3,112 research outputs found
The magnetic behavior of Li2MO3 (M=Mn, Ru and Ir) and Li2(Mn1-xRux)O3
The present study summerizes magnetic and Mossbauer measurements on ceramic
Li2MO3 M= Mn, Ru and Ir and the mixed Li2(Mn1-xRux)O3 materials, which show
many of the features reflecting to antiferromagnetic ordering or to existence
of paramagnetic states. Li2IrO3 and Li2RuO3 are paramagnetic down to 5 K.
Li2(Mn1-xRux)O3 compounds are antiferromagnetically ordered at TN = 48 K for
x=0. TN decreases as the Ru content increases and, for x=0.8, TN =34 K.Comment: accepted to Physica
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Personalization via collaboration in web retrieval systems: a context based approach
World Wide Web is a source of information, and searches on the Web can be analyzed to detect patterns in Web users' search behaviors and information needs to effectively handle the users' subsequent needs. The rationale is that the information need of a user at a particular time point occurs in a particular context, and queries are derived from that need. In this paper, we discuss an extension of our personalization approach that was originally developed for a traditional bibliographic retrieval system but has been adapted and extended with a collaborative model for the Web retrieval environment. We start with a brief introduction of our personalization approach in a traditional information retrieval system. Then, based on the differences in the nature of documents, users and search tasks between traditional and Web retrieval environments, we describe our extensions of integrating collaboration in personalization in the Web retrieval environment. The architecture for the extension integrates machine learning techniques for the purpose of better modeling users' search tasks. Finally, a user-oriented evaluation of Web-based adaptive retrieval systems is presented as an important aspect of the overall strategy for personalization
Monitoring wild animal communities with arrays of motion sensitive camera traps
Studying animal movement and distribution is of critical importance to
addressing environmental challenges including invasive species, infectious
diseases, climate and land-use change. Motion sensitive camera traps offer a
visual sensor to record the presence of a broad range of species providing
location -specific information on movement and behavior. Modern digital camera
traps that record video present new analytical opportunities, but also new data
management challenges. This paper describes our experience with a terrestrial
animal monitoring system at Barro Colorado Island, Panama. Our camera network
captured the spatio-temporal dynamics of terrestrial bird and mammal activity
at the site - data relevant to immediate science questions, and long-term
conservation issues. We believe that the experience gained and lessons learned
during our year long deployment and testing of the camera traps as well as the
developed solutions are applicable to broader sensor network applications and
are valuable for the advancement of the sensor network research. We suggest
that the continued development of these hardware, software, and analytical
tools, in concert, offer an exciting sensor-network solution to monitoring of
animal populations which could realistically scale over larger areas and time
spans
Systems Developers Define their Own Information Needs
Access to the right information is a significant contributor to success in many endeavors. It is, however, difficult to characterize what constitutes right information. This is an important question for systems development projects, which continue to exhibit a sub-par track record of success. This paper describes patterns of information seeking such as nature of information sought and sources of information consulted in the context of tasks performed during systems development projects. The analysis uses task-oriented information seeking as a theoretical perspective, inferring patterns from longitudinal data collected from multiple student teams engaged in real-world systems development efforts. The results show that the nature of tasks themselves varies for routine versus innovative projects, with implications for the nature of information sought and sources consulted. Some of the counter-intuitive findings include increasing incidence of genuine decision tasks over time; and use of the web for genuine decision tasks versus people for routine tasks. Implications of the findings for practice are discussed
Stochastic population dynamics under regime switching II
This is a continuation of our paper [Q. Luo, X. Mao, Stochastic population dynamics under regime switching, J. Math. Anal. Appl. 334 (2007) 69-84] on stochastic population dynamics under regime switching. In this paper we still take both white and color environmental noise into account. We show that a sufficient large white noise may make the underlying population extinct while for a relatively small noise we give both asymptotically upper and lower bound for the underlying population. In some special but important situations we precisely describe the limit of the average in time of the population
On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation
Understanding which function classes are easy and which are hard for a given algorithm is a fundamental question for the analysis and design of bio-inspired search heuristics. A natural starting point is to consider the easiest and hardest functions for an algorithm. For the (1+1) EA using standard bit mutation (SBM) it is well known that OneMax is an easiest function with unique optimum while Trap is a hardest. In this paper we extend the analysis of easiest function classes to the contiguous somatic hypermutation (CHM) operator used in artificial immune systems. We define a function MinBlocks and prove that it is an easiest function for the (1+1) EA using CHM, presenting both a runtime and a fixed budget analysis. Since MinBlocks is, up to a factor of 2, a hardest function for standard bit mutations, we consider the effects of combining both operators into a hybrid algorithm. We rigorously prove that by combining the advantages of k operators, several hybrid algorithmic schemes have optimal asymptotic performance on the easiest functions for each individual operator. In particular, the hybrid algorithms using CHM and SBM have optimal asymptotic performance on both OneMax and MinBlocks. We then investigate easiest functions for hybrid schemes and show that an easiest function for an hybrid algorithm is not just a trivial weighted combination of the respective easiest functions for each operator.publishersversionPeer reviewe
An Improved Algorithm for Fast K-Word Proximity Search Based on Multi-Component Key Indexes
A search query consists of several words. In a proximity full-text search, we
want to find documents that contain these words near each other. This task
requires much time when the query consists of high-frequently occurring words.
If we cannot avoid this task by excluding high-frequently occurring words from
consideration by declaring them as stop words, then we can optimize our
solution by introducing additional indexes for faster execution. In a previous
work, we discussed how to decrease the search time with multi-component key
indexes. We had shown that additional indexes can be used to improve the
average query execution time up to 130 times if queries consisted of
high-frequently occurring words. In this paper, we present another search
algorithm that overcomes some limitations of our previous algorithm and
provides even more performance gain.
This is a pre-print of a contribution published in Arai K., Kapoor S., Bhatia
R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in
Intelligent Systems and Computing, vol 1251, published by Springer, Cham. The
final authenticated version is available online at:
https://doi.org/10.1007/978-3-030-55187-2_3
The Influence of Canalization on the Robustness of Boolean Networks
Time- and state-discrete dynamical systems are frequently used to model
molecular networks. This paper provides a collection of mathematical and
computational tools for the study of robustness in Boolean network models. The
focus is on networks governed by -canalizing functions, a recently
introduced class of Boolean functions that contains the well-studied class of
nested canalizing functions. The activities and sensitivity of a function
quantify the impact of input changes on the function output. This paper
generalizes the latter concept to -sensitivity and provides formulas for the
activities and -sensitivity of general -canalizing functions as well as
canalizing functions with more precisely defined structure. A popular measure
for the robustness of a network, the Derrida value, can be expressed as a
weighted sum of the -sensitivities of the governing canalizing functions,
and can also be calculated for a stochastic extension of Boolean networks.
These findings provide a computationally efficient way to obtain Derrida values
of Boolean networks, deterministic or stochastic, that does not involve
simulation.Comment: 16 pages, 2 figures, 3 table
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