467 research outputs found
Using Explainability for Constrained Matrix Factorization
Explainable Model Black Box (opaque) predictors such as Deep learning and Matrix Factorization are accurate, ... but lack interpretability and ability to give explanations. White Box models such as rules and decision trees are interpretable (explainable), ... but lack accuracy
Towards a pedagogy for critical security studies: politics of migration in the classroom
International Relations (IR) has increasingly paid attention to critical pedagogy. Feminist, post-colonial and poststructuralist IR scholarship, in particular, have long been advancing the discussions about how to create a pluralist and democratic classroom where ‘the others’ of politics can be heard by the students, who can critically reflect upon complex power relations in global politics. Despite its normative position, Critical Security Studies (CSS) has so far refrained from joining this pedagogical conversation. Deriving from the literatures of postcolonial and feminist pedagogical practices, it is argued that an IR scholar in the area of CSS can contribute to the production of a critical political subject in the 'uncomfortable classroom', who reflects on violent practices of security. Three pedagogical methods will be introduced: engaging with the students’ life worlds, revealing the positionality of security knowledge claims, and opening up the class-room to the choices about how the youth’s agency can be performed beyond the classroom. The argument is illustrated through the case of forced migration with specific reference to IR and Politics students’ perceptions of Syrian refugees in Turkey. The article advances the discussions in critical IR pedagogy and encourages CSS scholarship to focus on teaching in accordance with its normative position
Estimation of nasal cavity and conchae volumes by stereological method
Background: Studies evaluating the mean volumes of nasal cavity and concha
are very rare. Since there is little date on the mentioned topic, we aimed to
carry out the presented study to obtain a volumetric index showing the relation
between the nasal cavity and concha.
Material and methods: The volumes of the nasal cavity and concha were
measured in 30 males and 30 females (18–40 years old) on computed tomography
images using stereological methods.
Results: The mean volumes of nasal cavity, concha nasalis media, and concha
nasalis inferior were 5.95 ± 0.10 cm3, 0.56 ± 0.22 cm3, and 1.45 ± 0.68 cm3;
7.01 ± 0.18 cm3, 0.67 ± 0.31 cm3 and 1.59 ± 0.98 cm3 in females and males,
respectively. There were statistically significant differences in the volume of the
nasal cavity and concha nasalis media (p < 0.05) between males and females,
except for concha nasalis inferior (p > 0.05).
Conclusions: Our results could provide volumetric indexes for the nasal cavity
and concha, which could help the physician to manage surgical procedures
related to the nasal cavity and concha
Performance comparison of ASN.1 encoder/decoders using FTAM
Abstract Syntax Notation-One (ASN.1) is a standard external data representation language used to define messages of application layer protocols. Its encoding rules, the Basic Encoding Rules (BER), are also international standards that define the encoding/decoding of data values into/from a transfer syntax. Various approaches to automating BER encoding/decoding are examined; in particular, two widely used software packages (ISODE and CASN 1) are studied. A hardware BER encoder/decoder called VASN 1 is presented. Performance of software and hardware approaches are evaluated on real instances of file transfer using a standard FTAM protocol. Benchmarks obtained from running CASN 1 on one of the fastest workstations and from running VHDL simulations of VASN 1 indicate the superiority of the hardware approach. © 1993
Définir des priorités de recherche à l’échelle du Canada pour les programmes de simulation agréés par le Collège royal
To advance the field of health sciences simulation, research must be of high quality and would benefit from multi-institutional collaboration where centres can leverage and share expertise as well as work together to overcome limits to the generalizability of research findings from single-institution studies. A needs assessment in emergency medicine simulation has illustrated the importance of identifying research priorities in Canada. The main purpose of this study was to identify simulation research priority directions for Canadian simulation centres. The current survey study drew on 16 research priorities developed through a two-round internal Delphi study at McGill University that 15 of 17 simulation centre advisory board members participated in. The final 16 research priorities were then rated by a total of 18 of 24 simulation centre directors and/or delegates contacted from 15 of 19 Royal College of Physicians and Surgeons of Canada-accredited simulation centres in Canada. Results revealed 9 common research priorities that reached 70% or higher agreement for all respondents. We anticipate that our findings can contribute to building a shared vision of priorities, community, and collaboration to enhance health care simulation research quality amongst Canadian simulation centres.Pour faire progresser le domaine de la simulation en sciences de la santé, il faut tendre vers une recherche de haute qualité, qui serait favorisée par une collaboration multi-institutionnelle permettant aux programmes de tirer parti de leur expertise, de la partager et de surmonter les limites de la généralisabilité des résultats de recherche provenant d’études menées dans un seul établissement. Une évaluation des besoins en matière de simulation en médecine d’urgence a illustré l’importance de définir des priorités de recherche à l’échelle du Canada. Le principal objectif de cette étude était de dresser les orientations prioritaires des programmes de simulation canadiens pour la recherche en simulation. Elle est basée sur 16 priorités de recherche dégagées d’une étude Delphi à deux tours réalisée à l’Université [masqué], à laquelle 15 des 17 membres du comité consultatif de son centre de simulation ont participé. Les 16 priorités de recherche finales ont ensuite été évaluées par 18 des 24 directeurs ou délégués de centres de simulation contactés, provenant de 15 des 19 programmes de simulation agréés par le Collège royal des médecins et chirurgiens du Canada. Les résultats font état de neuf priorités de recherche communes ayant obtenu un taux d’accord de 70 % ou plus parmi l’ensemble des répondants. Nous pensons que nos résultats peuvent contribuer à l’élaboration d’une vision commune des priorités parmi les programmes de simulation canadiens, à la création d’une communauté de pratique et à une collaboration pour améliorer la qualité de la recherche en simulation dans le domaine des soins de santé
Estimation of Fiber Orientations Using Neighborhood Information
Data from diffusion magnetic resonance imaging (dMRI) can be used to
reconstruct fiber tracts, for example, in muscle and white matter. Estimation
of fiber orientations (FOs) is a crucial step in the reconstruction process and
these estimates can be corrupted by noise. In this paper, a new method called
Fiber Orientation Reconstruction using Neighborhood Information (FORNI) is
described and shown to reduce the effects of noise and improve FO estimation
performance by incorporating spatial consistency. FORNI uses a fixed tensor
basis to model the diffusion weighted signals, which has the advantage of
providing an explicit relationship between the basis vectors and the FOs. FO
spatial coherence is encouraged using weighted l1-norm regularization terms,
which contain the interaction of directional information between neighbor
voxels. Data fidelity is encouraged using a squared error between the observed
and reconstructed diffusion weighted signals. After appropriate weighting of
these competing objectives, the resulting objective function is minimized using
a block coordinate descent algorithm, and a straightforward parallelization
strategy is used to speed up processing. Experiments were performed on a
digital crossing phantom, ex vivo tongue dMRI data, and in vivo brain dMRI data
for both qualitative and quantitative evaluation. The results demonstrate that
FORNI improves the quality of FO estimation over other state of the art
algorithms.Comment: Journal paper accepted in Medical Image Analysis. 35 pages and 16
figure
Escaping the Big Brother: an empirical study on factors influencing identification and information leakage on the Web
This paper presents a study on factors that may increase the risks of personal information leakage, due to the possibility of connecting user profiles that are not explicitly linked together. First, we introduce a technique for user identification based on cross-site checking and linking of user attributes. Then, we describe the experimental evaluation of the identification technique both on a real setting and on an online sample, showing its accuracy to discover unknown personal data. Finally, we combine the results on the accuracy of identification with the results of a questionnaire completed by the same subjects who performed the test on the real setting. The aim of the study was to discover possible factors that make users vulnerable to this kind of techniques. We found out that the number of social networks used, their features and especially the amount of profiles abandoned and forgotten by the user are factors that increase the likelihood of identification and the privacy risks
Effective and Efficient Similarity Index for Link Prediction of Complex Networks
Predictions of missing links of incomplete networks like protein-protein
interaction networks or very likely but not yet existent links in evolutionary
networks like friendship networks in web society can be considered as a
guideline for further experiments or valuable information for web users. In
this paper, we introduce a local path index to estimate the likelihood of the
existence of a link between two nodes. We propose a network model with
controllable density and noise strength in generating links, as well as collect
data of six real networks. Extensive numerical simulations on both modeled
networks and real networks demonstrated the high effectiveness and efficiency
of the local path index compared with two well-known and widely used indices,
the common neighbors and the Katz index. Indeed, the local path index provides
competitively accurate predictions as the Katz index while requires much less
CPU time and memory space, which is therefore a strong candidate for potential
practical applications in data mining of huge-size networks.Comment: 8 pages, 5 figures, 3 table
Cultures of conflict:Protests, violent repression, and community values
What are the cultural origins of societal conflicts that revolve around democratization, women’s rights, and modern libertarian values? We propose that deep-seated differences in community-based collective values (at the micro-level) may be related to why people support anti-government protest and why they support repression of such protests (at the macro-level). The hypothesis was examined among residents of Turkey (N = 500). Cultural values, measured at the individual level and community level with the community collectivism scale, correlated with political orientation and emotions, as well as with subsequent support for anti-governmental protest or its repression. The main conclusions are that both support for protest and support for repression are related to the cultural values people hold and their subsequent political orientations and emotions. Micro-level cultural values in local communities may thus play a role in explaining macro-level socio-political divides
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