Reviewerly/exHarmony huggingface dataset:
ANALISIS MINAT BELAJAR DARING MATEMATIKA SISWA KOMUNITAS STUDYGRAM KELAS VII SEKOLAH MENENGAH PERTAMA

This study aims to analyze the interest in learning mathematics online of students who are members of the StudyGram community and the positive impact it has. So that learning innovations can be developed using StudyGram to increase interest in learning mathematics online. The research method is descriptive research. The population in the study were 13 students of grade VII SMP who are members of the StudyGram community in Indonesia, the sample was taken by purposive sampling, with the following inclusion criteria: 1) Having a StudyGram account; 2) Class VII high school students in Indonesia. Exclusion criteria; 1) Not actively posting learning materials; 2) Not part of the StudyGram community in the WhatsApp group. The data collection technique used a scale questionnaire of students' mathematics learning interest which contained 10 statements with 7 indicators. The data analysis technique uses the formula for the percentage of students' answers and is described by the criteria for interpreting the percentage of answers. The results of the analysis show that students in the study program community have an interest in learning mathematics, this can be seen from the majority of students having an interest in learning mathematics. With this, online learning innovations can be developed using StudyGram.
L’autorità tecno-procedurale del diritto e un destino della politica

Historical crisis of democracy and its representative forms suggests a crisis of the transcendental foundation of politics on values and will. New technological tools seem to fill the gap between representative political institutions and represented political actors. Are the A.I. innovative technologies in lawmaking able to restore a political demand in front of the law or the modern technic of lawmaking in western civilization is in itself free from the need of politics due to its techno-procedural authority?Keywords: Techno-normativity; Positive law; Juridical nihilism.
Colour thresholding-based automatic Ki67 counting procedure for immunohistochemical staining in meningioma

Nuclei segmentation is the initial process in the histopathological image analysis. This process plays a vital role in cell counting. The Ki67 is a nuclear that was widely used among the pathologists to measure the tumour cell proliferation. Generally, the pathologists use the manual counting technique for counting the Ki67 cells. However, the counting results have poor reliability and lack of accuracy. The current study aimed to propose an automatic Ki67 cell counting for meningioma images by using the colour thresholding approach. The proposed method has been tested on 12 photomicrographs of meningiomas. The results showed that the proposed method was able to segment the positive and negative Ki67 cells with an average accuracy of more than 90%. For counting results, the proposed system produced good results in counting the Ki67 cells with an average relative accuracy of 0.91 for positive Ki67 cells and 0.89 for negative cells.
Multiple sclerosis â Diagnosis, Types and Complications

Multiple Sclerosis (MS) may be a doubtless disabling illness of the brain and medulla spinalis (central nervous system).In MS, the system attacks the protecting sheath (myelin) that covers nerve fibers and causes communication issues between your brain and therefore the remainder of your body. Eventually, the disease will cause permanent injury or deterioration of the nerves.
UPAYA PENINGKATAN MINAT BACA DI LINGKUNGAN SEKOLAH DAN MASYARAKAT DI SMA NEGERI 1 JEBUS PADA TAHUN 2019

The library is the heart of the formal education world, so the library needs to be arranged in such a way as to become a space or place that is interesting and fun for all readers. Informing or organizing a library, it is necessary for the cooperation of all school residents to obtain the expected results. This paper seeks to explain the efforts of schools and libraries in increasing student and community interest in reading. In order to attract students to visit the library of Jebus 1 Public High School, librarians package the library in such a way as to give the name Depati Bahrin reading park with the aim to arouse interest, increase references by procuring new books, widening space and spatial planning, working with stakeholders, establishing gazebos, forming natural classes, procuring information literacy galleries, procuring mobile literacy with keraca (reading baskets), adding supporting libraries and thematic libraries, and adding facilities and infrastructure including security gates, barcodes, air conditioners, etc.From the various efforts that have been made by the school and librarians, there has been an increase in visits from both students and the community, this library also gained achievements at the local, regional and national level.
Integrating rules and ontologies in the First-order stable model semantics (Preliminary Report)

We present an approach to integrating rules and ontologies on the basis of the first-order stable model semantics proposed by Ferraris, Lee and Lifschitz. We show that some existing integration proposals can be uniformly reformulated in terms of the first-order stable model semantics. The reformulations are simpler than the original proposals in the sense that they do not refer to grounding.
A Recommendation Algorithm Based on Efficient Dense Subsequence and Data Generation

The recommendation effect of the user-based collaborative filtering algorithm is improved by extracting the effective dense sub-sequence between the user and the project and generating the data information of the project that the user participates in with high probability, The problem of data sparsity is alleviated to some extent, and the validity of binary data method in expressing user interest is verified.[methods]There are two steps to extract the effective dense subsequences from the user rate sequence, Firstly, the effective dense subsequence is extracted based on the time range; secondly, the subsequence is extracted twice by judging the items in the subsequence with high probability that do not conform to the user's interest.Generating data for projects with high probability of user participation requires the use of project attributes of user participation projects.The validity of the binary data method is mainly verified by the comparison experiment with the scoring data and the final result of the recommendation algorithm.[results] The experimental results show that RMSE (root mean square error) is reduced by more than 0.04 on the ml-latest-small data set compared with the classical traditional collaborative filtering algorithm.When F value (the harmonic mean of accuracy and recall rate) is taken as the evaluation standard, the algorithm proposed in this paper is more accurate than other classical algorithms, and the recommendation accuracy has been significantly improved.[conclusions] The method of extracting the effective dense subsequence between the user and the project is better than the traditional collaborative filtering method in terms of recommendation effect, and using binary data in the algorithm to replace the original rate data can bring better recommendation effect.
Concept of Designing Online Manuals

In recent years, no field of human activity has advanced as rapidly as in the field of computer technology. Here, the most impressive advances have been made in the creation of the Internet and, as a consequence, web technologies. The article deals with the formation of the concept of online leadership both in general terms and taking into account the specifics of the educational environment of Georgia. Based on our interests, it is proposed to provide training materials to users simultaneously in several, at least two languages. The concept of the formation of such guides proposed in the article is considered on the example of teaching the Javascript language of one of the subject on web technologies. In particular, the article deals with the development of structuring rules and the name of files containing training materials that would make it easy to make the changes required over time.
Информационно-педагогическая технология формирования профессиональной компетентности будущего педагога-математика

The article substantiates the relevance of the formation of professional competence of the future teacher-mathematician through the development and use of information and pedagogical technology as a practical way to implement the competence approach in the educational process. The information and communication subject environment on school mathematics course on the updated educational program in the virtual system Moodle is offered as the developed means of formation. The results of the study are shown: the theoretical foundations and the main provisions of the formation of professional competence of the future teacher-mathematician through the development of information and communication subject environment for the school course of mathematics are defined; the qualitative indicators of the components of professional competence are defined; criteria of formation of professional competence of future teacher of mathematics are developed; it is shown that the direct participation of future teachers of mathematics in the development of information and communication subject environment on school mathematics contributes to the formation of their professional competence. The methodological basis of the study is the basic provisions of the theory of knowledge and competence formation, personal-activity approach, theoretical provisions on the relationship of learning and development, pedagogical and innovative technologies in the education system, the theory of gradual formation of concepts and mental actions of P. Y. Galperin, the concept of the educational system of Kazakhstan. The practical significance of the research results lies in the fact that the development of the information and communication subject environment in the Moodle virtual system according to the school course of mathematics will allow the future teacher: to learn to recognize the real state of the education system at the moment; to carry out informational interaction of users in the educational space, both among themselves and with on-screen representations of the studied objects; influence the processes or phenomena under consideration, educational plots of a given specific subject area; to be able to work in the context of the implementation of built-in learning technologies, focused on the laws of this particular subject area.
Techniques for Representing the Author in Alexander Sokurov’s films

One of the features of A. Sokurov's art is the author's manifest subjectivation of the material. In addition to the implicit presence of the author evident in the choice of the idea, the main character, the entire artistic solution, the director explicitly manifests himself in films. In this regard, both the degree and the quality of the author's presence in his own work are of interest. The focus of this study is the obviousness of the author's direct involvement in the very fabric, the structure of the film. The main purpose of the work is to identify and study the methods of the author's self-representation. The article analyzes films united by the pronounced author's presence: the so-called cycle of non-fiction “Elegies”, the films “Maria”, “Russian Ark” and “Francophonie”. This approach makes it possible to identify several basic techniques the director uses to represent the author's image. The first one is typical of Sokurov’s art and presupposes the author who becomes the narrator of the film and models the narrated construction into a subjective artistic image. Another way of doing it, when the author acts as an interviewer, the latter is replaced by a silent interlocutor observing his hero. In this case, the director uses the principle of long-term observation, which allows him to see what is usually hidden behind words and external phenomena. Perhaps, the very unique way is turning Sokurov himself into the main character of his own film. Here the maximum subjectivation is achieved: the author shares his thoughts, feelings, enters the frame, actively interacts with the characters, forcing them to violate the principle of the “fourth wall”. Sokurov even removes the figure of the actor and takes his place himself, in order to literally appeal directly to his viewer, lure him after with him. Thus, this study allows us to reveal Sokurov's combination of documentary cinema, television broadcasting, first-person computer game technologies and augmented reality simulators, expanding the boundaries of filmic reality and the language of cinema.
A Generative Model Based Approach for Zero-Shot Breast Cancer Segmentation Explaining Pixels’ Contribution to the Model’s Prediction

Deep learningDeep learning has extensively helped us to analyze complicated distributions of data and extract meaningful information from the same. But the fundamental problem still remains—what if there is no or rare occurrence of any instance which needs to be predicted? This is a significant problem in the health-care sector. The primary motivation of the work is to detect the region of anomaly in the context of breast cancerBreast cancer detection. The novelty here lies in designing a zero-shot learning induced Generative Adversarial Network (GAN)Generative adversarial networks based architecture which has the efficacy to detect anomaly and thereby to discriminate the healthy and anomalous images even if the network is trained with the healthy instances only. In addition, this work has also been extended to segmentation of the anomalous region. To be precise, the novelty of this approach lies in the fact that the GAN takes only healthy samples in the training phase, though it is capable of segmenting tumors in the “unseen” anomalous samples explaining each pixel’s contribution to the model’s prediction. Experiments have been conducted on the mini MIAS breast cancerBreast cancer dataset and significantly appreciable results have been obtained.
Recommendation Decision Support System Smartphone Selection By Method Web-Based Simple Additive Weighting (SAW)

Smartphones are already a must-have communication technology to make it easier to live your daily life. However, with so many choices can make consumers confused in determining the appropriate choice. The Simple Additive Weighting (SAW) method can help in the simple process that can be applied to decision-making cases such as in smartphone selection recommendations with a wide range of attributes. In the case of this study, the results were obtained that the Realme X3 Superzoom smartphone scored the highest preference with a value of 22. With this research, it is hoped that this decision support system can help potential consumers to more easily consider in the selection of smartphones that suit their wishes or needs
Prediction Of The Number Of Tourists To Visit Bali Province Using Backpropagation Artificial Neural Network (Case Study: Data 1990-2016)

Bali Island is the most popular tourist destination in Indonesia. The total number of foreign tourists visiting Indonesia through the entrance of Ngurah Rai Airport reached 40% as of October 2016, with the value of Bali's foreign exchange receipts for Indonesia from the tourism sector amounting to 70 Trillion Rupiah. Minister of Tourism (Menpar) Arief Yahya always uses the password "Bali" in promoting destinations throughout the world. Because in tourism, Bali is a gate that is passed by 40 percent of foreign tourists (tourists) to Indonesia. In support of more accurate decision making, the author makes a system of forecasting numbers of foreign tourists visiting Bali Province by taking a sample of Japan. Factors that are used as input to make predictions include the number of tourists visiting before, the population of the country of origin of foreign tourists, Gross Domestic Product, and the Relative Consumer Price Index of the countries of origin of foreign tourists. In this research, optimization of the activation function, hidden neuron, and learning rate parameters is performed. Forecasting results using the backpropagation method produce a pretty good accuracy with an accuracy of Mean Square Error = 0.0050558, and test data accuracy of MSE = 0.031695. ANN architecture in the training process is then used to calculate predictions of visits by foreign tourists in the testing process
EN Solar panels work and control system modeling in LabVIEW and LTSpice XVII. Comparison of the perspectives of panels using

This paper is dedicated to the research of solar energy issues, namely to increase the efficiency of solar panels and to compare the performance of solar panels in different configurations. The author researches and compares the performance of solar panels with and without trackers. The sun is an inexhaustible source of energy that mankind has yet to appreciate. Solar energy is the kinetic energy of radiation (mainly light) generated by thermonuclear reactions in the bowels of the sun. Solar energy is one such alternative, the neglect of which will in the near future lead to catastrophic consequences for humanity. Solar energy is a progressive method of obtaining various types of energy through solar radiation. Solar energy is one of the most promising and dynamic renewable energy sources (RES). Each year, the increase in commissioned capacity is approximately 40-50%. In the last fifteen years alone, the proportion of solar electricity in the world has exceeded the 5% mark. To increase the efficiency of solar panels, designers and engineers are developing new devices and devices, one of which is a solar tracker. A solar tracker is a device that allows you to control the movement of the sun across the sky, as well as move the solar panel to the position where the absorption of sunlight is most effective. After the conducted experiment , calculations an comparison we can see the next results. Without the solar tracker our panel generated maximum power in 2.4 Watt. After the solar tracking system integration, our panel generated almost 20 (19.8) Watt of power! After this comparison we can tell that the generated power increase in 8.25 Watts. We can also admit that the amount of generated power depends on light intensity. But solar panels are the most effective when the solar beam falls perpendicular to solar cell and solar panel is at an angle of 75 – 85 degrees
Graph Algorithms and Applications

This chapter provides a discussion of various sequential graph algorithms and issues in their implementations. After describing fundamental algorithms like traversals, shortest paths, etc., more specialized algorithms such as betweenness centrality, page rank, etc. follow. The chapter ends with a focused discussion of applications of graph analytics in different domains such as graph mining and graph databases.
Trends in the methodology of media consumption study in the field of cinema in Russia

The relevance of the topic is conditioned by the need for scientific understanding of media analytics and a qualitative understanding of its methods as promotion tools, as well as for the introduction of the research stage of media consumption into the film production process to popularize and further promote domestic film products among the Russian audience. In the Russian film industry, this experience is especially necessary within modern economic conditions. The need to ensure the financial success of Russian film products, which are subsidized by the state, has led to the interest in finding new approaches promoting and increasing the loyalty of the cinema audience, which is especially important at a time when only 1 out of 10 domestic films pays for their film production during the distribution period.
The sonic creative process through Ciat-Lonbarde modular synthesizers

Media files notes:Sound Composition.Description:The artistic component of the master's thesis: a sound composition.
OGGN: A Novel Generalized Oracle Guided Generative Architecture for Modelling Inverse Function of Artificial Neural Networks

This paper presents a novel Generative Neural Network Architecture for modelling the inverse function of an Artificial Neural Network (ANN) either completely or partially. Modelling the complete inverse function of an ANN involves generating the values of all features that corresponds to a desired output. On the other hand, partially modelling the inverse function means generating the values of a subset of features and fixing the remaining feature values. The feature set generation is a critical step for artificial neural networks, useful in several practical applications in engineering and science. The proposed Oracle Guided Generative Neural Network, dubbed as OGGN, is flexible to handle a variety of feature generation problems. In general, an ANN is able to predict the target values based on given feature vectors. The OGGN architecture enables to generate feature vectors given the predetermined target values of an ANN. When generated feature vectors are fed to the forward ANN, the target value predicted by ANN will be close to the predetermined target values. Therefore, the OGGN architecture is able to map, inverse function of the function represented by forward ANN. Besides, there is another important contribution of this work. This paper also introduces a new class of functions, defined as constraint functions. The constraint functions enable a neural network to investigate a given local space for a longer period of time. Thus, enabling to find a local optimum of the loss function apart from just being able to find the global optimum. OGGN can also be adapted to solve a system of polynomial equations in many variables. The experiments on synthetic datasets validate the effectiveness of OGGN on various use cases. Our code is available at https://github.com/mohammadaaftabv/OGGN .
Intelligent prediction of HER2 status based on breast histopathology

Objective: To study the association between histopathological features and HER2 overexpression/amplification in breast cancers using deep learning algorithms. Methods: A total of 345 HE-stained slides of breast cancer from 2012 to 2018 were collected at the China-Japan Friendship Hospital, Beijing, China. All samples had accurate diagnosis results of HER2 which were classified into one of the 4 HER2 expression levels (0, 1+, 2+, 3+). After digitalization, 204 slides were used for weakly supervised model training, and 141 used for model testing. In the training process, the regions of interest were extracted through cancer detected model and then input to the weakly supervised classification model to tune the model parameters. In the testing phase, we compared performance of the single- and double-threshold strategies to assess the role of the double-threshold strategy in clinical practice. Results: Under the single-threshold strategy, the deep learning model had a sensitivity of 81.6% and a specificity of 42.1%, with the AUC of 0.67 [95% confidence intervals (0.560,0.778)]. Using the double-threshold strategy, the model achieved a sensitivity of 96.3% and a specificity of 89.5%. Conclusions: Using HE-stained histopathological slides alone, the deep learning technology could predict the HER2 status using breast cancer slides, with a satisfactory accuracy. Based on the double-threshold strategy, a large number of samples could be screened with high sensitivity and specificity.