Deriving a Priori Co-occurrence Probability Estimates for Object Recognition from Social Networks and Text Processing

2007 ◽  
pp. 509-518 ◽  
Author(s):  
Guillaume Pitel ◽  
Christophe Millet ◽  
Gregory Grefenstette
Keyword(s):  
Social Networks ◽  
Object Recognition ◽  
Text Processing ◽  
A Priori ◽  
Occurrence Probability ◽  
Probability Estimates

The Stages of Team Venture Formation: A Decision-making Model

1993 ◽  
Vol 17 (2) ◽  
pp. 17-27 ◽  
Author(s):  
Judith B. Kamm ◽  
Aaron J. Nurick
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Critical Points ◽  
A Priori ◽  
Feedback Loops ◽  
Second Stage ◽  
Or Groups ◽  
Decision Making Model

This model of multi-founder organizational formation assumes that organizations emerge In stages, following an a priori sequence of transitions. The idea stage comes first. In it, individuals or groups within the context of their social networks make decisions about the business concept and what Is needed to implement it. The second stage consists of implementation decisions, Including who will supply resources, what Inducements will be used to attract more partners if necessary, and how the team will be kept together. Feedback loops Indicate that the process may return to the concept and implementation needs decisions, depending upon choices made at certain critical points.

Utility of Fetal Karyotype in the Evaluation of Phenotypically Abnormal Stillbirths

2009 ◽  
Vol 12 (3) ◽  
pp. 217-221 ◽  
Author(s):  
Halit Pinar ◽  
Marshall Carpenter ◽  
Benjamin J. Martin ◽  
Umadevi Tantravahi
Keyword(s):  
Karyotype Analysis ◽  
A Priori ◽  
Fetal Tissue ◽  
Tissue Samples ◽  
Perinatal Pathology ◽  
Karyotypic Abnormality ◽  
Probability Estimates ◽  
Resolution Level ◽  
Low Incidence ◽  
Karyotype Abnormality

The objectives of this study are to test the hypothesis that stillbirths without aneuploidy-associated phenotypes have a low incidence of karyotypic abnormalities, similar among those with and without other anatomic defects. We employed a uniform postmortem protocol to examine fetuses and placentas in 962 consecutive stillbirths measuring ≥20 weeks in clinically determined gestational age submitted to the Women and Infants Hospital Division of Perinatal Pathology from 1990 through 2005. Classification of anatomic (macroscopic) abnormalities was based on a priori criteria. Anatomic fetal abnormalities were noted in 387 cases. Conventional karyotype analysis was successfully performed on 346 fetal tissue samples, 114 in anatomically normal and 232 in anatomically abnormal fetuses. The distribution of karyotypic abnormalities among cases with and without anatomic abnormalities was compared. Of the 962 stillbirths, 40% (387) had malformations. Tissue culture for karyotype analysis was attempted in 412 cases from both groups and failed in 66 cases (16%). At the 450 to 500-band resolution level, 60 of the remaining 346 karyotypes were abnormal. Of the 232 malformation cases with successful karyotyping, 59 had phenotypic attributes indicative of aneuploidy, all of which had later karyotype confirmation. Of the remaining 173 anomalous fetuses with karyotype analysis, only 1 demonstrated a karyotypic abnormality. All 114 karyotypes performed in stillbirths without anatomic abnormalities were normal. Among ≥20-week stillbirths, aneuploid karyotypes are uncommon except in fetuses with suspect phenotypes. The 95% probability estimates of karyotype abnormality in the phenotypically abnormal and normal stillbirths, 5.5% and 5.6%, respectively, do not differ. These data do not have sufficient power to detect a small difference in rates of karyotypic abnormalities between the 2 groups of ≥20-week stillbirths. However, this series indicates that this technology is uninformative among stillborn fetuses that lack aneuploidy phenotypes.

AN ABDUCTIVE REASONING BASED IMAGE INTERPRETATION SYSTEM

1996 ◽  
Vol 10 (06) ◽  
pp. 613-641
Author(s):  
SANTANU CHAUDHURY ◽  
ARBIND GUPTA ◽  
GUTURU PARTHASARATHY ◽  
S. SUBRAMANIAN
Keyword(s):  
Object Recognition ◽  
Domain Knowledge ◽  
A Priori ◽  
Image Interpretation ◽  
Abductive Reasoning ◽  
Recognition Problem ◽  
Aerial Image ◽  
Interpretation System ◽  
Different Types

This paper describes an abductive reasoning based inferencing engine for image interpretation. The inferencing strategy finds an acceptable and consistent explanation of the features detected in the image in terms of the objects known a priori. The inferencing scheme assumes representation of the domain knowledge about the objects in terms of local and/or relational features. The inferencing system can be applied for different types of image interpretation problems like 2-D and 3-D object recognition, aerial image interpretation, etc. In this paper, we illustrate functioning of the system with the help of a 2-D object recognition problem.

Introduction: Urban friendship networks: Affective negotiations and potentialities of care

Urban Studies ◽  
2017 ◽  
Vol 55 (3) ◽  
pp. 491-504 ◽  
Author(s):  
Laavanya Kathiravelu ◽  
Tim Bunnell
Keyword(s):  
Social Capital ◽  
Social Networks ◽  
Everyday Life ◽  
Urban Environment ◽  
Urban Studies ◽  
A Priori ◽  
Friendship Networks ◽  
Special Issue ◽  
Economic Class ◽  
Ethnic Solidarity

Issues of integration, assimilation and the place of ‘strangers’ within metropolitan contexts have been overwhelmingly conceptualised within the larger structural frames of ethnicity, nationality, immigration status and socio-economic class. This raises and reflects important issues around strategies of differentiation, urban exclusion and the hierarchies inherent in everyday life within contemporary cities. However, in privileging such modes of analysis, other more dynamic, elastic, latent and surreptitious forms of affinity, relatedness and connection within the urban environment are often left unexamined. Friendship is one of these. The articles in this special issue initiate a deeper and more sustained focus on friendship as a relational modality that characterises many urban interactions, and that also takes on particular forms within demographically diverse city spaces. The particular contribution of this special issue is in bringing together the literature from urban studies, research on diversity, understandings of social capital and networks and contemporary discussions of friendship. This introduction to the special issue argues that adopting alternative frameworks of enquiry such as friendship can serve to unsettle a priori assumptions about co-ethnic solidarity, and provide alternative epistemological starting points in understanding social networks. In doing so, this research not only contributes to contemporary readings of diverse cities but extends understandings of the routine affective and material labour that urban dwellers regularly undertake. Calling for a focus on informal bonds like friendship, this article suggests that it is within such unexplored spheres that possibilities of care and convivial city living exist.

scholarly journals How to make methodological decisions when inferring social networks

2019 ◽  
Author(s):  
André C. Ferreira ◽  
Rita Covas ◽  
Liliana R. Silva ◽  
Sandra C. Esteves ◽  
Inês F. Duarte ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Data Collection ◽  
Network Inference ◽  
A Priori ◽  
Pilot Studies ◽  
Multiple Hypotheses Testing ◽  
Sociable Weavers ◽  
Breeding Groups

ABSTRACTConstructing and analysing social networks data can be challenging. When designing new studies, researchers are confronted with having to make decisions about how data are collected and networks are constructed, and the answers are not always straightforward. The current lack of guidance on building a social network for a new study system might lead researchers to try several different methods, and risk generating false results arising from multiple hypotheses testing. We suggest an approach for making decisions when developing a network without jeopardising the validity of future hypothesis tests. We argue that choosing the best edge definition for a network can be made using a priori knowledge of the species, and testing hypotheses that are known and independent from those that the network will ultimately be used to evaluate. We illustrate this approach by conducting a pilot study with the aim of identifying how to construct a social network for colonies of cooperatively breeding sociable weavers. We first identified two ways of collecting data using different numbers of feeders and three ways to define associations among birds. We then identified which combination of data collection and association definition maximised (i) the assortment of individuals into ‘breeding groups’ (birds that contribute towards the same nest and maintain cohesion when foraging), and (ii) socially differentiated relationships (more strong and weak relationships than expected by chance). Our approach highlights how existing knowledge about a system can be used to help navigate the myriad of methodological decisions about data collection and network inference.SIGNIFICANCE STATEMENTGeneral guidance on how to analyse social networks has been provided in recent papers. However less attention has been given to system-specific methodological decisions when designing new studies, specifically on how data are collected, and how edge weights are defined from the collected data. This lack of guidance can lead researchers into being less critical about their study design and making arbitrary decisions or trying several different methods driven by a given preferred hypothesis of interest without realising the consequences of such approaches. Here we show that pilot studies combined with a priori knowledge of the study species’ social behaviour can greatly facilitate making methodological decisions. Furthermore, we empirically show that different decisions, even if data are collected under the same context (e.g. foraging), can affect the quality of a network.

Using a priori data for prediction and object recognition in an autonomous mobile vehicle

2003 ◽  
Author(s):  
Christopher Scrapper ◽  
Ayako Takeuchi ◽  
Tommy Chang ◽  
Tsai Hong Hong ◽  
Michael Shneier
Keyword(s):  
Object Recognition ◽  
A Priori ◽  
Mobile Vehicle

scholarly journals Associating Events with People on Social Networks Using A-PRIORI

2015 ◽  
Author(s):  
Srijan Khare ◽  
Vyankatesh Agrawal ◽  
Gaurav Tiwari ◽  
Gourav Arora ◽  
Bhaskar Biswas
Keyword(s):  
Social Networks ◽  
A Priori

ORACLE: An Integrated Learning Approach for Object Recognition

1997 ◽  
Vol 11 (06) ◽  
pp. 961-990 ◽  
Author(s):  
John Ming ◽  
Bir Bhanu
Keyword(s):  
Object Recognition ◽  
Classification Tree ◽  
Current Model ◽  
A Priori ◽  
Recognition System ◽  
Machine Learning Techniques ◽  
Object Model ◽  
Model Based ◽  
Model Database ◽  
Over Time

Model-based object recognition has become a popular paradigm in computer vision research. In most of the current model-based vision systems, the object models used for recognition are generally a priori given (e.g. obtained using a CAD model). For many object recognition applications, it is not realistic to utilize a fixed object model database with static model features. Rather, it is desirable to have a recognition system capable of performing automated object model acquisition and refinement. In order to achieve these capabilities, we have developed a system called ORACLE: Object Recognition Accomplished through Consolidated Learning Expertise. It uses two machine learning techniques known as Explanation-Based Learning (EBL) and Structured Conceptual Clustering (SCC) combined in a synergistic manner. As compared to systems which learn from numerous positive and negative examples, EBL allows the generalization of object model descriptions from a single example. Using these generalized descriptions, SCC constructs an efficient classification tree which is incremently built and modified over time. Learning from experience is used to dynamically update the specific feature values of each object. These capabilities provide a dynamic object model database which allows the system to exhibit improved performance over time. We provide an overview of the ORACLE system and present experimental results using a database of thirty aircraft models.

scholarly journals Finding the Intersection of Neuroplasticity, Stroke Recovery, and Learning: Scope and Contributions to Stroke Rehabilitation

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Leeanne Carey ◽  
Alistair Walsh ◽  
Achini Adikari ◽  
Peter Goodin ◽  
Damminda Alahakoon ◽  
...  
Keyword(s):  
Stroke Rehabilitation ◽  
Text Processing ◽  
Concept Map ◽  
A Priori ◽  
Stroke Recovery ◽  
Network Graph ◽  
Clinical Text ◽  
Novel Approach ◽  
Core Concepts ◽  
The Common

Aim. Neural plastic changes are experience and learning dependent, yet exploiting this knowledge to enhance clinical outcomes after stroke is in its infancy. Our aim was to search the available evidence for the core concepts of neuroplasticity, stroke recovery, and learning; identify links between these concepts; and identify and review the themes that best characterise the intersection of these three concepts. Methods. We developed a novel approach to identify the common research topics among the three areas: neuroplasticity, stroke recovery, and learning. A concept map was created a priori, and separate searches were conducted for each concept. The methodology involved three main phases: data collection and filtering, development of a clinical vocabulary, and the development of an automatic clinical text processing engine to aid the process and identify the unique and common topics. The common themes from the intersection of the three concepts were identified. These were then reviewed, with particular reference to the top 30 articles identified as intersecting these concepts. Results. The search of the three concepts separately yielded 405,636 publications. Publications were filtered to include only human studies, generating 263,751 publications related to the concepts of neuroplasticity (n=6,498), stroke recovery (n=79,060), and learning (n=178,193). A cluster concept map (network graph) was generated from the results; indicating the concept nodes, strength of link between nodes, and the intersection between all three concepts. We identified 23 common themes (topics) and the top 30 articles that best represent the intersecting themes. A time-linked pattern emerged. Discussion and Conclusions. Our novel approach developed for this review allowed the identification of the common themes/topics that intersect the concepts of neuroplasticity, stroke recovery, and learning. These may be synthesised to advance a neuroscience-informed approach to stroke rehabilitation. We also identified gaps in available literature using this approach. These may help guide future targeted research.

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