Reviewerly/exHarmony huggingface dataset:
On cropped versus uncropped training sets in tabular structure detection

Automated document processing for tabular information extraction is highly desired in many organizations, from industry to government. Prior works have addressed this problem under table detection and table structure detection tasks. Proposed solutions leveraging deep learning approaches have been giving promising results in these tasks. However, the impact of dataset structures on table structure detection has not been investigated. In this study, we provide a comparison of table structure detection performance with cropped and uncropped datasets. The cropped set consists of only table images that are cropped from documents assuming tables are detected perfectly. The uncropped set consists of regular document images. Experiments show that deep learning models can improve the detection performance by up to 9% in average precision and average recall on the cropped versions. Furthermore, the impact of cropped images is negligible under the Intersection over Union (IoU) values of 50%-70% when compared to the uncropped versions. However, beyond 70% IoU thresholds, cropped datasets provide significantly higher detection performance.
Selisik Pasar Legi Kotagede sebagai Sumber Belajar BIPA A2 Topik Berbelanja

The goal of this study is to characterize the Kotagede Legi Market as a BIPA A2 Shopping Topics learning resource. The purpose of this study is to look at the market's history, current state, and utilization of the market as a learning resource for BIPA students. In this study, a descriptive method with a qualitative approach was adopted. The qualitative approach can be viewed as a research project. The qualitative approach can be thought of as a research strategy that relies on data collecting and analysis to investigate the occurrence of occurrences. The following are the findings of this study: 1) Pasar Legi Kotagede Yogyakarta is a traditional market with a unique variety that attracts many domestic and local visitors; 2) BIPA students learn to compose sentences using good language in accordance with aspects of Javanese language and culture in order to play a role as sellers and buyers in Pasar Legi Kotagede Yogyakarta.
Multi-intelligence-based literacy learning training to improve teacher pedagogic competence

This community service activity was carried out at SD Sukomanah, Purwodadi District, Purworejo Regency. The activity was carried out by involving 30 elementary school teachers in Purwodadi, Purworejo, with the aim of improving the pedagogic abilities of teachers in empowering lifelong learners through literacy learning based on multiple intelligences. The methods used in service activities are socialization, simulation, monitoring and evaluation. Most of the participants have understood and three participants have even practiced multiple intelligence-based literacy learning for lifelong learners.
Creativity in Internal Marketing with Performance Improvement Approach (Case study: Water and Wastewater Company)

Purpose: The purpose of this research is to provide a conceptual model of creativity in domestic marketing with a performance improvement approach in the water and wastewater industry. Method: The method of analysis of this study was a Structural Interpretative Method (ISM). Using this method, the analysis of the proposed model was performed. Findings: The results show that the variables of the comprehensive motivational system, the economic attitude towards the water industry, the comprehensive human capital system, the system of competence in appointments, prospects, and the formulation of strategy and process management in the hybrid region. Impact-dependency strength diagram An analytical method has been used to show that the variables in this area have a penetration power and a high degree of dependence. Ultimately, these dimensions are considered as key variables, or the key dimensions of internal marketing, and they have been particularly important for the implementation of internal marketing in the water and wastewater industry.
치기공과 학생의 대면과 비대면 수업의 인식 및 만족도

Purpose: To study the perception and satisfaction of in-person and online classes for dental technology students. Methods: A total of 420 questionnaires were distributed to dental technology students between June 1 and June 30, 2021. Of these, 225 questionnaires were assessed using frequency analysis, one-way analysis of variance, Pearson's Chi-squared test, and independent t-tests via IBM SPSS Statistics ver. 22.0 (IBM). Results: For theory subjects, satisfaction was higher for online classes than in-person classes (p=0.001). For practical subjects, satisfaction was higher for in-person classes than online classes (p=0.002). Both the learning effect and motivation for learning were higher for in-person classes than online classes (p=0.001). Conclusion: When in-person and online classes become coexistent, there should be educational guidelines for improving the quality and effectiveness of learning in these different contexts.
Fast and Slow Enigmas and Parental Guidance

We describe several additions to the ENIGMA system that guides clause selection in the E automated theorem prover. First, we significantly speed up its neural guidance by adding server-based GPU evaluation. The second addition is motivated by fast weight-based rejection filters that are currently used in systems like E and Prover9. Such systems can be made more intelligent by instead training fast versions of ENIGMA that implement more intelligent pre-filtering. This results in combinations of trainable fast and slow thinking that improves over both the fast-only and slow-only methods. The third addition is based on “judging the children by their parents”, i.e., possibly rejecting an inference before it produces a clause. This is motivated by standard evolutionary mechanisms, where there is always a cost to producing all possible offsprings in the current population. This saves time by not evaluating all clauses by more expensive methods and provides a complementary view of the generated clauses. The methods are evaluated on a large benchmark coming from the Mizar Mathematical Library, showing good improvements over the state of the art .
RANCANG BANGUN SISTEM VALIDASI IJAZAH BERBASIS QR-CODE

A certificate of diploma is a student's graduation letter obtained after completing a diploma education. The certificate of diploma is used for various needs such as file completeness to applying for a job, the requirement for continuing to higher level education. In fact, there are many problems that occur on falsification the certificate. To solve these problems, a system for printing and validating diplomas is needed, where it is run with an android based QR-Code scanning system. This system is a very appropriate solution for the process of making a certificate of diploma and the validation process is done quickly and accurately
Image Edge Detection for Batak Ulos Motif Recognition using Canny Operators

Batak ulos is one of the handicrafts originating from North Sumatra. In Batak Ulos, there are various kinds of motifs that are characteristic of these ulos. One way to find out the type of ulos is by knowing the motives found on the ulos. For that we need a system that can detect ulos and then can recognize these ulos. The system was built using the canny edge detection method proposed by Jhon Canny in 1986, and is known as the optimal edge detection operator. Canny operator is one of edge detection which is very good in detecting image edges. Canny operators have met the criteria in detecting, namely detecting very well, responding well and localizing well and clearly. The system built also uses the C # programming language in Microsoft Visual Studio 2010.
Predict App Rank on Google Play Using the Random Forest Method

Application developers and users are the keys to the market impact on application development. In application development, developers need to predict applications in the market accurately, accurate prediction results are very important in showing user ratings that affect the success of an application. Ratings are given by users to judge that the application is good or not. The higher the rating given by the user, it means that the user likes the application and can be a benchmark for other users to download the application. It is undeniable that there are so many apps available on the google play store, it is impossible for users to select one by one app on the google play store. Therefore, a rating prediction system is needed to determine the right application based on the rating given by the user to an application. Predictions will be made using the random forest algorithm as the method used to predict application ratings. This study using the Google Play Store dataset. This dataset has 10840 rows and 13 attributes. The results of this study can be seen from the use of the random forest algorithm with an average accuracy of 93.8%. Keywords: Google Play Store, Rating, Prediction, Random Forest.
Logical-mathematical thinking in teachers of secondary education: an ethnomathematical perspective

The objective of the research was to identify the relationship between the development of logical-mathematical thinking and ethnomathematics as pedagogical resources in teachers of secondary. A research with a quantitative approach, quasi-experimental design, and explicative level was carried out. Also, a non-probability sampling was carried out to choose 60 teachers of secondary of two educational institutions of the city of Lima, Peru. A methodology with pre and post-test was applied to an experimental group and control groups, using a test of mathematical skills as an instrument of data collection. The experimental group was intervened through the application of six topics related to the fundamental mathematical operations under an ethnomathematical approach. The results were analyzed through a descriptive statistic and a variance analysis, with a reliability level of 95 %. The intervention, carried out under the ethnomathematical approach, influences the increase of skills of logical-mathematical thinking in a significant way in comparison with the level shown at the beginning of the research.
Pelatihan Model Pembelajaran Sentra (Beyond Centre And Circle Time) pada Bunda dan Wali Murid di PPT Teratai Gayungan Surabaya

The BCCT approach is a very complex and quite complex approach. In fact, it requires a large enough space to do the learning, all devices must be continuous. So many schools do not want to do this approach because they have limited space because the location of the school is in a dense urban area. The teacher must also be very creative in preparing the learning tools in such a way that children can be interested in learning through the play system. From this information, it can be estimated that less than 50% of PAUD in the city of Surabaya, especially in the Gayungan Subdistrict, which uses the center / BCCT approach becomes a learning model that is carried out every day. Furthermore, many parents also complained when their children were less enthusiastic at school because they were always taught to write in books, read, count in a devised without the children knowing in advance what their goals were for learning. Even the occurrence of a school breakdown can be caused by children becoming lazy because they are constantly told to sit quietly in a chair and write at the table while their age is playing. And they do not have demands in terms of memorization, writing, books, etc. They are not not to be taught but we can introduce. Today's generation can no longer be compared to the past where we always sat writing, silent, and calm. Now it's not the same anymore there must be interesting learning innovations and make children not bored. Currently in PPT Lotus which is located on Jalan Menanggal VII / RW RW 03 Menanggal Village, Gayungan Subdistrict, still uses the group learning model because of the condition of PPT which is in a dense and narrow environment. Lotus PPT consists of 2 study groups (Rombel) consisting of 1 group A and 1 group B. Group B. The total number of students is 21 children with 4 teaching staff, 1 head of PPT and 1 administrative staff. This condition reflects that the school is not permanent, but it is a pair of installments, because the place is actually a RW Hall. Efforts that have been made by teachers to motivate children to be more excited at school are by providing more games and toys provided as well as outdoor class activities. But the results are still not optimal because the costs incurred will be more and more. Whereas in this environment many parents are from the middle class and below, so if the costs are too much it will result in many who do not want to send their children to the PPT again.
The Management of Teaching in Online and Blended Learning Applied in the Project “Modern Competences of Academic Teachers – the Key to Modern Higher Education Institutions” – Acronym MOCAT

The management of teaching is connected and could be increased by using a wide range of different methods especially when we refer to Online and Blended learning. In the first part, the paper is aiming at reviewing the literature regarding the concepts and benefits of Online and Blended learning. Based on this considerations, 8 partner universities from 8 countries jointly developed the Project “Modern competences of academic teachers – the key to modern Higher Education Institutions (HEI)” – Acronym MOCAT. The paper underlines the goals and achievements of the MOCAT project that proposes a conceptual process to increase the management performance in teaching. The paper shows in an organized manner the main deficiencies that are altering the teaching competencies of academic teachers and in connection with this, the project offers solutions to improve the methodological competency of the teachers regarding the development and use of modern approaches. The outcomes of the project consist in the development and implementation of a Multicultural Model of an Academic Teacher Competencies and in 10 online courses that represent modern training materials in the field of teaching methodology. In the end are exposed the way the results of the project can be evaluated in time as well as the anticipated effects of the project implementation.
ARTISTIC AND CREATIVE ENVIRONMENT IN THE PROCESS OF FORMATION OF MUSIC-PERFORMANCE COMPETENCE OF THE FUTURE TEACHER OF MUSIC ART

The article substantiates the pedagogical conditions determined by the essence and content of musical performance activity of the future teachers of musical art. The effective pedagogical condition is the creation of art-creative environment, which integrates competence and personality oriented scientific approaches and is based on the principle of art-pedagogical dialogue. The scientific analysis of the investigated problem allowed determining the pedagogical conditions, which are determined by the essence and content of professional training, peculiarities of art education and allow effectively building the process of formation of musical and performing competence of future teachers of musical art. Such pedagogical condition is determined by the creation of art-creative environment on the basis of competence, personality-oriented and developing learning as pedagogically organized environment, which is conditioned by the specificity of professional activity of a future music art teacher characterized by the systemic interconnection of its objects, integrity, art and aesthetic functionality, provides the use of a set of pedagogical influences, which in turn contribute to the development of professionally significant personal qualities, the formation of artistic and communicative skills, the ability to communicate in a dialogue, creative activity, and to create opportunities for creative self-expression and self-realisation. Dialogue in music pedagogy is the essential basis of music education process, its methodological principle, as the music itself is an act of interpersonal communication. The art-pedagogical dialogue presupposes subject-subject interaction of all the participants of the art communication process, provides its spiritual and emotional richness, contributes to the formation of interpreting skills, development of creative activity of every student. Creating an artistic and creative environment is an effective pedagogical condition based on interdependent scientific approaches to learning, in particular, competence and personality-oriented. Dialogue principles of interaction between teacher and student involve the creation of a new type of communication – artistic and pedagogical dialogue, based on mutual understanding, exchange of views and judgments, evaluative approaches to artistic creativity. The result of such joint activities is the organization of independent creative and exploratory activities of students, knowledge, assimilation and acquisition of creative and executive experience, ability to independent creative activity, self-regulation, self-development, self-expression and self-realization in further professional and life activities.
The theory of the firm

In Part 1 of this book, I have shown that blockchain and antitrust have a common objective. But for antitrust to help blockchain communities, it must be enforceable, a subject I examine in this chapter. More specifically, I explain that the theory of the firm, as introduced by Ronald Coase in 1937, is a pillar of modern antitrust law. It is the foundation of the legal fiction on which antitrust rests (Section 1) and is thus an essential tool to analyze market dynamics and anticompetitive practices (Section 2). In the meantime, because one can ultimately define the firm as a zone where vertical control is used to minimize transaction costs, blockchain layer 1 doesn’t fit into it. It follows that the legal fiction of the “firm” does not capture the layer that serves as the underlying infrastructure for blockchain transactions. Blockchain thus falls beyond the confines of antitrust law. (Section 3).
Structured Learning and Prediction in Facial Emotion Classification and Recognition

Structured prediction methods have become, in recent years, an attractive tool for many machine-learning applications especially in the image processing area as in customers satisfaction prediction by using facial recognition systems, in criminal investigations based on face sketches recognition, in aid to autistic children and so. The main objective of this paper is the identification of the emotion of the human being, based on their facial expressions, by applying structured learning and perfect face ratios. The basic idea of our approach is to extract the perfect face ratios from a facial emotion image as the features, this face emotional images are labeled with their kind of emotions (the seven emotions defined in literature). For this end, first we determined sixty-eight landmarks point of image faces, next we applied a new deep geometric descriptor to calculate sixteen features representing the emotional face. The training and the testing tasks are applied to the Warsaw dataset: The Set of Emotional Facial Expression Pictures (WSEFEP) dataset. Our proposed approach can be also applied in others competitor facial emotion datasets. Based on experiments, the evaluation demonstrates the satisfactory performance of our applied method, the recognition rate reaches more than 97% for all seven emotions studied and it exceeds 99.20% for neutral facial images.
A new parallel data geometry analysis algorithm to select training data for support vector machine

&lt;abstract&gt;&lt;p&gt;Support vector machine (SVM) is one of the most powerful technologies of machine learning, which has been widely concerned because of its remarkable performance. However, when dealing with the classification problem of large-scale datasets, the high complexity of SVM model leads to low efficiency and become impractical. Due to the sparsity of SVM in the sample space, this paper presents a new parallel data geometry analysis (PDGA) algorithm to reduce the training set of SVM, which helps to improve the efficiency of SVM training. The PDGA introduce Mahalanobis distance to measure the distance from each sample to its centroid. And based on this, proposes a method that can identify non support vectors and outliers at the same time to help remove redundant data. When the training set is further reduced, cosine angle distance analysis method is proposed to determine whether the samples are redundant data, ensure that the valuable data are not removed. Different from the previous data geometry analysis methods, the PDGA algorithm is implemented in parallel, which greatly saving the computational cost. Experimental results on artificial dataset and 6 real datasets show that the algorithm can adapt to different sample distributions. Which significantly reduce the training time and memory requirements without sacrificing the classification accuracy, and its performance is obviously better than the other five competitive algorithms.&lt;/p&gt;&lt;/abstract&gt;
Blockchain: from ideology to implementation

Blockchain is a recent technology with ancient roots (Section 1). It all started during the sixties, in a van in California, owned by Stewart Brand who was editing the Whole Earth Catalog, a recollection of tools for individual empowerment. A few years later, cypherpunks made cryptography and privacy the new means for emancipating the individual from an oppressive state, very much in Brand’s fashion. Many processes used by blockchain stem from their work. Today, a new community has formed around this technology (Section 2). It stands in solidarity by sharing a common ideal.
A Novel Cluster Ensemble based on a Single Clustering Algorithm

In recent years, several cluster ensemble methods have been developed, but they still have some limitations.They commonly use different clustering algorithms in both stages of the clustering ensemble method, such as the ensemble generation step and the consensus function, resulting in a compatibility issue in terms of working functionality between different clustering algorithms.In addition, in a clustering ensemble method, the accuracy of the final results is a major concern.To deal with it, we propose a novel cluster ensemble method based on a single clustering algorithm (CES).In this method, we iterate a clustering algorithm affinity propagation (AP) ten times in the ensemble generation step to obtain multiple base partitions with a high level of diversity in each iteration due to its nature of producing a random number of clusters.Furthermore, with a few modifications, the same algorithm AP is used to propose a novel consensus function for combining these base partitions into a single partition.The proposed consensus function takes advantage of little side-information in the form of partial labels by using pairwise constraints with AP and number of clusters in a dataset.By employing this information, AP is limited to produce an actual number of cluster centres in a dataset rather than a random number of clusters, which considerably enhanced the accuracy of final outcomes.As a result, CES uses the same clustering functionality in both stages of proposed cluster ensemble method and produces the desired number of clusters in the final partition of a dataset which is significantly improving accuracy when compared to state-of-the-art cluster ensemble methods.Furthermore, as a result of these modifications, the CES outperforms AP in terms of accuracy and execution time.Experiments on real-world datasets from various sources show that CES improves accuracy by 5% on average compared to state-of-the-art cluster ensemble methods and by 55.54% compared to AP while consuming 44.60% less execution time.