutus on esitetty työn käytännön osassa.

Use of social networks for academic purposes: a case study

Purpose- This paper aims to analyse various aspects of an academic social network: the profile of users, the reasons for its use, its perceived benefits and the use of other social media for scholarly purposes. Design/methodology/approach- The authors examined the profiles of the users of an academic social network. The users were affiliated with 12 universities. The following were recorded for each user: sex, the number of documents uploaded, the number of followers, and the number of people being followed. In addition, a survey was sent to the individuals who had an email address in their profile. Findings- Half of the users of the social network were academics and a third were PhD students. Social sciences scholars accounted for nearly half of all users. Academics used the service to get in touch with other scholars, disseminate research results and follow other scholars. Other widely employed social media included citation indexes, document creation, edition and sharing tools and communication tools. Users complained about the lack of support for the utilisation of these tools. Research limitations/implications- The results are based on a single case study. Originality/value- This study provides new insights on the impact of social media in academic contexts by analysing the user profiles and benefits of a social network service that is specifically targeted at the academic community.

Business potential evaluation of wireless local area networks: Teleoperator’s view

The objective of the thesis was to evaluate business potential of wireless local area networks (WLAN, Wireless LAN). At first, the scope of business potential evaluation of technology was introduced. Next, a general framework of business potential evaluation of technology based on literature was presented. In addition, convergence of cellular networks and data networks was studied in order to get an insight of current situation of mobile telecommunications industry. Finally, wireless local area networks business potential was evaluated. A wireless local area network is a data communication system, which combines data connectivity with mobility and is implemented in unlicensed frequency bands, allowing new business opportunities to emerge. The main markets of WLAN are corporate networks, public area networks and access networks. At the moment the penetration of WLAN terminals is low which derives to low demand of wireless LAN services. In addition, unlicensed spectrum forces the teleoperators to set the service price relatively low. The business potential is in integrating wireless LANs to cellular networks and in offering value added services to end users. The future of wireless LAN is to be complementary network to cellular networks. In this vision cellular networks provide voice and low data services and broadband wireless networks enable multimedia services.

Cooperative and Competitive Spreading Dynamics on the Human Connectome.

Increasingly detailed data on the network topology of neural circuits create a need for theoretical principles that explain how these networks shape neural communication. Here we use a model of cascade spreading to reveal architectural features of human brain networks that facilitate spreading. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we investigate scenarios where perturbations initiated at seed nodes result in global cascades that interact either cooperatively or competitively. We find that hub regions and a backbone of pathways facilitate early spreading, while the shortest path structure of the connectome enables cooperative effects, accelerating the spread of cascades. Finally, competing cascades become integrated by converging on polysensory associative areas. These findings show that the organizational principles of brain networks shape global communication and facilitate integrative function.