Color harmony is the focus of many researchers in the field of art and design, and its research results have been widely used in artistic creation and design activities. With the development of signal processing and artificial intelligence technology, new ideas and methods are provided for color harmony theory and color harmony calculation. In this article, psychological experimental methods and information technology are combined to design and quantify the 16-dimensional physical features of multiple colors, including multi-color statistical features and multi-color (...) contrast features. Eighty-four subjects are invited to give a 5-level score on the degree of color harmony for 164 multi-color materials selected from the screenshots of film and television scenes. Based on the multi-color physical features and the subjective evaluation experiment, the correlation analysis is firstly carried out, which shows that the overall lightness, difference of the color tones, number of multiple colors, lightness contrast, color tone contrast, and cool/warm contrast are significantly correlated with color harmony. On the other hand, the regression prediction model and classification prediction model of color harmony are constructed based on machine learning algorithms. In terms of regression prediction model, the prediction accuracy of linear models is higher than that of nonlinear models, with 63.9% as the highest, indicating that the multi-color physical features can explain color harmony well. In terms of classification prediction model, the Random Forest has the best prediction performance, with an accuracy of 80.2%. (shrink)

Child trauma plays an important role in the etiology of Bordeline Personality Disorder. Of all traumas, sexual trauma is the most common, severe and most associated with receiving a BPD diagnosis when adult. Etiologic models posit sexual abuse as a prognostic factor in BPD. Here we apply machine learning using Multiple Kernel Regression to the Magnetic Resonance Structural Images of 20 BPD and 13 healthy control to see whether their brain predicts five sources of traumas: sex abuse, emotion neglect, emotional (...) abuse, physical neglect, physical abuse. We also applied the same analysis to predict symptom severity in five domains: affective, cognitive, impulsivity, interpersonal for BPD patients only. Results indicate that CTQ sexual trauma is predicted by a set of areas including the amygdala, the Heschl area, the Caudate, the Putamen, and portions of the Cerebellum in BPD patients only. Importantly, interpersonal problems only in BPD patients were predicted by a set of areas including temporal lobe and cerebellar regions. Notably, sexual trauma and interpersonal problems were not predicted by structural features in matched healthy controls. This finding may help elucidate the brain circuit affected by traumatic experiences and connected with interpersonal problems BPD suffer from. (shrink)

Emotional labor generally exists in organization members. Emotional labor will not only affect employees’ interpersonal relationships, but also affect employees’ mental health. Affected by many factors such as the economic environment, they often need to bear multiple pressures. The degree of stress is positively correlated with the depth of the development of the times and people’s education. As mental health research has become the frontier and hot spot in the field of psychology, the role of mental health in the process (...) of employee creativity has been paid more and more attention. Therefore, this paper proposes a study on the causes of employees’ psychological stress based on emotional feature clustering. Based on the clustering of emotional characteristics, this paper analyzes the causes of employees’ mental health stress from an economic perspective. For teams with low level of team openness, with the improvement of team heterogeneity, team task performance shows a slight upward trend. It is clear from the experiment that when the number of experiments reaches 100, the task performance of high atmosphere level is 12.14, while the task performance of low atmosphere level is only 9.89. Therefore, the atmosphere of team employees is very important to team task performance. Through the cluster analysis of employees’ mental health characteristics, it not only increases employees’ spare time life, but also reduces employees’ daily contradictions. It eases the work pressure of employees, and becomes a platform for employees to improve their awareness and a promoter of harmonious employee relations. (shrink)

A computer-based age estimation is a technique that predicts an individual's age based on visual traits derived by analyzing a 2D picture of the individual's face. Age estimation is critical for access control, e-government, and effective human–computer interaction. The other-race effect has the potential to cause techniques designed for white faces to underperform when used in a region with black faces. The outcome is the consequence of intermittent training with faces of the same race and the encoding structure of the (...) trained face images, which is based on the feature extraction technique used. This study contributes to a constructive comparison of three feature-extraction techniques, namely, local binary pattern, Gabor Wavelet, and wavelet transformation, used in the development of a genetic algorithm -artificial neural network -based age estimation system. The feature extraction techniques used are proven to produce a wealth of shape and textural information. The GA-ANN constitutes the age classifier module. The correct classification rate was chosen as the performance metrics in this study. The results demonstrated that the LBP is a more robust representation of the black face than the GW and Wavelet transformations, as evidenced by its accuracy rate of 91.76 compared to 89.41 and 84.71 achieved with the GW and Wavelet transformation age estimation systems, respectively. (shrink)

In face recognition systems, highly robust facial feature representation and good classification algorithm performance can affect the effect of face recognition under unrestricted conditions. To explore the anti-interference performance of convolutional neural network reconstructed by deep learning framework in face image feature extraction and recognition, in the paper, first, the inception structure in the GoogleNet network and the residual error in the ResNet network structure are combined to construct a new deep reconstruction network algorithm, with the random gradient (...) descent and triplet loss functions as the model optimizer and classifier, respectively, and it is applied to the face recognition in Labeled Faces in the Wild face database. Then, the portrait pyramid segmentation and local feature point segmentation are applied to extract the features of face images, and the matching of face feature points is achieved using Euclidean distance and joint Bayesian method. Finally, Matlab software is used to simulate the algorithm proposed in this paper and compare it with other algorithms. The results show that the proposed algorithm has the best face recognition effect when the learning rate is 0.0004, the attenuation coefficient is 0.0001, the training method is SGD, and dropout is 0.1, and the algorithm proposed in this paper has the largest mean average precision compared to other CNN algorithms. The correct rate of face feature matching of the algorithm proposed in this paper is 84.72%, which is higher than LetNet-5, VGG-16, and VGG-19 algorithms, the correct rates of which are 6.94%, 2.5%, and 1.11%, respectively, but lower than GoogleNet, AlexNet, and ResNet algorithms. At the same time, the algorithm proposed in this paper has a faster matching time and a higher correct matching rate than the joint Bayesian method, indicating that the deep reconstruction network algorithm proposed in this paper can be used in face image recognition, FE, and matching, and it has strong anti-interference. (shrink)

Cognitive theories based on a fixed feature set suffer from frame and symbol grounding problems. Flexible features and other empirically acquired constraints (e.g., analog-to-analog mappings) provide a framework for letting extrinsic relations influence symbol manipulation. By offering a biologically plausible basis for feature learning, nonorthogonal multiresolution analysis and dimensionality reduction, informed by functional constraints, may contribute to a solution to the symbol grounding problem.

Many views define the concept of automaticity in terms of a number of features, but they differ with regard to the features they put most emphasis on, as well as with regard to the coherence they assume among the features. One contemporary account is the gradual and decompositional view, which proposes to investigate each automaticity feature separately and determine the degree to which it is present. In this chapter, we engage in a detailed analysis of the most important (...) features in order to examine whether they can indeed be regarded as gradual, and whether they can be conceptually and logically separated. (shrink)

Significant associations have been found between specific human leukocyte antigen (HLA) alleles and organ transplant rejection, autoimmune disease development, and the response to infection. Traditional searches for disease associations have conventionally measured risk associated with the presence of individual HLA alleles. However, given the high level of HLA polymorphism, the pattern of amino acid variability, and the fact that most of the HLA variation occurs at functionally important sites, it may be that a combination of variable amino acid sites shared (...) by several alleles (shared epitopes) are better descriptors of the actual causative genetic variants. Here we describe a novel approach to genetic association analysis in which genes/proteins are broken down into smaller sequence features and then variant types defined for each feature, allowing for independent analysis of disease association with each sequence feature variant type. We have used this approach to analyze a cohort of systemic sclerosis patients and show that a sequence feature composed of specific amino acid residues in peptide binding pockets 4 and 7 of HLA-DRB1 explains much of the molecular determinant of risk for systemic sclerosis. (shrink)

Sentiment analysis is one of the important tasks of online opinion analysis and an important means to guide the direction of online opinion and maintain social stability. Due to the multiple characteristics of linguistic expressions, ambiguity, multiple meanings of words, and the increasing speed of new words, it is a great challenge for the task of text sentiment analysis. Commonly used machine learning methods suffer from inadequate text feature extraction, and the emergence of deep learning has (...) brought a turnaround for this purpose. In this paper, we investigate the problem of text sentiment analysis using methods related to deep learning. In order to incorporate user and product information in a more diverse way in the model, this paper proposes a model based on a deep bidirectional long-and short-term memory network-self-attention mechanism-custom classifier. The model first identifies contextual associations and acquires deep text features through a deep bidirectional long- and short-term memory network and then captures important features in the text using a self-attentive mechanism. The model finally combines user information and product information to build a custom classifier module and uses context-aware attention mechanisms to assign specific parameters to user information and product information, which improves the performance of the model on public datasets compared with current common models. The results show that the accuracy of the algorithm in this paper is high, and it is about 5% lower than the traditional algorithm. The method can reduce the number of iterations and the running time of the algorithm. (shrink)

While the idea of philosophy as conceptual analysis has attracted many adherents and undergone a number of variations, in general it suffers from an authority problem with two dimensions. First, it is unclear why the analysis of a concept should have objective authority: why explicating what we mean should express how things are. Second, conceptual analysis seems to lack intersubjective authority: why philosophical analysis should apply to more than a parochial group of individuals. I argue that (...) Hegel’s conception of social ontology, focused on his concept of “ethical life” (Sittlichkeit), helps to explain how concepts (and their explication) have both objective and intersubjective authority in the social domain. Hegel claims that modern institutions are the product of self-conscious purposes, so that they are conceptually constituted. Concepts do not just represent these objects and so depend on a contingent relation to them. As many contemporary social ontologists agree, this means that our concepts of these institutions are uniquely epistemically “transparent.” They have objective authority. Concepts have intersubjective authority in the modern world as well, according to Hegel. However, I show that this feature of Hegel’s account does not rely on the solution to a philosophical problem. Rather, since the concepts of modern ethical life are “essentially contested,” their content depends on the practical and political agreement of modern subjects. This means that concepts can only have objective authority if some prior intersubjective agreement has been reached. The role of philosophy as conceptual analysis is thus importantly dependent on political developments. (shrink)

Ontologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal (...) ontologies and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated. (shrink)

Ontologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal (...) ontologies and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated. (shrink)

Ontologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal (...) ontologies and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated. (shrink)

Studyholism is a new potential obsessive-compulsive -related disorder recently introduced in the literature. According to its theorization, there are two types of Studyholic: Engaged and Disengaged Studyholics, which are characterized, respectively, by high and low levels of Study Engagement. This study aims to shed light on the role of internalizing and externalizing features as antecedents and outcomes of Studyholism and Study Engagement. Moreover, it aims to analyze the differences in psychopathology and sensation seeking between students demonstrating Disengaged and Engaged Studyholism. (...) We performed four path analyses, MANOVAs, and Mann–Whitney tests on 1,223 Italian college students. Among the main findings, Studyholism is associated with psychological and academic impairment, while Study Engagement predicts better mental health and academic functioning; though, the β values are lower for Study Engagement. Moreover, Studyholism is positively predicted by internalizing symptoms and negatively predicted by externalizing variables. Finally, students showing Engaged Studyholism have lower levels of obsessive-compulsive symptoms than those demonstrating Disengaged Studyholism. In conclusion, this study shows the critical importance of implementing preventive interventions aimed at reducing Studyholism levels in college students. Moreover, it provides support to the conceptualization of problematic overstudying as a new potential OCD-related disorder and to the value of distinguishing between Engaged and Disengaged Studyholics for tailored clinical interventions. Finally, it highlights the need to use two different theorizations and operationalizations for problematic overworking and overstudying. However, the literature on problematic overstudying is too scant to reach any firm conclusion. Hence, future studies should deepen the analysis of problematic overstudying, possibly using longitudinal designs, to unveil its internalizing and/or externalizing nature. (shrink)

Discovering high-level causal relations from low-level data is an important and challenging problem that comes up frequently in the natural and social sciences. In a series of papers, Chalupka etal. (2015, 2016a, 2016b, 2017) develop a procedure forcausal feature learning (CFL) in an effortto automate this task. We argue that CFL does not recommend coarsening in cases where pragmatic considerations rule in favor of it, and recommends coarsening in cases where pragmatic considerations rule against it. We propose a new (...) technique, pragmatic causal feature learning (PCFL), which extends the original CFL algorithm in useful and intuitive ways. We show that PCFL has the same attractive measure-theoretic properties as the original CFL algorithm. We compare the performance of both methods through theoretical analysis and experiments. (shrink)

ABSTRACTAnxiety and depression diagnoses are associated with suicidal thoughts and behaviours. However, a categorical understanding of these associations limits insight into identifying dimensional mechanisms of suicide risk. This study investigated anxious and depressive features through a lens of suicide risk, independent of diagnosis. Latent class analysis of 97 depression, anxiety, and suicidality-related items among 616 psychiatric outpatients indicated a 3-class solution, specifically: a higher suicide-risk class uniquely differentiated from both other classes by high reported levels of depression and anxious (...) arousal; a lower suicide-risk class that reported levels of anxiety sensitivity and generalised worry comparable to Class 1, but lower levels of depression and anxious arousal; and a low to non-suicidal class that reported relatively low levels across all depression and anxiety measures. Discriminants of the higher suicide-risk class included borderline personality disorder; report... (shrink)

ABSTRACT Corporate Social Responsibility denotes a movement away from shareholder theories of the corporation, and refers to a set of practices designed to have an economic, environmental, and social impact. Public companies report on their CSR practices annually in the form of multimodal reports which are made available on the companies’ websites, and are typically read by investors who seek standardisation across this genre. Thus, most companies across the globe follow the Global Reporting Initiative framework for reporting, a framework developed (...) within the Global North. The dominance of the Global North in CSR practices is also evident in the academic literature – while applied linguists have gone some way in highlighting the generic, interpersonal, and ideational features of reports, such studies have predominantly focused on multinational corporations. There is, comparatively, very little literature on the CSR practices and discourses circulating in the Global South or former colonial contexts and because of this we have limited insight into how companies operating in these contexts discursively represent themselves, their employees and their suppliers within the same context. To address this shortcoming, this study draws on analytical approaches developed within Critical Discourse Analysis coupled with postcolonial theory in order to comment on the ideational features of the four most recent CSR reports of one South African company. (shrink)

With the deepening of globalization, brand plays an important role in determining the competitiveness of enterprises. It is worth thinking about how to quantify the brand value reasonably to achieve the purpose of improving the competitiveness of enterprises. The research of commercial brands based on emotion analysis extracts the views of consumers on the evaluation data of brand attributes, analyzes the emotional tendency of consumers' views, and then helps enterprises adjust their production strategies. The purpose of emotion analysis (...) is to judge users' views and attitudes toward goods or services by analyzing texts. In this paper, the linear support vector machine model is used to extract and study the features in sentiment analysis. Then, the brand based on the fusion model is evaluated, and the experimental conclusions are drawn: the method of fusing the depth features extracted by word vector and the named entity extracted by CRF makes the brand effect of fusing emotional factors better than the feature extraction method only using CRF named entity recognition. It is proved that the model method proposed in this paper has a certain role in actual business. Feature fusion often combines shallow model methods and fuses various shallow feature screening technologies based on word segmentation results. This paper introduces fusion features and supplements feature vectors based on the results of the deep learning word vector model. Support Vector Machine maps feature vectors to some sample points in the space, finds a plane that can realize sample classification, and maximizes the distance between the two sample points closest to the plane in two types of samples, to maximize the classification performance and improve the generalization of the model. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other (...) objects based on shared and non-shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non-shared features and did not include shared features. This indicates that shared features may play less of a role in early word learning than non-shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)

The prediction of the secondary structure of a protein from its amino acid sequence is an important step towards the prediction of its three-dimensional structure. However, the accuracy of ab initio secondary structure prediction from sequence is about 80 % currently, which is still far from satisfactory. In this study, we proposed a novel method that uses binomial distribution to optimize tetrapeptide structural words and increment of diversity with quadratic discriminant to perform prediction for protein three-state secondary structure. A benchmark (...) dataset including 2,640 proteins with sequence identity of less than 25 % was used to train and test the proposed method. The results indicate that overall accuracy of 87.8 % was achieved in secondary structure prediction by using ten-fold cross-validation. Moreover, the accuracy of predicted secondary structures ranges from 84 to 89 % at the level of residue. These results suggest that the feature selection technique can detect the optimized tetrapeptide structural words which affect the accuracy of predicted secondary structures. (shrink)

In this work, a system for the classification of liver dynamic contest- enhanced CT images is presented. The system simultaneously analyzes the images with the same slice location, corresponding to three typical acquisition moments. At first, the texture features are extracted separately for each acquisition mo- ment. Afterwards, they are united in one “multiphase” vector, characterizing a triplet of textures. The work focuses on finding the most appropriate features that characterize a multi-image texture. At the beginning, the features which are (...) unstable and dependent on ROI size are eliminated. Then, a small subset of remaining features is selected in order to guarantee the best possible classification accuracy. In total, 9 extraction methods were used, and 61 features were calculated for each of three acquisition moments. 1511 texture triplets, corresponding to 4 hepatic tissue classes were recognized. As a classifier, an adaptive boosting algorithm with a C4.5 tree was used. Experiments show that a small set of 12 features is able to ensure classification accuracy exceeding 90%, while all of the 183 features provide an accuracy rate of 88.94%. (shrink)

Schyns, Goldstone & Thibaut oppose the notion of fixed feature analysis, suggesting the possibility of flexible feature creation in object recognition and categorisation. Such proposals cannot be assessed until clear definitions of the objects in question and their decompositions are formulated. Flexibility may come from the decompositions of objects rather than from feature creation.

BackgroundApproximately 7% of the general population is affected by an orphan disease, which, in the United States, is defined as affecting fewer than 1 in 1500 people. Disease awareness is often low and time-to-diagnosis delayed. Different legislations worldwide have created incentives for pharmaceutical companies to develop drugs for orphan diseases. A journalistic article in Bloomberg Businessweek has claimed that pharmaceutical companies have tried marketing orphan drugs by placing a specific disease into the popular television series “House, M.D.” which features diagnostic (...) journeys and was produced between 2004 and 2012. This study aimed to describe the presentation of orphan diseases in the television series “House, M.D.”, to test in an exploratory fashion the hypothesis that treatable orphan conditions are overrepresented in “House, M.D.” and to discuss whether such marketing practices may or may not be ethical.MethodsA list of all medical cases depicted in the television series “House, M.D.” was obtained and classified as orphan or non-orphan according to the Orphanet database. The ratios of orphan diseases among all diseases, such with an orphan drug designation and such with an orphan drug approval by the FDA were then compared with conservative approximations of real world conditions (chi-squared tests for equality of proportions). STROBE criteria were respected.ResultsOut of a total of n = 181 different medical diagnoses, n = 42 (23.2%) were orphan diseases. The difference in percentages in between “House, M.D.” and reality was not statistically significant for orphan diseases overall (p = 0.96), yet was statistically significantly higher for both orphan diseases with one or more orphan drug designations (p = 0.0192) and such with one or more approved orphan drugs (p < 0.0001).ConclusionsOrphan diseases with a designated and/or approved orphan drug were overrepresented in the television series “House, M.D.” with statistical significance while orphan diseases overall were not. This may be explained by (so far) undocumented efforts of pharmaceutical companies to place their orphan drugs in the television series, as described in the article in Bloomberg Businessweek. Further research is needed into marketing practices in popular and emerging media formats. (shrink)

Judging similarities among objects, events, and experiences is one of the most basic cognitive abilities, allowing us to make predictions and generalizations. The main assumption in similarity judgment is that people selectively attend to salient features of stimuli and judge their similarities on the basis of the common and distinct features of the stimuli. However, it is unclear how people select features from stimuli and how they weigh features. Here, we present a computational method that helps address these questions. Our (...) procedure combines image-processing techniques with a machine-learning algorithm and assesses feature weights that can account for both similarity and categorization judgment data. Our analysis suggests that a small number of local features are particularly important to explain our behavioral data. (shrink)

The article carries out a comprehensive comparative analysis of the understanding of "practice" in the context of thinkers of two directions of Marxism – Ukrainian-Soviet and Chinese philosophers. When examining the concept of "practice" in Ukrainian Soviet Marxism, the work of the following domestic thinkers is studied: P. Kopnin, V. Shynkaruk, V. Tabachkovskyi, V. Ivanov, O. Yatsenko. It is substantiated that domestic thinkers in the 60s and 80s of the XX century. focused their attention on practice not so much (...) in the epistemological or socio-philosophical content, but in the anthropological and existential one. According to most of them, practice is not so much the opposite of theory, but a fundamental principle of consideration of all scientific and theoretical problems through the prism of their humanistic content, which allows us to realize the connection of theoretical knowledge with all the variety of ways of mastering a person. being, reveals the essence of knowledge as a cultural phenomenon. The work "On Practice" by Mao Zedong is analyzed, which reveals the prospect of further understanding of the researched concept within the framework of Chinese Marxism. In particular, he singles out two key aspects of the explanation of "practice": epistemological and political-philosophical. Therefore, Marxism in China is used to solve its problems and transform the rich practical experience of the state into theory, as well as in combination with Chinese history and unique Chinese traditional culture. (shrink)

This book concentrates on argumentation as it emerges in ordinary discourse, whether the discourse is institutionalized or strictly informal. Crucial concepts from the theory of argumentation are systematically discussed and explained with the help of examples from real-life discourse and texts. The basic principles are explained that are instrumental in the analysis and evaluation of argumentative discourse. Methodical instruments are offered for identifying differences of opinion, analyzing and evaluating argumentation and presenting arguments in oral and written discourse. In addition, (...) the book provides a great variety of exercises and assignments to improve the students' skill in presenting argumentation. The authors begin their treatment of argumentation theory at the same juncture where argumentation also starts in practice: The difference of opinion that occasions the evolvement of the argumentation. Each chapter begins with a short summary of the essentials and ends with a number of exercises that students can use to master the material. _Argumentation_ is the first introductory textbook of this kind. It is intended as a general introduction for students who are interested in a proper conduct of argumentative discourse. Suggestions for further reading are made for each topic and several extra assignments are added to the exercises. Special features: * A concise and complete treatment of both the theoretical backgrounds and the practice of argumentation analysis and evaluation. * Crucial concepts from pragmatics presented in a non-technical way; introducing the theory of verbal communication. * Unique coverage of both oral and written presentation of arguments. * Exercises and assignments based on real-life texts from a variety of contexts. (shrink)

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other (...) objects based on shared and non‐shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non‐shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non‐shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning. (shrink)

Tetris provides a difficult, dynamic task environment within which some people are novices and others, after years of work and practice, become extreme experts. Here we study two core skills; namely, choosing the goal or objective function that will maximize performance and a feature-based analysis of the current game board to determine where to place the currently falling zoid so as to maximize the goal. In Study 1, we build cross-entropy reinforcement learning models to determine whether different goals (...) result in different feature weights. Two of these optimization strategies quickly rise to performance plateaus, whereas two others continue toward higher but more jagged heights. In Study 2, we compare the zoid placement decisions made by our best CERL models with those made by 67 human players. Across 370,131 human game episodes, two CERL models picked the same zoid placements as our lowest scoring human for 43% of the placements and as our three best scoring experts for 65% of the placements. Our findings suggest that people focus on maximizing points, not number of lines cleared or number of levels reached. They also show that goal choice influences the choice of zoid placements for CERLs and suggest that the same is true of humans. Tetris has a repetitive task structure that makes Tetris more tractable and more like a traditional experimental psychology paradigm than many more complex games or tasks. Hence, although complex, Tetris is not overwhelmingly complex and presents a right-sized challenge to cognitive theories, especially those of integrated cognitive systems. (shrink)

This article presents an analytical overview of the critical modernisation features of Socialism with Chinese characteristics doctrine in the new era, which was proposed at the 20th National Congress of the Communist Party of China. The authors reconstructed and systematically represented the central philosophical and political principles of the doctrine of Socialism with Chinese characteristics in the context of the fundamental principles of Chinese Marxism. The authors also analysed and presented in a systematic form the essence and basic theoretical principles (...) of the concept of Socialism with Chinese characteristics following Xi Jinping's works and reports. The study includes a comparative analysis that concludes with the critical features of the modern concept of socialism with Chinese characteristics. These features embrace the need for constant modernisation of the very doctrine of socialism with Chinese characteristics, the state management system, as well as social and cultural practices, which are possible through the implementation of innovations and the integration of modern philosophical thought with traditional Chinese philosophy and culture. The article concludes that the main feature of the modernisation of Socialism with Chinese characteristics at the current stage reveals in the development and implementation of a system of creative practices at the level of everyday culture, high-tech sectors of social production and the practice of intercultural communication within the framework of China's Belt and Road Initiative. In the discussion, the authors argue that implementing creative practices and creative industries could become an effective tool for developing China's Belt and Road Initiative in European countries and improving mutual understanding in the intercultural communication practices between China, European countries, and Ukraine. (shrink)

Exploring the dynamics feature of robust chaotic system is an attractive yet recent topic of interest. In this paper, we introduce a three-dimensional fractional-order chaotic system. The important finding by analysis is that the position of signalx3descends at the speed of 1/cas the parameterbincreases, and the signal amplitude ofx1,x2can be controlled by the parametermin terms of the power function with the index −1/2. What is more, the dynamics remains constant with the variation of parametersbandm. Consequently, this system can (...) provide rich encoding keys for chaotic communication. By considering the properties of amplitude and position modulation, the partial projective synchronization and partial phase synchronization are realized with linear control scheme. The distribution map of optimal synchronization region in the control-parameter space is charted by defining the power consumption of controller. Numerical simulations are executed to confirm the theoretical analysis. (shrink)

B a c k g r o u nd. The article focuses on the study of modern adaptations and modifications of Marxist principles in the context of the practice of the Chinese Communist Party (CCP). Focusing on the process of modernization, the article explores how Marxism developed and adapted to China's unique socio-political and economic landscape. Through an in-depth analysis of the CCP's policy and ideological changes, the article sheds light on the distinctive features characterizing the modernization of Marxism (...) in the Chinese context. The study covers not only theoretical aspects but also practical aspects, providing a refined understanding of the specifics of the relationship between Marxist ideology and the dynamic realities of Chinese governance. M e t h o d s. The article uses an in-depth analysis of the politics, ideological changes, and practical aspects of the CCP. The research is based on an analysis of primary sources, including official documents, political speeches and ideological narratives. R e s u l t s. The authors found that the ideology of the CCP is based on Marxism, but adapted to the unique historical context of China, often framed in the concept of "socialism with Chinese characteristics". This adaptation reflects the CCP's recognition of China's special conditions, cultural heritage, and development needs. At its core, Marxism provides the theoretical foundation for the ideology of the CCP, emphasizing class struggle, historical materialism, and the ultimate goal of achieving a classless communist society. However, the CCP recognizes that the application of Marxist principles must take into account the specific realities of China, distinguishing its path from the classical Marxist trajectory. C o n c l u s i o n s. The study highlights that the CCP recognizes the importance of adapting Marxist principles to the specific conditions of China. Acceptance of the concept of "socialism with Chinese characteristics" defines a pragmatic approach to the integration of Marxist ideology with the conditions of the country, taking into account its path of economic development and modernization. (shrink)

Tetris provides a difficult, dynamic task environment within which some people are novices and others, after years of work and practice, become extreme experts. Here we study two core skills; namely, choosing the goal or objective function that will maximize performance and a feature-based analysis of the current game board to determine where to place the currently falling zoid so as to maximize the goal. In Study 1, we build cross-entropy reinforcement learning models to determine whether different goals (...) result in different feature weights. Two of these optimization strategies quickly rise to performance plateaus, whereas two others continue toward higher but more jagged heights. In Study 2, we compare the zoid placement decisions made by our best CERL models with those made by 67 human players. Across 370,131 human game episodes, two CERL models picked the same zoid placements as our lowest scoring human for 43% of the placements and as our three best scoring experts for 65% of the placements. Our findings suggest that people focus on maximizing points, not number of lines cleared or number of levels reached. They also show that goal choice influences the choice of zoid placements for CERLs and suggest that the same is true of humans. Tetris has a repetitive task structure that makes Tetris more tractable and more like a traditional experimental psychology paradigm than many more complex games or tasks. Hence, although complex, Tetris is not overwhelmingly complex and presents a right-sized challenge to cognitive theories, especially those of integrated cognitive systems. (shrink)

There is a paradox lying at the heart of the study of heredity. To understand the ways in which features are passed down from one generation to the next, we have to dig deeper and deeper into the ultimate nature of things - from organisms, to genes, to molecules. And yet as we do this, increasingly we find we are out of focus with our subjects. What has any of this to do with the living, breathing organisms with which we (...) started? Organisms are living. Molecules are not. How do we relate one to the other? In Genetic Analysis, one of the most important empirical scientists in the field in the twentieth century attempts, through a study of history and drawing on his own vast experience as a practitioner, to face this paradox head-on. His book offers a deep and innovative understanding of our ways of thinking about heredity. (shrink)

This scientific article is devoted to the study of the features of mediatization of the socio-political sphere in modern Ukrainian society. Using methodological approaches, the author proposes to clarify the main theoretical principles underlying the study of mediatization.The article identifies and classifies the key factors that influence the process of mediatization in Ukrainian society. Special attention is paid to the impact of the Internet, information warfare, media space and “new media” on the socio-political sphere.Applying content analysis of reports of (...) analytical centers of Ukraine, the author identifies and systematizes specific signs of mediatization of Ukrainian society. Analyzing these features, the article examines the impact of mediatization on the socio-political landscape of the country and identifies potential challenges and opportunities that arise in connection with this process. It has been proven that the progress of the technical component of the mediatization process entails both the emergence of new opportunities and significant threats to national security. It was established that the development of “new mass media” leads to a gradual increase in the role of messengers as sources of reliable information and the displacement of other (non-digital) ways of information dissemination. Initiatives unrelated to state intervention and self-regulation mechanisms in the information sphere are singled out as one of the most effective means of combating disinformation.The final part of the article provides recommendations regarding state regulation of the mediatization process in Ukrainian society. The author reveals the essence of the institution of public diplomacy as a potential means of strengthening national security in the context of the information society. The author points to the need for effective regulation, balanced protection of the rights and freedoms of citizens in the media environment, and also emphasizes the importance of developing media literacy among the population. The article offers a valuable contribution in the context of understanding the process of mediatization of the socio-political sphere in Ukrainian society and provides practical recommendations aimed at ensuring the sustainable development of this process.Keywords: Inte. (shrink)

This paper presents the concept and algorithm of data mining and focuses on the linear regression algorithm. Based on the multiple linear regression algorithm, many factors affecting CET4 are analyzed. Ideas based on data mining, collecting history data and appropriate to transform, using statistical analysis techniques to the many factors influencing the CET-4 test were analyzed, and we have obtained the CET-4 test result and its influencing factors. It was found that the linear regression relationship between the degrees of (...) fit was relatively high. We further improve the algorithm and establish a partition-weighted K-nearest neighbor algorithm. The K-weighted K nearest neighbor algorithm and the partition algorithm are used in the CET-4 test score classification prediction, and the statistical method is used to study the relevant factors that affect the CET-4 test score, and screen classification is performed to predict when the comparison verification will pass. The weight K of the input feature and the adjacent feature are weighted, although the allocation algorithm of the adjacent classification effect has not been significantly improved, but the stability classification is better than K-nearest neighbor algorithm, its classification efficiency is greatly improved, classification time is greatly reduced, and classification efficiency is increased by 119%. In order to detect potential risk graduating students earlier, this paper proposes an appropriate and timely early warning and preschool K-nearest neighbor algorithm classification model. Taking test scores or make-up exams and re-learning as input features, the classification model can effectively predict ordinary students who have not graduated. (shrink)

Architecture culture is the synthesis of material possession and spiritual wealth, created by human society history development and reflects historic continuity and nationality character. This paper has a comprehensive comparison analysis on distinctions of originality, architecture characteristic, developing logic, art forms, and intention between China and Western Countries exhibited on architectural culture, including three parts: ancient period, current period, and future development. Through comparison studies, it presents a comprehensive cognition on different cultural backgrounds and unique exhibition forms for different (...) architectural styles on China and Western Countries; have a deeper understanding on architectural culture communion in two different civilization zones; and find a future developing way with ethical features and spirit for Chinese and Western architecture. (shrink)

The image of St. Petersburg is an integral part of Russian art, in particular, in watercolor painting. This article is devoted to the analysis of the work of Russian watercolor artists, identifying the specifics and characteristic features of the image of the city on the Neva in their work. The object of the study is watercolors by Russian artists, the subject is expressive means, techniques and methods through which the image of St. Petersburg is embodied. On the example of (...) watercolor works by E.P. Gau, I.A. Vladimirova, A.S. Vedernikov, A.P. Ostroumova-Lebedeva, P.P. Grigoryants, G.P. Fitingof, A. Ermolaev, V.V. Proshkin, K. Kuzema, V. Kolbasov, O. Litvinenko, etc. the historical transformation of the artistic image of St. Petersburg, its conditionality by cultural and historical factors and the nature of the life of the inhabitants of the city is shown. The study concluded that the image of St. Petersburg is important for Russian artists, as well as a significant variety of its creative interpretations. Each watercolor work demonstrates the subjective attitude of artists to St. Petersburg, thanks to which real urban landscapes acquire spirituality and unique expressiveness. The complex historical fate of this cultural and artistic center of Russia, which was once a magnificent capital, experienced revolutionary events and went through military destruction, determined the versatility of creative approaches to the embodiment of the city, as a result of various turns of history, it lost, then regained its greatness, beauty and attractiveness. Petersburg in watercolors is invariably filled with vitality, lyrical feelings and the love of artists. (shrink)