scholarly journals Intention and Attention in Image-Text Presentations: A Coherence Approach

2021 ◽  
Vol 1 ◽  
pp. 273
Author(s):  
Ilana Torres ◽  
Kathryn Slusarczyk ◽  
Malihe Alikhani ◽  
Matthew Stone
Keyword(s):  
Coherence Theory ◽  
Visual Salience ◽  
Text And Image ◽  
Text Data ◽  
Data Set ◽  
Text Interpretation ◽  
Coherence Relations ◽  
Pronoun Use ◽  
Image Context ◽  
The Relationship

In image-text presentations from online discourse, pronouns can refer to entities depicted in images, even if these entities are not otherwise referred to in a text caption. While visual salience may be enough to allow a writer to use a pronoun to refer to a prominent entity in the image, coherence theory suggests that pronoun use is more restricted. Specifically, language users may need an appropriate coherence relation between text and imagery to license and resolve pronouns. To explore this hypothesis and better understand the relationship between image context and text interpretation, we annotated an image-text data set with coherence relations and pronoun information. We find that pronoun use reflects a complex interaction between the content of the pronoun, the grammar of the text, and the relation of text and image.

scholarly journals RDMMFET: Representation of Dense Multimodality Fusion Encoder Based on Transformer

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xu Zhang ◽  
DeZhi Han ◽  
Chin-Chen Chang
Keyword(s):  
Question Answering ◽  
Language Model ◽  
Visual Images ◽  
Text And Image ◽  
Data Set ◽  
Fine Grained ◽  
Natural Language Question ◽  
The Relationship ◽  
Language Question ◽  
Better Than

Visual question answering (VQA) is the natural language question-answering of visual images. The model of VQA needs to make corresponding answers according to specific questions based on understanding images, the most important of which is to understand the relationship between images and language. Therefore, this paper proposes a new model, Representation of Dense Multimodality Fusion Encoder Based on Transformer, for short, RDMMFET, which can learn the related knowledge between vision and language. The RDMMFET model consists of three parts: dense language encoder, image encoder, and multimodality fusion encoder. In addition, we designed three types of pretraining tasks: masked language model, masked image model, and multimodality fusion task. These pretraining tasks can help to understand the fine-grained alignment between text and image regions. Simulation results on the VQA v2.0 data set show that the RDMMFET model can work better than the previous model. Finally, we conducted detailed ablation studies on the RDMMFET model and provided the results of attention visualization, which proves that the RDMMFET model can significantly improve the effect of VQA.

Diagnostics of professional competence of IT students based on digital footprint data

2020 ◽  
pp. 4-11
Author(s):  
I. G. Zakharova ◽  
Yu. V. Boganyuk ◽  
M. S. Vorobyova ◽  
E. A. Pavlova
Keyword(s):  
Information Technology ◽  
Educational Program ◽  
Professional Competence ◽  
Objective Data ◽  
Text Data ◽  
Data Set ◽  
Job Requirements ◽  
Digital Footprint ◽  
Graduate Employment ◽  
The University

The article goal is to demonstrate the possibilities of the approach to diagnosing the level of IT graduates’ professional competence, based on the analysis of the student’s digital footprint and the content of the corresponding educational program. We describe methods for extracting student professional level indicators from digital footprint text data — courses’ descriptions and graduation qualification works. We show methods of comparing these indicators with the formalized requirements of employers, reflected in the texts of vacancies in the field of information technology. The proposed approach was applied at the Institute of Mathematics and Computer Science of the University of Tyumen. We performed diagnostics using a data set that included texts of courses’ descriptions for IT areas of undergraduate studies, 542 graduation qualification works in these areas, 879 descriptions of job requirements and information on graduate employment. The presented approach allows us to evaluate the relevance of the educational program as a whole and the level of professional competence of each student based on objective data. The results were used to update the content of some major courses and to include new elective courses in the curriculum.

A Review on Sentiment Classification: Natural Language Understanding

2019 ◽  
Vol 13 (1) ◽  
pp. 20-27 ◽  
Author(s):  
Srishty Jindal ◽  
Kamlesh Sharma
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Natural Language Understanding ◽  
Business Analytics ◽  
Language Understanding ◽  
Text Data ◽  
Data Set ◽  
Market Positioning ◽  
Illegal Activities

Background: With the tremendous increase in the use of social networking sites for sharing the emotions, views, preferences etc. a huge volume of data and text is available on the internet, there comes the need for understanding the text and analysing the data to determine the exact intent behind the same for a greater good. This process of understanding the text and data involves loads of analytical methods, several phases and multiple techniques. Efficient use of these techniques is important for an effective and relevant understanding of the text/data. This analysis can in turn be very helpful in ecommerce for targeting audience, social media monitoring for anticipating the foul elements from society and take proactive actions to avoid unethical and illegal activities, business analytics, market positioning etc. Method: The goal is to understand the basic steps involved in analysing the text data which can be helpful in determining sentiments behind them. This review provides detailed description of steps involved in sentiment analysis with the recent research done. Patents related to sentiment analysis and classification are reviewed to throw some light in the work done related to the field. Results: Sentiment analysis determines the polarity behind the text data/review. This analysis helps in increasing the business revenue, e-health, or determining the behaviour of a person. Conclusion: This study helps in understanding the basic steps involved in natural language understanding. At each step there are multiple techniques that can be applied on data. Different classifiers provide variable accuracy depending upon the data set and classification technique used.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals The Study of Multiple Classes Boosting Classification Method Based on Local Similarity

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 37
Author(s):  
Shixun Wang ◽  
Qiang Chen
Keyword(s):  
Image Retrieval ◽  
Loss Function ◽  
Single Mode ◽  
Local Similarity ◽  
Text And Image ◽  
Data Set ◽  
Standard Data ◽  
Weak Learner ◽  
Great Progress ◽  
Data Points

Boosting of the ensemble learning model has made great progress, but most of the methods are Boosting the single mode. For this reason, based on the simple multiclass enhancement framework that uses local similarity as a weak learner, it is extended to multimodal multiclass enhancement Boosting. First, based on the local similarity as a weak learner, the loss function is used to find the basic loss, and the logarithmic data points are binarized. Then, we find the optimal local similarity and find the corresponding loss. Compared with the basic loss, the smaller one is the best so far. Second, the local similarity of the two points is calculated, and then the loss is calculated by the local similarity of the two points. Finally, the text and image are retrieved from each other, and the correct rate of text and image retrieval is obtained, respectively. The experimental results show that the multimodal multi-class enhancement framework with local similarity as the weak learner is evaluated on the standard data set and compared with other most advanced methods, showing the experience proficiency of this method.

Railroad Integration and Uneven Development on the European Periphery, 1870–1910

2021 ◽  
Vol 45 (2) ◽  
pp. 261-289
Author(s):  
Eduard J. Alvarez-Palau ◽  
Alfonso Díez-Minguela ◽  
Jordi Martí-Henneberg
Keyword(s):  
Economic Development ◽  
Positive Impact ◽  
Data Set ◽  
Per Capita Gdp ◽  
Catching Up ◽  
Nation States ◽  
Railroad Network ◽  
Per Capita ◽  
European Periphery ◽  
The Relationship

AbstractThis study explores the relationship between railroad integration and regional development on the European periphery between 1870 and 1910, based on a regional data set including 291 spatial units. Railroad integration is proxied by railroad density, while per capita GDP is used as an indicator of economic development. The period under study is of particular relevance as it has been associated with the second wave of railroad construction in Europe and also coincides with the industrialization of most of the continent. Overall, we found that railroads had a significant and positive impact on the growth of per capita GDP across Europe. The magnitude of this relationship appears to be relatively modest, but the results obtained are robust with respect to a number of different specifications. From a geographical perspective, we found that railroads had a significantly greater influence on regions located in countries on the northern periphery of Europe than in other outlying areas. They also helped the economies of these areas to begin the process of catching up with the continent’s industrialized core. In contrast, the regions on the southern periphery showed lower levels of economic growth, with this exacerbating the preexisting divergence in economic development. The expansion of the railroad network in them was unable to homogenize the diffusion of economic development and tended to further benefit the regions that were already industrialized. In most of the cases, the capital effect was magnified, and this contributed to the consolidation of newly created nation-states.

scholarly journals RESTING HEART RATE MODERATES THE RELATIONSHIP BETWEEN NEUROPSYCHIATRIC SYMPTOMS, MCI, AND ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S641-S641
Author(s):  
Shanna L Burke
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Heart Rate ◽  
Relative Risk ◽  
Neuropsychiatric Symptoms ◽  
Cognitive Status ◽  
Resting Heart Rate ◽  
Data Set ◽  
Increased Risk ◽  
The Relationship

Abstract Little is known about how resting heart rate moderates the relationship between neuropsychiatric symptoms and cognitive status. This study examined the relative risk of NPS on increasingly severe cognitive statuses and examined the extent to which resting heart rate moderates this relationship. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform Data Set was undertaken, using observations from participants with normal cognition at baseline (13,470). The relative risk of diagnosis with a more severe cognitive status at a future visit was examined using log-binomial regression for each neuropsychiatric symptom. The moderating effect of resting heart rate among those who are later diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) was assessed. Delusions, hallucinations, agitation, depression, anxiety, elation, apathy, disinhibition, irritability, motor disturbance, nighttime behaviors, and appetite disturbance were all significantly associated (p<.001) with an increased risk of AD, and a reduced risk of MCI. Resting heart rate increased the risk of AD but reduced the relative risk of MCI. Depression significantly interacted with resting heart rate to increase the relative risk of MCI (RR: 1.07 (95% CI: 1.00-1.01), p<.001), but not AD. Neuropsychiatric symptoms increase the relative risk of AD but not MCI, which may mean that the deleterious effect of NPS is delayed until later and more severe stages of the disease course. Resting heart rate increases the relative risk of MCI among those with depression. Practitioners considering early intervention in neuropsychiatric symptomology may consider the downstream benefits of treatment considering the long-term effects of NPS.

scholarly journals Spatial pattern and genetic diversity estimates are linked in stochastic models of population differentiation

2000 ◽  
Vol 23 (3) ◽  
pp. 541-544 ◽  
Author(s):  
José Alexandre Felizola Diniz-Filho ◽  
Mariana Pires de Campos Telles
Keyword(s):  
Genetic Diversity ◽  
Spatial Pattern ◽  
Stochastic Models ◽  
Population Differentiation ◽  
Real Data ◽  
Population Heterogeneity ◽  
Data Set ◽  
Mantel’S Test ◽  
The Relationship ◽  
Diversity Estimates

In the present study, we used both simulations and real data set analyses to show that, under stochastic processes of population differentiation, the concepts of spatial heterogeneity and spatial pattern overlap. In these processes, the proportion of variation among and within a population (measured by G ST and 1 - G ST, respectively) is correlated with the slope and intercept of a Mantel's test relating genetic and geographic distances. Beyond the conceptual interest, the inspection of the relationship between population heterogeneity and spatial pattern can be used to test departures from stochasticity in the study of population differentiation.

scholarly journals Intergovernmental Organizations and Foreign Policy Behavior: Some Empirical Findings

1979 ◽  
Vol 73 (2) ◽  
pp. 494-504 ◽  
Author(s):  
James M. McCormick ◽  
Young W. Kihl
Keyword(s):  
Foreign Policy ◽  
Data Base ◽  
Comparative Research ◽  
Intergovernmental Organizations ◽  
Data Set ◽  
The World ◽  
The Relationship ◽  
Policy Behavior ◽  
High Politics ◽  
Foreign Policy Behavior

In this study, we evaluate whether the increase in the number of intergovernmental organizations (IGOs) has resulted in their increased use for foreign policy behavior by the nations of the world. This question is examined in three related ways: (1) the aggregate use of IGOs for foreign policy behavior; (2) the relationship between IGO membership and IGO use; and (3) the kinds of states that use IGOs. Our data base consists of the 35 nations in the CREON (Comparative Research on the Events of Nations) data set for the years 1959–1968.The main findings are that IGOs were employed over 60 percent of the time with little fluctuation on a year-by-year basis, that global and “high politics” IGOs were used more often than regional and “low politics” IGOs, that institutional membership and IGO use were generally inversely related, and that the attributes of the states had limited utility in accounting for the use of intergovernmental organizations. Some of the theoretical implications of these findings are then explored.

Customer satisfaction, value for money and repurchase intent in the context of system delivery projects: a longitudinal study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matti Haverila ◽  
Jenny Carita Twyford
Keyword(s):  
Project Management ◽  
Customer Satisfaction ◽  
Effect Sizes ◽  
Relational Exchange ◽  
Value For Money ◽  
Data Set ◽  
Content Type ◽  
Repurchase Intent ◽  
The Relationship ◽  
Relational Exchange Theory

PurposeDrawing upon the relational exchange theory, the longitudinal relationship between various stages of project management customer satisfaction, value for money and repurchase intent are examined.Design/methodology/approachUsing a survey questionnaire, data were gathered over four consecutive quarters (N = 2,537). The statistical methods included exploratory factor analysis, confirmatory composite analysis (CCA) and partial least squares structural equation modeling (PLS-SEM).FindingsProject management was perceived as a three-dimensional construct (proposal, installation, commissioning/start-up). There was a significant longitudinal relationship between project stages and satisfaction in the complete data set. The results varied on the quarterly basis. The relationship customer satisfaction/repurchase intent was significant in the whole data set and during all quarters. This was the case for the relationships between value for money and customer satisfaction and between value for money and repurchase intent. The effect sizes were small between project management stages and customer satisfaction, small to medium for the value for money construct and large for the customer satisfaction construct.Originality/valueAn important implication is the significant relationship between the stages of project management and satisfaction. However, the effect sizes were small, however. The importance of the effect size in comparison to the significance of the relationships is highlighted especially when the sample size is large. The paper also confirms the linear relationship between satisfaction and repurchase intent. The nature of the relationship between customer satisfaction and loyalty is based on a moderate exchange relationship in the relational exchange continuum. The study contributes to the relational exchange theory in the context of project management.

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