Reviewerly/exHarmony huggingface dataset:
Breaking the Glass Ceiling in Education Sector

The Glass ceiling has become a central notion in the topic of gender in every organization. It is not only a barrier for an individual based on the individual's incapacity to manage a higher-level work, rater it relates specifically to women as a group who are prevented from going further in their careers because they are women. The barriers that constitute the glass ceiling can be of various types like Individual, Societal, Organizational, etc. It is vital to identify those barriers and install suitable measures so that this stumbling block called glass ceiling can be removed from the career path of skillful female academicians. This paper is intended to discuss the barriers that women face in their career pursuits for senior-level jobs because of the Glass ceiling and what they must do to go ahead and reach the leadership level they want or put it rightly, they deserve. This empirical study done in first grade colleges of Mangalore city is a preliminary attempt to identify the impact of Glass ceiling on women in education sector especially in their career advancement. It is evident from the findings that the existence of Glass ceiling in private institutions are far more when compared to government institutions.
COOPERATION OF OMSK STATE PEDAGOGICAL UNIVERSITY AND EDUCATIONAL ORGANIZATIONS OF OMSK DURING THE PERIOD OF PEDAGOGICAL PRACTICE

The article is devoted to the adaptation of the work experience internship “Classroom Management” to the educational program of the educational organization, on the basis of which the practice is carried out. The practical training of students in accordance with the concept of the Core of Higher Pedagogical Education, the features of working with children with signs of giftedness and disabilities, as well as ways to implement an internship program in the specific conditions of an educational organization are considered.
«Еластичність его» – специфіка загальної обдарованості артиста мюзиклу

The purpose of the work is to reveal the essence and specifics of the general talent of the musical artist in line with the concept of autopoetry of living systems. The research methodology is based on general philosophical methods – analysis, synthesis, substantiation; practical methods – comparison, observation, coordination of practical experience. A systematic approach provides an opportunity to understand and reconcile creative experience and research in substantiating the share of cognitive and emotional intelligence in the professional process of a musical artist, which logically explains the ‘elasticity’ of the musical artist as a mechanism for deciphering the intonation semantics of authorial musical material. Scientific novelty: the concept of ‘elasticity of the ego’ of the musical artist is formulated in view of the selfdriving creative process and self-driving consciousness of the artist, aspects of emotional intelligence of the musical artist are revealed, the mechanism of cognitive and emotional intelligence of the musical artist is analyzed. Conclusions: For the artist of the musical, emotional and cognitive intelligence are operational tools that interact with the original musical impression with a further conscious professional algorithm. The term ‘ego elasticity’ is introduced because we do not divide the interaction of cognitive and emotional intelligence into stages, but consider it the only conscious and unconscious essence of the general talent that allows the artist to be successfully implemented in creative activity. Given the auto-poetic nature of the musical artist’s creative process, ‘ego elasticity’ is understood as an operational property of the artist’s overall talent, which implies a specific cognitive-emotional quality of effective relationships between the components of the musical artist’s talent structure. Ego elasticity is considered a manifestation of the artist’s self-poetic nature.
Assembly Line Quality Assurance Through Hand Tracking and Object Detection

This work presents a vision-based quality assurance system that does assembly line monitoring. The system is developed using machine learning hand tracking and object detection methods to monitor the worker’s hand movement while evaluating the correctness of the assembly. Feedback about the order of the steps the worker has taken is continuously shown to the user. This work has the potential to reduce the amount of manual work required for quality assurance in assembly line.
Electro-Optic Single Photon Source based on a Superconducting and Optical X(2) Material Platform

A single-photon source based on a superconducting qubit as an artificial atom and nonlinear optical readout via sum-frequency generation is presented. The analysis done via master equation and Quitp suggest efficiencies of 98% and g (2) (0)=5e-5.
How Does Open Research Impact Student Outcomes? A Big Team Science Review and Evidence Synthesis

In this talk, I will provide a summary of a large-scale review of how embedding open and reproducible scholarship may impact student outcomes across educational contexts. This project aimed to reduce barriers to embed open and reproducible scholarship into research training, by reviewing, synthesising, and clearly articulating how embedding such an approach can confer benefits for students. We provide the first comprehensive review of how integrating open and reproducible science into teaching and learning impacts students, using a large-scale, collaborative, Big Team Science approach. This project focused on interdisciplinary undergraduate and postgraduate students, on an international level. In the talk, I will describe the key findings of the review and also reflect upon the value of employing Big Team Science approaches to the study of open pedagogy.
Multi-Train Path Finding Revisited

Multi-Train Path Finding (MTPF) is a coordination problem that asks us to plan collision-free paths for a team of moving agents, where each agent occupies a sequence of locations at any given time. MTPF is useful for planning a range of real-world vehicles, including rail trains and road convoys. MTPF is closely related to another coordination problem known as k-Robust Multi-Agent Path Finding (kR-MAPF). Although similar in principle, the performance of optimal MTPF algorithms in practice lags far behind that of optimal kR-MAPF algorithms. In this work, we revisit the connection between them and reduce the performance gap. First, we show that, in many cases, a valid kR-MAPF plan is also a valid MTPF plan, which leads to a new and faster approach for collision resolution. We also show that many recently introduced improvements for kR-MAPF, such as lower-bounding heuristics and symmetry reasoning, can be extended to MTPF. Finally, we explore a new type of pairwise symmetry specific to MTPF. Our experiments show that these improvements yield large efficiency gains for optimal MTPF.
Learning Pseudo-Backdoors for Mixed Integer Programs

We propose a machine learning approach for quickly solving Mixed Integer Programs (MIP) by learning to prioritize a set of decision variables, which we call pseudo-backdoors, for branching that results in faster solution times. Learning-based approaches have seen success in the area of solving combinatorial optimization problems by being able to flexibly leverage common structures in a given distribution of problems. Our approach takes inspiration from the concept of strong backdoors, which corresponds to a small set of variables such that only branching on these variables yields an optimal integral solution and a proof of optimality. Our notion of pseudo-backdoors corresponds to a small set of variables such that only branching on them leads to faster solve time (which can be solver dependent). A key advantage of pseudo-backdoors over strong backdoors is that they are much amenable to data-driven identification or prediction. Our proposed method learns to estimate the solver performance of a proposed pseudo-backdoor, using a labeled dataset collected on a set of training MIP instances. This model can then be used to identify high-quality pseudo-backdoors on new MIP instances from the same distribution. We evaluate our method on the generalized independent set problems and find that our approach can efficiently identify high-quality pseudo-backdoors. In addition, we compare our learned approach against Gurobi, a state-of-the-art MIP solver, demonstrating that our method can be used to improve solver performance.
Robust Recommendation Algorithm Based on User Suspicious Probability and Item Weight

With the extensive development of recommendation technology, the threat of shilling attacks faced by the existing collaborative recommendation algorithms is also increasing sharply.To face more and more complex shilling attacks, this paper constructs a robust recommendation algorithm that can resist shilling attacks from the perspective of recommendation algorithm.Existing robust recommendation algorithms usually improve robustness by sacrificing some recommendation accuracy and reduce the recommendation accuracy.To solve this problem, this paper proposes a robust recommendation algorithm based on user suspicious probability and item weight.Firstly, we establish the relevance vector machine classifier according to user profile features to evaluate user suspicious probability in the database.Secondly, we construct singular value decomposition algorithm based on Hebbian learning and matrix factorization algorithm by integrating user suspicion information.Finally, a dynamic weighting scheme is used in combination with the above algorithm and the collaborative filtering algorithm based on item weight, and the above algorithms are mixed according to a certain weight to obtain a robust collaborative filtering algorithm SRICF.By adjusting the weight ratio, advantages of each algorithm are brought into play, thereby improving recommendation accuracy and robustness of the algorithm.Experimental results show that our algorithm has good prediction accuracy and robustness compared with other single algorithms.
Accuracy of Rapid Diagnostic Test for Malaria Compared to Microscopy

Objective: To determine the diagnostic accuracy of the Rapid Diagnostic Test in the detection of malaria by taking routine microscopy as a gold standard.&#x0D; Study design: Cross-sectional study.&#x0D; Place and Duration of Study: Department of Haematology, Pakistan Naval Ship Rahat Hospital, Karachi Pakistan, from Aug 2018 to Jan 2019.&#x0D; Methodology: Patients diagnosed as a case with malaria were included. Malaria was confirmed by using a Rapid detection test and microscopy. Mean and standard deviations were calculated for the quantitative variables like age. Frequencies and percentages were calculated for the qualitative variables like gender. Sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy were calculated.&#x0D; Results: Out of 175 patients in the study, the mean age was 39.30 ± 11.29 years. 85 (48.6%) were male, and 90 (51.4%) were female. Out of 175 patients, sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of the rapid diagnostic test for malaria, keeping microscopy as the gold standard was found to be 87.2%, 74.15%, 67.34%, 85.71% and 80.57% respectively.&#x0D; Conclusion: Rapid immune-capture tests can have excellent applicability in malaria diagnosis. Field workers can reliably read such tests without any supervision. It appears to satisfy the desired criteria of being rapid, easy to perform, interpret and reasonably accurate.
EXAMPLE NON-EXAMPLE METHOD FOR IMPROVING STUDENTS' WRITING DESCRIPTIVE TEXT

This study aims to improve students' ability to write an essay in the descriptive text genre. Descriptive text is a genre that serves to explain something to the reader through writing. To make it easier for researchers to conduct research, researchers use the CAR (Classroom Action Research) method to make it easier for researchers to be closer to the sample. The sample in this study were students of SMPN 5 Percut Sei Tuan with a total of 30 students. Researchers have conducted research with five meetings in four stages, namely planning, and observing. action, and reflection. Quantitative and Qualitative data are tools used in collecting data. Quantitatively, the value of the students' descriptive text is as data, which has been carried out in two cycles. Started the pre-test with a total score of 1953,3 with an average of 64.5. In the first cycle, the total score was 2204.05 with an average of 73.4. The researcher again conducted a post-test in the second cycle to achieve the requirements for teaching success, namely 85%. In cycle 2 the total score was 2621.6 with an average of 87.3. This proves that there is a significant change in student scores using the example non-example method. Qualitative data taken from observation sheets, interviews, and writer's diaries show that it is easier for students to understand teaching and can attract students' attention with an image applicator that guides students to write an essay.
DistPro: Searching a Fast Knowledge Distillation Process via Meta Optimization

Recent Knowledge distillation (KD) studies show that different manually designed schemes impact the learned results significantly. Yet, in KD, automatically searching an optimal distillation scheme has not yet been well explored. In this paper, we propose DistPro, a novel framework which searches for an optimal KD process via differentiable meta-learning. Specifically, given a pair of student and teacher networks, DistPro first sets up a rich set of KD connections from the transmitting layers of the teacher to the receiving layers of the student, and in the meanwhile, various transforms are also proposed for comparing feature maps along their pathways for distillation. Then, each combination of connection and transform (pathway) is associated with a stochastic weighting process which indicates its importance at every step during the distillation. At the searching stage, the process can be effectively learned through our proposed bi-level meta-optimization strategy. At the distillation stage, DistPro adopts the learned processes for knowledge distillation, which significantly improves the student accuracy especially when faster training is required. Lastly, we find the learned processes can be generalized between similar tasks and networks. In our experiments, DistPro produces state-of-the-art (SoTA) accuracy under varying number of learning epochs on popular datasets, i.e. CIFAR100 and ImageNet, which demonstrates the effectiveness of our framework. Codes are available at https://github.com/xdeng7/DistPro .
The Impact of a Balanced Literacy Program on the Gradual Release of the Instructor’s Accountability

Under no circumstances can anyone argue with the eminent saying, “A child who reads will be an adult who thinks.” Literacy does matter. It’s never a privilege; it is a right. Every child has the right to understand the significance of being educated as it needs hard work as well as persistence to pay off. Therefore, literacy is crucial to any progress and advancement. The purpose of this study is to show how young learners can, eventually, sustain, tolerate, and then master balanced and effective literacy independently. Instructors can gradually release their responsibility in order to set their learners free to learn autonomously. To reach this level, several steps and phases will be highlighted as well as taken into consideration. This research paper presents literacy aspects to be studied within appropriate settings and learning environments; suitable curricula, and applicable time and framework. The study engaged mixed methods (qualitative and quantitative approaches) and analytical methods where surveys, observations, facts, and many measurements are markedly deliberated by the researcher through interviews held by an amount number of teachers and a questionnaire that was distributed online. The researcher, then, received and analyzed all the answers delivered. The results reveal that a balanced and effective literacy program has a positive impact on learners to work and learn independently. Learners will also be able to use different strands in contexts across the curriculum especially when it is held professionally, proactively, and under regular observations. finally, the study approves the gradual release of the instructor’s responsibility while delivering teaching methods and giving the learners the opportunity to be independent.
Sentiment Analysis of Hate Speech on Twitter Public Figures with AdaBoost and XGBoost Methods

Public figures are often scrutinized by social media users, either because of what they say or even because of their role in a television series. Generally, public figures upload something on their social media accounts to help shape their image. But not everyone who sees it is happy. Some even dislike the upload. This study aims to determine public sentiment towards public figure Anya Geraldine conveyed on Twitter in Indonesian. The classification process in this study uses the Adaptive Boosting (AdaBoost) and Extreme Gradient Boosting (XGBoost) classification methods with text preprocessing using cleaning, case folding, tokenization, and filtering. The data used are tweets in Indonesian with the keyword ”@anyaselalubenar”, with a total dataset of 7,475 tweets divided into 6,887 positive and 588 negative tweets. From the label results using oversampling to avoid excessive overfitting problems. The feature used is TF-IDF weighting. Four experimental scenarios were carried out to validate the effectiveness of the model used: first model performance without oversampling, second model performance with oversampling, third model performance with undersampling, and fourth model performance with Hyperparameter tune. The experimental results show that XGBoost+SMOTE+Hyperparameter achieved 95% compared to AdaBoost+SMOTE+Hyperparameter of 87%. The application of SMOTE and Hyperparameter tune is proven to overcome the problem of data imbalance and get better classification results.
Identifying the stages of visual and auditory aesthetic development in students based on their gender

Identifying the stages of visual and auditory aesthetic development in students based on their gender
Las expectativas del estudiantado subgraduado de un programa de aprendizaje en línea

&#x0D; &#x0D; &#x0D; This article describes the process of translation and validation of the “Student Expectations of Online Learning Survey” questionnaire (SEOLS), as well as its administration to all fully online undergraduate students at the Inter-American University of Puerto Rico, Ponce Campus (UIPR-Ponce). This quantitative-descriptive research was conducted during the spring semester of 2017 with a random sample of 225 participants, who completed online SEOLS questionnaire. The findings reveal that the online student body has a high mastery of the technology and the management of the system or platform used for the course delivery. In addition, it has high expectations about everything related to navigation in the online courses and teaching staff offered by these courses. The dimensions related to the content of the courses and the social interaction in the online courses received the lowest scores. In conclusion, for this university population, SEOLS is a valid and reliable instrument. In addition, that distance education students have varied levels of expectations for each of the dimensions described in SEOLS. The results of this research can be useful in the design and review of courses, as well as in the training of teachers who offer online courses.&#x0D; &#x0D; &#x0D;
The Connection between Language and Identity: the Yoruba-Arabic Literates and The Street Urchins of Ibadan

The current paper is dedicated to investigate the connection between language and identity, with a special reference to two ambivalent social groups in Ibadan, i.e., the Yoruba-Arab literates and the street urchins. The research shall be carried out with samples of online videos as well as other online resources. One major phenomenon that connects people with varying degrees of social status, religious, ages etc. is the language they speak. In every society, language plays a herculean task in reflecting the identity of the people, and in most times, its usage shows the social class of the speaker. It is incontrovertible that, language and identity go together. We identify people and affiliate them with certain tribe, race or ethnic as the result of language they speak. In other words, we may say, there is no identity without language, this is because the language we speak gives people the opportunity to link us with certain community.
Evaluation and Recommendation User Interface of Batamnews Based on User Experience using User-Centered Design

Batamnews is a media that presents news about Batam. Batamnews currently has an application that aims to make it easier for users to continue to be updated regarding news in Batam. But from the results of interviews and the distribution of questionnaires with Batamnews users, there are problems experienced by application users due to the User Interface which makes users uncomfortable using the application. Users feel that Batamnews is not optimal in terms of appearance, and the user's uninterested use of icons (symbols). In addition, Users complain about features that should be available but not in the app. Therefore, this study aims to make a design using the User-Centered Design (UCD) method because UCD focuses on user needs. Then for testing the design, the System Usability Scale (SUS) evaluation method will be used because it can be measured for effectiveness, efficiency, and satisfaction from users. The results of this study are recommendations for the User Interface Design of the Batamnews application and have an increased value on usability from 54 to 74 which is expected to be a reference for Batamnews application developers. So, it can be concluded that the UCD method can increase the SUS usability value in an application as well.
Certain issues of legal regulation of the placement of intellectual property objects on the Internet: problematic aspects and search for solutions

We provide a legal description of the problems that arise as a result of the placement of intellectual property objects on the Internet, mediated violations of the rights of legitimate copyright holders. The purpose of the study: to conduct a legal analysis (legal characteristics and analysis of judicial practice) of problematic issues of regulating the placement of intellectual property objects on the Internet. We point out that the legal protection of intellectual property subjects is possible through the implementation of criminal law and civil law measures adapted to the existing objective realities in cyberspace. We carry out a characterization of the subject composition of copyright holders and subjects of responsibility, cases from judicial practice are given. In addition, we consider pre-trial ways to resolve disputes between authors of works and owners of Internet resources. The study is based on formal legal and comparative legal methods, which have found their application in the legal analysis of the problems of protecting audiovisual works on the Internet. As a conclusion, we express the need for more effective, efficient protection of this institution of law at the present stage of its development by optimizing the criminal law and civil law means of protecting the institution of intellectual property law and the legitimate interests of copyright holders.