Tracing the evolution of physics on the backbone of citation networks

Many innovations are inspired by past ideas in a nontrivial way. Tracing these origins and identifying scientific branches is crucial for research inspirations. In this paper, we use citation relations to identify the descendant chart, i.e., the family tree of research papers. Unlike other spanning trees that focus on cost or distance minimization, we make use of the nature of citations and identify the most important parent for each publication, leading to a treelike backbone of the citation network. Measures are introduced to validate the backbone as the descendant chart. We show that citation backbones can well characterize the hierarchical and fractal structure of scientific development, and lead to an accurate classification of fields and subfields. © 2011 American Physical Society.

Understanding inter-firm networks and types of innovation in SMEs:a social network perspective

Innovation is one of the key drivers for gaining competitive advantages in any firms. Understanding knowledge transfer through inter-firm networks and its effects on types of innovation in SMEs is very important in improving SMEs innovation. This study examines relationships between characteristics of inter-firm knowledge transfer networks and types of innovation in SMEs. To achieve this, social network perspective is adopted to understand inter-firm knowledge transfer networks and its impact on innovation by investigating how and to what extend ego network characteristics are affecting types of innovation. Therefore, managers can develop the firms'network according to their strategies and requirements. First, a conceptual model and research hypotheses are proposed to establish the possible relationship between network properties and types of innovation. Three aspects of ego network are identified and adopted for hypotheses development: 1) structural properties which address the potential for resources and the context for the flow of resources, 2) relational properties which reflect the quality of resource flows, and 3) nodal properties which are about quality and variety of resources and capabilities of the ego partners. A questionnaire has been designed based on the hypotheses. Second, semistructured interviews with managers of five SMEs have been carried out, and a thematic qualitative analysis of these interviews has been performed. The interviews helped to revise the questionnaire and provided preliminary evidence to support the hypotheses. Insights from the preliminary investigation also helped to develop research plan for the next stage of this research.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

A hálózati pozíció és a versenyképesség kapcsolata (Business networks: network position and competitiveness in Hungary)

A cikk fókuszában az üzleti hálózatok állnak. Az IMP-csoport (Industrial Marketing and Purchasing Group) üzleti kapcsolatokkal, üzleti hálózatokkal foglalkozó több évtizedes kutatási eredményeire és fogalomrendszerére építve a szerzők áttekintik a téma alapvető megközelítéseit, majd a Versenyképesség-kutatás 2009. évi felmérésének adatait Felhasználva, megvizsgálják a vállalatvezetők által észlelt hálózati pozíció és a versenyképesség összefüggéseit. A vállalatvezetők értékelése szerint elemzik az iparági hálózatukban központi szerepet játszó, befolyással bíró (domináns hálózati pozícióval rendelkező) vállalatokat, különös tekintettel az üzleti teljesítmény és a versenyképesség jellemzőire. / === / The paper analyses the business network position of Hungarian companies, based on data of the Competitiveness research program. After an overview of the theoretical background of business relationships, business networks and network position – based on the IMP (Industrial Marketing and Purchasing Group) approach, the authors analyse the performance and competitiveness characteristics of firms with central position in their industrial network.

Üzleti hálózatok – Hálózati pozíció és versenyképesség = Business networks: network position and competitiveness in Hungary

Tanulmányunk fókuszában az üzleti hálózatok állnak. Az IMP csoport (Industrial Marketing and Purchasing Group) üzleti kapcsolatokkal, üzleti hálózatokkal foglalkozó több évtizedes kutatási eredményeire és fogalomrendszerére alapozva áttekintjük a téma alapmegközelítéseit, majd a Versenyképesség-kutatás 2009. évei felmérése adatainak felhasználásával vizsgáljuk a hálózati kép és a versenyképesség összefüggéseit. Jellemezzük a vállaltvezetők értékelése szerint az iparági hálózatukban központi szerepet játszó, befolyással bíró (domináns hálózati pozícióval rendelkező) vállalatokat, különös tekintettel az üzleti teljesítmény és versenyképesség jellemzőire. ________ The paper analyses the business network position of Hungarian companies, based on data of the Competitiveness research program. After an overview of the theoretical background of business relationships, business networks and network position – based on the IMP (Industrial Marketing and Purchasing Group) approach, we analyse the performance and competitiveness characteristics of firms with central position in their industrial network.

Trust and cooperation in buyer–seller relationships and networks. The co-evolution of structural balance and trust in iterated PD games

Our study has two aims: to elaborate theoretical frameworks and introduce social mechanisms of spontaneous co-operation in repeated buyer-seller relationships and to formulate hypotheses which can be empirically tested. The basis of our chain of ideas is the simple two-person Prisoner’s Dilemma game. On the one hand, its repeated variation can be applicable for the distinction of the analytical types of trust (iteration trust, strategy trust) in co-operations. On the other hand, it provides a chance to reveal those dyadic sympathy-antipathy relations, which make us understand the evolution of trust. Then we introduce the analysis of the more complicated (more than two-person) buyer-seller relationship. Firstly, we outline the possible role of the structural balancing mechanisms in forming trust in three-person buyer-seller relationships. Secondly, we put forward hypotheses to explain complex buyer-seller networks. In our research project we try to theoretically combine some of the simple concepts of game theory with certain ideas of the social-structural balance theory. Finally, it is followed by a short summary.

Kis- és középvállalatok innovációs tevékenysége a válság idején – hálózatok szerepe (Innovation of small and medium-sized enterprises in times of crises – The role of networks)

A hálózati megközelítés alapján a vállalatok nem izoláltan működő szervezetek. A kis- és középvállalkozások számára a hálózatok, a partnerkapcsolatok jelentős támogatást képesek biztosítani a növekedés, a tanulás és az innovációs tevékenység során. A szerző a hálózati, partneri kapcsolatok szerepét a válság idején vizsgálta, kvalitatív kutatás keretében. A tanulmány fontos megállapítása, hogy nem kizárólag a hálózatban rejlő lehetőségek, hanem a korábban biztos partneri kapcsolatok megszűnése is indukálhat innovációt a válság idején, valamint a biztonság, a tartalék-erőforrások megléte esetén lassabb a piaci reagálás, kevésbé kerül előtérbe a változás, s főként az innovációs tevékenység ______ Based on the network perspective companies are not isolated organizations. Networks and partnerships mean a significant support for SMEs in growth, learning and innovation. The author examines the role of networks and partnerships during the crisis, in a qualitative research. An important result of the paper is that not only the opportunities in networks but also the decomposition of prior secure relationships can induce innovation during the crisis. Moreover in case of safety and slack resources the reaction is slower, change and innovation come to the front less.

The possibilities of biodiversity monitoring based on Hungarian Light Trap Networks

Our method is presented with displaying time series, consisting of the daily amount of precipitation of 100 years, which has meant a separate challenge, as the precipitation data shows significant deviations. By nowadays, mankind has changed its environment to such an extent that it has a significant effect on other species as well. The Lepidoptera data series of the National Plant Protection and Forestry Light Trap Network can be used to justify this. This network has a national coverage, a large number of collected Lepidoptera, and an available, long data series of several years. For obtaining information from these data, the setting up of an easy to manage database is necessary. Furthermore, it is important to represent our data and our results in an easily analysable and expressive way. In this article the setting up of the database is introduced, together with the presentation of a three dimensional visualization method, which depicts the long-range and seasonal changes together.

The regulatory environment of the section of the non-standardized goods market - The findings of an interview research on Hungarian construction industry small enterprises

In this paper the behavior of economic actors shown in the uncertain quality goods markets is examined from the perspective of the sociology of markets. The analysis uses the findings of in-depth interviews conducted in 2011 and 2012 respectively amongst small and medium size entrepreneurs working in construction industry. In the Hungarian construction industry neither formal rules, nor vocational chambers, are able to create a safe environment for entrepreneurs. Nevertheless, networks created as a result of micro-selection steps might be able to enforce the quality of services, observe deadlines and what is more, ensure payment discipline. In this market, the typical high risk can be reduced by relationships. Networks reduce also the cost of transactions, since the important part of the services in this field could only be standardized at significant costs.

Knowledge and innovation as value drivers in professional services firms: an empirical research in Central and Eastern Europe

The purpose of this study was to investigate empirically the role of knowledge and innovation within Central and Eastern Europe’s changing economy. We applied qualitative research methods, and focused only on professional services firms within the region. The connection between knowledge and innovation as well as knowledge and competitiveness was analyzed by top managers and senior industry experts. Our findings revealed that knowledge might be a real value driver for professional services firms. These companies can significantly contribute to the development of modern economies through the dissemination of their internal best practices in knowledge management. We found three factors that might influence the effectiveness of knowledge management. These three factors are the involvement of international knowledge networks, the investments in human capital, and focus on critical resources. These issues proved to be essential to maximize the potential of knowledge and to leverage this into increased business performance.

Pavement performance prediction using adaptive logic networks

Pavement performance is one of the most important components of the pavement management system. Prediction of the future performance of a pavement section is important in programming maintenance and rehabilitation needs. Models for predicting pavement performance have been developed on the basis of traffic and age. The purpose of this research is to extend the use of a relatively new approach to performance prediction in pavement performance modeling using adaptive logic networks (ALN). Adaptive logic networks have recently emerged as an effective alternative to artificial neural networks for machine learning tasks. ^ The ALN predictive methodology is applicable to a wide variety of contexts including prediction of roughness based indices, composite rating indices and/or individual pavement distresses. The ALN program requires key information about a pavement section, including the current distress indexes, pavement age, climate region, traffic and other variables to predict yearly performance values into the future. ^ This research investigates the effect of different learning rates of the ALN in pavement performance modeling. It can be used at both the network and project level for predicting the long term performance of a road network. Results indicate that the ALN approach is well suited for pavement performance prediction modeling and shows a significant improvement over the results obtained from other artificial intelligence approaches. ^

Secure routing and trust computation in multihop infrastructureless networks

Today's wireless networks rely mostly on infrastructural support for their operation. With the concept of ubiquitous computing growing more popular, research on infrastructureless networks have been rapidly growing. However, such types of networks face serious security challenges when deployed. This dissertation focuses on designing a secure routing solution and trust modeling for these infrastructureless networks. ^ The dissertation presents a trusted routing protocol that is capable of finding a secure end-to-end route in the presence of malicious nodes acting either independently or in collusion, The solution protects the network from active internal attacks, known to be the most severe types of attacks in an ad hoc application. Route discovery is based on trust levels of the nodes, which need to be dynamically computed to reflect the malicious behavior in the network. As such, we have developed a trust computational model in conjunction with the secure routing protocol that analyzes the different malicious behavior and quantifies them in the model itself. Our work is the first step towards protecting an ad hoc network from colluding internal attack. To demonstrate the feasibility of the approach, extensive simulation has been carried out to evaluate the protocol efficiency and scalability with both network size and mobility. ^ This research has laid the foundation for developing a variety of techniques that will permit people to justifiably trust the use of ad hoc networks to perform critical functions, as well as to process sensitive information without depending on any infrastructural support and hence will enhance the use of ad hoc applications in both military and civilian domains. ^

An indexing structure and application model for vehicles moving on road networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles' location and motion information, range queries on current and history data, and prediction of vehicles' movement in the near future. ^ To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. ^ Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. ^ An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed. ^

An investigation of location effect on trip production using artificial neural networks

As traffic congestion exuberates and new roadway construction is severely constrained because of limited availability of land, high cost of land acquisition, and communities' opposition to the building of major roads, new solutions have to be sought to either make roadway use more efficient or reduce travel demand. There is a general agreement that travel demand is affected by land use patterns. However, traditional aggregate four-step models, which are the prevailing modeling approach presently, assume that traffic condition will not affect people's decision on whether to make a trip or not when trip generation is estimated. Existing survey data indicate, however, that differences exist in trip rates for different geographic areas. The reasons for such differences have not been carefully studied, and the success of quantifying the influence of land use on travel demand beyond employment, households, and their characteristics has been limited to be useful to the traditional four-step models. There may be a number of reasons, such as that the representation of influence of land use on travel demand is aggregated and is not explicit and that land use variables such as density and mix and accessibility as measured by travel time and congestion have not been adequately considered. This research employs the artificial neural network technique to investigate the potential effects of land use and accessibility on trip productions. Sixty two variables that may potentially influence trip production are studied. These variables include demographic, socioeconomic, land use and accessibility variables. Different architectures of ANN models are tested. Sensitivity analysis of the models shows that land use does have an effect on trip production, so does traffic condition. The ANN models are compared with linear regression models and cross-classification models using the same data. The results show that ANN models are better than the linear regression models and cross-classification models in terms of RMSE. Future work may focus on finding a representation of traffic condition with existing network data and population data which might be available when the variables are needed to in prediction.

Location management and routing in urban vehicular ad hoc networks

In recent years, urban vehicular ad hoc networks (VANETs) are gaining importance for inter-vehicle communication, because they allow for the local communication between vehicles without any infrastructure, configuration effort, and without expensive cellular networks. But such architecture may increase the complexity of routing since there is no central control system in urban VANETs. Therefore, a challenging research task is to improve urban VANETs' routing efficiency. ^ Hence, in this dissertation we propose two location-based routing protocols and a location management protocol to facilitate location-based routing in urban VANETs. The Multi-hop Routing Protocol (MURU) is proposed to make use of predicted mobility and geometry map in urban VANETs to estimate a path's life time and set up robust end-to-end routing paths. The Light-weight Routing Protocol (LIRU) is proposed to take advantage of the node diversity under dynamic channel condition to exploit opportunistic forwarding to achieve efficient data delivery. A scalable location management protocol (MALM) is also proposed to support location-based routing protocols in urban VANETs. MALM uses high mobility in VANETs to help disseminate vehicles' historical location information, and a vehicle is able to implement Kalman-filter based predicted to predict another vehicle's current location based on its historical location information. ^