Reviewerly/exHarmony huggingface dataset:
Uncovering the Citation Landscape: Exploring OpenCitations COCI, OpenCitations Meta, and ERIH-PLUS in Social Sciences and HumanitiesJournals - Workflow v3

Purpose The main purpose of this research is to answer to three different questions and find out: the number of citations which refer to publications in Social Sciences and Humanities journals included in ERIH-PLUS, by looking at citations data contained in OpenCitations COCI and OpenCitations Meta; the most citing and the most cited SSH discipline, according to the above mentioned datasets; the citations coming from and going to publications contained in OpenCitations Meta which are not included in SSH journals. We want to draw a line that connects these three different datasets, aiming at offering an overall view of the citations landscape of each of them. Methodology For this purpose, we approach the problem from a computational point of view. We extract only the relevant data by operating a first preprocessing of COCI, ERIH-PLUS and META's datasets. Then we build a python software able to analyze CSVs data, querying them to retrieve information needed and to present the results in a clear and understandable way. Findings The findings show that the majority of citations come from and go to psychology publications, and a deep gap exists between the number of citations included in SSH journals and the number of citations that are not included in SSH journals. Originality/Value The research conducted by us has the purpose to add information to existing resources with the aim of facilitating their use and allowing the researchers to have a clearer view of the data contained in each dataset. In addition, the research has the purpose to gather information that may be useful for understanding which is the most influential discipline in the SSH field and to provide a solid starting point for further studies regarding this subject. Keywords: COCI, Meta, ERIH-PLUS, OpenCitation, SSH, Journals
Implementation of Blog-Based Learning Media: Community Service for Elementary School Teachers

Elementary schools in Driyorejo Gresiks consist of 11 private elementary schools and 26 public elementary schools. The location of the school is mostly located in rural areas and most teachers are rarely involved in scientific activities carried out by universities, so that the knowledge and understanding of teachers is still not related to learning media or other learning innovations. The results of interviews obtained from several teachers in public and private elementary schools at UPTD Driyorejo, Gresik Regency obtained information that some teachers almost never use blog-based learning media because the media does not exist and the ability of teachers to develop it is also lacking. This has an impact on the implementation of learning activities that take place less meaningfully and tend to be rote in nature. The use of blog-based learning is expected to increase teacher innovation, motivate, and increase student achievement optimally. Community service is carried out by conducting training on the implementation of blog-based learning media. The training implementation stage is carried out in two sessions. The first session explained the blog-based learning media material. Second session of training iimplementation of blog-based learning media for elementary school teachers in Driyorejo Gresik.
Impact of the Leadership in Managing the Quality of Care: A Comparative Analysis of Healthcare in Qassim Saudi Arabia

The aim of this paper was to find the relationship between leadership and its impact on quality of healthcare. Survey approach using questionnaire was used for data collection. Population of the study was from Qassim health sector employees. A total of 200 completed questionnaires were collected back and used in the analysis in this study. Correlation analysis and regression analysis were used to test hypotheses. It was found that all the predictors and criterion have moderate and positive relationship. Likewise, there is significant impact of leadership found on quality of healthcare in Saudi Arabia; finding are consistent with that previous studies. Based on findings, the study suggests that participative style of the leader not only encourage the people to give their input in decision making and formulation of plans but also play greater role in implementation too. Therefore, friendly, accommodative, democratic, encouraging, and liberal work environment may be created by management of the hospitals because such kind of an environment increase the level of performance and advantageous in materializing the predefined objectives of quality management, that also supplements better healthcare outcomes. Future researcher can conduct studies with larger sample to generalize the findings since this study used a small sample size only from one region.
LIGHT PAYLOAD QUADCOPTER DESIGN FOR THE TRANSPORTATION OF ESSENTIAL GOODS TO PEOPLE IN SELF-ISOLATION

A quadcopter, also called a quadrotor helicopter or quadrotor is a multirotor helicopter that is lifted and propelled by four rotors. In case of lockdown or self-isolation, companies as well as governments can make use of unmanned aerial vehicles equipped with obstacle detection and collision avoidance technology. It is paramount to understand the importance of flight safety with unmanned aerial vehicles. If rules and restrictions are not followed because the user with the controller made an error or was unconscious, a sophisticated system will detect possible conflict and save the drone before collision. In this paper, a digital model was created using MatLab software, in order to analyze and understand how a quadcopter works in its environment. Using the trajectory tools, a well-defined trajectory is defined for a quadcopter in order to better represent its behavior during a light parcel transport assignment. The results obtained can be used to design a drone for the delivery of small packages containing essential goods for people in self-isolation.
Sentiment Analysis of Amazon Product Reviews using Supervised Machine Learning Techniques

Today, everything is sold online, and many individuals can post reviews about different products to show feedback. Serves as feedback for businesses regarding buyer reviews, performance, product quality, and seller service. The project focuses on buyer opinions based on Mobile Phone reviews. Sentiment analysis is the function of analyzing all these data, obtaining opinions about these products and services that classify them as positive, negative, or neutral. This insight can help companies improve their products and help potential buyers make the right decisions. Once the preprocessing is classified on a trained dataset, these reviews must be preprocessed to remove unwanted data such as stop words, verbs, pos tagging, punctuation, and attachments. Many techniques are present to perform such tasks, but in this article, we will use a model that will use different inspection machine techniques.
Score-balanced Loss for Multi-aspect Pronunciation Assessment

With rapid technological growth, automatic pronunciation assessment has transitioned toward systems that evaluate pronunciation in various aspects, such as fluency and stress. However, despite the highly imbalanced score labels within each aspect, existing studies have rarely tackled the data imbalance problem. In this paper, we suggest a novel loss function, score-balanced loss, to address the problem caused by uneven data, such as bias toward the majority scores. As a re-weighting approach, we assign higher costs when the predicted score is of the minority class, thus, guiding the model to gain positive feedback for sparse score prediction. Specifically, we design two weighting factors by leveraging the concept of an effective number of samples and using the ranks of scores. We evaluate our method on the speechocean762 dataset, which has noticeably imbalanced scores for several aspects. Improved results particularly on such uneven aspects prove the effectiveness of our method.
PERAN AKUNTAN DALAM MENGHADAPI DIGITALISASI EKONOMI MENJELANG ERA SOCIETY 5.0

The digitalization of the economy toward the Society 5.0 era has begun to be realized in Indonesia. The era of Society 5.0 is shown by all the facilities obtained by humans through systems, technology, and robots. The existence of an accountant in the era of Society 5.0 is expected to decrease. This study aims to determine the description of the accounting profession in the era of Society 5.0 and efforts that can be made by an accountant in dealing with that era. This study uses a qualitative approach research method with data collection techniques derived from literature review. The results of this study indicate differences in the practice of accountants in the past and the era towards Society 5.0. Accountants' task has become more effective and efficient because of the digitalization of the economy. Era Society 5.0 also provides opportunities and challenges for accountants. Therefore, an accountant requires skills in the field of information technology in order to survive in the era of Society 5.0 and following eras.
STEM EDUCATION ON OPEN EDUCATIONAL PLATFORMS

Modern society functions under the influence of technology, thanks to which all areas of its life are developing. This contributed to the emergence of a new direction in education - the STEM direction, which combines natural sciences (Science), technology (Technology), engineering (Engineering) and mathematics (Mathematics). This direction is focused on applied research in solving specific problems and using at the same time interdisciplinary connections, concepts and methods, which today are followed and formed in natural and technical sciences and mathematics and digital technologies. The study of the STEM direction is not yet provided for in the main curriculum of educational institutions but takes place mostly through webinars, advanced training courses, conferences, etc. And with the introduction of distance learning into the educational process, electronic educational platforms for mastering certain knowledge have become relevant. The purpose of the article is the analysis of educational resources regarding the provision of STEM education or the training of teachers for its implementation. The article examines well-known foreign (Coursera, edX, Udemy) and Ukrainian (Prometheus and EdEra) open educational platforms. The choice of these platforms is based on: popularity, a convenient interface with the ability to filter courses, the presence of courses with the word "STEM" in the title, free access. The considered quantitative analysis of STEM courses on the specified platforms showed that there are no STEM courses on Ukrainian platforms. To get an idea of the capacity (content) of STEM-related courses, we took individual courses on the Coursera, edX, Udemy platforms. Namely, the course "Emprendiendo en STEM" (Coursera), "Advancing Learning Through Evidence-Based STEM Teaching" (edX), "Finding the Art in Engineering - STEM to STEAM" (Udemy). Based on the results of the analysis of courses on open educational platforms related to STEM education, it was concluded that Coursera contains the largest number of courses that mention STEM. At the same time, examples of their completion show that the developers do not offer courses specifically for acquiring STEM education.
The Effect of Resampling on Classifier Performance: an Empirical Study

An imbalanced class on a dataset is a common classification problem. The effect of using imbalanced class datasets can cause a decrease in the performance of the classifier. Resampling is one of the solutions to this problem. This study used 100 datasets from 3 websites: UCI Machine Learning, Kaggle, and OpenML. Each dataset will go through 3 processing stages: the resampling process, the classification process, and the significance testing process between performance evaluation values of the combination of classifier and the resampling using paired t-test. The resampling used in the process is Random Undersampling, Random Oversampling, and SMOTE. The classifier used in the classification process is Naïve Bayes Classifier, Decision Tree, and Neural Network. The classification results in accuracy, precision, recall, and f-measure values are tested using paired t-tests to determine the significance of the classifier's performance from datasets that were not resampled and those that had applied the resampling. The paired t-test is also used to find a combination between the classifier and the resampling that gives significant results. This study obtained two results. The first result is that resampling on imbalanced class datasets can substantially affect the classifier's performance more than the classifier's performance from datasets that are not applied the resampling technique. The second result is that combining the Neural Network Algorithm without the resampling provides significance based on the accuracy value. Combining the Neural Network Algorithm with the SMOTE technique provides significant performance based on the amount of precision, recall, and f-measure.
Generating Images with Multimodal Language Models

We propose a method to fuse frozen text-only large language models (LLMs) with pre-trained image encoder and decoder models, by mapping between their embedding spaces. Our model demonstrates a wide suite of multimodal capabilities: image retrieval, novel image generation, and multimodal dialogue. Ours is the first approach capable of conditioning on arbitrarily interleaved image and text inputs to generate coherent image (and text) outputs. To achieve strong performance on image generation, we propose an efficient mapping network to ground the LLM to an off-the-shelf text-to-image generation model. This mapping network translates hidden representations of text into the embedding space of the visual models, enabling us to leverage the strong text representations of the LLM for visual outputs. Our approach outperforms baseline generation models on tasks with longer and more complex language. In addition to novel image generation, our model is also capable of image retrieval from a prespecified dataset, and decides whether to retrieve or generate at inference time. This is done with a learnt decision module which conditions on the hidden representations of the LLM. Our model exhibits a wider range of capabilities compared to prior multimodal language models. It can process image-and-text inputs, and produce retrieved images, generated images, and generated text -- outperforming non-LLM based generation models across several text-to-image tasks that measure context dependence.
Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers

In a hyper-relational knowledge graph, a triplet can be associated with a set of qualifiers, where a qualifier is composed of a relation and an entity, providing auxiliary information for the triplet. While existing hyper-relational knowledge graph embedding methods assume that the entities are discrete objects, some information should be represented using numeric values, e.g., (J.R.R., was born in, 1892). Also, a triplet (J.R.R., educated at, Oxford Univ.) can be associated with a qualifier such as (start time, 1911). In this paper, we propose a unified framework named HyNT that learns representations of a hyper-relational knowledge graph containing numeric literals in either triplets or qualifiers. We define a context transformer and a prediction transformer to learn the representations based not only on the correlations between a triplet and its qualifiers but also on the numeric information. By learning compact representations of triplets and qualifiers and feeding them into the transformers, we reduce the computation cost of using transformers. Using HyNT, we can predict missing numeric values in addition to missing entities or relations in a hyper-relational knowledge graph. Experimental results show that HyNT significantly outperforms state-of-the-art methods on real-world datasets.
Forty thousand kilometers under quantum protection

Abstract Quantum key distribution (QKD) is a revolutionary cryptography response to the rapidly growing cyberattacks threat posed by quantum computing. Yet, the roadblock limiting the vast expanse of secure quantum communication is the exponential decay of the transmitted quantum signal with the distance. Today’s quantum cryptography is trying to solve this problem by focusing on quantum repeaters. However, efficient and secure quantum repetition at sufficient distances is still far beyond modern technology. Here, we shift the paradigm and build the long-distance security of the QKD upon the quantum foundations of the Second Law of Thermodynamics and end-to-end physical oversight over the transmitted optical quantum states. Our approach enables us to realize quantum states’ repetition by optical amplifiers keeping states’ wave properties and phase coherence. The unprecedented secure distance range attainable through our approach opens the door for the development of scalable quantum-resistant communication networks of the future.
Disruptive Effects In Highschool Studentsʼ Assessment

According to the literature invoked in our paper, assessment can be a means of subjective measurement, a factor of issuing a value judgment based on certain particular theory, which has the status of preventing the continuous study that could lead towards improvement or the achievement of the highest possible performance.Regarding the disturbing factors, once settled, they induce quite significant and at the same time relevant variations either at the same examiner at different times or at different examiners.Disruptive effects that may occur in school assessment are: the Halo effect, the anchoring effect, the Pygmalion effect or Oedipal effect, the examiner's personal equation, the central tendency effect, the similarity effect, the contrast effect, the order effect, the logic error and role effect.In our paper we will present several of these disruptive effects found by students in different situations in high school classes.These are disruptive effects reported in a research that involved a number of one hundred students.They were asked to describe one of the assessment errors they had experienced during the evaluation process.The main conclusion of the research is that all these students were subjectively assessed in some situations, so there were various disruptive effects in the assessment.
Legislative Strategies Regarding The Professional Development Of Teachers In Pre-University Education

The article "Legislative strategies regarding the professional development of teachers in pre-university education", aims at the subsystem of training and evolution in the teaching career of teachers from the point of view of the contextualization of the legislative framework, the subsequent changes and additions, which outline the legislative milestones and framework methodology at the level national in defining the necessary competencies for the foundation of the teaching career, the main professional counselling interventions that define the typology of the teaching career model, the accredited institutions in order to organize professional training programs, but also the evolution in the teaching career within the education system.In this context, it is established that the status of the teaching staff represents a professional and social responsibility, a balance between personal, professional, and social life, and through the transformation skills through the training of teaching staff, professional success is achieved and contributes to the quality and the optimization of the didactic act.From this point of view, the generated teaching career model and the professional development profile aim to train a competent, expert, reflective, innovative teaching staff, an architect of the vision of contemporary pedagogy.Pursuing this desired, it is necessary to activate and dynamize the commission for didactic mentoring and training in the didactic career at the level of school institutions, which in accordance with the legislative framework and framework methodology in force, should aim as its object at the activity of training, improvement and professional development and teaching staff.
Leadership And Quality In The Mentorship Of Teaching Practice

The article presents the results of a study conducted within the project "Professionalization of teaching career -PROF" (POCU / 904/6/25/146587), focused on leadership and the application of quality management principles in teaching career mentorship.The study aimed at pinpointing the opinions of mentor teachers who had participated in the study, trainees in the Prof II programme, regarding the application of leadership model in mentorship and the principles of quality management in mentorship, in order to increase the quality of teaching practice for future teachers.The conclusions of the article highlighted specific methods utilised by mentor teachers in the application of quality management principles in their mentoring activities such as the focus on the future teacher, leadership in mentorship, result-oriented quality mentorship, process-based approach, approach of management as a system, learning, innovation and continuous quality improvement, fact-based approach in decision-making process, involvement of future teachers in the process of their own professional training.Leadership and quality principles applied in the management of mentoring activities contribute significantly to the development of the skills mentor teachers need to acquire and to providing higher quality in teaching practice programmes.
Educational Robotics Inclusive And Technology Education

Computational thinking is a fundamental competence in the training.The fundamental motivation is to be found in the ability, which must be transversal, to learn methods of approach to problem solving.A skill that goes beyond simple problem solving but is configured as intelligence and as such can be trained and developed.At the same time, it becomes essential to put oneself in the perspective of an education that is inclusive.An education attentive to inclusion is an education attentive to the enhancement of the skills of each one to develop skills.On the other hand, we must pay continuous attention to emerging technologies, evaluating, and integrating them into learning paths, aware that they are integrated into a complex framework.Starting from these considerations, we intend to reflect and propose educational paths that use educational robotics not with the aim of learning the programming or the functions of an android, but configuring themselves as an innovative approach to teaching, a pedagogical method to increase the centrality of the student in the learning-teaching processes, promote an individualization aimed at the inclusion of all the children in the class.The background of this reflection is the focus of some eidetic structures that mark the new processes of knowledge in the world of robotics; this means going in search of the connective structures of robotic systems within the weaving of relationships with the context, then identifying the nodes that make the parts of the same system interdependent in relation to educational instances.