Reviewerly/exHarmony huggingface dataset:
PERANCANGAN SISTEM INFORMASI PARIWISATA DI KABUPATEN SUKABUMI BERBASIS WEB

Referring to Law Number 22 Year 1999, which regulates the authorities and obligations of the autonomous region to regulate and manage government affairs and the interests of the local community. This is benefited by the tourism office as the authority in promoting tourism in Sukabumi Regency in the technology sector which is expected to reduce the costs of the tourism office in promoting tourism information. This research uses the waterfall method with the aim of creating a Web-based Design of a Tourism Information System in Sukabumi Regency, as a promotional media in the form of superior tourism information, lodging, restaurants, traditional culinary, traditional arts, and creative industries which visitors will be diverted to the Dekranasda website link. ., and this study uses the PIECES method as problem identification. The results of this research are in the form of a web application that can be used by visitors and the tourism office.
Teachers’ Strategies in Teaching English to Young Learners in Private Primary Schools in Yogyakarta

Teaching English to young learners is not easy, because English is not the mother tongue and it makes children difficult to master English well. Strategies are needed when teaching it. For that reason, the researchers conducted this study to describe the problems faced by the teachers in teaching English to young learners and to explain their strategies in teaching English to private primary schools students. This research was conducted by using descriptive qualitative research. The data were collected through semi-structured interviews with teachers at private primary schools in Yogyakarta. The subjects of the research involved six English teachers in the even semester of the academic year 2019/2020 at the private primary schools in Yogyakarta. To get the validity of the data, the triangulation of data sources with the same technique, namely interview was used, and the result of this research was checked by the research subjects to ensure the data are valid. In this study, the researchers analyzed the data, categorizing the data, making explanations, and finally drawing conclusions. The result of this research indicated that there are nine problems faced by the teacher when teaching English to young learners. They are limited time, diverse characters of students, less focused students, bickering students, the English position in the national curriculum, a large number of students and classes, unsupported facilities, learning media, and the fact that English is not a tool of communication. Every teacher has his or her strategies when teaching English to young learners, the strategies are cooperative, contextual, think together with the students, expository, inquiry, exploration-elaboration-collaboration, TPR, students active learning, and using video strategies
An efficient data masking method for encrypted 3D mesh model

The industrial 3D mesh model (3DMM) plays a significant part in engineering and computer aided designing field. Thus, protecting copyright of 3DMM is one of the major research problems that require significant attention. Further, the industries started outsourcing its 3DMM to cloud computing (CC) environment. For preserving privacy the 3DMM are encrypted and stored on cloud computing environment. Thus, building efficient data masking of encrypted 3DMM is considered to be efficient solution for masking information of 3DMM. First, using the secret key, the original 3DMM is encrypted. Second without procuring any prior information of original 3DMM it is conceivable mask information on encrypted 3D mesh models. Third, the original 3DMM are reconstructed by extracting masked information. The existing masking methods are not efficient in providing high information masking capacity in reversible manner and are not robust. For overcoming research issues, this work models an efficient data masking (EDM) method that is reversible nature. Experiment outcome shows the EDM for 3DMM attain better performance in terms of PSNR and RMSE over existing data masking methods. Thus, the EDM model brings good tradeoffs between achieving high data masking capacity with good reconstruction quality of 3DMM.
Correlations between working memory capacity and EFL reading comprehension: an investigation with Brazilian university students

Reading in a foreign language is considered a high cognitive function, believed, thus, to impose demands on working memory resources. Studies have shown significant correlations between working memory capacity and foreign language reading comprehension, but its underlying mechanisms are still open to discussion. This article reports on a study whose objective was to investigate possible correlations between working memory capacity and foreign language reading comprehension considering the knowledge of the first language as a possible source of interference. A recall task was conducted in two conditions, one in which readers performed the task in English and another, in Portuguese. Results showed a weak but statistically significant correlation between working memory capacity and recall scores in the second condition and no correlations between working memory capacity and reading time. Exploratory data analyses suggested that the correlation observed was influenced by foreign language reading proficiency and that the ratio of recall scores to reading time is a better measure of comprehension efficiency.
Virtual Reality from the Standpoint of Complexity Science

An extended approach to the comprehension of virtual reality is developed in the article. Virtual reality is understood not only as a logically possible or cybernetically constructed reality but also as continuous turbulence of potencies of the complex natural and social world we live in, the wandering of complex systems and organizations over a field of possibilities, such a realization of forms and structures in which many formations remain in latent, potential forms, and are in the permanent process of making and multiplying a spectrum of possibilities, lead to the growth of the evolutionary tree of paths of development. It is shown that such an understanding of virtual reality corresponds to concepts and notions developed in the modern science of complexity. The most significant concepts are considered, such as the nonlinearity of time, the relationship of space and time, the uncertainty of the past and the openness of the future, the choice and construction of the future at the moments of passing the bifurcation points. Some cultural and historical prototypes of these modern ideas of virtual reality are given. It is substantiated that the vision of virtual reality being developed today can play the role of a heuristic tool for understanding the functioning and stimulation of human creativity.
Automated Crisis Content Categorization for COVID-19 Tweet Streams

Social media platforms, like Twitter, are increasingly used by billions of people internationally to share information. As such, these platforms contain vast volumes of real-time multimedia content about the world, which could be invaluable for a range of tasks such as incident tracking, damage estimation during disasters, insurance risk estimation, and more. By mining this real-time data, there are substantial economic benefits, as well as opportunities to save lives. Currently, the COVID-19 pandemic is attacking societies at an unprecedented speed and scale, forming an important use-case for social media analysis. However, the amount of information during such crisis events is vast and information normally exists in unstructured and multiple formats, making manual analysis very time consuming. Hence, in this paper, we examine how to extract valuable information from tweets related to COVID-19 automatically. For 12 geographical locations, we experiment with supervised approaches for labelling tweets into 7 crisis categories, as well as investigated automatic priority estimation, using both classical and deep learned approaches. Through evaluation using the TREC-IS 2020 COVID-19 datasets, we demonstrated that effective automatic labelling for this task is possible with an average of 61% F1 performance across crisis categories, while also analysing key factors that affect model performance and model generalizability across locations.
The accelerated Gisin state: its non-locality, quantum correlations and efficiency to perform quantum masking

The local and non local behavior of the accelerated Gisin state are investigated either before or after filtering process. It is shown that, the possibility of predicting the non-local behavior is forseen at large values of the weight of the Gisin and acceleration parameters. Due to the filtering process, the non-locality behavior of the Gisin state is predicted at small values of the weight parameter. The amount of non classical correlations are quantified by means of the local quantum uncertainty (LQU)and the concurrence, where the LQU is more sensitive to the non-locality than the concurrence. The phenomenon of the sudden changes is displayed for both quantifiers. Our results show that, the accelerated Gisin state could be used to mask information, where all the possible partitions of the masked state satisfy the masking criteria. Moreover, there is a set of states, which satisfy the masking condition, that is generated between each qubit and its masker qubit. For this set, the amount of the non-classical correlations increases as the acceleration parameter increases . Further, the filtering process improves these correlations, where their maximum bounds are much larger than those depicted for non-filtered states.
Проблемы определения понятия «информационные ресурсы» в эпоху формирования информационного пространства

The study is novel in that the author attempts to define unequivocally the term to be integrated into scientific, professional and regulatory discourse. The concept of information resources is one of the key ones for building information society and information space, meanwhile it has been still interpreted equivocally. The author analyzes the meaning of the term “information resources” as used in reference, legal, regulatory and scientific documents. He also reviews its historical background from the very introduction till nowadays. In considering the phenomenon of information resources, the author proceeds from the category knowledge, which serves as a link in embracing the nature, development and use of technologies, and life activities. This approach forms the basis for the model of information resources circulation from individuals to the society using computer and communication technology. The importance of information resources in the era of information space development is emphasized. The author proposes the component structure of information resources to comprise five elements: the society, hardware, software (software), data and knowledge bases, and communication. Each element of this structure comprises a number of complementary components. The findings of the study evidence on the significant role of the term in research, library and information activities, as well on the need to include this term in law and regulatory documents.
Pendorong dan Penghambat Sistem Pembelajaran Jarak Jauh: Gambaran dari Lembaga Diklat Pemerintah di Indonesia

The purpose of this article is to find the driving and inhibiting factors for implementing a distance learning system (PJJ) based on a Learning Management system (LMS)  by analyzing previois research on the effectiveness of PJJ institutions in Indonesia in the last five years. This study uses a qualitative approach  consisting of an analysis of the factors driving and inhibiting the implementation of PJJ in various agencies and regions. The research found inhibiting factors in the form of low learning culture, weak supervision, low perception of the relevance of PJJ to work, differences between what is recorded in the system and what is found in the field, and technical problems such as networks, devices, and digital literacy. Meanwhile, the driving factors include innovative aspects of the learning system, cost savings, the possibility factors include innovative aspects of the learning system, cost savings, the possibility to study anywhere an anytime, opportunities for cross regional collaboration without distance restrictions,  and the adaptability of participants and widyaiswara. After the inhibiting factors are obtained, then, an LMS development model is produced that adheres to five principles, namely flexibility, consistency, efficiency, monitoring and evaluation, and function.  These principles are supported by individual, social, cultural and technical factors from external organizers. Guided by this model, the implementation of PJJ is expected to be even better and become a capable Human Research  development strategy in creating smart ASN and bureaucratic reform Keyword: distance learning, institutional training, learning management system, ASN competency development model
Sistem Pendukung Keputusan Pemilihan Dokter Kandungan Menggunakan TOPSIS

Obstetrician on duty to examine and monitor the development of the fetus in the womb as well as the health of pregnant women. Pregnancy check is also very important to diagnose the risk of abnormalities or illness. To get maximum service, it takes the best obstetrician. The selection of obstetricians is currently done by surveying obstetricians around the dwelling place or by collecting information from other people, either by asking directly to the person or via forums on the internet. The data used is the experience of obstetricians by age, consultation rates, delivery rates, obstetrician popularity based on the number of patients, and distance traveled from residence to the obstetrician. The results of this study by using TOPSIS method is a recommendation of obstetrician.Keywords: obstetrician, decision support system, TOPSIS
Classification of tools for promoting films in social networks and the Internet

Within the framework of the study, a classification of tools for promoting films on the Internet and social networks was proposed and analyzed, and the advantages and disadvantages of specific methods of promoting films in modern realities were studied
Extensions of Karger's Algorithm: Why They Fail in Theory and How They Are Useful in Practice

The minimum graph cut and minimum $s$-$t$-cut problems are important primitives in the modeling of combinatorial problems in computer science, including in computer vision and machine learning. Some of the most efficient algorithms for finding global minimum cuts are randomized algorithms based on Karger's groundbreaking contraction algorithm. Here, we study whether Karger's algorithm can be successfully generalized to other cut problems. We first prove that a wide class of natural generalizations of Karger's algorithm cannot efficiently solve the $s$-$t$-mincut or the normalized cut problem to optimality. However, we then present a simple new algorithm for seeded segmentation / graph-based semi-supervised learning that is closely based on Karger's original algorithm, showing that for these problems, extensions of Karger's algorithm can be useful. The new algorithm has linear asymptotic runtime and yields a potential that can be interpreted as the posterior probability of a sample belonging to a given seed / class. We clarify its relation to the random walker algorithm / harmonic energy minimization in terms of distributions over spanning forests. On classical problems from seeded image segmentation and graph-based semi-supervised learning on image data, the method performs at least as well as the random walker / harmonic energy minimization / Gaussian processes.
Adaptive data hiding scheme based on magic matrix of flexible dimension

Magic matrix-based data hiding schemes are applied to transmit secret information through open communication channels safely.With the development of various magic matrices, some higher dimensional magic matrices are proposed for improving the security level.However, with the limitation of computing resource and the requirement of real time processing, these higher dimensional magic matrix-based methods are not advantageous.Hence, a kind of data hiding scheme based on a single or a group of multi-dimensional flexible magic matrices is proposed in this paper, whose magic matrix can be expanded to higher dimensional ones with less computing resource.Furthermore, an adaptive mechanism is proposed to reduce the embedding distortion.Adapting to the secret data, the magic matrix with least distortion is chosen to embed the data and a marker bit is exploited to record the choice.Experimental results confirm that the proposed scheme hides data with high security and a better visual quality.
FasTensor User Interface

In this chapter, we describe the user interface of the FasTensor library, a C++ implementation of the FasTensor programming model presented in previous chapters. Hence, the term FasTensor will mostly refer to the FasTensor library that implements the FasTensor programming model. Currently, the FasTensor programming model is available in C++. Support for other languages, such as Java, Python, and Julia, are planned.
Framework of diacritic segmentation for Arabic handwritten document

In recent Arabic standard language and Arabic dialectal texts, diacritics and short vowels are absent. There are some exceptions have been made for the Arabic beginner learner scripts, religious texts and as well as a significant political text. In addition, the text without diacritics is considered ambiguous due to numerous words with different diacritic marks seem identical. However, this paper we present a framework for segmenting diacritics from Arabic handwritten document by using region-based segmentation technique. Since Arabic handwritten and Mushaf Al Quran contain many diacritical marks. Hence, the diacritics must be properly extracted from Arabic handwritten document to avoid losing some good features. Furthermore, the proposed framework is devised specifically to segment diacritics from Arabic handwritten image, thus there will be no feature extraction, feature selection, and classification processes included. Besides, we will present the methodology that is used to fulfil the objectives of this paper. The pre-processing phases will be explained and more specifically segmentation phase for segmenting diacritics which is the phase we concentrate more in this article. Lastly, we will identify the proposed technique region-based segmentation to facilitate our development throughout the experimental process.
An improved measure for belief structure in the evidence theory.

Dempster-Shafer evidence theory (D-S theory) is suitable for processing uncertain information under complex circumstances. However, how to measure the uncertainty of basic probability distribution (BPA) in D-S theory is still an open question. In this paper, a method of measuring total uncertainty based on belief interval distance is proposed. This method is directly defined in the D-S theoretical framework, without the need of converting BPA into probability distribution by Pignistic probability transformation. Thus, it avoids the loss of information. This paper analyzes the advantages and disadvantages of the previous total uncertainty of measurement, and the uncertainty measurement examples show the effectiveness of the new uncertainty measure. Finally, an information fusion method based on the new uncertainty measure is proposed. The validity and rationality of the proposed method are verified by two classification experiments from UCI data sets.
Marginalisasi Gender dalam Teks Pidato Menpora Republik Indonesia pada Perayaan Hari Sumpah Pemuda ke-91: Analisis Wacana Kritis

Abstract: This study aims at describing the gender marginalization contained in the speech text of the Minister of Youth and Sports of the Republic of Indonesia in commemoration of the 91st Youth Pledge Day in 2019. In the discourse analysis of the speech text, researchers found the potential for gender inequality or gender bias in the content of the speech text such as marginalization. and subordination. In conducting this research, the researcher applied a qualitative method through the Sara Mills critical discourse analysis approach. Sara Mills's perspective critical discourse analysis focuses on biased texts in presenting women. The results show that there are findings related to the position of the subject, the position of the object, and the position of the reader / listener which are in accordance with Sara Mills theory. This research also shows forms of gender bias in the calls and invitations contained in the speech texts of the Minister of Youth and Sports of the Republic of Indonesia. Abstrak: Penelitian ini bertujuan untuk menggambarkan marginalisasi gender yang terdapat dalam teks pidato Menteri Pemuda dan Olahraga Republik Indonesia dalam perayaan hari Sumpah Pemuda ke-91 tahun 2019. Dalam analisis wacana teks pidato tersebut, peneliti menemukan potensi ketidaksetaraan gender atau bias gender dalam isi teks pidato seperti marginalisasi dan subordinasi. Dalam melakukan penelitian ini, peneliti menerapkan metode kualitatif melalui pendekatan analisis wacana kritis Sara Mills. Analisis wacana kritis perspektif Sara Mills memiliki fokus terhadap teks bias dalam menampilkan wanita. Hasil penelitian menunjukkan bahwa ada temuan terkait dengan posisi subjek, posisi objek, dan posisi pembaca/pendengar yang sesuai dengan teori Sara Mills. Penelitian ini juga menunjukkan bentuk-bentuk diskriminasi gender dalam seruan dan ajakan yang terkandung pada teks pidato Menpora.
Cervical Cancer Prediction Using Deep Neural Network

The most common and severe disease among women is cervical cancer (CC). Predicting CC is at risk since screening is not possible at an earlier stage. Physicians collect the cervical cells and, by manual intervention, predict cancer types. This approach affects the prediction rate because of human negligence, highly cost-effective, and time-consuming. In this paper, we present an automatic CC prediction using a deep neural network classifier to overcome the issue. The proposed work comprises four stages namely, pre-processing, outlier elimination, dimension reduction, and prediction. Initially, remove the missing data. Second, eliminate the non-matched data based on similarity values. Third, apply the principal component analysis (PCA) to overcome the restrictions caused by high dimensionality data. Finally, input the reduced dimension dataset to the proposed deep neural network classifier (DNN) and classify the input data as normal or abnormal in the classifier. We execute the efficiency of the suggested approach using Python and analyze effectiveness with different metrics.