Extraction and evaluation of action expression related to person perception using correlational analyses

Mapping Intimacies ◽

10.31234/osf.io/efczy ◽

2021 ◽

Author(s):

Okamoto Masahiro ◽

Satoshi Eifuku

Keyword(s):

Person Perception ◽

Semantic Network ◽

Real Life ◽

Network Models ◽

Semantic Networks ◽

Point Of View ◽

Social Knowledge ◽

Correlational Approach ◽

Semantic Associations ◽

Methodological Principles

It is well known that people spontaneously infer traits when they observe behavior (spontaneous trait inference, STI). In order to make such inferences fast and efficient, our knowledge about others should be well organized. Along this line of thinking, it is suitable that our social knowledge is modeled as semantic networks in which traits are placed in the position of central nodes and linked to multiple behaviors on the basis of semantic associations. From the point of view of the semantic network models, researchers have examined their hypotheses by using cognitive memory tasks. For those tasks, researchers have to select a limited number of behavior-descriptive words/phrases as stimuli since there are vast amounts of behavior patterns in real life. There are, however, few methodological principles that adequately guide the sampling and selecting the stimuli and evaluating the semantic associations. In this setting, it seems required that words/phrases should be quantitatively sampled and selected and that the semantic associations should be objectively evaluated. A suitable approach for this purpose is the correlational analyses of free responses. In the present research, we provide evidence for the usefulness of the correlational analysis of free responses. First, we extracted behavior-descriptive words (verbs) that would exemplify trait concepts by using correspondence analysis, one of the correlational analyses (Study 1). Then, we examine the semantic associations between the extracted verbs with psychological experiments (Studies 2, 3). As a result, we found that the research participants identified the extracted verbs for specific traits, suggesting that the correlational approach is useful to reveal the organization of social knowledge. Finally, we discuss the limitations and issues of the correlational approach.

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Remotely Close Associations: Openness to Experience and Semantic Memory Structure

10.31237/osf.io/42wex ◽

2020 ◽

Author(s):

Alexander P. Christensen

Keyword(s):

Semantic Memory ◽

Graphical Models ◽

Verbal Fluency ◽

Semantic Network ◽

Semantic Networks ◽

Openness To Experience ◽

Semantic Structure ◽

Semantic Network Analysis ◽

Creative Cognition ◽

Semantic Associations

Openness to experience—the enjoyment of novel experiences, ideas, and unconventional perspectives—has shown several connections to cognition that suggest open people might have different cognitive processes than those low in openness. People high in openness are more creative, have broader general knowledge, and show greater cognitive flexibility. The associative structure of semantic memory might be one such cognitive process that people in openness differ in. In this study, 497 people completed a measure of openness to experience and verbal fluency. Three groups of high (n = 115), moderate (n = 121), and low (n = 118) openness were created to construct semantic networks—graphical models of semantic associations that provide quantifiable representations of how these associations are organized—from their verbal fluency responses. The groups were compared on graph theory measures of their respective semantic networks. The semantic network analysis revealed that as openness increased, the rigidity of the semantic structure decreased and the interconnectivity increased, suggesting greater flexibility of associations. Semantic structure also became more condensed and had better integration, which facilitates open people’s ability to reach more unique associations. These results were supported by open people coming up with more individual and unique responses, starting with less conventional responses, and having a flatter frequency proportion slope than less open people. In summary, the semantic network structure of people high in openness to experience supports the retrieval of remote concepts via short associative pathways, which promotes unique combinations of disparate concepts that are key for creative cognition.

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Generalized Boolean Networks

Handbook of Research on Computational Methodologies in Gene Regulatory Networks ◽

10.4018/978-1-60566-685-3.ch018 ◽

2010 ◽

pp. 429-449 ◽

Cited By ~ 1

Author(s):

Christian Darabos ◽

Mario Giacobini ◽

Marco Tomassini

Keyword(s):

Biological Networks ◽

Regulatory Networks ◽

Dynamical Behavior ◽

Real Life ◽

Network Models ◽

Cell Types ◽

Boolean Networks ◽

Genetic Regulatory Networks ◽

Point Of View ◽

Scale Free

Random Boolean Networks (RBN) have been introduced by Kauffman more than thirty years ago as a highly simplified model of genetic regulatory networks. This extremely simple and abstract model has been studied in detail and has been shown capable of extremely interesting dynamical behavior. First of all, as some parameters are varied such as the network’s connectivity, or the probability of expressing a gene, the RBN can go through a phase transition, going from an ordered regime to a chaotic one. Kauffman’s suggestion is that cell types correspond to attractors in the RBN phase space, and only those attractors that are short and stable under perturbations will be of biological interest. Thus, according to Kauffman, RBN lying at the edge between the ordered phase and the chaotic phase can be seen as abstract models of genetic regulatory networks. The original view of Kauffman, namely that these models may be useful for understanding real-life cell regulatory networks, is still valid, provided that the model is updated to take into account present knowledge about the topology of real gene regulatory networks, and the timing of events, without loosing its attractive simplicity. According to present data, many biological networks, including genetic regulatory networks, seem, in fact, to be of the scale-free type. From the point of view of the timing of events, standard RBN update their state synchronously. This assumption is open to discussion when dealing with biologically plausible networks. In particular, for genetic regulatory networks, this is certainly not the case: genes seem to be expressed in different parts of the network at different times, according to a strict sequence, which depends on the particular network under study. The expression of a gene depends on several transcription factors, the synthesis of which appear to be neither fully synchronous nor instantaneous. Therefore, we have recently proposed a new, more biologically plausible model. It assumes a scale-free topology of the networks and we define a suitable semi-synchronous dynamics that better captures the presence of an activation sequence of genes linked to the topological properties of the network. By simulating statistical ensembles of networks, we discuss the attractors of the dynamics, showing that they are compatible with theoretical biological network models. Moreover, the model demonstrates interesting scaling abilities as the size of the networks is increased.

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SEMANTIC NETWORK OF THE WORD ASSOCIATION IN THE FIELD OF LAW

LITERA ◽

10.21831/ltr.v18i3.26513 ◽

2019 ◽

Vol 18 (3) ◽

pp. 430-446

Author(s):

Arti Prihatini

Keyword(s):

Word Association ◽

Semantic Network ◽

Case Study Research ◽

Semantic Networks ◽

Point Of View ◽

Semantic Relations ◽

Response Word ◽

Descriptive Case Study ◽

Word Categorization

Word association can be utilized for identifying semantic network and describing point of view and prior knowledge of someone. This study aims to discuss two focuses, (1) the categorization of response word and (2) language factors that form semantic networks from the response words of word association in the field of law. This research uses a qualitative approach which is a type of descriptive case study research. Data collection held by using a word association questionaire. Based on the word categorization, the results showed that the stimulus words in the form of nouns were the most responded by nouns, verbs were the most responded by nouns, while the adjectives were responded more by an adjectives. Overall, responses in the form of nouns are 64.71%, verbs are 17.70%, adjectives are 17.58%. The responses in the form of nouns are related to the semantic relations of argument and predication, while the adjective response tends to be related to other adjectives in the unity of the semantic network. The response words form semantic network based on language factors, namely (1) lexical factors that consist of meaning relationship, connotation of meaning, concreteness and abstractness and (2) grammatical factors that consist of syntagmatic-paradigmatic and predication-argument relationship. Keywords: semantic network, word association, mental lexicon

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Methods of Network Planning and Management when Implementing Territory Planning Projects

Promyshlennoe i Grazhdanskoe Stroitel stvo ◽

10.33622/0869-7019.2019.08.49-54 ◽

2019 ◽

pp. 49-54

Keyword(s):

Large Scale ◽

Housing Stock ◽

Network Planning ◽

Network Models ◽

Point Of View ◽

Residential Areas ◽

Basic Principles ◽

Planning And Management ◽

Planning Project ◽

Complex Process

The success of the Program of housing stock renovation in Moscow depends on the efficiency of resource management. One of the main urban planning documents that determine the nature of the reorganization of residential areas included in the Program of renovation is the territory planning project. The implementation of the planning project is a complex process that has a time point of its beginning and end, and also includes a set of interdependent parallel-sequential activities. From an organizational point of view, it is convenient to use network planning and management methods for project implementation. These methods are based on the construction of network models, including its varieties – a Gantt chart. A special application has been developed to simulate the implementation of planning projects. The article describes the basic principles and elements of modeling. The list of the main implementation parameters of the Program of renovation obtained with the help of the developed software for modeling is presented. The variants of using the results obtained for a comprehensive analysis of the implementation of large-scale urban projects are proposed.

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Bleak Weather for Sun-Shine AG: A Case Study of Impairment of Assets

Issues in Accounting Education ◽

10.2308/iace-51007 ◽

2014 ◽

Vol 30 (2) ◽

pp. 113-126 ◽

Cited By ~ 4

Author(s):

Dominic Detzen ◽

Tobias Stork genannt Wersborg ◽

Henning Zülch

Keyword(s):

Real Life ◽

Accounting Standards ◽

Point Of View ◽

Professional Judgment ◽

Economic Point ◽

Instructional Resource

ABSTRACT This case originates from a real-life business situation and illustrates the application of impairment tests in accordance with IFRS and U.S. GAAP. In the first part of the case study, students examine conceptual questions of impairment tests under IFRS and U.S. GAAP with respect to applicable accounting standards, definitions, value concepts, and frequency of application. In addition, the case encourages students to discuss the impairment regime from an economic point of view. The second part of the instructional resource continues to provide instructors with the flexibility of applying U.S. GAAP and/or IFRS when students are asked to test a long-lived asset for impairment and, if necessary, allocate any potential impairment. This latter part demonstrates that impairment tests require professional judgment that students are to exercise in the case.

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Generative Adversarial Networks to Improve the Robustness of Visual Defect Segmentation by Semantic Networks in Manufacturing Components

Applied Sciences ◽

10.3390/app11146368 ◽

2021 ◽

Vol 11 (14) ◽

pp. 6368

Author(s):

Fátima A. Saiz ◽

Garazi Alfaro ◽

Iñigo Barandiaran ◽

Manuel Graña

Keyword(s):

Ad Hoc ◽

Data Augmentation ◽

Semantic Network ◽

Semantic Networks ◽

Stereo Image ◽

Generative Adversarial Networks ◽

Specific Class ◽

Adversarial Networks ◽

Augmentation Techniques ◽

Image Acquisition System

This paper describes the application of Semantic Networks for the detection of defects in images of metallic manufactured components in a situation where the number of available samples of defects is small, which is rather common in real practical environments. In order to overcome this shortage of data, the common approach is to use conventional data augmentation techniques. We resort to Generative Adversarial Networks (GANs) that have shown the capability to generate highly convincing samples of a specific class as a result of a game between a discriminator and a generator module. Here, we apply the GANs to generate samples of images of metallic manufactured components with specific defects, in order to improve training of Semantic Networks (specifically DeepLabV3+ and Pyramid Attention Network (PAN) networks) carrying out the defect detection and segmentation. Our process carries out the generation of defect images using the StyleGAN2 with the DiffAugment method, followed by a conventional data augmentation over the entire enriched dataset, achieving a large balanced dataset that allows robust training of the Semantic Network. We demonstrate the approach on a private dataset generated for an industrial client, where images are captured by an ad-hoc photometric-stereo image acquisition system, and a public dataset, the Northeastern University surface defect database (NEU). The proposed approach achieves an improvement of 7% and 6% in an intersection over union (IoU) measure of detection performance on each dataset over the conventional data augmentation.

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The contribution of the Italian residents in neurology to the COVID-19 crisis: admirable generosity but neurological training remains their priority

Neurological Sciences ◽

10.1007/s10072-021-05346-4 ◽

2021 ◽

Author(s):

Cristina Tassorelli ◽

Vincenzo Silani ◽

Alessandro Padovani ◽

Paolo Barone ◽

Paolo Calabresi ◽

...

Keyword(s):

Clinical Training ◽

Real Life ◽

Healthcare Management ◽

Point Of View ◽

Research Activity ◽

High Quality ◽

Research Activities ◽

Italian Regions ◽

Training And Research

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic has severely impacted the Italian healthcare system, underscoring a dramatic shortage of specialized doctors in many disciplines. The situation affected the activity of the residents in neurology, who were also offered the possibility of being formally hired before their training completion. Aims (1) To showcase examples of clinical and research activity of residents in neurology during the COVID-19 pandemic in Italy and (2) to illustrate the point of view of Italian residents in neurology about the possibility of being hired before the completion of their residency program. Results Real-life reports from several areas in Lombardia—one of the Italian regions more affected by COVID-19—show that residents in neurology gave an outstanding demonstration of generosity, collaboration, reliability, and adaptation to the changing environment, while continuing their clinical training and research activities. A very small minority of the residents participated in the dedicated selections for being hired before completion of their training program. The large majority of them prioritized their training over the option of earlier employment. Conclusions Italian residents in neurology generously contributed to the healthcare management of the COVID-19 pandemic in many ways, while remaining determined to pursue their training. Neurology is a rapidly evolving clinical field due to continuous diagnostic and therapeutic progress. Stakeholders need to listen to the strong message conveyed by our residents in neurology and endeavor to provide them with the most adequate training, to ensure high quality of care and excellence in research in the future.

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Adherence, Persistence, and Effectiveness in Real Life. Multicenter Long-Term Study on the Use of Pirfenidone and Nintedanib in the Treatment of Idiopathic Pulmonary Fibrosis

Journal of Pharmacy Practice ◽

10.1177/08971900211008625 ◽

2021 ◽

pp. 089719002110086

Author(s):

Fiorenzo Santoleri ◽

Luigia Auriemma ◽

Antonella Spacone ◽

Stefano Marinari ◽

Fabio Esposito ◽

...

Keyword(s):

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Pharmacological Study ◽

Functional Decline ◽

Real Life ◽

Point Of View ◽

Response To Treatment ◽

First Year ◽

Long Term Study ◽

Second Year

Background: In the treatment of idiopathic pulmonary fibrosis (IPF), nintedanib and pirfenidone, with their different mechanisms of action, lead to a reduction in the rate of progression of the fibrosis process measured by the reduction of functional decline, and, in particular, the decrease in forced vital capacity (FVC) and of the diffusion capacity of the lungs for carbon monoxide (DLCO). The objective of this study was to analyze real-life adherence, persistence and efficacy in the use of pirfenidone and nintedanib in the treatment of IPF. Methods: A non-interventional multicenter retrospective observational pharmacological study in real-life treat-ment at 1 and 2 years was conducted. Furthermore, we analyzed the levels of FVC and DLCO at 6 and 12 months, respectively, from the start of treatment. Results: We identified 144 patients in the period between January 2013 and April 2019. From the point of view of adherence, there is no difference between the two drugs, even though patients who used pirfenidone had increasingly higher values: 0.90 vs 0.89, in the first year, and 0.91 vs 0.84, in the second year. In the first year of treatment, the percentage of persistent patients was 67% and 76%, while in the second year, it dropped to 47% and 53% for pirfenidone and nintedanib, respectively. Conclusion: The stratification of the adherence values as a function of the response to treatment in terms of FVC at 12 months for both study drugs showed that patients with optimal response scored adherence of more than 90%.

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ALVIC versus the Internet: Redesigning a Networked Virtual Environment Architecture

International Journal of Computer Games Technology ◽

10.1155/2008/594313 ◽

2008 ◽

Vol 2008 ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

Peter Quax ◽

Jeroen Dierckx ◽

Bart Cornelissen ◽

Wim Lamotte

Keyword(s):

Virtual Environment ◽

Large Scale ◽

Virtual Communities ◽

Real Life ◽

Point Of View ◽

The Internet ◽

Generic Framework ◽

Short Period ◽

Networked Virtual Environment ◽

Near Future

The explosive growth of the number of applications based on networked virtual environment technology, both games and virtual communities, shows that these types of applications have become commonplace in a short period of time. However, from a research point of view, the inherent weaknesses in their architectures are quickly exposed. The Architecture for Large-Scale Virtual Interactive Communities (ALVICs) was originally developed to serve as a generic framework to deploy networked virtual environment applications on the Internet. While it has been shown to effectively scale to the numbers originally put forward, our findings have shown that, on a real-life network, such as the Internet, several drawbacks will not be overcome in the near future. It is, therefore, that we have recently started with the development of ALVIC-NG, which, while incorporating the findings from our previous research, makes several improvements on the original version, making it suitable for deployment on the Internet as it exists today.

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