Reviewerly/exHarmony huggingface dataset:
GRAMMATICAL MISTAKES IN WRITING NARRATIVE TEXT BY EEC STUDENTS

ABSTRACT&#x0D; This article explores about grammatical mistakes in writing narrative text in English Extensive course (EEC). EEC is an English program held by Sanata Dharma University. In case, there are five srtudents as participants that learn writing as subject in EEC. In learning writing, EEC students face some problems especially grammatical errrors. This article raises some problems and difficulties to write a narrative text by EEC students. This research used descriptive qualitative as a methodogy. Data collection are analyzed through the narrative text and the grammatical method. The aim of this research is to find, even in higher education level, there still found mistakes in grammar. Not mentioning vocabulary or certain spelling. Beside that reasearchers wants to find how much mistakes that has been made in grammar and mistakes that often made by students in learning writing. In conclusion, the result showed there was every student made error in each indicator. And the most error that students made was error in tense.&#x0D; Keywords: Grammatical Mistakes; Narrative Text; English Extension Course
Evaluation of Deep Learning and Conventional Approaches for Image Steganalysis

Steganography is the technique that’s used to embed secret messages into digital media without changing their appearances. As a countermeasure to steganography, steganalysis detects the presence of hidden data in a digital content. For the last decade, the majority of image steganalysis approaches can be formed by two stages. The first stage is to extract effective features from the image content and the second is to train a classifier in machine learning by using the features from stage one. Ultimately the image steganalysis becomes a binary classification problem. Since Deep Learning related architecture unify these two stages and save researchers lots of time designing hand-crafted features, the design of a CNN-based steganalyzer has therefore received increasing attention over the past few years. In this paper, we will examine the development in image steganalysis, both in spatial domain and in JPEG domain, and discuss the future directions.
Improving Studentsâ€™ Reading Comprehension On Narrative Texts Using Reap Strategy

ABSTRACTThe objective of this research was to find out whether or not there was significant difference on reading comprehension achievement between the eleventh grade students of SMA Karya Ibu Palembang who were taught by usingÂ Â REAP technique and those who were not. The population of this research was the eleventh graders of SMA Karya Ibu Palembang. 62 students were selected as the sample of this study by using purposive sampling technique. They were divided into two groups, experimental and control group. Each of them consisted of 31 students. To conduct this research, quasi experimental design was applied. The instrument for collecting data used was reading comprehension test that was distributed to the sample twice (pretest and posttest). There were 30 valid items of questions in the form of multiple choices. The result of the test was analyzed by percentage formula. The data obtained were also analyzed statistically by using SPSS. The result of the test showed that the significance two tailed was 0.027 which was lower than 0.05. With df 60, the result of independent sample t-test revealed that the t-table was 2.0003. As the t-obtained was higher than t-table (2.260), hence the null hypothesis (Ho) was rejected and the alternative hypothesis (Ha) was confirmed. It can be said that there was a significant difference on reading comprehension achievement between the students who were taught by using REAP (Reading, Encoding, Annotating, Pondering) technique, and those who were not.Keywords : Reading Comprehension, REAP Technique, Narrative TextsABSTRAKTujuan penelitian ini adalah untuk mengetahui adakah perbedaan yang signifikan terhadap prestasi pemahaman membaca antara siswa kelas XI SMA Karya Ibu Palembang yang diajar dengan menggunakan teknik REAP dan yang tidak. Populasi dalam penelitian ini adalah siswa kelas XI SMA Karya Ibu Palembang. 62 siswa dipilih sebagai sampel penelitian ini dengan menggunakan teknik purposive sampling. Mereka dibagi menjadi dua kelompok, kelompok eksperimen dan kelompok kontrol. Masing-masing terdiri dari 31 siswa. Untuk melakukan penelitian ini, desain quasi eksperimental diterapkan. Instrumen untuk mengumpulkan data yang digunakan adalah tes pemahaman membaca yang dibagikan kepada sampel sebanyak dua kali (pretest dan posttest). Ada 30 item pertanyaan yang valid dalam bentuk pilihan ganda. Hasil tes dianalisis dengan rumus persentase. Data yang diperoleh juga dianalisis secara statistik dengan menggunakan SPSS. Hasil tes menunjukkan bahwa signifikansi two tailed adalah 0,027 yang lebih rendah dari 0,05. Dengan df 60, hasil dari sampel independen t-test menunjukkan bahwa t-tabel adalah 2.0003. Karena t-hitung lebih tinggi dari t-tabel (2,260), maka hipotesis nol (Ho) ditolak dan hipotesis alternatif (Ha) dikonfirmasi. Dapat dikatakan bahwa ada perbedaan yang signifikan pada pencapaian pemahaman membaca antara siswa yang diajar dengan menggunakan teknik REAP (Reading, Encoding, Annotating, Pondering), dan mereka yang tidak.Kata kunci: Pemahaman Membaca, Teknik REAP, Narrative Texts
Grammatical Optionality in Translations

Previous research has repeatedly shown that translations in English exhibit a clearer preference for explicit that (vs. a zero marker) in complement clauses compared to non-translated English. The present chapter investigates whether this explicitation tendency in translations can be confirmed in a large dataset of Dutch-to-English translations and which underlying mechanisms guide translators to use that much more often than a zero marker. The results of the analysis show that translators indeed prefer the explicit signal significantly more often than non-translators; via a novel multivariate approach – MuPDAR (Gries & Deshors 2015) – it was found that this preference is related to risk aversion (that is the safest variant to choose, since it is the more frequent option and it clearly demarcates the syntactic structure) and source-language transfer (the absence of Dutch dat in the source sentence led translators to choose the zero marker more often); a clear effect of parallel-language complexity, however, could not be found.
Developing Junior Pupils’ Orthoepic Skills at the Russian Lessons

The article is devoted to the problem of junior pupils’ orthoepic training at the Russian lessons. The authors reveal techniques to develop orthoepic skills at the primary-school Russian lessons, show the potential of orthoepic training at the Russian lessons by the example of a primary-school educational and methodological programme, introduce and describe different types of orthoepic exercises. The conducted research allows concluding about the possibility to organize a task-oriented systematic work on developing junior pupils’ orthoepic skills while studying orthographic and grammatical topics at the primary-school Russian lessons.
Measuring Web Content Credibility Using Predictive Models

Web content credibility is a measure of believable and trustworthy of the web content that is perceived. Content can turn out to be unreliable if it is not up-to-date and it is not measured for quality or accuracy and therefore, web content credibility is important for the individuals to access the content or information. The analysis of content credibility is an important and challenging task as the content credibility is expressed on essential factors. This paper focus on building predictive models to discover and evaluate credibility of a web page content through machine learning technique. A corpus of 300 web page contents have been developed and the factors like Readability, Freshness, Duplicate Content are defined and captured to model the credibility of web content. Two different labeling such as binary labeling and numeric labeling are used for defining credibility. In case of binary labeling, the high and low credibility of web content are represented by 1 and 0, respectively, whereas in case of numeric labeling five-point scale rating is used to mark the content credibility. Accordingly, two independent datasets have been developed. Different regression algorithms such as Linear Regression, Logistic Regression, Support Vector Regression (SVR) are employed for building the predictive models. Various experiments have been carried out using two different datasets and the performance analysis shows that the Logistic Regression model outperforms well when compared to other prediction algorithms.
LBCC LibGuides: School of Career Technical Education: Organic Foods

This guide highlights the course- and discipline-specific guides for the offerings in the School of Career Technical Educations. In each guide you will find the methods for finding books and other resources curated by the LBCC Librarians.
Teaching Reading by Using Jumble Summary Strategy

Reading is the process of knowing, understanding, and getting information about the contents of the text. Teaching Reading is the process of teaching students to understand and comprehend texts. There are some problems in teaching reading. Therefore, the teacher needs to implement several strategies. One strategy is the Jumble Summary strategy. This is a strategy used by the teacher to present key words and phrases that are randomly ordered from the lesson or topic to students. Students place terms and phrases in paragraphs or logical sequences to show understanding. This research is an experiment. The population of this research is the eighth-grade students of SMPN 2 Suliki District. There are 6 classes in the school. A cluster sampling technique is used to determine the sample. Experimental classes are taught with the Jumble Summary Strategy, and the control class is taught by the strategies currently used by the teacher. This research tool is a multiple-choice reading test. This test is validated because the material is taught to students before taking the test. To check the reliability of the test, researchers used a half-separate test formula. After that, the data were analyzed using the t-test formula suggested by Gay, Mills, and Airasian [1]. From the data analysis, the t-count is 3.214, while the t-table is 2.021, which means that the t-count is greater than the t-table. In other words, the research hypothesis is accepted. So it can be concluded teaching reading by using the Jumble Summary Strategy has had a significant influence on learning to read. Therefore, it is recommended that English teachers apply the Jumble Summary Strategy in reading learning.
Periodic Graphics: The chemistry of snow and ice

The chemistry of snow and ice To download a PDF of this article, visit: cenm.ag/snowice References used to create this graphic: Connor, Deanna. How snowflakes get their shapes. Accessed Jan. 21, 2020. McNeill , V. Faye and Hastings, Meredith G. Ice in the environment: connections to atmospheric chemistry. Environ. Res. Lett. (2008) DOI: 10.1088/1748-9326/3/4/045004 The Shapes of Snowflakes. Compound Interest. Accessed Jan. 21, 2020. A collaboration between C&EN and Andy Brunning, author of the popular graphics blog Compound Interest
Impact and User Observation of Online Journals in Periyar University (PU): An Empirical Study

This paper has made an attempt to investigate the usage and impact of electronic journals or online journals among the users such as post-graduate students, MPhil scholars, and Ph.D. research candidates from the department of School of Social Sciences at Periyar University, Salem, Tamilnadu, India. It found for the analysis the filled questionnaires rate was 83% and also found among the four departments, Journalism and Mass Communication department has got ranked first with 24% to fill the questionnaire. The main purpose of this research is to analyze the impact and the utilization of electronic journals which are provided by the University Library to the user community. For data analysis, a total of two hundred questionnaires were distributed among the four departments to fill the questionnaire. Out of 200, we received only 166 dully filled questionnaires at the rate of 83%. The result shows that the majority of respondents were female with 61.55% whereas the remaining was male with 38.45% and a huge number of 73 (43.97%) respondents were postgraduate students. The majority of 83 (50.0%) respondents were preferred to use the pdf format out of 166 users of the department of the School of Social Sciences. 73 (43.96%) user communities were using the electronic journals weekly. Among the 166 respondents, 77 (46.39%) respondents were using the Internet to access electronic journals.
Influencer-marknadsföring - En granskning av hur influencer-marknadsföring förhåller sig till marknadsföringslagen

As social media is increasingly integrated into our everyday lives and with the rise of so-called influencers, consumers are getting used to a new type of marketing. This type of is often referred to as marketing which is a collective term used to describe companies using influencers' to market various products and services via the influencer's social media platforms. Influencer has rapidly increased in popularity and there are still many unanswered questions regarding how this type of relates to the Marketing Act. In late 2019, Sweden's first court case on the subject was determined and the court's decision is expected to give some guidance as to how future cases regarding influencer will be handled. This thesis, therefore, aims to examine when influencer should be assessed according to the Marketing Act and what obligations influencers have to identify commercial messages on social media. The thesis also studies who can be held responsible for law violations concerning influencer marketing. The study shows that messages published by influencers on social media should be assessed according to the Marketing Act if the messages are purely commercial. Simply put, the Marketing Act is applicable if an influencer receives compensation for posting a certain message. As for what requirements apply when posting commercial messages on social media the court has determined that the average consumer should be able to identify messages quickly and with ease. It should also be clear which company is behind the message in question. The study also shows that in addition to the company behind a law violating message, an influencer who published the message can be held responsible for participation, whilst a party who participated in mediating the advertising assignment can stand completely without responsibility. (Less)
The Gâteaux-Hopfield Neural Network method

In the present work a new set of differential equations for the Hopfield Neural Network (HNN) method were established by means of the Linear Extended Gateaux Derivative (LEGD). This new approach will be referred to as Gâteaux-Hopfiel Neural Network (GHNN). A first order Fredholm integral problem was used to test this new method and it was found to converge 22 times faster to the exact solutions for α &gt; 1 if compared with the HNN integer order differential equations. Also a limit to the learning time is observed by analysing the results for different values of α. The robustness and advantages of this new method will be pointed out.
Traditional Academic Library Networks in Digital Culture

The transition from printed to digital culture has fundamentally changed the approaches, forms and methods (or products and services) that university and academic libraries use for information support of scientific research. Activity of library-information network of the Siberian branch of the Russian Academy of Sciences (SB RAS), organized in the era of printed culture as a three-level system, is undergoing significant changes in connection with the development of digital technologies, scientific communications and reforming of the RAS. These circumstances required the creation of a new model of the library network as an actual information-communication channel, firstly, the way to preserve the accumulated traditional collections. The purpose of this article is to show the advance model for academic library system or network operating within a single complex scientific organizational structure, with their unique printed book collections. To build the model, the author used data on the information behaviour of researchers from the SB RAS, collected through questionnaires, data on the activity trends of university libraries, presented on their websites and in peer-reviewed journals, as well as monitoring data of the activities of scientific libraries. The author took into account both general external factors (information behaviour of users of scientific information, organizational changes in library networks, current trends and experience of scientific research support by academic and university libraries, changes in the scientific environment) and internal (specific) factors related to the reforming of the RAS. The article describes two stages of reorganization of the current model of library-information network of the SB RAS. The article shows how the new model radically changes the old one, as it transforms the structure of resources and collections, the functions of libraries and demonstrates the development trends of competences and skills of library staff.
A Real-time Location Method Under Unknown Wall Characteristics in Through-wall Imaging

To solve the real-time through-wall location problem under unknown wall characteristics, a method based on extreme learning machine (ELM) is proposed in this paper. Through the training process of ELM, the nonlinear and sick relationship between the scattered signals and the target location is established, then the location will be estimated according to the relationship. The number of random hidden neurons, the activation function, and normalization of data in ELM are discussed. Numerical results demonstrate that all these factors have an impact on the accuracy of the location, and the ELM method is suitable for real-time locating under unknown wall characteristics both for noiseless and noisy circumstances.
Pattern-based Wordiness Reduction System for Thai Texts

In this paper, we propose a method and web application to reduce wordiness in Thai by adapting pattern-based analysis with wordiness initial corpus. The small amount of Thai text is gathered to create the initial corpus for grammatically analyzing the patterns of Thai wordiness. 18 wordiness have been decided to intensely analyze the co-occurrence, patterns contexts and construction rules. And 99 wordiness patterns are discovered for the experiments. The experiment has been done with 100 documents from Thai National Corpus by 15 students. For the user satisfaction which is analyzed from the questionnaire, users are highly satisfied with the use of the proposed system. And the wordiness reduction result of the experiment shows the effectiveness of the wordiness identification and reduction which the accuracy is 86.51%. The 13.49% of errors come from word segmentation and unknown words. Wordiness automatically corpus will be developed for further experiment in the future.
Vision-based control of UR5 robot to track a moving object under occlusion using Adaptive Kalman Filter

This paper presents a robust method to track a moving object under occlusion using an off-the-shelf monocular camera and a 6 Degree of Freedom (DOF) articulated arm. The visual servoing problem of tracking a known object using data from a monocular camera can be solved with a simple closed loop controller. However, this system frequently fails in situations where the object cannot be detected and to overcome this problem an estimation based tracking system is required. This work employs an Adaptive Kalman Filter (AKF) to improve the visual feedback of the camera. The role of the AKF is to estimate the position of the object when it is occluded/out of view and remove the noise and uncertainties associated with visual data. Two estimation models for the AKF are selected for comparison and among them, the Mean-Adaptive acceleration model is implemented on a 6-DOF UR5 articulated arm with a monocular camera mounted in eye-in-hand configuration to follow the known object in 2D cartesian space (without using depth information).
Multisequences with high joint nonlinear complexity from function fields

Multisequences over finite fields play a pushing role in the applications that relate to parallelization, such as word-based stream ciphers and pseudorandom vector generation. It is interesting to study the complexity measures for multisequences. In this paper, we propose three constructions of multisequences over finite fields from rational function fields and Hermitian function fields. We also analyze the joint nonlinear complexity of these multisequences. Moreover, the length and dimension of these multisequences are flexible.
GAN-Based Deep Matrix Factorization for Recommendation Systems

Recommendation systems can be divided into two categories: a generator model for predicting the relevant item given a user; or a discriminator model for predicting relevancy given a user-item pair. In order to combine the two models for better recommendation, we propose a novel deep matrix factorization model based on a generative adversarial network which uses collaborative graphs to relieve data sparsity. With interactive records, user-collaboration-graph and item-collaboration-graph are constructed. Then, we use the neighbor nodes’ information in collaborative graphs including user-based information and item-based information to alleviate interaction matrix data sparsity. Finally, the pre-filled matrix is fed into a deep generator and a deep discriminator respectively to learn the feature representations of users and items in a common low-dimensional space through adversarial training, which generates better top-N recommendation results. We conduct extensive experiments on two real-world datasets to demonstrate the effectiveness of our model.
Information System for Determining Earthquake and Tsunami Evacuation Paths in Bengkulu City Based on Android

Facility of directions to the evacuation places in the city of Bengkulu is very minimal, so that people are very difficult to find an efficient route to the evacuation places. The problem is how to determine the evacuation route/gathering point. Indonesia is prone to earthquakes because logically, the Indonesian archipelago is at the confluence of three tectonic plates: the Eurasian plate, the Australian plate and the Pacific plate. In the event of an earthquake and tsunami disaster, if disaster preparedness is not prepared, it will cause damage to buildings, offices and can result in fatalities such as the events in Nangro Aceh Darussalam. Therefore, we need a system that can help overcome this disaster management. The system that can be made is the Information System for Determining Earthquake and Tsunami Evacuation Paths in the city of Bengkulu Using Android. By using Android, it will be easier for people to imitate an evacuation route or place during an earthquake and tsunami.
A New Angle on Lattice Sieving for the Number Field Sieve

Lattice sieving in two or more dimensions has proven to be an indispensable practical aid in integer factorization and discrete log computations involving the number field sieve. The main contribution of this article is to show that a different method of lattice enumeration in three dimensions will provide a significant speedup. We use the successive minima and shortest vectors of the lattice instead of transition vectors to iterate through lattice points. We showcase the new method by a record computation in a 133-bit subgroup of $\mathbb{F}_{p^6}$, with $p^6$ having 423 bits. Our overall timing nearly $3$ times faster than the previous record of a 132-bit subgroup in a 422-bit field. The approach generalizes to dimensions 4 or more, overcoming a key obstruction to the implementation of the tower number field sieve.