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TMT social capital, network position and innovation: the nature of micro-macro links

TMT social capital, network position and innovation: the nature of micro-macro links

Firms with prestige have a favorable network position, which has a positive effect on organizational innovation (Zhu et al. 2017). Though network position provides value and allows the actors to develop trust to access resources through embedded linkages (Li et al. 2014), innovations also carry risks (Merton 2013). One of the biggest threats in the process of innovation is financing constraints. According to resource-based the- ory, the resources inside firms are insufficient for a firm ’ s development. Financing con- straints occur when capital market imperfections exist (Hottenrott and Peters 2009), thus obtaining a bank’s support is especially vital in the imperfect capital market insti- tutional environment in China. TMT’s bank social capital, which is a shortcut to break the funding bottleneck, naturally becomes a useful way to remedy capital market im- perfections, and is a beneficial solution to financing constraints. In the process of accel- erating enterprise human resource management and the innovation process, compensation and incentive mechanisms play a vital role in enterprise human resource management, and are important in the integration and use of corporate social capital. Additionally, they decrease the breakage risk of capital chain from firm prestige to innovation practices. Taking these expectations together, we propose the following:

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Network Position, Technological Distance and Firm’s Cooperation Innovation

Network Position, Technological Distance and Firm’s Cooperation Innovation

3) The relationship between technology distance negatively regulating net- work centrality and cooperative technology innovation performance positively moderates the relationship between structural holes and cooperative technology innovation performance. When the firm is not in the network center, the firm acquired from the network information resources are limited, the firm can properly select firm’s technology gap to establish technical cooperation, to make up for the firms in the network position advantage, actively acquire new know- ledge in order to promote the technology on the development of the firm’s co- operative network. When the firm is in the structure holes position of the coop- erative network, firms can obtain more heterogeneous knowledge and commu- nication and control of heterogeneous knowledge in the network, if the estab- lishment of cooperative relationship between firms and the selection of technol- ogy is large, the value of information and control of income will be further en- larged. Therefore, this paper provides guidance for firms to build cooperative technology innovation network, select the location of firms in the network and how to select partners.

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Developmental stress predicts social network position

Developmental stress predicts social network position

The quantity and quality of social relationships, as captured by social network analysis, can have major fitness consequences. Various studies have shown that individual differences in social behaviour can be due to variation in exposure to developmental stress. However, whether these developmental differences translate to consistent differences in social network position is not known. We experimentally increased levels of the avian stress hormone corticosterone (CORT) in nestling zebra finches in a fully balanced design. Upon reaching nutritional independence, we released chicks and their families into two free-flying rooms, where we measured daily social networks over five weeks using passive integrated transponder tags. Developmental stress had a significant effect on social behaviour: despite having similar foraging patterns, CORT chicks had weaker associations to their parents than control chicks. Instead, CORT chicks foraged with a greater number of flock mates and were less choosy with whom they foraged, resulting in more central network positions. These findings highlight the importance of taking developmen- tal history into account to understand the drivers of social organization in gregarious species.

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How “Dark Side” Personality Traits Affect Social Network Position

How “Dark Side” Personality Traits Affect Social Network Position

Burt, Jannota, & Mahoney (1998) were probably the first to integrate person- ality research in SNA methodology. The authors investigated whether personal- ity traits vary systematically with “structural holes”, which is defined as non- redundant information that is contained by two separate structures/“cliques”. The results indicated that people with the least constrained networks (entrepre- neurial networks) had a tendency to seek advice from their colleagues (accuracy of information), perceived themselves to be in a position of authority (inde- pendence) and were able to create an aura of excitement (persuasion). The find- ings were in line with a study by Kalish & Robins (2006). They showed that peo- ple who were more individualistic, more controlling, and more neurotic tended to occupy structural hole positions.

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Leadership in complex networks: the importance of network position and strategic action in a translational cancer research network

Leadership in complex networks: the importance of network position and strategic action in a translational cancer research network

One way of looking at leadership in these complex net- works is to use a social network approach in which graph theory is used to quantify and explore the complex set of ties (relationships and interactions) between members [11,12]. Rather than considering the attributes or human capital held by members, such as expertise or skill sets, so- cial network analysis considers members’ social capital. Here, we use social capital in the sense that Burt and Coleman use it; that is, to indicate the advantage that comes from a member’s individual positions within the overall configuration of their web of relationships [13,14]. Translational research networks are social networks that, in contrast to their formal structure, are defined by ties of communication or collaboration between members. Key players in social network terms are network members (‘ac- tors’) who hold powerful or influential positions with high social capital [15], but it is not always true that key players are the mandated leaders [10,16]. Central actors are key players who interact with the most other actors, while brokers form links between isolated clusters, aiding cohe- sion through mediation behaviours [17]. Actors can hold

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Centre Stage: How Social Network Position Shapes Linguistic Coordination

Centre Stage: How Social Network Position Shapes Linguistic Coordination

found that in the Wikipedia corpus it is actually Be- tweenness centrality that correlates somewhat more strongly with coordination. This may have some- thing to say about the relationship between the two mechanisms mentioned above. While it may still be true that people align to power for the immedi- ate social benefit, the greater effect of Betweenness centrality suggests that the social benefit of coordi- nation may be mediated by something more than the power of the individual who is being responded to. One possible explanation is that community mem- bers who are more vital to the connectivity of the social network (i.e., those with high Betweenness centrality) tend to conform better with the linguistic norms of the community as a whole (rather than, for example, to the norms of some clique or subgroup). Assuming that some of the social motivations for alignment are expressly linguistic, this would ex- plain why Betweenness centrality correlates better with coordination received than the centrality mea- sure more typically associated with social power. More research is needed to determine whether (a) community members with high Betweenness cen- trality better represent the linguistic norms of the community and (b) immediate linguistic coordina- tion is the mechanism by which those norms are propagated.

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A Predetermined Position Wise Node Deployment for Optimizing Lifetime in Visual Sensor Network

A Predetermined Position Wise Node Deployment for Optimizing Lifetime in Visual Sensor Network

To arrive at the optimization level on behalf of harmonizing the power preservation plus the time essential for usage purpose for the network by providing the restraint to the gaps for the power, in addition to that the most chief thing is to come across the location using the sensory nodes and intimate the emergency locale from the target place is the genuine intent of this application.

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AN EFFICIENT ADIABATIC FULL ADDER DESIGN APPROACH FOR LOW POWER

AN EFFICIENT ADIABATIC FULL ADDER DESIGN APPROACH FOR LOW POWER

Full adder is a combinational circuit that performs the addition of 3 binary digits. The input variables are represented by A, B, Cin.A and B represent the 2-input variables and Cin represents the carry from the previous lower significant position. In the full adder, whenever we add two binary numbers, each having two or more binary bits, the least significant bits can be added using half adder. The logic symbol of full adder is shown in “Fig. 2”.

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Performance Evaluation of Routing Protocol for Mobile Ad Hoc Network

Performance Evaluation of Routing Protocol for Mobile Ad Hoc Network

Abstract- Congestion in mobile ad hoc network is the most important problem. That leads to communication delays, packet loss, reason wastage of time and energy on recovery. Routing protocols which are customize to the congestion position of a mobile ad hoc network can improve the network performance .In this paper, we compare the performance of an on-demand reactive routing protocol for mobile ad hoc networks and a mobile agent related congestion conscious routing protocol. Performance is evaluated with respect to packet loss and network throughput.

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Galaxy Position based Solar Power Prediction System using Neural Network

Galaxy Position based Solar Power Prediction System using Neural Network

In the proposed system, the system will calculates the availability of sun light of any location from the provided locations geographical coordinates and the time of installation provided. It predicts the weather situation by checking the previous days weather data and Calculates sun’s position at time and angle of incident of light on earths provided location. Based on this availability of sun light and climate conditions we can calculate the number of cells required to cater the needs to our power consumption. Also this application gives expert opinion on the angle of installation of the solar panels. This also takes care of the climate conditions also. In this method we implement a neural network concept on historical data to fetch the climatic condition based on latitude and longitude and store that information in the knowledge base. Here we are predicting the weather data using the clustering and neural networks[1] and this gives a better results compared to other existing systems. It also has a better configuration system where we can simulate data based on given data.

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Hierarchical Attention Based Position Aware Network for Aspect Level Sentiment Analysis

Hierarchical Attention Based Position Aware Network for Aspect Level Sentiment Analysis

182 encoding the sentence. We argue that the position of a candidate aspect is important for the sentence modelling. For instance, consider the sentence “I bought a mobile phone, its camera is wonderful but the battery life is a bit short”. For the candidate aspect “battery life”, “wonderful” and “short” are both likely to be considered as its adjunct word. In this case, if we encode the position information into the representation of each word effectively, we would have more confidence in concluding that the “short” is the adjunct word of “battery life” and predict the sentiment as negative. Then, the next problem is how to introduce the position information. In some previous works (Tang et al., 2016b; Chen et al,. 2017), they weighted the representation of each word according to the position, and the words close to the aspect could be paid more attention. However, this operation is not always reasonable and sometimes the adjunct word may be far away from the target word. Thus, we introduce position embeddings when modelling the sentence and further generate the position- aware representations. In other words, the position information is considered as a kind of features and embedded into position embeddings. The model will learn to exploit both of the semantic information and the position clues.

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The interaction between inter-firm and interlocking directorate networks on firm's new product development outcomes

The interaction between inter-firm and interlocking directorate networks on firm's new product development outcomes

Several scholars have established the importance of a prominent board on the firm‟s economic-financial performance broadly (Non and Franses, 2007; Horton et al., 2012; Croci and Grassi, 2013; Larcker et al., 2013; Li et al., 2013) and on NPD, in particular (Wincent et al., 2010). Germane to this study, a prominent board positively influences both the firms‟ process and product innovation (Wincent et al., 2010). In appointing board members, firms therefore pay attention to the resource provision function of the board and aim to enhance the board and therefore the firm‟s SC by appointing experienced executives with a track record and reputation within their industry (Haynes and Hillman, 2010). To achieve prominence in the interlock directorate network, firms appoint members who sit on boards of other reputable companies thus providing the focal firm board with direct and indirect benefits of information and knowledge access. The web of relationships in the interlock directorate network

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The Effect of the Position of Educational Organizations within the Social Network on Their Collaboration Levels

The Effect of the Position of Educational Organizations within the Social Network on Their Collaboration Levels

Social network studies in education as in other areas focus on how interpersonal relationship patterns facilitate the flow of relational resources (such as knowledge, expertise, attitudes and friendship) which act as a lever and how accessing the resources is affected. Network perspective does not only present a set of methods for the understanding of the importance of individual behavior, but also the understanding of the dynamics of social processes in education[97]. The increase in the number of concepts unique to social networks more and more in the area of education as well as in other areas has reflected on studies on education too. Studies conducted through numerous social network analysis perspectives which deal with the various dimensions of the relationships between teachers, students, administrators and schools and other organizations have increased in the recent years ([16], [17], [25], [30], [64], [77], [83], [98]). These kinds of studies in which various relationships patterns such as supporting educational reforms, the effect of various network relationships between teachers on performance, the vocational development of teachers and knowledge and information transmission have begun to increase all over the world. However, although studies conducted with the social network perspective are quite limited in number, they are not wide-spread yet in educational studies. Studies in which schools’ relationships with other organizations are evaluated with the social network perspective have not been come across. However, collaboration relationships of educational organizations among themselves and with other organizations in Turkey are wide-ranging.

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Visualized Social Network Analysis on Spatial Dynamics of International Trade between China and League of Arab States

Visualized Social Network Analysis on Spatial Dynamics of International Trade between China and League of Arab States

We can find out the following characteristics by the calculation results of the three index-Degree Centrality, Closeness Centrality and Betweenness Centrality:(1) Countries whose Degree Centrality and Closeness Centrality reach max 100 are more and more, the number in 2001 is seven and increase to eleven in 2009,and then became twelve in 2017. It shows that countries who are in the central status are more and more. Trade is in a dispersive trend, not concentrate on some specific countries because of the trade diffusion effect. (2) Important node countries made some changes on the basis of stability. Degree Centrality and Closeness Centrality of China, Omen, Lebanon, Morocco and Saudi Arabia is 100 in these three years, which shows that these countries are always in the central status in trade network. UAE was in central status before 2009 and its Degree Centrality and Closeness Centrality declined to 68.182 and 75.862. UAE lost its core status and it is consistent with the foregoing trade spatial structure evolution. Countries which have abundant oil and gas resources like Algeria, Egypt, Qatar and Kuwait have ascending Centrality. (3)Through the entire centrality distribution, three centrality exist the obvious difference, which shows a level features. The distribution of Degree Centrality and Closeness Centrality mainly verify the characteristics of Core-Periphery layer in Spatial structure evolution and reveals Betweenness Centrality doesn't have an obvious layer characteristics.

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A Position Encoding Convolutional Neural Network Based on Dependency Tree for Relation Classification

A Position Encoding Convolutional Neural Network Based on Dependency Tree for Relation Classification

With the renaissance of neural network in re- cent years, relation classification has again become a research hotspot in natural lan- guage processing, and leveraging parse trees is a common and effective method of tack- ling this problem. In this work, we offer a new perspective on utilizing syntactic infor- mation of dependency parse tree and present a position encoding convolutional neural net- work (PECNN) based on dependency parse tree for relation classification. First, tree- based position features are proposed to en- code the relative positions of words in depen- dency trees and help enhance the word repre- sentations. Then, based on a redefinition of “context”, we design two kinds of tree-based convolution kernels for capturing the semantic and structural information provided by depen- dency trees. Finally, the features extracted by convolution module are fed to a classifier for labelling the semantic relations. Experiments on the benchmark dataset show that PECNN outperforms state-of-the-art approaches. We also compare the effect of different position features and visualize the influence of tree- based position feature by tracing back the con- volution process.

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Position aware and QoS based Service Discovery using TOPSIS for Vehicular Network

Position aware and QoS based Service Discovery using TOPSIS for Vehicular Network

Vehicular network is a challenging research area due to the wide variety of applications to provide driving comfort and road safety for the passengers. It is one of the building blocks of intelligent transportation system that helps to take decisions while travelling. There are numerous services provided by different service provider in the vehicular network. There are also some service providers providing similar services but with different Quality of Service parameters. Vehicles while traveling needs to discover services with desired QoS parameters in their region of interest. A Service discovery methodology is required to find the appropriate service provider who provides the service with the desired quality of service requirements by the service requester. This study proposes Position Aware and QoS based Service Discovery Protocol using TOPSIS (PQoSVSDP). Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is one of the multi criteria decision making methods for selecting appropriate service providers matching the quality parameters on the request of service requester. Simulation has been performed using the proposed method. The TOPSIS based service discovery on the vehicular network has been found to be efficient with reduced service discovery time. Keywords: Vehicular network; Service Discovery; QoS; TOPSIS; PQoSVSDP

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II. PROBLEM DESCRIPTION A. Network Topology Control [1][2][3]

II. PROBLEM DESCRIPTION A. Network Topology Control [1][2][3]

We can realize the optimizing process of WSN and get corresponding simulation results through using PSO algorithm,. If we put up N nodes randomly, through the optimal process of sink nodes, we can find out that sink nodes are no more than ten percent of the whole nodes through the optimal process. This is accpetable for the network optimization of WSN. The new added nodes can make network connected, and there are no doubt that the algorithm can get massive optimal results by using few calculation. So, this algorithm has practical engineering value.

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On training strategies for parsimonious learning feed-forward controllers

On training strategies for parsimonious learning feed-forward controllers

In the last graph we see, that the feedback control signal decreases for every path, even for paths that are considered to be training improperly. We should probably explain this from the fact that a neural network can always approximate a certain data set. In casu this means that a path can always be learnt to some extent, thus reducing the feedback control signal. This thought is supported by the fact that the positional error is decreasing as well. From this we should conclude that both the error reduction and the feedback control signal reduction on the path itself are not appropriate to evaluate the quality of learning. To overcome this, a validation path should be used. However, in the current simulations this was not needed, since the network contents can be compared with the theoretical optimal values. This is a global criterion, whereas a validation path is still subjective in this sense, that it may not necessarily test the quality of learning in an exhaustive way. The reason why especially path P 1 yields the best feedback control signal reduction, is probably found in the fact that this is the simplest path, so its control signal can be learnt the best.

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Using Position Based and Cognitive Radio in Vehicular Ad-hoc Network

Using Position Based and Cognitive Radio in Vehicular Ad-hoc Network

Position routing protocol is based on routing process where the source sends a packet to the destination using the positional information rather than network address. When the source node send a packet to the destination it will stores the information in packet header and it will be helpful in forwarding the packet to destination without route maintenance, discovery or even awareness of the network topology.

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Dynamic position changeable Stackelberg game for user provided network control algorithms

Dynamic position changeable Stackelberg game for user provided network control algorithms

Gao et al. [13] designed an optimal pricing and re- imbursing strategy for a mobile virtual network oper- ator that maximized its total revenue while considering the necessary incentives to the operator. They employed a game-theoretic analysis and mod- eled the interaction between the operator and the hosts as a two-stage leader-follower Stackelberg game. In the first stage, the operator decided the price and free data quota reimbursing plan. In the second stage, every host decides how much data would be con- sumed for its own needs and how much data would be forwarded for clients. Finally, they systematically analyzed the game equilibrium, which can capture a variety of system characteristics, including the service types of hosts or clients, the capacities of hosts’ Inter- net connections, and the energy consumption patterns of hosts [13].

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