Reviewerly/exHarmony huggingface dataset:
A Study on the Strategic Application of Semantic Segmentation Based on Improved Convolutional Neural Networks on English-Chinese Interaction

Teachers need to provide numerous examples sentences for students to translate in the process of teaching English, but the number of sentences given by teachers to practice subjectively is not enough. Therefore, the study constructs a text generation model using an improved convolutional neural network semantic segmentation method, where the corpus utterances are keyword extracted and new shorter utterances are generated based on the keywords for language learners to practice translation. The research first uses the textRank algorithm to extract semantic keywords to obtain a dataset, and then uses CNN to construct an encoder to achieve semantic encoding of the keyword dataset. However, during the research process, it was found that traditional CNN models are relatively sensitive to the location of input data. Therefore, the research introduces the idea of Decomposition Machine (FM) to improve the encoder. In order to control text generation, research has introduced a weighted additive attention mechanism in the decoding process to associate the meaning of the generated text sequence with the meaning of the keyword set. Based on this, a text generation model for generating a translation related corpus in English teaching is constructed. This results in a text generation model that can be used to generate a translation-linked corpus for English language teaching. The average BLEU value of model 1 is 0.924, Inform value is 98.40, the Success value is 97.64, and the Combine value is 101.24, which can achieve high-quality text generation by the keyword lexical meaning and provide technical guarantee for the establishment of the corpus in educating in English.
A Hybrid Continuous-Time Dynamic Graph Representation Learning Model by Exploring Both Temporal and Repetitive Information

Recently, dynamic graph representation learning has attracted more and more attention from both academic and industrial communities due to its capabilities of capturing different real-world phenomena. For a dynamic graph represented as a sequence of timestamped events, there are two kinds of evolutionary essences: temporal and repetitive information. At present, the temporal information of interactions (e.g., timestamps) have been deeply explored. However, as another vital nature of dynamic graphs, the repetitive information of interactions between two nodes is neglected, which may lead to inaccurate node representation. To address this issue, we propose a novel continuous-time dynamic graph representation learning model, which consists of a node-level-memory based module, a historical high-order neighborhood based vertical aggregation module and a repetitive-topological information based horizontal aggregation module. In particular, to characterize the evolving pattern of the repetitive information of interactions between a pair of nodes, we put forward a repetitive-interaction based attention mechanism to integrate the two key attributes (i.e., the content and the number of interactions) of repetitive interactions at different moments, based on the insight that the repetitive behaviors of nodes are widespread and essential. We conduct extensive experiments including future link prediction tasks (for transductive and inductive learning) and dynamic node classification task, and results on three real-life dynamic graph datasets demonstrate that the proposed method significantly outperforms state-of-the-art baselines, for both observed nodes and new ones.
Estimation of Impedance Features and Classification of Carcinoma Breast Cancer Using Optimization Techniques

Breast cancer is the most prevalent form of cancer and the primary cause of cancer-related mortality among women globally. Breast cancer diagnosis involves multiple variables, making it a complex process. Therefore, the accurate estimation of features for diagnosing breast cancer is of great importance. The present study used a dataset of 21 patients with carcinoma breast cancer. Polynomial regression analysis was used to non-invasively estimate six impedance features for the diagnosis of breast cancer, including the phase angle at 500 KHz (PA500), impedance distance between spectral ends (DA), area normalized by DA (A/DA), maximum of the spectrum (Max IP), the distance between impedivity (ohm) at zero frequency and the real part of the maximum frequency point (DR), and length of the spectral curve (P). The results indicated that the polynomial degrees needed to estimate the PA500, DA, A/DA, Max IP, DR, and P features based on tumor size were 2, 2, 3, 3, 2, and 2, respectively. Additionally, we utilized a nonlinear constrained optimization (NCO) analysis to calculate the eight threshold levels for the classification of the impedance features. The deduction of eight classifications for each feature may also be an effective tool for decision-making in breast cancer. These findings may help oncologists to estimate the impedance features for breast cancer diagnosis non-invasively.
Instance Segmentation of Irregular Deformable Objects for Power Operation Monitoring Based on Multi-Instance Relation Weighting Module

Electric power operation is necessary for the development of power grid companies, where the safety monitoring of electric power operation is difficult. Irregular deformable objects commonly used in electrical construction, such as safety belts and seines, have a dynamic geometric appearance which leads to the poor performance of traditional detection methods. This paper proposes an end-to-end instance segmentation method using the multi-instance relation weighting module for irregular deformable objects. To solve the problem of introducing redundant background information when using the horizontal rectangular box detector, the Mask Scoring R-CNN is used to perform pixel-level instance segmentation so that the bounding box can accurately surround the irregular objects. Considering that deformable objects in power operation workplaces often appear with construction personnel and the objects have an apparent correlation, a multi-instance relation weighting module is proposed to fuse the appearance features and geometric features of objects so that the relation features between objects are learned end-to-end to improve the segmentation effect of irregular objects. The segmentation mAP on the self-built dataset of irregular deformable objects for electric power operation workplaces reached up to 44.8%. With the same 100,000 training rounds, the bounding box mAP and segmentation mAP improved by 1.2% and 0.2%, respectively, compared with the MS R-CNN. Finally, in order to further verify the generalization performance and practicability of the proposed method, an intelligent monitoring system for the power operation scenes is designed to realize the actual deployment and application of the proposed method. Various tests show that the proposed method can segment irregular deformable objects well.
Tools at the Service of Public Administrations to Fight Digital Gender Inequalities

This article seeks to highlight how the emergence of the information society and, with it, the New Information and Communication Technologies, despite their benefits, have also brought with them important challenges in the fight against gender discrimination. Moreover, after their consolidation, we can speak of a new digital gender gap that has certainly been intense in rural environments, which are particularly disadvantaged in the implementation of virtual reality. For this reason, mechanisms are established to fight against this new form of discrimination, which should be articulated primarily by the Public Administrations as guarantors of equality among all citizens and the fight for the satisfaction of the general interest, which should only result in the well-being of all. Consequently, the paper begins with a brief introduction that highlights the current context and then goes on to highlight the regulatory guidelines for achieving gender equality in the field of the information society, as well as some relevant initiatives carried out by public bodies, concluding with possible measures to be adopted by the Administrations in favour of gender equality in the digital environment, in which, together with the legal provisions, several public initiatives in favour of the integration of women in the digital environment will also be taken into consideration, trying to reduce digital gender gaps, highlighting, in this respect, the IV Plan for Equal Opportunities between Women and Men 2003-2006 or, of course, the most recent and current, III Strategic Plan for the Effective Equality of Women and Men 2022-2025.
Semantic Knowledge-Based Hierarchical Planning Approach for Multi-Robot Systems

Multi-robot systems have been used in many fields by utilizing parallel working robots to perform missions by allocating tasks and cooperating. For task planning, multi-robot systems need to solve complex problems that simultaneously consider the movement of the robots and the influence of each robot. For this purpose, researchers have proposed various methods for modeling and planning multi-robot missions. In particular, some approaches have been presented for high-level task planning by introducing semantic knowledge, such as relationships and domain rules, for environmental factors. This paper proposes a semantic knowledge-based hierarchical planning approach for multi-robot systems. We extend the semantic knowledge by considering the influence and interaction between environmental elements in multi-robot systems. Relationship knowledge represents the space occupancy of each environmental element and the possession of objects. Additionally, the knowledge property is defined to express the hierarchical information of each space. Based on the suggested semantic knowledge, the task planner utilizes spatial hierarchy knowledge to group the robots and generate optimal task plans for each group. With this approach, our method efficiently plans complex missions while handling overlap and deadlock problems among the robots. The experiments verified the feasibility of the suggested semantic knowledge and demonstrated that the task planner could reduce the planning time in simulation environments.
Study on the Remunerations for National University Professors

교육기본법, 교육공무원법, 그리고 교원의 지위 향상 및 교육활동 보호를 위한 특별법에서는 교원의 보수를 우대하여야 한다고 규정하고 있다. 그러나 현실적으로 국립대학 교원의 보수는 우대되고 있지 아니하다. 국립대학 교원의 보수는 연봉, 수당, 그리고 교육·연구 및 학생지도비(교연비)로 구성되며, 교연비는 다음과 같은 문제점을 가지고 있다. 첫째, 인건비가 아닌 사업비로 책정되어 교원의 통상업무인 교육·연구 및 학생지도 활동 외에 별도의 교육·연구 및 학생지도 “사업”을 수행하여야 한다. 둘째, 일반적 교육을 받는 모든 학생들이 납부하는 수업료 재원으로 일반적 교육이 아닌 별도의 사업비용을 충당한다. 셋째, 교육공무원법에서 위임한 각종 수당에 대한 규정을 대통령령에서 반영하고 있지 않다. 넷째, 지급기준이 불명확하여 각 대학마다 상이한 수준의 교연비를 지급하고 있다. 다섯째, 직접적으로 교육․연구 및 학생지도를 하지 않는 직원과 조교에게도 교연비가 지급되고 있다. 여섯째, 교육·연구 및 지도의 대상이 되는 학생이 교원의 성과를 심의하고 있다. 따라서 정부에서는 기형적인 교연비 제도를 폐지하고, 교육공무원법에 따라 국립대학 교원들에게 특별수당, 연구수당, 교직수당을 지급하도록 공무원보수규정을 개정하여야 한다. According to Educational Officials Act and Special Act for the Improvement of Teachers’ Status and the Protection of their Educational Activities, the remunerations for National University Professors need to be favorable. However, the laws are inconsistent with realities. The Teaching, Researching, and Student Counseling Allowance (TRSC) of professors at national universities are rife with the following problems. First, TRSC is not a wage but extra working expenses. Second, common students pay extra working expenses. Third, the presidential decree has no guidelines about various extra pays delegated by Educational Officials Act. Forth, each university pays a different TRSC because of the ambiguity of the payment standard. Fifth, national universities pay TRSC to the staffs and assistants who do not teach, research, and counsel student. Sixth, students having no experience in teaching and researching evaluate the TRSC performance of professors. In conclusion, I recommend that the government should abolish TRSC and pay research and teaching allowances by amending the Public Officials Remuneration Regulations.
A Transfiguration Paradigm for Quest Design

Quest design is an important design aspect of video games. The current approach to quest design is dominated by a task-orientated paradigm in which a quest is viewed as a series of tasks to be completed as part of the narrative structure of the game. This paper presents an alternative paradigm that shifts away from the predominant task-based approach to quest design. Based on a study of existing quest models, a dual quest framework of singular and synergy quests is proposed. Within the frameworks, tasks become an intermediary step within the quest which is now focused on the transfiguration of the player character. This approach offers a practical design structure for both procedural and manual quest design.
Communication and Coordination Issues in Managing Distributed Scrum Teams

Software development companies have progressively been experiencing the need to migrate their traditional development processes to agile environments. Several frameworks have emerged that support this paradigm, and Scrum is one of the most widely adopted on a global scale. However, Scrum was originally designed to work in small, local team environments. The challenge lies in designing its adoption in large-scale environments with geographically distributed teams. This chapter seeks to explore this challenge by identifying communication and coordination issues that may arise when adopting distributed Scrum. Three case studies are considered to allow comparison of different approaches considering structural and contextual factors associated with each organization.
Virtual currencies and money laundering: existing and prospects for jurisdictions that comprehensively prohibited virtual currencies like Pakistan

Purpose This study aims to examine the Financial Action Task Force’s recommendations on virtual currencies (VCs) and how Pakistan has responded to them. Design/methodology/approach Qualitative document and jurisprudence analysis techniques were used to achieve the study’s goal. Findings According to this study, VCs are modern FinTech that no jurisdiction can ignore. However, Pakistan has not adopted regulations to govern VCs but comprehensively prohibits their use. It is primarily due to the apathy of various regimes and regulators. Furthermore, the geographical location, undocumented economy and rampant corruption could facilitate the abuse of VCs for money laundering. Originality/value This study has provided a significant overview for developing regulations for VCs in Pakistan and other developing jurisdictions with the same characteristics.
Proposal for effective Operation of Liberal Science Education in University－Focusing on case studies of 〈University Basic Physics〉 and 〈Introduction to Natural Science〉

With the development of modern science in the era of the 4th industrial revolution, the necessity of science education is in more demanded than even for cultivating convergent human resources to meet the needs of the times and for understanding science at the liberal arts level. Liberal science education is essential for all college students in order for them to achieve any level of prosperity in a society that so steeped in science and technology, as is our current, modern society. However, It is an important issue for us to consider whether or not the liberal arts enhances science and scientific literacy. In this study, the necessity of liberal science education in the era of the 4th industrial revolution was examined, and the case studies of basic science and integrated science education were studied for a more effective educational experience of university liberal arts students. The course content and class operation method of &lt;the basic physics&gt;and &lt;introduction to natural science&gt; were reviewed. Also, the distribution of the grades of students majoring in science and engineering, as wlee as those of non-science majors, were analyzed, along with the contents of questionnaires and course evaluation results. Through the operation results of the two subjects, the operation methods of classes are checked to examine the problems and to come up with some improvements for liberal sciences education. For more effective liberal sciences education in university, it is suggested that liberal sciences classes should be operated by dividing students into science and engineering departments and non-science departments according to their majors.
Exploring the Use of the Metaverse in Liberal Arts Education

The purpose of this study is to investigate the educational applications of the metaverse and to gather empirical data on its uses. The metaverse encompasses various types applications, such as augmented reality, life logging, a mirror world, and a virtual world. Many universities have already incorporated or are planning to introduce the metaverse into their curricula or non-curricular events. In conclusion, metaverse literacy is becoming increasingly important in liberal arts education, and in order for instructors to effectively use these tools in their classes, it is necessary for them to employ a variety of platforms as motivational tools.
An Analysis of Error Aspects in the Discussions of University Freshmen

My study analyzed and considered the error patterns that appear in discussion classes for university freshmen, focusing on their papers and discourse for discussion. Debate is the activity of asking and answering questions regarding the justification for an argument. The conclusion and the ground, or the basis for supporting a certain conclusion, constitute an argument. The conclusion is well justified when the ground supports the conclusion well, is acceptable, and contains content that can answer the counterargument. Therefore, whether or not the arguments in any given discussion were erroneous was analyzed on the basis of the acceptability, relevance, and sufficiency of the aforementioned grounds. A wide range of discussion errors appeared in both the composition and presentation level of the argument, and the process of asking and answering the reason by constructing the argument. In particular, I often found that grounds unrelated to the conclusions were presented by ‘begging the question’, ‘appealing to the majority’, or simply by confusing the meaning of the concept. In addition, errors were found that provided grounds which were difficult to accept or provided grounds which did not sufficiently support the conclusions. My analysis of error patterns found in discussions is significant for providing a basis for discussion classes in universities which apply various thinking experiments in order for us to move in the direction of expanding the depth and breadth of our students' thoughts.
A Study on the Current State and Adaptation of the Cross-entry Students between the Field of Liberal Arts and Science －Focusing on the case of S University

University admission through cross-entry admission is active and expected to accelerate further. However, due to this, it is expected that more students will drop out due to maladaptation to their department. Accordingly, universities must prepare systematic management, including the academic counseling necessary for students entering the Liberal Arts and Sciences Cross Application. Therefore, the purpose of this study is to identify the current status of cross-application and the needs of cross-entry students in 2021 and 2022 at S University. Academic counseling was planned and conducted to help students‘ academic achievement and school adaptation. Primary research was conducted to help students with liberal arts and science cross-entry status to have a successful college life. First, in the 2021 school year, most of the cases involved students who completed liberal arts courses in high school and had applied to university science courses for reasons that were advantageous for employment. On the other hand, in the 2022 school year, science majors in high school applied to the field of liberal arts for reasons of admission to universities with a higher pass estimate. Second, among the 2021 cross-entry students who entered the science field, there was a phenomenon in which female students cross-applied again to the liberal arts field in 2022. Third, in terms of satisfaction with the department entered, compared to students enrolled in 2021, the satisfaction level of students enrolled in 2022 was lower at a statistically significant level, indicating that students who cross-applied for liberal arts have greater difficulty adapting to their department than students who cross-apply for science. This shows that the combined test for cross-application among liberal arts and science students can cause difficulties in their adaptation to college. This study sought and suggested alternatives for successful college adaptation for newly admitted students who requested academic counseling. This study also serves as primary research for universities to better help them understand and prepare their cross-application entrance exams.
Effective Management Plan of Group Activities in College Liberal Arts Classes

In the 2010s, universities recognized the limitations of lecture-oriented teaching methods and are expanding the educational method in which students actively participate in learning. Although the educational effects of small group activities such as improving one’s communication ability, one’s problem-solving ability, and one’s interpersonal competency have been proven, learners have many complaints about such teaching methods. This study intends to investigate how learners perceive group activities that are conducted in parallel with the class and to find ways to effectively operate group activities in college liberal arts classes. To this end, this study conducted a survey on how group activities are perceived by students who took the liberal arts classes as &lt;Thought and Expression&gt; courses in S University. According to the survey, students recognize that group activities are necessary but are reluctant to do small group activities because of the burden of carrying out a class assignment while communicating with unfamiliar schoolmates, as well as the anxiety they feel about having to work with schoolmates that are not diligent. Therefore, this study suggests that we strengthen the motivation for group activities, to reinforce the function of peer evaluation, and to provide effective feedback as professors regarding group activities as ways to effectively operate small group activities in college liberal arts classes. Through these methods, it is expected that students will be able to reduce their negative perception of group activities, recognize the meaning and value of collaboration, and be able to achieve learning effects such as improving their communication and problem-solving abilities.
TAMformer: Multi-Modal Transformer with Learned Attention Mask for Early Intent Prediction

Human intention prediction is a growing area of research where an activity in a video has to be anticipated by a vision-based system. To this end, the model creates a representation of the past, and subsequently, it produces future hypotheses about upcoming scenarios. In this work, we focus on pedestrians’ early intention prediction in which, from a current observation of an urban scene, the model predicts the future activity of pedestrians that approach the street. Our method is based on a multi-modal transformer that encodes past observations and produces multiple predictions at different anticipation times. Moreover, we propose to learn the attention masks of our transformer-based model (Temporal Adaptive Mask Transformer) in order to weigh differently present and past temporal dependencies. We investigate our method on several public benchmarks for early intention prediction, improving the prediction performances at different anticipation times compared to the previous works.