Reviewerly/exHarmony huggingface dataset:
Issues of information technology crime control in the Republic of Turkey

The problem of cybercrime is a problem not only of domestic character but also of the whole world. Therefore, we decided to consider the experience of other countries in combating cybercrime. The article discusses the policy issues of the Turkish Republic in the field of combating the cybercrime. And also it was considered the experience of the police organizations work in this field in Turkey. The article analyzed the legislative framework of the Turkish Republic on the fight against cybercrime. The history of the development of police organizations and their work in this area was investigated and described in detail. The article also contains information about the policy of continuous education of employees on the fight against cybercrime and there was shown a scheme of work in the field of education. According to the results of the study we can confidently say that Turkey is currently doing effective work in combating cybercrime. The experience in this field can be used in the CIS countries and other countries to effectively combat crime in the field of information technology
Kesalahan Berbahasa dalam Majalah Pandawa IAIN Surakarta Edisi 2018 pada Tataran Ejaan dan Sintaksis

Language is a tool to express an opinion or statement that will be conveyed to others. There are two types in language media, namely oral language and written language. One work that uses written language as a communication medium is a magazine. To write a magazine, you must use a language structure that is good and right or in accordance with the rules of language. But often times in a magazine there are still many mistakes, for example, in the 2018 edition of Pandawa magazine, there are errors in language spelling and at the syntactic level. Types of language errors at the spelling level include errors in letter usage, word writing, use of punctuation, and combination spelling. Types of language errors at the syntactic level include, discourse, sentences, clauses, and phrases. This study aims to describe language errors, especially at the spelling level and at the syntactic level. The method used in this study is descriptive qualitative research, which describes the object of language errors in the 2018 edition of the Pandawa IAIN magazine. The techniques of data collection and data analysis are (1) collecting language errors, (2) identifying errors based on linguistic level (syntax, phonology, morphology, and spelling), (3) ranking errors, i.e. sorting errors based on the number of errors, (4) explaining conditions, explaining what is wrong, the cause of errors, and how to correct errors, (5) predicting linguistic level that is prone to errors, (6) correcting errors, namely correcting errors, finding the right way to reduce or eliminate these errors. The results of this study, namely errors in the spelling level in the Pandawa IAIN Surakarta magazine, there are capital letters writing errors, italics, punctuation marks, and hyphens; errors at the syntactic level in the Pandawa IAIN Surakarta magazine, there are mistakes in phrases, and sentences.
The matrix-valued numerical range over finite fields

In this paper we define and study the matrix-valued $k\times k$ numerical range of $n\times n$ matrices using the Hermitian product and the product with $n\times k$ unitary matrices $U$ (on the right with $U$, on the left with its adjoint $U^\dagger = U^{-1}$). For all $i, j=1,\dots ,k$ we study the possible $(i,j)$-entries of these $k\times k$ matrices. Our results are for the case in which the base field is finite, but the same definition works over $\mathbb {C}$. Instead of the degree $2$ extension $\mathbb {R}\hookrightarrow \mathbb {C}$ we use the degree $2$ extension $\mathbb {F} _q\hookrightarrow \mathbb {F} _{q^2}$, $q$ a prime power, with the Frobenius map $t\mapsto t^q$ as the nonzero element of its Galois group. The diagonal entries of the matrix numerical ranges are the scalar numerical ranges, while often the nondiagonal entries are the entire $\mathbb {F} _{q^2}$. We also define the matrix-valued numerical range map.
A Comparative Analysis of the Intensifiers Quite, Rather, and Pretty Used by Americans and British People: A Corpus Study

&lt;p&gt;Words have many different meanings and this can cause problems for nonnative speakers of English. Because words can mean many different things depending on the sentence that they appear in, Indonesian learners of English often have trouble telling the different meanings apart, especially when the words are synonyms or from specific group of words like intensifiers. From this, the writer would like to do a research on the topic of the comparison between American and British English. The research is limited to comparing the intensifiers &lt;strong&gt;&lt;em&gt;quite&lt;/em&gt;&lt;/strong&gt;, &lt;strong&gt;&lt;em&gt;rather&lt;/em&gt;&lt;/strong&gt;and &lt;strong&gt;&lt;em&gt;pretty&lt;/em&gt;&lt;/strong&gt;. The data is taken from COCA for the American English and BNC for the British English. The result shows that in general, the three intensifiers are more or less similar in meaning, with only slight differences. The usages of these three intensifiers by Americans and British people are also not too different.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt; intensifier, American and British people, corpus
IMPLEMENTASI STRATEGI BERMAIN PERAN DENGAN STIK BONEKA UNTUK MENINGKATKAN KREATIVITAS DAN KEMAMPUAN BERBICARA BAHASA INGGRIS

The research investigated how the implementation of stick puppet role play in enhancing the speaking ability is. The reseach method used was Classroom Action Research proposed by Kemmis and Mc Taggart. The procedures contained five steps: modeling, drafting, creating, rehearsing, dan performing. In modeling, the teacher gave models of several types of conversations. In drafting, the students made the drafs of the conversations while in creating, the students made stick puppets as characterized in the conversations. Next in rehearsing, the students practiced how to do role play using stick puppets while the teacher gave feedback for the improvement. At last, in performing, the students performed the role play and was recorded by the observer. The result showed that from thirty two students, twenty six students got predicate fair, two students got predicate good, and four students got predicate very good. Therefore, 32 students (100 %) were able to reached the criteria of success as their scores were at least or more than 70. The mean score was 74. The highest scores was 85 dan the lowest score is 70. This strategy is able to give positive impacts to the students in delivering the vocabulary, getting the easiness of showing ideas, improving the speaking skill, enhancing excitement, enthusiasm, confidence, and the efectiveness of the strategy. English teachers are suggested to use this strategy in teaching speaking for other language functions and genres. To the future researcher, it is suggested to do research on the receptive skill such as listening and reading as this study focuses on the productives skill especially speaking skill.
Priors for Diversity and Novelty on Neural Recommender Systems

PRIN is a neural based recommendation method that allows the incorporation of item prior information into the recommendation process. In this work we study how the system behaves in terms of novelty and diversity under different configurations of item prior probability estimations. Our results show the versatility of the framework and how its behavior can be adapted to the desired properties, whether accuracy is preferred or diversity and novelty are the desired properties, or how a balance can be achieved with the proper selection of prior estimations.
MEMBACA TEKS/BUKU BERBAHASA INGGRIS BERSAMA ANAK-ANAK DI SMA NEGERI 1 ABEPURA JAYAPURA

The community service activity aims to be able to help improving the ability and English language skills of children at Abepura 1 Public High School, foster a love of reading English texts / books, and also to increase children's sense of enlightenment in reading texts or books. in English language. The specific purpose of the service activities for children at Abepura 1 High School introduces the folklore text from the Dani (Wamena) tribe that has been translated into English that is suitable for the age of the high school students, which are fun and interesting, so hopefully, the love of local culture in the form of Papuan folklore would also increase. The community service activities involved several students of English Language Education Study Program FKIP, who had participated in the KBA course (Middle / High School Curriculum and Teaching Materials), where this activity was also one form of application of the learned science and theory in the course. This community service activity was held for approximately one month including the selection of Dani folklores, deepening of folklore material, making media to deliver text to children, and explaining the participants students from English Language Education Study Program FKIP UNCEN about their understanding of folklore texts given through learning media he made before going to the field, surveying the location, implementation, and results seminar. This activity is useful for deepening the knowledge of English for children in SMA Negeri 1 Abepura, Jayapura, in understanding English texts through Dani folklores so that it will enhance both the sense of mind and confidence in reading English texts and love of stories people who have culture around their environment. The use of local folklore and the creation of media used to invite children to read while learning is a valuable field experience for prospective students of English teachers in the English Language Education Study Program FKIP UNCEN in applying their knowledge and knowledge.Keywords: Reading English Texts, Children, Papuan Folklore, Jayapura
Moving Beyond Labels: Text, Images and Biases in Categorization

Recent research has emphasized that signaling clear membership in product categories influences how products perform. In this paper we focus on two shortcomings in the categorization literature. First, while prior literature has focused primarily on category labels as signals of categorical membership, other mechanisms that communicate association to a category–such as semantic networks and images–have been under-researched. We draw on the literature on multi-modal processing of information to explain how text-based mechanisms such as the use of labels and semantic networks differ from visual-based mechanisms such as the use of images. Second, the prior literature has overlooked the asymmetry in the effect of positive and negative labels on performance. We draw on an extensive literature within psychology to argue that negative labels have a stronger effect on performance than positive labels. Using original data from the crowdfunding website Indiegogo from 2010 to 2015, we find that both text-based mechanisms, semantic networks and labels, and visual mechanisms of signaling category membership are associated with performance. Our findings also suggest that images convey category membership by activating different cognitive structures than text. Furthermore, we find that labels with negative valence have a stronger effect on performance than positive labels. Our study theorizes and provides empirical support for a more complete understanding of how producers can signal categorical membership to shape the performance of their products.
PLEC, A Participative Processfor GUI Prototyping

GUI is one of the key aspect of an information system from the point of view of customers and users. This paper introduces PLEC, a participative process for designing GUI interfaces with the collaboration of the final users and stakeholders. Participants do not need technical knowledge of GUI prototype. A case study has been developed and carried out to verify if PLEC process is feasible.
3D-like Bounding Box for Vehicle Detection

In this work, we propose a 3D-like bounding box to detect vehicles in RGB image based on the 2D bounding box detection. Taking advantage of key-points detection by detecting eight corners of the 3D box surrounding the vehicle, our 3D-like bounding box is capable of estimating the vehicle position more accurately than traditional object detection methods, while provides the information of the front and back of the vehicle or even the orientation that is of great help in advanced driver assistance system. We present two improved strategies for data annotation to evaluate the proposed method. The experiments on KITTI object detection database show that our presented two strategies exhibit promising performance.
Improving Deep Learning for Face Verification Using Color Histogram Equalization Data Augmentation

This paper proposes a new method of improving face verification learning using color histogram equalization by incorporating the results of deep convolutional neural networks (CNNs).The entire process of face verification using deep learning and color histogram equalization is described in detail.This research uses advanced deep learning methods for face verification tasks.Because the CNN achieves the best results for larger datasets, the main challenge is to increase the smaller dataset enhancements and validate in environments different from the training datasets.This paper presents a new training enhancement method.When the face-image datasets were small, we could use our enhanced method to expand the dataset and improve the accuracy of face verification to adopt different environments.Consequently, the accuracy reached 99.7996%, i.e., approximately 7% higher than the result trained on the original dataset.
High-order moment Bayesian state estimation of nonlinear Markov jump system

To deal with problem of complexity in state distribution, a recursive state estimator with high-order moment component form of a nonlinear Markov jump system (MJS) with state variable non-Gaussian. The nonlinear MJS is transformed into a nonlinear deterministic system with high-order moment component form by means of cumulant generating function. Based on the transformed single-mode nonlinear deterministic system, a recursive state estimation in Bayesian framework is given to estimate the error of the state with high-order moment component form. To describe the non-Gaussian state distribution, the generalized Gaussian distribution (GGD) is used which introduces the high-order moment information compared with the first- and second-order information, mean and variance in Gaussian distribution (GD). With the help of high-order moment information such as the skewness and kurtosis in the GGD, the performance of state estimation will be much more precise. The numerical example in the simulation part shows the performance of the state estimation and the comparison of errors in different moment, which demonstrate the effectiveness.
Error Analysis on Han Character Stroke Writing (汉字 Hànzì) of Mandarin Language Teachers (Participants on Training for Senior High Schools/Vocational Schools/ Islamic High Schools Chinese Language Teachers on Critical Literacy and HOTS)

ABSTRACT&#x0D; Mandarin language has been one of the subjects in 2013 Curriculum as one of the foreign languages taught in schools starting from elementary to universities. Due to high interest in Chinese language in opening career opportunities to people who can master the language, there is also an increase of interest on not only the language but also on how to teach the language. Teachers in this context the teachers of Mandarin language at least master the basic of teaching Mandarin language in the five elements. On this matter, there are errors in the writing of Han Characters that occurs during the learning process on learners and teachers. The errors cover the strokes misalignment on written texts of describing oneself. This study analyzes the common mistakes of Chinese stroke writing on Teachers of Chinese language teachers in Indonesia on training programmes.&#x0D; Key Words: Han Characters; Error Analysis in writing; writing misalignment; Chinese stroke writing and Mandarin Language Teachers.
The Effect of Transformational Leadership on Innovation in Syrian Universities

Previous studies have pointed out that transformational leadership is an important factor affecting innovation in an organization.However, there is a lack of models linking transformational leadership and innovation at universities within developing countries, particularly Syria.The purpose of this study was to examine the effect of transformational leadership on innovation in Syrian universities.The quantitative method was used in data collection.A stratified random sampling technique was conducted which comprised of 368 valid responses to test the causal relationship between transformational leadership and innovation.PLS-SEM technique was used to analyze the relationship between the variables in this study.The results show that there was a significant relationship between transformational leadership and innovation.
Active Reading Comprehension: A Dataset for Learning the Question-Answer Relationship Strategy

Reading comprehension (RC) through question answering is a useful method for evaluating if a reader understands a text.Standard accuracy metrics are used for evaluation, where a high accuracy is taken as indicative of a good understanding.However, literature in quality learning suggests that task performance should also be evaluated on the undergone process to answer.The Question-Answer Relationship (QAR) is one of the strategies for evaluating a reader's understanding based on their ability to select different sources of information depending on the question type.We propose the creation of a dataset to learn the QAR strategy with weak supervision.We expect to complement current work on reading comprehension by introducing a new setup for evaluation.
Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding

We describe a new way of reasoning about symmetric collisions for Multi-Agent Path Finding (MAPF) on 4-neighbor grids. We also introduce a symmetry-breaking constraint to resolve these conflicts. This specialized technique allows us to identify and eliminate, in a single step, all permutations of two currently assigned but incompatible paths. Each such permutation has exactly the same cost as a current path, and each one results in a new collision between the same two agents. We show that the addition of symmetry-breaking techniques can lead to an exponential reduction in the size of the search space of CBS, a popular framework for MAPF, and report significant improvements in both runtime and success rate versus CBSH and EPEA* – two recent and state-of-the-art MAPF algorithms.
The Green Indicator System of Distance Open Education Based on the APP Terminal Learning

With the help of the APP learning platform, learners can make the real-time and seamless access to the top-quality curriculum resources, community education resources and teaching resources of the open education platform, and obtain the relevant information of the educational administration systems, including the learning achievement, the learning progress and the examination information. The App has not only stimulated the students’ initiatives and enthusiasms in learning, but also properly solved the existing problem of the information island. This makes it possible for learners to carry out the debris learning in any place and at any time, which provides a reference for other colleges to develop their APPs.
An algorithm for rationality estimation of movement trend based on big data analysis

The traditional reasonable estimation algorithm of data movement trend has some problems, such as easily falling into local optimum, high computational complexity, and poor generality. This paper presents a reasonable estimation algorithm of data movement trend based on big data analysis. The combination of particle swarm optimization (PSO) and mutation operation can prevent the stagnation of particle swarm evolution and improve the estimation ability. While using the PSO algorithm for global search, it combines the characteristics of the movement vector effectively, selects the appropriate particle population, and uses the appropriate termination strategy to reduce the computational complexity and obtain the constraint conditions of the trend trajectory of the data movement. Through the database system center server and the location server, the data access is carried out co processing and querying, and the differential evolution algorithm is used to estimate the original database in the system initialization stage. Experiments show that the proposed algorithm can reasonably estimate the trend of data movement under big data analysis, with low computational complexity and good versatility.
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract)

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the requirement of maintaining symmetric weights in a physical neural system. To better understand RBP, we compare different algorithms in terms of the information available locally to each neuron. In the process, we derive several alternatives to RBP, including skipped RBP (SRBP), adaptive RBP (ARBP), sparse RBP, and study their behavior through simulations. These simulations show that many variants are also robust deep learning algorithms, but that the derivative of the transfer function is important in the learning rule. Finally, we prove several mathematical results including the convergence to fixed points of linear chains of arbitrary length, the convergence to fixed points of linear autoencoders with decorrelated data, the long-term existence of solutions for linear systems with a single hidden layer and convergence in special cases, and the convergence to fixed points of non-linear chains, when the derivative of the activation functions is included.
Rancang Bangun Engine ETL Data Warehouse dengan Menggunakan Bahasa Python

Big companies that have many branches in different locations often have difficulty with analyzing transaction processes from each branch. The problem experienced by the company management is the rapid delivery of massive data provided by the branch to the head office so that the analysis process of the company's performance becomes slow and inaccurate. The results of this process used as a consideration in decision making which produce the right information if the data is complete and relevant. The right method of massive data collection is using the data warehouse approach. Data warehouse is a relational database designed to optimize queries in Online Analytical Processing (OLAP) from the transaction process of various data sources that can record any changes in data that occur so that the data becomes more structured. In applying the data collection, data warehouse has extracted, transform, and load (ETL) steps to read data from the Online Transaction Processing (OLTP) system, change the form of data through uniform data structures, and save to the final location in the data warehouse. This study provides an overview of the solution for implementing ETL that can work automatically or manually according to needs using the Python programming language so that it can facilitate the ETL process and can adjust to the conditions of the database in the company system.