scholarly journals The Identity Labeling Problem and a Corresponding Solution

2018 ◽  
Author(s):  
Kenneth Joseph ◽  
Jonathan Morgan
Keyword(s):  
Survey Data ◽  
Predictive Models ◽  
Social Spaces ◽  
Definition Of The Situation ◽  
Novel Approach ◽  
Definition Of

The present work introduces and mathematically formalizes the identity labeling problem - given an individual in a social situatio, can we predict what identity(ies) he or she will be labeled with by someone else (the “labeler”)? We argue that existing predictive models of identity labeling are theoretically incomplete and provide results from a survey-based stimuli that confirm this intuition. We then introduce a novel approach to the identity labeling problem, which we call Latent Cognitive Social Spaces (LCSS). We demonstrate that LCSS is a better predictor of identity labeling in survey data than previous models and discuss its theoretical implications for linking the definition of the situation to identity theories.

scholarly journals Learning Curves: A Novel Approach for Robustness Improvement of Load Forecasting

2021 ◽  
Vol 5 (1) ◽  
pp. 38
Author(s):  
Chiara Giola ◽  
Piero Danti ◽  
Sandro Magnani
Keyword(s):  
Load Forecasting ◽  
Learning Curves ◽  
Machine Learning Techniques ◽  
Essential Information ◽  
Set Size ◽  
Novel Approach ◽  
Learning Techniques ◽  
Energy Plant ◽  
Definition Of ◽  
The Right

In the age of AI, companies strive to extract benefits from data. In the first steps of data analysis, an arduous dilemma scientists have to cope with is the definition of the ’right’ quantity of data needed for a certain task. In particular, when dealing with energy management, one of the most thriving application of AI is the consumption’s optimization of energy plant generators. When designing a strategy to improve the generators’ schedule, a piece of essential information is the future energy load requested by the plant. This topic, in the literature it is referred to as load forecasting, has lately gained great popularity; in this paper authors underline the problem of estimating the correct size of data to train prediction algorithms and propose a suitable methodology. The main characters of this methodology are the Learning Curves, a powerful tool to track algorithms performance whilst data training-set size varies. At first, a brief review of the state of the art and a shallow analysis of eligible machine learning techniques are offered. Furthermore, the hypothesis and constraints of the work are explained, presenting the dataset and the goal of the analysis. Finally, the methodology is elucidated and the results are discussed.

scholarly journals A network-based approach to integrate nutrient environment in the prediction of synthetic lethality in cancer metabolism

2021 ◽  
Author(s):  
Iñigo Apaolaza ◽  
Edurne San José-Enériz ◽  
Luis Valcarcel ◽  
Xabier Agirre ◽  
Felipe Prosper ◽  
...  
Keyword(s):  
Cancer Metabolism ◽  
Synthetic Lethality ◽  
Experimental Proof ◽  
Synthetic Lethal ◽  
New Family ◽  
Novel Approach ◽  
Synthetic Lethal Interactions ◽  
Nutrient Environment ◽  
Tumor Environment ◽  
Definition Of

Synthetic Lethality (SL) is a promising concept in cancer research. A number of computational methods have been developed to predict SL in cancer metabolism, among which our network-based computational approach, based on genetic Minimal Cut Sets (gMCSs), can be found. A major challenge of these approaches to SL is to systematically consider tumor environment, which is particularly relevant in cancer metabolism. Here, we propose a novel definition of SL for cancer metabolism that integrates genetic interactions and nutrient availability in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase inhibition in different environments. Finally, our novel approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.

Czech and Slovak Society

1993 ◽  
Vol 28 (4) ◽  
pp. 479-495 ◽  
Author(s):  
Jiří Musil
Keyword(s):  
Structural Analysis ◽  
List Type ◽  
Cultural Institutions ◽  
Definition Of The Situation ◽  
Czechoslovak Society ◽  
Slovak Society ◽  
The Difference ◽  
Definition Of ◽  
Czech Lands ◽  
Political Economic

THIS STUDY IS ONE OF COMPARATIVE STRUCTURAL ANALYSIS deliberately avoiding a sociological definition of the situation. It is assumed that two societies had existed in Czechoslovakia for some time and the difference between them, and possible analogies, are examined. There is also an assumption that the division of Czechoslovakia occurred especially because ‘Czechoslovak society’ as such had not yet been established; this was in spite of the fact that the two societies, at the time of the split, had substantially more in common than they had had at the time of Czechoslovakia's formation. There exists the view, which we want to verify, that during the decline of the federation the following factors were significant:1. The differences in economic, social, cultural and dispositional structures;2. The asynchronous and differing processes of modernization in both societies;3. The different consequences of the formation of societies of Soviet type in the Czech Lands in Slovakia;4. The differing processes for rectification of political, economic and cultural institutions in both republics after November 1989.

From Finding to Explaining

2018 ◽  
pp. 1535-1551
Author(s):  
Valentina Dragos
Keyword(s):  
Information Retrieval ◽  
Semantic Integration ◽  
Challenging Problem ◽  
Domain Experts ◽  
User Interests ◽  
Maritime Surveillance ◽  
Novel Approach ◽  
Basic Facts ◽  
Anomaly Analysis ◽  
Definition Of

Supporting anomaly analysis in the maritime field is a challenging problem because of the dynamic nature of the task: the definition of abnormal or suspicious behaviour is subject to change and depends on user interests. This paper provides a novel approach to support anomaly analysis in the maritime domain through the exploration of large collections of interpretation reports. Based on observables or more sophisticated patterns, the approach provides information retrieval strategies going from basic facts retrieval that guide short-term corrective actions to more complex networks of related concepts that help domain experts to understand or to explain abnormal vessel behaviours. Semantic integration is used to link various information sources, by using a commonly adopted standard. The paper seeks to explore different aspects of using information retrieval to support the analysis and interpretation of abnormal vessel behaviours for maritime surveillance.

A Novel Approach on Negative Association Rules

2011 ◽  
pp. 1425-1430
Author(s):  
Ioannis N. Kouris
Keyword(s):  
Association Rules ◽  
Positive Association ◽  
Negative Influence ◽  
Negative Association ◽  
Association Rules Mining ◽  
Novel Approach ◽  
Negative Effect ◽  
Negative Association Rules ◽  
The Subject ◽  
Definition Of

Research in association rules mining has initially concentrated in solving the obvious problem of finding positive association rules; that is rules among items that exist in the stored transactions. It was only several years after that the possibility of finding also negative association rules became especially appealing and was investigated. Nevertheless researchers based their assumptions regarding negative association rules on the absence of items from transactions. This assumption though besides being dubious, since it equated the absence of an item with a conflict or negative effect on the rest items, it also brought out a series of computational problems with the amount of possible patterns that had to be examined and analyzed. In this work we give an overview of the works having engaged with the subject until now and present a novel view for the definition of negative influence among items.

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