2,063 research outputs found
Improved memory loading techniques for the TSRV display system
A recent upgrade of the TSRV research flight system at NASA Langley Research Center retained the original monochrome display system. However, the display memory loading equipment was replaced requiring design and development of new methods of performing this task. This paper describes the new techniques developed to load memory in the display system. An outdated paper tape method for loading the BOOTSTRAP control program was replaced by EPROM storage of the characters contained on the tape. Rather than move a tape past an optical reader, a counter was implemented which steps sequentially through EPROM addresses and presents the same data to the loader circuitry. A cumbersome cassette tape method for loading the applications software was replaced with a floppy disk method using a microprocessor terminal installed as part of the upgrade. The cassette memory image was transferred to disk and a specific software loader was written for the terminal which duplicates the function of the cassette loader
Voter model with non-Poissonian interevent intervals
Recent analysis of social communications among humans has revealed that the
interval between interactions for a pair of individuals and for an individual
often follows a long-tail distribution. We investigate the effect of such a
non-Poissonian nature of human behavior on dynamics of opinion formation. We
use a variant of the voter model and numerically compare the time to consensus
of all the voters with different distributions of interevent intervals and
different networks. Compared with the exponential distribution of interevent
intervals (i.e., the standard voter model), the power-law distribution of
interevent intervals slows down consensus on the ring. This is because of the
memory effect; in the power-law case, the expected time until the next update
event on a link is large if the link has not had an update event for a long
time. On the complete graph, the consensus time in the power-law case is close
to that in the exponential case. Regular graphs bridge these two results such
that the slowing down of the consensus in the power-law case as compared to the
exponential case is less pronounced as the degree increases.Comment: 18 pages, 8 figure
Social Ranking Techniques for the Web
The proliferation of social media has the potential for changing the
structure and organization of the web. In the past, scientists have looked at
the web as a large connected component to understand how the topology of
hyperlinks correlates with the quality of information contained in the page and
they proposed techniques to rank information contained in web pages. We argue
that information from web pages and network data on social relationships can be
combined to create a personalized and socially connected web. In this paper, we
look at the web as a composition of two networks, one consisting of information
in web pages and the other of personal data shared on social media web sites.
Together, they allow us to analyze how social media tunnels the flow of
information from person to person and how to use the structure of the social
network to rank, deliver, and organize information specifically for each
individual user. We validate our social ranking concepts through a ranking
experiment conducted on web pages that users shared on Google Buzz and Twitter.Comment: 7 pages, ASONAM 201
Minority Becomes Majority in Social Networks
It is often observed that agents tend to imitate the behavior of their
neighbors in a social network. This imitating behavior might lead to the
strategic decision of adopting a public behavior that differs from what the
agent believes is the right one and this can subvert the behavior of the
population as a whole.
In this paper, we consider the case in which agents express preferences over
two alternatives and model social pressure with the majority dynamics: at each
step an agent is selected and its preference is replaced by the majority of the
preferences of her neighbors. In case of a tie, the agent does not change her
current preference. A profile of the agents' preferences is stable if the
preference of each agent coincides with the preference of at least half of the
neighbors (thus, the system is in equilibrium).
We ask whether there are network topologies that are robust to social
pressure. That is, we ask if there are graphs in which the majority of
preferences in an initial profile always coincides with the majority of the
preference in all stable profiles reachable from that profile. We completely
characterize the graphs with this robustness property by showing that this is
possible only if the graph has no edge or is a clique or very close to a
clique. In other words, except for this handful of graphs, every graph admits
at least one initial profile of preferences in which the majority dynamics can
subvert the initial majority. We also show that deciding whether a graph admits
a minority that becomes majority is NP-hard when the minority size is at most
1/4-th of the social network size.Comment: To appear in WINE 201
Multiple agency perspective, family control, and private information abuse in an emerging economy
Using a comprehensive sample of listed companies in Hong Kong this paper investigates how family control affects private information abuses and firm performance in emerging economies. We combine research on stock market microstructure with more recent studies of multiple agency perspectives and argue that family ownership and control over the board increases the risk of private information abuse. This, in turn, has a negative impact on stock market performance. Family control is associated with an incentive to distort information disclosure to minority shareholders and obtain private benefits of control. However, the multiple agency roles of controlling families may have different governance properties in terms of investors’ perceptions of private information abuse. These findings contribute to our understanding of the conflicting evidence on the governance role of family control within a multiple agency perspectiv
The Routing of Complex Contagion in Kleinberg's Small-World Networks
In Kleinberg's small-world network model, strong ties are modeled as
deterministic edges in the underlying base grid and weak ties are modeled as
random edges connecting remote nodes. The probability of connecting a node
with node through a weak tie is proportional to , where
is the grid distance between and and is the
parameter of the model. Complex contagion refers to the propagation mechanism
in a network where each node is activated only after neighbors of the
node are activated.
In this paper, we propose the concept of routing of complex contagion (or
complex routing), where we can activate one node at one time step with the goal
of activating the targeted node in the end. We consider decentralized routing
scheme where only the weak ties from the activated nodes are revealed. We study
the routing time of complex contagion and compare the result with simple
routing and complex diffusion (the diffusion of complex contagion, where all
nodes that could be activated are activated immediately in the same step with
the goal of activating all nodes in the end).
We show that for decentralized complex routing, the routing time is lower
bounded by a polynomial in (the number of nodes in the network) for all
range of both in expectation and with high probability (in particular,
for and
for in expectation),
while the routing time of simple contagion has polylogarithmic upper bound when
. Our results indicate that complex routing is harder than complex
diffusion and the routing time of complex contagion differs exponentially
compared to simple contagion at sweetspot.Comment: Conference version will appear in COCOON 201
Site selective reading of epigenetic markers by a dual-mode synthetic receptor array.
Variably functionalized self-folding deep cavitands form an arrayed, fluorescent indicator displacement assay system for the detection of post-translationally modified (PTM) histone peptides. The hosts bind trimethyllysine (KMe3) groups, and use secondary upper rim interactions to provide more sensitive discrimination between targets with identical KMe3 binding handles. The sensor array uses multiple different recognition modes to distinguish between miniscule differences in target, such as identical lysine modifications at different sites of histone peptides. In addition, the sensor is affected by global changes in structure, so it is capable of discriminating between identical PTMs, at identical positions on amino acid fragments that vary only in peptide backbone length, and can be applied to detect non-methylation modifications such as acetylation and phosphorylations located multiple residues away from the targeted binding site. The synergistic application of multiple variables allows dual-mode deep cavitands to approach levels of recognition selectivity usually only seen with antibodies
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