Reviewerly/exHarmony huggingface dataset:
Study on Application of Optimized GA-BPNN Algorithm in English Teaching Quality Evaluation System

The assessment of teaching quality is a very complex and fuzzy nonlinear process involving many factors and variables, so developing a mathematical model is difficult, and the traditional method of evaluating teaching quality is no longer fully competent. In order to evaluate teaching quality effectively and accurately, an optimized GA-BPNN algorithm based on genetic algorithm (GA) and backpropagation neural network (BPNN) is proposed. Firstly, an index system of teaching quality evaluation is established, and a questionnaire is designed according to the index system to collect data. Then, an English teaching quality evaluation system is established by optimizing model parameters. The simulation shows that the average evaluation accuracy of the GA-BPNN algorithm is 98.56%, which is 13.23% and 5.85% higher than those of the BPNN model and the optimized BPNN model, respectively. The comparison results show that the GA-BPNN algorithm in teaching quality evaluation can make reasonable and scientific results. The GA-BPNN technique developed in this study searches locally near the global optimal solution, which effectively overcomes the classic approach's sluggish convergence speed while also overcoming the problem of being easily local confined to the minimum.
New challenges to online learning: Ethical aspect

The article is devoted to the study of ethical challenges arising in the field of higher education, due to a shift of education to distance learning. This task is carried out based on a study of the results of the survey of students of the Krasnoyarsk State Pedagogical University named after V.P. Astafiev and analysis of educational practices used by teachers in distance learning and analysis of students’ behaviors in the situation of total e-learning. The study addresses two sets of problems: 1) ethical problems of teaching staff caused by their work in an electronic university environment, 2) ethical problems of the student audience in the context of distance learning. The analysis identifies some issues that need to be addressed, namely: 1) a new value and normative environment need to be created, taking into account the changes brought about by the transformations of the education system in the digitization process, increasing attention not only to the ethical, but also to the etiquette aspect of personal behavior in virtual space; 2) there is a need to investigate the transformations of pedagogical communication in a shift from offline to online format and related ethical issues.
Interdisciplinarity of Cognitive Science

Definitions of cognitive science typically emphasize the field’s interdisciplinary roots. As a case study of the field of cognitive science, we analyzed the activities of the Cognitive Science Society with a particular emphasis on the interdisciplinary nature of the field, now and since its inception. Analyses of departmental affiliations, training backgrounds, research methodology, and paper citations suggest that the journal Cognitive Science and the Annual Meeting of the Cognitive Science Society are dominated by cognitive psychology and computer science, rather than being an equal division among the constituent disciplines of cognitive science. However, at many levels, a growing percentage of work was found to involve a conjunction of multiple disciplines, such that approximately 30-50% of recent work in the Cognitive Science Society is interdisciplinary. The goal of this symposium is to discuss the factors (psychological, historical, sociological, and others) that have lead to the current state of affairs, and what may be done to further increase interdisciplinarity in cognitive science.
Updating Memory Representations during Reading: The Role of Cohort Competition

Forming a coherent representation from texts is key to comprehension. The processes of building and maintaining such representations are very complex and dynamic. In this presentation, we describe a computational model of reading comprehension — the competitive cohort model (CCM) — which captures how readers construct an interconnected network of memory representation during reading. The data from modeling are compared to existing human data.
Attitudes, Expectations and Interests among Students for Education and Career Development in the Sphere of Social Pedagogy

The article reflects the results of a survey among students majoring in Social Pedagogy at Sofia University. The research was conducted through a focus group and a survey and aims to establish the general attitudes for continuing education and career development in the social pedagogy field. The analysis of the results allows to outline guidelines for improving the quality of education and optimizing the curriculum in master's programs in this specialty in order to attract more students and meet the need for qualified and motivated staff working in the social pedagogy sphere.
Examples And Generalisations: Using Surface Versus Structural Recall Biases To Probe Conceptual Storage

We argue that the key question in conceptual storage is best viewed not as a question of instances versus generalisations, but rather one of unitary versus multiple representation accounts of conceptual storage. On previous evidence, it has been difficult to determine whether a particular result stems from stored information regarding the concept or from the processes that operate in invoking a particular concept (Komatsu, 1992). In this paper, we attempt to shed some light on the nature of stored conceptual structure using the different influences that surface and structural features have been shown to have on the recall of a particular representation (Gentner, Ratterman and Forbus, 1993). We conclude that at least some concepts may not be stored using a unitary representation.
Effects of Creative Drama Activity Using Picture Books on Peer Competence of Children with Maladaptive Behavior

This study aims to investigate the effect of creative drama activity using picture books on the peer competence of children with maladaptive behavior. The subjects of this study were 60 6-year-old children, chosen by utilizing the PBQ and peer competency scale. The authors selected 12 infants included in both categories: as six in the experimental group and six in the control group. The play program creative drama activity using picture books included eight sessions. The experimental group performed creative drama activity using picture books, while only picture books were provided to the control group. For processing the obtained data, pre- and post-group mean and standard deviation, t-tests were performed using SPSS WIN 21.0, and the changed behavior was observed. As a result of the study, the authors found that children with maladaptive behavior experienced a positive effect on peer competence through creative drama activity using picture books.
Exploring Gang Effects By Output Node Similarity In Neural Networks

If a network is trained to minimize mean squared error then it will also learn to maximize the posterior probability of the output given the input (Kuan, et al., 1994). In other words, a network learns to maximize expectations. However, some interesting and relevant psychological modeling are more often concerned with the nature of generalizations across classes of input. In the case of Simple Recurrent Networks (SRNs) these learning effects can occur in temporal context of the feedback connections. For example, Elman (1989) showed how a SRN can learn a simple grammar in a prediction task and the network will learn to produce expectations for all items in a class, even though not all combinations were seen in training. In this work I take a geometric viewpoint toward understanding how a feedforward networks have a “gang” effect due to class similarity in output, and a SRN can have “gang” effects in context. The problem is related to several connectionists models in language that have shown that a network can have generalizations for unseen input. (e.g. Hare, 1990). I will look at generalizations for unseen combinations of bigrams (input-to-output mapping) and trigrams (context and input-to-output mapping), and extend the findings of Bartell, et al. (1993).
Learned Categorical Perception Effects in Neural Networks

A number of recent studies have demonstrated what have come to be known as ‘learned categorical perception’ effects in humans (e.g., Goldstone, 1994). The most common form of these effects is called ‘compression’: People have greater difficulty discriminating or judge to be more similar patterns that they have learned to classify together, compared to people who have not learned to classify the patterns.
A Study on Developing English Online Teaching and Learning Models

The purpose of this study is to develop online teaching and learning models for English classes. With the prolonged COVID-19, online classes were implemented nationwide. However, according to both the survey and interview on implementing online classes, there are various limitations in fully implementing online classes at school. In other words, the physical and human infrastructure necessary for conducting online classes were not sufficiently established. In addition, there was a lack of guidelines or reference materials to help design online teaching and learning. Moreover, there was a lack of examples of practical teaching and learning materials that could be immediately used at school. In order to provide practical help in designing and implementing online classes, this study developed a model of online lesson plan. This study also presented online teaching and learning principles and detailed guidelines. In addition, this study suggested an online lesson design procedure model that teachers can utilize in the phase of development. The conceptual model, components, principles and guidelines for lesson design, and design procedures which were proposed in this study were applied to develop a lesson procedure for speaking class. This lesson plan was developed to hone learners’ reading and speaking skills by reading articles on Korean cultural places and activities and by speaking in English about Korean culture. Through this lesson, learners are expected to cultivate English communication competency, community competency, information processing competency, and self-management competency by investigating and presenting Korean cultures. The results of this study can be expected not only to play a role as a practical online lesson design guide for teachers, but also to contribute to students development of English communication skills.
Cast of Main Characters of the Press Freedom Period

Bardewijck, Hermann Ludolph (?-
How Purdue University Commercializes Its Research: Yung-Hsiang Lu helps turn research results into revenue

For Yung-Hsiang Lu, improving the energy efficiency of computer technology to provide real-world benefits has been a lifelong focus.
Social risks of student youth in the context of the Higher Education transformation

Higher education transformation creates the basis for the emergence and development of social risks for all its participants, first of all, students. The research aim was to describe the degree of intensity and characteristics of educational, socio-cultural, socio-economic and other risks appearing among students. The results of the extensive survey show that the relevant social risks for students are the risks in education and employment. The author identified three groups of student youth according to the parameters of ascriptive status and analysed the features of social risks in these groups. The measures to minimize social risks among student youth through university organizational and managerial activities are introduced in the article. The author concludes that there is the necessity to search for effective methods of social risk management among young people, as well as in higher education institutions.
Familiarity assessment in visual word recognition and the transformation hypothesis

The use of word-shape as a source of information in visual word recognition is a controversial issue where holists and analytics take different views (Paap et. al., 1984). The majority of experiments on case influence, has resorted to the alternating case paradigm as a method of investigation. Although this is a successful paradigm, the extreme disruption it causes to the string’s appearance produces a stimulus not normally found in the environment. Consequently, the strategies used to deal with these strings may not be the same as those used in normal processing.
Summarization of financial reports with TIBER

This paper reports an approach for summarizing financial texts that combine several techniques for sentence representation and neural document modeling. Our approach is extractive and it follows the classic pipeline of ranking and consequent selecting of the top-ranked text chunks. We evaluate our method on the financial reports provided in the Financial Narrative Summarization (FNS 2021) shared task. The data for the shared task was created and collected from publicly available UK annual reports published by firms listed on the London Stock Exchange. The reports composed FNS 2021 dataset are very long, have many sections, and are written in “financial” language using various special terms, numerical data, and tables. The results show that our approach outperforms the FNS topline with a very serious advantage. In addition to its performance, our approach is also time-efficient.
Categorization under the Influence

In the first experiment, participants learned an easy rule that allowed perfect categorization that they had to automate. During learning, a new ancillary dimension was systematically associated with the defining feature of each category. In the test phase, items in which the association created during learning was broken were categorized more slowly than those in which the association was present, even for participants who did not notice the association. However, when the category-defining and the ancillary features were reversed in a second experiment, we did not get the anticipated results: there was no effect of the implicit association created during the learning phase. Results are explained in terms of dependencies between properties during processing. It is argued that similarity to previous exemplars dons not explain the results obtained here.
Detecting an ‘Anomalous State of Knowledge'for Proactive Information Filtering

Information filters for the world wide web (WWW) require that users formulate a more or less stable information need. Often, however, an ‘anomalous state of knowledge’ (Belkin & Kwasnik, 1986) occurs: the user needs information but is not aware of this. With the rapid growth of information available on line, it is likely that this need could be filled, if only there were a mechanism to detect this need on the user’s behalf. We implemented such a mechanism in an agent architecture, as part of the proactive information filter Profile (Honnkamp, 1997). The mechanism subsumes three modules:
Rational Categories

We adopt the interpretation of rationality according to which an organism’s behavior is rational if it is optimally adapted to its environment (Anderson, 1990, 1991a, 1991b). Rationality, according to this view, often implies mechanisms that are as informationally efficient as possible. We interpret the problem of basic-level categorization (Rosch & Mervis, 1975) as one of data compression within an information theory framework, to define a framework whereby the best classification on a set of items is the one that maximally compresses the description of the similarity structure of these items. This framework is then used to examine whether participants in two experiments classified meaningless items in a way that reflected such a compression bias. In addition to the implications for human basic-level categorization, an objective criterion is established for assessing the relative merits of alternative clustering solutions on the same domain.
The Participation of Bulgarian School Students in Informatics Competitions for 2021

A brief overview of the school student competitions in informatics held in Bulgaria and the participation of Bulgarian students in international competitions in 2021 is considered. Some notes are given about the organization of these competitions and their technological support.
A production system model of memory for spatial descriptions

When people read spatial descriptions they construct a mental model. When they attempt to remember the spatial description they may rely on memory for the description itself, memory for the constructed model, and/or memory for the operations used to construct the mental model - an episodic construction trace (Payne, 1993). This paper reports an ACT-R simulation of this multiplerepresentation account of memory for spatial descriptions. The simulation shows that the idea of a remembered construction trace can arise naturally from ACT-R’s treatment of goals as declarative memory elements. The simulation captures the most important experimental data in favour of the construction trace hypothesis.
Image Watermarking with Polar Harmonic Moments

Orthogonal polar image moments are frequently applied in image watermarking. Polar harmonic transform (PHT) is one such an image moment. It is the collection of three image moments, namely polar cosine transform (PCT), polar complex exponential transform (PCET) and polar sine transform (PST). The character of the evoked watermark relies on the truth of the estimated image moments. In this regard, different kinds of algorithms have been proposed for reckoning the accurate image moments. In this study, the application of PHT in image watermarking is discussed. The PHT is scaling and rotation invariant, which permits the watermark to sustain against geometric attacks as well as signal processing attacks. The experimental result analysis also suggests the caliber and stability of the proposed algorithm against these attacks.
A Computational Model Of Recognizing and Revising Inappropriate Advice1

Advice-giving is improved by understanding and responding to user feedback. Previous models of this task treat user responses as misunderstandings or misconceptions and focus on generating alternate or corrective explanations. By and large, however, these models do not consider the possibility that the system’s advice is inappropriate and may need revision during the course of an on-going dialog. This paper presents a model of the process of revising plan-oriented advice in response to user feedback. Our focus is on mechanisms for evaluating planning alternatives, for determining when to revise advice, and for dynamically generating explanations of these revisions.
Syntactic Systematicity Arising from Semantic Predictions in a Hebbian-Competitive Network

A Hebbian-inspired, competitive network is presented which learns to predict the typical semantic features of denoting terms in simple and moderately complex sentences. In addition, the network learns to predict the appearance of syntactically key words, such as prepositions and relative pronouns. Importantly, as a by-product of the network’s semantic training, a strong form of syntactic systematicity emerges. Moreover, the network can integrate novel nouns and verbs into its training process. This is achieved by assigning predicted semantic features as a default meaning when a novel word is encountered. All network training is unsupervised with respect to error feedback. Issues addressed here have been the subject of debate by notable psychologists, philosophers, and linguists within the last decade.
Project of the technological community of primary professionalization

The article is devoted to the creation of a project of the technological community for the subjects of the educational process. It is assumed that the main ideas of the community will be implemented on the digital platform “Faculty”. The authors of the article outlined the goal of creating a community, the benefits and opportunities from its use by interested parties. In the course of the work, possible risks of launching and functioning of the community were identified, a roadmap (milestones) of the project was prepared, and indicators for evaluating the effectiveness of using the technology community were identified.
A Cognitive Study of the Semantic Memory activated by Pictures and by Words.

Here, the fundamental question is the existence of a mental lexicon for pictures, as it exists one for words. And so, what is the structure of the semantic memory and its relationships with access modalities ? In the first experiment we determine if a picture or a word can activate the same semantic structure by using the semantic priming paradigm. The classical effect of facilitation was found for word priming, but not for picture as prime. An hypothesis is that the semantic network activated by pictures is different from that activated by words. In the second experiment, we demonstrate that the semantic association structure for pictures and for words is different. So on the basis of these data, we replayed the experiment I. In this case, pictures as words could induce semantic priming of a word. And so we discuss the issue of multiple vs unitary semantic storage.
Extracting Information from Graphics

Graphics are used in situations where a large set of data is to be presented in an effective manner. Having a set of standards for the construction of graphics is critical for information graphics. The current work is the first step in a project motivated to establish connections between application-oriented work (e.g., Tufle, 1983) and the theoretical work (e.g., Cleveland & McGill, 1984; Pinker, 1990). Our model is an integration of Pinker’s (1990) and Cleveland and McGill’s (1984) theories. Our model of graphics comprehension states that comprehension of information represented in graphics is affected by the organizational tendencies and the limitations of the perceptual system, capacity constraints of the working memory, and knowledge stored in the memory system.
Socio-technological aspects of assessment and management of educational risks at University

The authors analyze social technological aspects of managing educational risks at a university, which help management make decisions that positively affect the level of educational services and competitiveness. This article highlights systemic nature and features of risk management at a modern university. The authors show the variety of educational risks and classify them by type. The definition of educational risks should be based, first of all, on the criteria for the quality of education of a university, based on external and internal goals determined by the state, consumers of services and a university. Management of external and internal risks determines an image and rating of a university, thereby ensuring its own competitiveness in the market of educational services. According to the authors, risk management planning should begin not only with identification of possible risks, but also with identification of the entire complex of risk factors. Management should take into account internal risks generated by a university, which affect external risks that either level or exacerbate them. They provide a simplified diagram of a model for assessing and managing educational risks at a university.