Reviewerly/exHarmony huggingface dataset:
Adversarial Graph Disentanglement With Component-Specific Aggregation

A real-world graph has a complex topological structure, which is often formed by the interaction of different latent factors. Disentanglement of these latent factors can effectively improve the robustness and expressiveness of the node representation of a graph. However, most existing methods lack consideration of the intrinsic differences in relations between nodes caused by factor entanglement. In this paper, we propose an <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>A</b></u> dversarial <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>D</b></u> isentangled <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>G</b></u> raph <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>C</b></u> onvolutional <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><b>N</b></u> etwork (ADGCN) for disentangled graph representation learning. To begin with, we point out two aspects of graph disentanglement that need to be considered, i.e., micro-disentanglement and macro-disentanglement. For them, a component-specific aggregation approach is proposed to achieve micro-disentanglement by inferring latent components that caused the links between nodes. On the basis of micro-disentanglement, we further propose a macro-disentanglement adversarial regularizer to improve the separability among component distributions, thus restricting the interdependence among components. Additionally, to reveal the topological graph structure, a diversity-preserving node sampling approach is proposed, by which the graph structure can be progressively refined in a way of local structure awareness. The experimental results on various real-world graph data verify that our ADGCN obtains more favorable performance over currently available alternatives. The source codes of ADGCN are available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/SsGood/ADGCN</uri> .
Deployment Optimization of Intelligent Wireless Sensor Network Using Graph Similarity Based on Multi-Granularity Cross Representation and Matching

Intelligent wireless sensor networks often face challenges such as redundancy and non-uniform deployment of sensor nodes, which can negatively impact monitoring performance and energy consumption. To address these challenges, we propose a novel method for identifying the sensor nodes that contribute the most to the monitoring quality of the network. It utilizes graph topology to transform the contribution weights of sensor nodes into the similarity of perturbation-based graphs. And we propose a multi-granularity cross representation and matching method to predict graph similarity, which consists of two stages: representation and matching. In the representation stage, we generate rich multi-granularity interaction features between graph pairs. In the matching stage, we integrate these features into higher-order and more abstract matching features for similarity prediction. To further evaluate the contribution weights of sensor nodes, we combine the obtained graph similarities with the weighted PageRank algorithm. The experimental results demonstrate that our algorithm effectively selects the nodes with greater contribution, leading to good monitoring quality and network performance. Moreover, compared with classical deployment optimization algorithms, the nodes selected by our algorithm are more representative.
PHAED: A Speaker-aware Parallel Hierarchical Attentive Encoder-Decoder Model for Multi-turn Dialogue Generation

This paper presents a novel open-domain dialogue generation model emphasizing the differentiation of speakers in multi-turn conversations. Differing from prior work that treats the conversation history as a long text, we argue that capturing relative social relations among utterances (i.e., generated by either the same speaker or different persons) benefits the machine capturing fine-grained context information from a conversation history to improve context coherence in the generated response. Given that, we propose a Parallel Hierarchical Attentive Encoder-Decoder (PHAED) model that can effectively leverage conversation history by modeling each utterance with the awareness of its speaker and contextual associations with the same speaker's previous messages. Specifically, to distinguish the speaker roles over a multi-turn conversation (involving two speakers), we regard the utterances from one speaker as responses and those from the other as queries. After understanding queries via hierarchical encoder with inner-query and inter-query encodings, transformer-xl style decoder reuses the hidden states of previously generated responses to generate a new response. Our empirical results with three large-scale benchmarks show that PHAED significantly outperforms baseline models on both automatic and human evaluations. Furthermore, our ablation study shows that dialogue models with speaker tokens can generally decrease the possibility of generating non-coherent responses.
PatchMatch Stereo - Cross Dynamic Windows Based on Textured Bithreshold Rule

Disparity maps are calculated based on stereo matching algorithms, with the key to the design of cost aggregation windows. PatchMatch stereo adopts the idea of slanted planes and iterative propagation, therefore it often achieves good results in weak and untextured regions, however requires a large aggregation window and time. This paper presents an adaptive window, through high and low textured double threshold and cross-arm search, to obtain a suitable dynamic window for each pixel. The problem of no texture in the small window and high texture matching error in large window is solved by effective segmentation of different regions of the image, and it obviously improves the calculation speed when the disparity map accuracy is largely consistent.
Deep Reinforcement Learning Approach Based Grammatical Error Correction

Abstract Natural Language Processing (NLP) is a field of study that focuses on the interaction between computers and human language. It encompasses various techniques and methodologies aimed at enabling machines to understand, interpret, and generate human language text or speech. NLP plays a crucial role in many applications, including machine translation, sentiment analysis, information retrieval, and Grammatical Error Correction (GEC). Grammatical Error Correction (GEC) is an important task in natural language processing that aims to automatically correct errors in written text. It involves detecting and correcting errors related to grammar, syntax, spelling, punctuation, and other linguistic aspects. However, existing study is solely based on classical machine learning and deep learning methods for GEC. This study proposes a new approach using a DQN model and leverages the C4_200M dataset to automate the GEC process. The main goal of this study is to optimize the selection of action-value function (Q-function) and train a DRL model for automatic grammatical error correction and set baseline results using reinforcement learning (RL) techniques. Findings show that the proposed DQN model outperformed machine learning and rule‑based techniques.
THE VARIANTS OF COMMUNICATION MODEL "MAN-PAPPET" EXISTENCE IN THEATRE AND MUSEUM CULTURAL PRACTICES

Relevance of the study. The museum is the place where information turns into a system of codes, signs and symbols, and any thing, getting in our hands, enters into dialogue with us. Main objectives of the study: to trace the dynamics and transformation of the communication model "Man-doll" in the museum space. Methodology: observation, comparative, analytical, structural-functional, hermeneutic. Results: This article is the result of the author's research in the field of theatrical art, collecting theatrical objects (theatrical doll). As a result of our research, we came to the following conclusion: a doll is a universal cultural artifact that exists in different cultural practices: play, therapeutic classes, collections of private and public collections, and of course in the space of the theater. A museum is the place where information turns into a system of codes, signs and symbols, and any thing that falls into the hands enters into a dialogue with us. Scientific novelty: the study was tested in the international project GameHub, the purpose of which was to create interactive dolls, computer heroes and, subsequently, the development of a game scenario to solve conflict situations in the educational process, to improve the quality of education. Analysis of scientific sources. We managed to reveal all aspects of this: Semiotics questions (Lotman); problems of cooperation and communication (J.Habermas); the nature of the doll as an artifact and the possibilities of its use in different cultural spaces -cinema, theater (Vasilkova A);); discussion of the doll as things (Miroslav Petrzhichek, Jan Pyatochka, E. Husserl); and also, looked at such authorities as therapeutic, psychological, Educational. Practical sig:nificance the main provisions and conclusions of the article can be used in scientific and pedagogical work, will be of interest to scientists, researchers from different fields of humanitarian science. This article is a result of the author's research in the sphere of theatre, collecting theatrical items (theatre puppet), that passed a test of the international project GameHub, which purpose was to create interactive puppets, computer heroes and, including the development of a game script for solving conflict situations in the educational process, for improving the quality of education. Conclusion: a pappet is a universal cultural artifact existing in various cultural practices: game, therapeutic activities, private and public collections, and of course in the theater space. Keywords: communication "man-pappet", a theatrical pappet as a text of culture, artifact, a thing in collections, cultural practices.
The mediating role of flow in the relationship between simulation design and simulation educational satisfaction in Korean nursing students: A cross-sectional study

Abstract Background In Korea, there has been recent interest in nursing simulation education. Although students may find simulation-based teaching techniques fresh and fascinating, it is important to assess students' satisfaction with these techniques beyond their novelty value. Flow, the state of absolute immersion in a specific activity, is an important ask of simulated learning. Therefore, this study examined the mediating effect of flow on the relationships between simulation design and simulation educational satisfaction. Method &amp; Materials: A cross-sectional study design was used. The participants of this study were 143 fourth-year nursing students who had participated in classes using simulations at three universities in Seoul, Daegu, and Jeonbuk. Data were collected from April 24 to May 3, 2023. Demographic data, simulation design scale, flow in simulation, and the educational satisfaction scale in simulation were collected via an online questionnaire. The data were analyzed using SPSS 25.0. Results Our results indicate that simulation design has a positive effect on flow and simulation educational satisfaction and flow has a positive effect on simulation educational satisfaction. Additionally, flow mediated the impact of simulation design on simulation educational satisfaction. Conclusion The significance of the current study lies in its confirmation of the link between simulation design and simulation educational satisfaction, as well as the mediating function of flow. Nursing students can achieve simulation educational satisfaction through simulation-based education if simulation educators follow best practices that improve flow through well-organized simulation design.
Why Convex Combination is an Effective Crossover Operation in Continuous Optimization: A Theoretical Explanation

When evolutionary computation techniques are used to solve continuous optimization problems, usually, convex combination is used as a crossover operation. Empirically, this crossover operation works well, but this success is, from the foundational viewpoint, a challenge: why this crossover operation works well is not clear. In this paper, we provide a theoretical explanation for this empirical success.
Distance Learning as A Strategic Priority of University Education

Distance learning is an active and technological method of education that significantly promotes self-discipline of the individual. That is, a set schedule of course instruction can build self-discipline and commitment. One of the advantages of distance learning is the availability of lessons and information over time.
The Educational Situation and Digital Technologies According to The International Commission on The Futures of Education of Unesco

This study analyzes the educational situation and digital technologies from the perspective of the UNESCO International Commission that was created in 2019. A content analysis has been carried out with the Atlas ti program, taking into account the problems, proposals or actions educational and technological within the context of COVID-19.
The Diachronic Change of Ren Rongrong’s Translation: A Corpus-based Research on Reduplication in His Chinese Translation of Children’s Literature

Based on a self-built corpus, a statistical and multidimensional comparative analysis is performed to determine the diachronic change in the application of reduplications in Ren’s five representative translated works for children literature (spanning 24 years) and relevant factors. The total number of reduplicated words in the five translated works showed a downward trend, as well as the frequency of AA and ANA. The frequency of ABB, ABAB, and AABB forms showed no obvious upward or downward trend but fluctuated significantly. The diversity and variation of the application of reduplication are not only related to the function of reduplicated words themselves but also influenced by the original text, translator, and readers.
Vocational education in a new format

The problems of vocational education that need to be overcome to ensure a new look of the Russian economy and the corresponding labor market are considered. The data on the personnel needs of the economy and the training of higher and middle-level specialists in vocational education organizations are presented. Noted a reduction in the training of the most popular category, namely workers. A proposal was made to create a State Committee for the training of mid-level personnel in the country. The necessity of revision of the education system taking into account the changed external world is shown, the purpose of the education system should change - education and training of a person who is able to find his place in a new, rapidly changing world. Attention is drawn to the decline in the interest of educational organizations in using the ideology of quality in training personnel for the modern economy.
The Garage Tapes

Exploring the sound of the parking garage in the building where I live, using cheap Casio electric keyboards, low end melodicas and a recorder. All instruments, electronic or not, have been played live in the garage as if they were purely acoustic instruments, making this an artistic exposition exclusively, intended to make people consider and reflect upon what can be done with humble instruments in the right sonic environment. Videos shot with an iPhone 5. No overdubs, mix, mastering or other tampering with the actual sound.
A path planning algorithm of intelligent transportation robot based on extended Kalman filter

Aiming at the problem of long calculation time and slow response speed of traditional intelligent transportation robot path planning algorithm, an intelligent transportation robot path planning algorithm based on extended Kalman filter is proposed. By analysing the relevant principles of optical flow localisation, aiming at the fact that a single optical flow sensor can not meet the needs of all application scenarios, multiple optical flow sensors are fused through extended Kalman filter, and the system model and observation model of intelligent transportation robot are established at the same time. The optical flow sensor is fixed on the intelligent transportation robot, the two-dimensional coordinates of the intelligent transportation robot are obtained in real time, and the moving path is planned. The results show that the proposed algorithm can reduce the operation time and improve the response efficiency.
Robust Path Planning Of Obstacle Avoidance For Unmanned delivery robot

Aiming at complex road conditions and difficult path planning of semi-structured roads in a park, a robust path planning method based on sequential quadratic programming (SQP) algorithm optimization is proposed. Firstly, an improved vector field histogram (VFH) algorithm is used to determine the optimal passable area, and then the determination method of the target state is given based on the optimal passable area; Secondly, according to a starting point and the target state, a description method of obstacle avoidance path is given based on a piecewise quadratic Bezier curve. Then, the problem of curve parameter optimization is established based on the vehicle running curvature constraint and the direction change margin constraint of the target point, and the SQP algorithm is used to optimize the curve parameters; Finally, the effectiveness and practicability of the proposed method are verified by simulation experiments and real vehicle experiments. Compared with other methods, this method has the shortest path and better robustness. DOI: 10.61416/ceai.v25i2.8595
An Automaton and Super-Twisting Sliding-Mode Control for Wall Following

This work proposes an approach for wall following with a differential drive robot in a polygonal environment using laser range finder measurements.We propose an automaton which manages the robot observationsand selects the control set-points according to the state in theautomaton. We also propose a super-twisting sliding-mode control whichrapidly reaches the control set-points.The approach allows the robot to continuously move without the need ofstopping when obstacles get in the path of the robot. Thisapproach allows the robot to following the walls fast and robustly.The wall following capability can be used to explore an unknown environment orto find objects in the environment. DOI: 10.61416/ceai.v25i2.8352
Blockchain and Freedom to Conduct a Business: Between Myth and Reality

Recent advances in technology have demonstrated the enormous flexibility of Distributed Ledger Technology (DLT), whose potential goes well beyond the cryptocurrency trading. This article explores the potential impact that the utilization of a permissioned blockchain could have on listed companies and how this could be an appropriate instrument for a more effective implementation of the provisions of the Shareholder Rights Directive II. This technological infrastructure could attest the correct formation of will within the shareholders’ meeting and contribute to the creation of a truly democratic space for the meeting and discussion among shareholders, thus allowing achievement of freedom to conduct a business. However, the most advanced use of blockchain technology has a disruptive effect and exposes us to the great danger of an “algocratic” drift. Therefore, this article analyses the main critical issues from both a technical and legal viewpoint of Decentralized Autonomous Organizations (DAOs).
Klasifikasi Gender Berdasarkan Fingerprint Menggunakan Metode Naive Bayes Classifier

No two fingerprints are identical, as everyone has their own characteristics. The most fundamental problem lies in the results of the fingerprint image, typically due to inconsistencies in the emphasis of the fingerprint and the position of the fingerprint, resulting in inconsistencies in the thickness of the black line and shifting positions, which negatively impact the overall performance of the system. To solve this issue, research is required on a classifier that assumes all attributes exist independently. The NBC (Naïve Bayes Classifier) is a classifier based on the assumption that all attributes are independent. The NBC method for gender classification based on fingerprints consists of three steps. The initial step is to evaluate the quality of the image to be processed. This is demonstrated by the consistency of the grayscale values, which are not skewed when converted to a binary image. The second is the selection of data that exhibits no data deviation, which also leads to errors in the classification procedure that follows. With the existence of machine learning, class-based measurement formulations can be acquired through training. Even with unbalanced data, it is preferable to use NBC for classification purposes.
Towards a Versatile Terminology Service for Empowering FAIR Research Data: Enabling Ontology Discovery, Design, Curation, and Utilization Across Scientific Communities

To fully harness the potential of data, the creation of machine-readable data and utilization of the FAIR Data Principles is vital for successful data-driven science. Ontologies serve as the foundation for generating semantically rich, FAIR data that machines can understand, enabling seamless data integration and exchange across scientific disciplines. In this paper, we introduce a versatile Terminology Service that supports various tasks, including discovery, provision, as well as ontology design and curation. This service offers unified access to a vast array of ontologies across scientific disciplines, encouraging their reuse, improvement, and maturation. We present a user-driven service development approach, along with a use case involving a collaborative ontology design process, engaging domain experts, knowledge workers, and ontology engineers. This collaboration incorporates the application and evaluation of the Terminology Service, as well as supplementary tools, workflows, and collaboration models. We demonstrate the feasibility, prerequisites, and ongoing challenges related to developing Terminology Services that address numerous aspects of ontology utilization for producing FAIR, machine-actionable data.
Perplexed by Idioms?

The aim of this study is to identify idiomatic expressions in English using the measure perplexity. The assumption is that idiomatic expressions cause higher perplexity than literal expressions given a reference text. Perplexity in our study is calculated based on n-grams of (i) PoS tags, (ii) tokens, and (iii) thematic roles within the boundaries of a sentence. In the setting of our study, we observed that no perplexity in the contexts of (i), (ii) and (iii) manages to distinguish idiomatic expressions from literals. We postulate that larger, extra-sentential contexts should be used for the determination of perplexity. In addition, the number of thematic roles in (iii) should be reduced to a smaller number of basic roles in order to avaiod an uniform distribution of n-grams.