Reviewerly/exHarmony huggingface dataset:
Exploring real domain problems on the second generation neural network

This paper presents a competitive performance of second generation neural network (CVNN) on the two dimensional space over first generation neural network (RVNN) on single dimensional space. The real datasets problems are selected for proposed research work. The second-generation neural network is based on the theory of complex number. Complex numbers are forms of subset of real numbers having magnitude and phase to represent a real valued phenomenon. For the testing and training of real valued problems in complex domain, a mathematical approach Hilbert transformation is used to convert all the real valued data in complex form by sifting the phase by ±90 degree with same amplitude. For learning the network RBP and CBP algorithm is used over proposed benchmark datasets (both real and complex) to train the neural network. A new complex activation function (amplitude and phase type) is utilising by second generation neural network (CVNN). The results show improved efficacy and minimum number of learning cycles for Second generation neural network in complex domain over the first generation neural network in real domain.
A Study on Improving Classroom Heads-Up Rate of "Ship Structural Mechanics" Based on Multifactorial Influence

Traditional teaching methods have been unable to meet the basic requirements of teaching in the new situation, triggering the classroom phenomenon of low head-up rate. This paper starts from the fundamental, from the teaching mode to the treatment of teaching materials, and then from the cognitive process to the teaching process for a reasonable analysis. Taking "Principle of Force Method" as an example, it focuses on the theme of rationally simplifying the mechanics model and designing the optimal structure, combines forward case and reverse inquiry, and reasonably integrates the elements of ideological and political into it, and analyses the teaching design and teaching process on the basis of it, which enhances the attractiveness, interestingness, logic, vividness and memorability of the course, and increases the head-up rate of the students.
Conditional Neural Network for Degraded Image Generation through Atmospheric Turbulence

We propose a conditional neural network to generate degraded images through isoplanatic turbulence. This work establishes the initial baseline for future machine learning developments to generate degraded images through anisoplanatic turbulence.
Real-time wide-range light-field camera using aerial imaging

We propose a novel light-field camera that uses aerial images of objects and a lens array. The prototype camera can capture light rays of moving objects with an angular range greater than 30°.
Relationship Between Blend-Ratio of the Face Image and the Incident Angle for Spatial Blending of Aerial Images

This paper clarifies relationship between the blend-ratio of the blended face images in spatial blending optics using aerial imaging by retro-reflection and the incident angle of light rays at which each proportional aerial image can be observed.
Wechat Table Tennis Small Program Design and Application in College Table Tennis Courses

Objective: To design a WeChat table tennis small program, intensive combat, points ranking, social networking and other functions in one. In order to cope with the col-lective course teaching in the special course of table tennis in colleges and universities cannot meet the individual needs of stude
The Potential of Metaverse in Speaking Skills of English Education

The Metaverse, a three-dimensional (3D) virtual world network that includes social and economic interactions through virtual reality (VR) and augmented reality (AR) devices, has been recognized as a transformative concept in a variety of fields, including education. As technology advances at a rapid
A Study on the Development of IEET Accreditation in Mainland China

With the growing importance of professional accreditation in engineering education, the demand for IEET (Institute of Engineering Education Taiwan) professional accreditation services in mainland China is on the rise. Regrettably, no literature currently compiles and analyzes IEET's accreditation se
Research on the Reform of Trinity Cooperative Teaching Mode in the Vocational Training

The implementation of multi-cooperative teaching is an important way to promote ed-ucation reform and train high-quality innovative talents. In order to improve the teaching level and talent training quality in military academies, this paper refers to the cooperative teaching mode of industry-univer
The Relationship of Social Control and Self-Management to Online Game Addiction in Adolescents

Background: Online game is a very popular game, including among teenagers. Addiction to online games is caused by low self-management, as a result, adolescents put aside their responsibilities, and adolescents in their social life have means in the form of control to regulate behavior so that adolescent behavior has conformist boundaries. Social control is a process that educates the public to comply with prevailing social norms and values. Self-management is an attempt to plan, for the activities carried out by adolescents. The purpose of this study was to identify the relationship between social control and self-management toward online game addiction in adolescents at LKSA Widhya Asih Melaya. Methods: This study used a cross-sectional design. The population in this study were all teenagers who play online games living at LKSA Widhya Asih Melaya. The sample of this research is 53 respondents. This research uses probability sampling with a simple random sampling technique. Data analysis was performed using univariate and bivariate analysis. Results: This study found the results of the analysis of social control on online game addiction in adolescents with a correlation coefficient (r) of 0.709, where r count &gt; r table (0.000) and p-value = 0.000 (p &lt;0.25) and the results of self-analysis management of online game addiction in adolescents correlation coefficient (r) of 0.454, where r count &gt; r table (0.000) and p-value = 0.001 (p &lt;0.25). Conclusion: There is a relationship between social control and self-management towards online game addiction in adolescents at LKSA Widhya Asih Melaya.
First-Year Students' Satisfaction by E-Learning

Universities around the world have been using electronic learning systems more and more in recent years. Due to the Covid-19 pandemic, Mongolian universities are changing the way of teaching online and thus starting from the second semester of the 2019-2020 academic year. The purpose of this study is to investigate the satisfaction of students towards e-learning and the factors affecting it.&#x0D; 321 first-year students of the School of Nursing of NUMS participated in this survey, the survey questionnaire filled in Google form, and received by electronically. The relationship between satisfaction and its influencing factors was evaluated by using the Pearson test (correlation coefficient).&#x0D; According to the indicators of the research results, students' satisfaction is the most satisfied with learning materials (4.16), student engagement (4.15), and the lowest with e-educational technology (3.25). Due to this, there is a didactic need to improve the quality of e-learning and to update the lesson technology.&#x0D; Students' satisfaction level had a direct strong positive correlation (r=0.65) with grade (r=0.65) and a weak direct positive correlation (r=0.38) with lesson access (p&lt;0.001), and e-learning satisfaction scores had a direct correlation (p&lt;0.001) to the quality of teaching, supply of learning materials, assessment, and student engagement.
On the structure of some arcs related to caps and the nonexistence of some optimal codes

In this paper we solve two instances of the main problem in coding theory for linear codes of dimension 5 over $\mathbb{F}_4$. We prove the nonexistence of $[395,5,295]_4$- and $[396,5,296]_4$-codes which implies the exact values $n_4(5,295)=396$ and $n_4(5,296)=397$. As a by-product, we characterize the arcs with parameters $(100,26)$ in $PG(3,4)$.
Resonances of the Global Sanitary Crisis on the Development of Cloud Accounting. The Impact on the Accounting and Tax Fields (I)

The effects on the economy generated by the global sanitation crisis that the whole humanity recently went through prove to be unprecedented. By means of the work hereby, we aim to outline the conceptual and pragmatic universe with regard to the impact created by the speed-up of accounting digitalization under the effect of technological changes occurred following the sanitation crisis. Thus, the research implies three stages: the description of the business digitalisation framework in terms of the implementation of modern technologies in its processes, succeeded by the adoption of cloud technology at the level of the financial-accounting department and completed with the impact of cloud phenomenon regarding the digitalization of several issues related to the taxation of processes within the companies. After following these steps, the results of the research are logically correlated with the unquestionable speed-up of business processes digitalization as a result of the crisis generated by COVID-19, an issue which determines a shift in the interest of the accounting area towards cloud accounting, facilitating the transition of phenomena corresponding to fiscality in cloud mode in view of simplifying the collaboration between entities and state institutions. The research methods used for the purpose of fulfilling the work’s objective are the review of specialty literature, the analysis, synthesis and comparison, techniques assigned to bibliometrics.
Innovative Teaching Methodology for Developing Digital Competence in Future Engineering Pedagogues

This article focuses on the development of a methodology aimed at fostering the digital competence of future engineering pedagogues through the utilization of digital tools. With the digital transformation of the education system, it becomes imperative to adapt the methods of working with educational stakeholders. The creation of a digital educational environment involves equipping organizations with modern equipment and advancing digital services and content. Future engineering pedagogues require digital competencies to effectively integrate digital technologies into the educational process. This article presents a concept for the methodology, which involves the design of practical tasks at three levels: basic, intermediate, and advanced. The results of an experiment conducted with students demonstrate that the proposed methodology yields higher grades compared to traditional methods. The findings underscore the importance of empowering engineering pedagogues with digital competences to prepare students for the digital era.
MERGERS AND ACQUISITIONS INVESTMENTS OF THE GREEK SYSTEMIC BANKS DURING THE LAST 20 YEARS. A FINANCIAL ANALYSIS

The banking system of any country is the engine for the development of the national economy. The purpose of this dissertation is the analysis through the use of numerical indicators of the financial situation of the four largest Greek banks (National Bank of Greece, Alpha Bank, EFG Eurobank Ergasias, Piraeus Bank) and their evaluation for the period 2003-2021. This period is critical, as it includes years before and after Greece's entry into the financial crisis. Therefore, the present analysis and its results are very important for the viability and future of Greek banks, especially in the current conditions of uncertainty.This paper is an attempt to analyze and evaluate the investment activity of Greek banks through the mergers and acquisitions that they carried out in the last decade after the advent of the euro, i.e. before and after the financial crisis, which invaded Greece essentially in the year 2010&#x0D; Keywords: Banks, Investments, Mergers and Acquisitions, Financial Ratios.&#x0D; JEL classification: G21, G33, G34.
A Model of an Automated System for Evaluating the Quality of Startups in the Field of Software Engineering

This article introduces an automated system for evaluating startups in the field of Software Engineering. It outlines the system's components, including database management, expert assessments, and project viability estimation. The article also presents a conceptual database model and discusses the user interface for assessment calculations. The system is designed to enhance the evaluation of Software Engineering startups and holds potential applications in various scenarios.
Der dritte Mann der Aufklärung

Abstract The article focusses on a conceptual gap concerning the technical activities of artisans whom we would call today engineers during the Age of Enlightenment. Research has not yet been able to fill this discursive gap systematically, which is located between science and craft. This article will first identify this lacunae and then contribute to further differentiating how knowledge was constructed at that time. It then explores the examples of the discourses surrounding the first balloon flights (after 1783) and the pioneers of aviation, above all the little-appreciated »showman« Jean-Pierre Blanchard, as well as Christian Wolff’s concept of a third man, an early notion of the modern engineer from the spirit of the enlightenment itself. Finally, an analysis of Jean Paul’s tale Das Kampaner Tal (1797) will be presented as a poetic adaptation of the discursive connection between technics and religion.
$$\textbf{E}^{3}$$-MG: End-to-End Expert Linking via Multi-Granularity Representation Learning

Expert linking is a task to link any mentions with their corresponding expert in a knowledge base (KB). Previous works that focused on explicit features did not fully exploit the fine-grained linkage and pivotal attribute inside of each expert work, which creates a serious semantic bias. Also, such models are more sensitive to specific experts resulting from the isolationism for class-imbalance instances. To address this issue, we propose $$\mathbf {E^{3}}$$ -MG (End-to-End Expert Linking via Multi-Granularity Representation Learning), a unified multi-granularity learning framework, we adopt a cross-attention module perceptively mining fine-grained linkage to highlight the expression of masterpieces or pivotal support information and a multi-objective learning process that integrates contrastive learning and knowledge distillation method is designed to optimize coherence between experts via document-level coherence. E $$^3$$ -MG enhances the representation capability of diverse characteristics of experts and demonstrates good generalizability. We evaluate E $$^3$$ -MG on KB and extern datasets, and our method outperforms existing methods.
Machine Unlearning with Affine Hyperplane Shifting and Maintaining for Image Classification

Machine unlearning enables a well-trained model to forget certain samples in the training set while keeping its performance on the remaining samples. Existing algorithms based on decision boundary require generating adversarial samples in input space in order to obtain the nearest but incorrect class labels. However, due to the nonlinearity of the decision boundary in input space, multiple iterations are needed to generate the adversarial samples, and the generated adversarial samples are affected by the bound of noise in adversarial attack, which greatly limits the speed and efficiency of unlearning. In this paper, a machine unlearning method with affine hyperplane shifting and maintaining is proposed for image classification, in which the nearest but incorrect class labels are directly obtained with the distance from the point to the hyperplane without generating adversarial samples for boundary shifting. Moreover, knowledge distillation is leveraged for boundary maintenance. Specifically, the output of the original model is decoupled into remaining class logits and forgetting class logits, and the remaining class logits is utilized to guide the unlearn model to avoid catastrophic forgetting. Our experimental results on CIFAR-10 and VGGFace2 have demonstrated that the proposed method is very close to the retrained model in terms of classification accuracy and privacy guarantee, and is about 4 times faster than Boundary Shrink.
TransCenter: Transformer in Heatmap and a New Form of Bounding Box

In current heatmap-based object detection, the task of heatmap is to predict the position of keypoints and its category. However, since objects of the same category share the same channel in the heatmap, it is possible for their keypoints to overlap. When this phenomenon occurs, existing heatmap-based detectors are unable to differentiate between the overlapping keypoints. To address the above issue, we have designed a new heatmap-based object detection model, called TransCenter. Our model decouples the tasks of predicting the object category and keypoint position, and treats object detection as a set prediction task. We use a label assignment strategy to divide the predicted sets into positive and negative samples for training. The purpose of this is to allow different objects to have their own heatmap channel without sharing with other, thereby completely eliminating the occurrence of overlapping. To make the model easier to learn, we leverage the characteristic that heatmaps can reduce the solution space, proposed a novel approach for predicting bounding boxes. We use the encoder-decoder structure in transformers, treat the prediction of bounding boxes as an encoding task, use the form of a heatmap to represent the position and size. Then, we treat category prediction and offset prediction of the bounding box as decoding tasks, where the offset prediction is outputted through regression.
Decoupling Style from Contents for Positive Text Reframing

The positive text reframing (PTR) task, where the goal is to generate a text that gives a positive perspective to a reader while preserving the original sense of the input text, has attracted considerable attention as one of the natural language generation (NLG). In the PTR task, large annotated pairs of datasets are not available and would be expensive and time-consuming to create. Therefore, how to interpret a diversity of contexts and generate a positive perspective from a small size of the training dataset is still an open problem. In this work, we propose a simple but effective Framework for Decoupling the sentiment Style from the Contents of the text (FDSC) for the PTR task. Different from the previous work on the PTR task that utilizes Pre-trained Language Models (PLM) to directly fine-tune the task-specific labeled dataset such as Positive Psychology Frames (PPF), our FDSC fine-tunes the model for the input sequence with two special symbols to decouple style from the contents. We apply contrastive learning to enhance the model that learns a more robust contextual representation. The experimental results on the PPF dataset, show that our approach outperforms baselines by fine-turning two popular Seq2Seq PLMs, BART and T5, and can achieve better text reframing. Our codes are available online ( https://github.com/codesedoc/FDSC ).
PROBLEMS OF HUMANISM IN THE WORKS OF YU.A. ZHDANOV

The article actualizes the humanistic pathos of the legacy of the prominent scientist, educator Yuri Andreevich Zhdanov, known as the rector of Rostov State University. In his works, great attention is paid to the problem of humanism and the education of the younger generation. Culture as a technology of human activity is the basis of upbringing, education and production of scientific knowledge. The scientist foresaw that culture is the sphere that is affected from the outside. And it is she who is the defining "core", thanks to which societies preserve themselves. All natural science and humanities nourish culture with their ideas, thereby determining the value vector of civilizations.
FEGI: A Fusion Extractive-Generative Model for Dialogue Ellipsis and Coreference Integrated Resolution

Dialogue systems in open domain have achieved great success due to the easily obtained single-turn corpus and the development of deep learning, but the multi-turn scenario is still a challenge because of the frequent coreference and information omission. In this paper, we aim to quickly retrieve the omitted or coreferred expressions contained in history dialogue and restore them into the incomplete utterance. Jointly inspired by the generative method for text generation and extractive method for span extraction, we propose a fusion extractive-generative dialogue ellipsis and coreference integrated resolution model(FEGI). In detail, we introduce two training tasks OMIT and SPAN to extract missing semantic expressions, then integrate the expressions obtained into the decoding initial and copy stages of the generative model respectively. To support the training tasks, we introduce an algorithm for secondary reconstruction annotation based on existing publicly available corpora via unsupervised technique, which can work in cases of no annotation of the missing semantic expressions. Moreover, We conduct dozens of joint learning experiments on the CamRest676 and RiSAWOZ datasets. Experimental results show that our proposed model significantly outperforms the state-of-the-art models in terms of quality.
Strategi Dakwah Ustadz Muslim Siregar Upaya Meningkatkan Pengetahuan Dan Pengalaman Ibadah Shalat

The main problem of this research is how the strategy used by Ustadz Muslim Siregar in Efforts to Build Application Data and Practices in the City of Gunung Tua Tumbu Jati. The problem in this proposition is to look at the method used by Ustadz Muslim Siregar With the Final Purpose of Growing Data and Application Practices for the Environment of Gunung Tua Tumbu Jati City. The type of investigation used by the maker is field research with an expressive abstract philosophy, the data grouping used is affirmation, collection, and documentation. The result of the assessment is Ustadz Muslim Siregar's Dakwah, explicitly by moving recitations where Ustadz Muslim Siregar uses 3 philosophies of da'wah namely Wise methodology (Al-manhaj-'athifi) offering direction in a sensitive way, a wise framework (Al-Manhaj Al-' Aqli) giving questions and answers to people who really don't sort out the material presented, material strategy (Al-manhaj al-'alhissi) by giving examples in daily attendance, for example coming to the mosque before starting the recitation time, welcoming neighbors ask, study dhikr.