Reviewerly/exHarmony huggingface dataset:
Real-time dynamic data desensitization method based on data stream

With the rapid development of the data mining industry, the value hidden in the massive data has been discovered, but at the same time it has also raised concerns about privacy leakage, leakage of sensitive data and other issues. These problems have also become numerous studies. Among the methods for solving these problems, data desensitization technology has been widely adopted for its outstanding performance. However, with the increasing scale of data and the increasing dimension of data, the traditional desensitization method for static data can no longer meet the requirements of various industries in today's environment to protect sensitive data. In the face of ever-changing data sets of scale and dimension, static desensitization technology relies on artificially designated desensitization rules to grasp the massive data, and it is difficult to control the loss of data connotation. In response to these problems, this paper proposes a real-time dynamic desensitization method based on data flow, and combines the data anonymization mechanism to optimize the data desensitization strategy. Experiments show that this method can efficiently and stably perform real-time desensitization of stream data, and can save more information to support data mining in the next steps.
Verbal Aggressiveness in Communication in Media and Online. A Case Study of the TV Cooking Show »Spread«

&#x0D; &#x0D; &#x0D; &#x0D; The paper discusses verbal aggressiveness and (im)politeness in media and online communication. The analysis focuses on transcriptions of communicative acts by participants of the TV reality Spread! ("Prostřeno!", a Czech version of the programme Come Dine with me) and viewers' comments in related online discussions.&#x0D; The analysis indicated that the use of face-threatening acts was determined by a type of communicative interaction and interlocutors' social roles. Striving to construct a positive self-image, the participants in the show did not take the risk of losing their face due to usage of derogatory or vulgar expressions in face-to-face inter- actions.&#x0D; The anonymous online discussions, on the contrary, did not pose any risk for the positive faces of the speakers; therefore, the interlocutors showed clear tendency to either appreciate and support, or attack the contestants as well as other speakers. &#x0D; &#x0D; &#x0D; &#x0D;
An Enhanced Document Referential, Classification And Retention System using Muiltinomial Naive Bayes Algorithm

Securing organizational data is an important information management issue that continues to pose significant challenges for organizations especially in developing countries.Different organizations have made several failed attempts to develop authentic solution that will centrally create and manage document referential, place documents in their respective categories and apply retention on the documents during end-oflive, in a seamless manner.There have been several complaints from users on issues bordering on missing documents, premature destruction of important documents, organization's top-secret documents been found in wrong hands and placement of documents in wrong categories as a result of no well-defined organizational policies.We developed an enhanced online document referential, classification and retention system, which combated these challenges.We used object-oriented analysis and design methodology (OOADM) in our approach.Microsoft ASP.Net and Python technologies were used for this implementation.Automated document referential, classification and retention system provides a platform for easy creation of document referential, placement of documents in respective document categories and automatic application of retention on documents at the end of their lifespan.From the results, the overall accuracy of the classification model is 88% which indicates that most predictions made by the model are correct.The specificity of the individual classes ranges between ninetyeight (98) and one hundred (100) percent, whereas their precision, recall and f1-scores are above 0.5 which is good for prediction.This work could be beneficial to both small, medium and large-sized organizations.
DESIGNING COMMUNITY LANGUAGE LEARNING METHOD BASED CLASSROOM ACTIVITIES USING ELEARNING RESOURCES TO TEACH LISTENING SKILLS AT THE TERTIARY LEVEL

In the current scenario, English plays an inevitable role in all the fields. The learners and teachers of this language understood the need of it and have taken certain steps to learn/teach language effectively using different methods to meet the needs of the society. Only recently, after the outlook of ELT scholars moved towards a blend of methods to suit the unique needs of a particular class and students during the post methods era, This paper is an attempt to design classroom activities based on CLL using E-learning materials to teach listening skills.
PENGEMBANGAN SISTEM INFORMASI JASA PENUKARAN VALAS

The role of money changers is very important in meeting the needs of foreign exchange for the community. This role can also be fulfilled by banks and other financial institutions. People who want to order foreign currencies at this time still have to go through traditional procedures, where the buyer is required to come directly to the place of foreign exchange. This study intends to build a system design that can make currency orders and provide information on foreign exchange rates contained in each money changer through a web-based application. This research uses the Object Oriented Analysis and Design (OOAD) method, literature study, and data collection methods using a questionnaire. Based on the problems outlined and the results of the study, this system can be a source of information on foreign exchange rates and also an alternative order for foreign exchange. Foreign exchange orders can be made online through this information system. This system will continue to be developed with various features such as payment methods using biometric security methods with the support of Artificial Intelligence (AI) technology. So users can search for foreign currency values and order them easily through online media.
Effective Image Segmentation using Composite Energy Metric in Levelset Based Curve Evolution

Accurate segmentation of anatomical organs in medical images is a complex task due to wide inter-patient variability and several acquisition dependent artefacts. Moreover, image noise, low contrast and intensity inhomogeneity in medical data further amplifies the challenge. In this work, we propose an effective yet simple algorithm based on composite energy metric for precise detection of object boundaries. A number of methods have been proposed in literature for image segmentation; however, these methods employ individual characteristics of image including gradient, regional intensity or texture map. Segmentation based on individual featres often fail for complex images, especially for medical imagery. Accordingly, we propose that the segmentation quality can be improved by integrating local and global image features in the curve evolution. This work employs the classic snake model aka active contour model; however, the curve evolution force has been updated. In contast to the conventional image-based regional intensity statistics, the proposed snake model evolves using composite image energy. Hence, the proposed method offers a greater resistance to the local optima problem as well as initialization perturbations. Experimental results for both synthetic and 2D (Two Dimensional) real clinal images are presented in this work to validate the performance of the proposed method. The performance of the proposed model is evaluated with respect to expert-based manual ground truth. Accordingly, the proposed model achieves higher accuracy in comparison to the state-of-the-art region based segmentation methods of Lankton and Yin as reported in results section.
PEMBELAJARAN STRUKTUR KALIMAT DENGAN METODE KOOPERATIF MODEL TUTOR SEBAYA DI SEKOLAH DASAR

The purpose of the research Learning sentence structure in State Primary School Bendungan 1 Subdistrict Kedawung Sragen to: (1) describe the planning of learning sentence structure with cooperative peer tutor model method in State Primary School Bendungan 1; (2) describe the implementation of learning sentence structure with the cooperative model of peer tutors in State Primary School Bendungan 1; (3) describe the obstacles in learning sentence structure with the cooperative model of peer tutors in State Primary School Bendungan 1; and (4) describe the solution constraints learning sentence structure with the cooperative model of peer tutors in State Primary School Bendungan 1.This research is a descriptive qualitative research.The subject of this research is the head of the school, the teachers and students of the State Primary School Bendungan 1. Data obtained using observation, interviews, and analysis of documents.The validity of the data is performed using the triangulation of the data.Data analysis was done using interactive analysis.The results showed that: (1) Learning sentence structure with the cooperative model of peer tutors in State Primary School Bendungan 1. beginning with open lessons, do apersepsi, held a question and answer, and deliver learning objectives.(2) Learning is done by dividing students into small groups.Each group gets a text sentence structure to be discussed.The teacher explains how to write a sentence structure by giving an example in front of the class.The teacher also gives the opportunity to the students to present their work in front of the class.Teachers close the lesson by giving her the motivation to students.(3) the obstacles that appear in learning sentence structure in State Primary School Bendungan 1: Ego students still high, students are still reluctant to observe the sruktur sentences, and Students still trouble memorizing sentence structure.(4) the teacher's Effort in overcoming barriers in learning sentence structure in State Primary School Bendungan 1, namely: the teacher awaken students to dare to perform in front of the class, give understanding and comprehension on the importance of collaboration in writing sentence structure, the teacher pointed to students, but not forcing it, and teachers lead students to pronounce a sentence properly.
PENINGKATAN KEMAMPUAN BERSAING DI DUNIA KERJA DENGAN PELATIHAN SOFTWARE ZAHIR ACCOUNTING

Institution Awareness to the citizens in order to increase the quality of education is a part of Tri Dharma Perguruan Tinggi. To apply the program, it needs a plan. Community service program. The general purpose of this community service program is to increase the competency of citizens of RW 003 Babakan Village, Kelapa Dua, Setu, South Tangerang using Zahir Accounting Software training. The activity of this community service program entitled Computerized Accounting. The trainers and the source speakers are from the lecturers of Accounting Major of Pamulang University (Universitas Pamulang). The result conducted on November, 1,2,3 2019 was increasing their ability to use computer and computerized accounting with Zahir Accounting Software. The trainees was enthusiastic with the material they had from the lecturers of Accounting Major of Pamulang University (Universitas Pamulang). The trainees directly used the software.Zahir Accounting Software becomes an attention for the entrepreneurs who need accounting software to support financial noting in their business easily, fast and accurately, so by practicing Zahir Accounting Software will increase the citizens' competence to look for a job Keywords: Software Zahir Accounting ; Computerized Accounting
Indonesian Text Dataset for Determining Sentiment Classification Using Mechine Learning Approach

Advances in information technology encourage the emergence of unlimited textual information with the use of online media developing so rapidly that the emergence of the need for information presentation without reducing the value of the information presented. Basicaly the concept of the dataset is a general form of almost every discipline, where the dataset provides empirical basic information for research activities. Sentiment analysis is done to see opinions or feelings about a problem or identify and classify information trends from the problem. The dataset analysis in determining sentiment classification is a model of sentiment classification that has relevance to the dataset with the use of machine learning techniques with supervision that learns from experience to predict output from labeled input data and output from machine learning. The results of experiments and tests that have been carried out on machine learning techniques with supervision can classify sentiments in the tweet text properly and the level of accuracy can still be improved to a better direction with data namely baseline 100 (days) and 83 (weeks), naivebayes 100 (days) and 82 (weeks), maxent 100 (days) and 83 (weeks), and SVM 100 (days) and 83 (weeks).
Optimization for Greedy Non-maximum Suppression Based on Multi-task Convolutional Neural Network

Non-maximum suppression (NMS) is an essential part of the face detection pipeline based on a convolutional neural network (CNN).The typical approach for NMS used by face detection is a greedy, locally optimal strategy, which is to localize objects from a set of candidate locations.However, NMS still has some shortcomings, such as sometimes the detection box has no relationship with a high classification score, which leads to misjudging face localization during NMS.In this paper, we observed that the NMS implemented on the multi-task convolutional neural network (MTCNN) is a cascaded network and the enhanced NMS based on MTCNN to achieve high performance during face detection and alignment.We employ WIDER FACE as the test dataset to evaluate our proposal.The precision and recall curves are drawn when using three subsets at different thresholds.The result shows that the proposed approach can perform better performance than traditional NMS.
The Psychological Component of the Resource-Based Approach in Higher Pedagogical Education

Background and Aim of Study:The integration of the resource-based approach into the management of the educational process in higher education institutions is essential since it allows to consider comprehensively the interaction of external and internal resources of the personality, which is important for the effective planning of educational activities aimed at high academic achievements, comprehensive personal development and successful professional formation.The aim of the study: to determine the essence and significance of the psychological component, which is a part of the internal resource of the individual, in the structure of the resource-based approach and its role in the management of the educational process. Materials and Methods:In the study, the following general scientific methods were used: analysis, comparison, generalization, literature systematization and interpretation of results. Results:The research reveals the constituent parts of the psychological resource that is considered as one of the key elements in most models of the personality structure or models of learning, determines their impact on the productivity of the educational process and personal and professional development of students.Conclusions: Consideration of the psychological substructure (the level of development of cognitive processes, mental properties of the personality, specific features of the emotional and volitional sphere, prevailing motives for behaviour, etc.) in the management of the educational process facilitates the activation of the resources of personality, which, in turn, increases the motivation for cognitive activity, improves academic achievement, affects personal and professional formation, and allows creating conditions for personality self-development.
Random Forest Lag Distributed Regression for Forecasting on Palm Oil Production

Palm oil is one of the most cultivated potential commodities so it is necessary to do research to determine the determinants of production and forecasting on palm oil production.The objectives are perform data modeling dan forecasting using random forest lag distributed regression on palm oil production.This analysis combines the lag distributed regression and random forest methods.The results showed that the performances for this model are the correlation value is 0.9302, RMSE is 20.379,MAE is 14.143, and R-Square is 0.829.The 5 most important variables were quantity of palm oil, land area, palm oil age, 8th lag of wind velocity, and 1st lag of temperature.The distribution of data forecasting results are not much different from the distribution of testing data and original data.
CONCEPT PARTS IN THE PROCESS OF FORMING OF THE NAMES IN INTERNET

concepT pARTS in The pRoceSS oF FoRMing oF The nAMeS in inTeRneT
Design and Build Disaster Emergency Response Systems Using Firebase Cloud Messaging Based on Android and SMS Gateway

Design and implementation emergency response system using firebase cloud messaging android based and sms gateway is a disaster notification information system using mobile android based media by utilizing support from firebase cloud message service and sms gateway. This study aims to assist BPBD Majalengka District in improving the effectiveness, accuracy, and speed of the process of delivering disaster information to the public. Applications use cross-platform messaging through firebase clouds that are able to perform real-time notification reporting to users with details or formatting of text, images, or map coordinates. This research uses Agile Method Development system with Rational Unified Process and software used in making this application is using Android Studio 2.3.2 and PHP programming language.
Discontinuous fringe pattern segmentation based on fully convolutional neural network

Optical interferometric techniques are very attractive in various research and application fields for the non-contact, high accuracy and full filed measurements they offered. Fringe patterns, which are the recorded results of these techniques, are difficult to analyze when containing discontinuity. Fringe patterns discontinuity detectable technique, i.e. discontinuous fringe pattern segmentation technique, is demanded. Inspired by the recent development of convolutional neural network, in this paper, we propose an automatic and robust single fringe pattern segmentation method based fully convolutional neural network (FCN). Both simulated and experimental fringe patterns are collected for network training and testing. With the identified discontinuous regions by FCN, the discontinues boundaries are estimated and obtained. The proposed discontinuous fringe pattern segmentation method is automatic and robust to noise and resolution changes. Simulated and experimental fringe patterns are tested and successful results have been obtained, which validate the proposed method.
Observasi Penerimaan Sosial Berbasis Aplikasi Realitas Tertambah di Bamboo Bar Sanur

The opening of internet access to the public in 1991 pushed information into people's daily needs (Birger, 1997). Telephone manufacturers adopt the internet naturally in their products by launching mobile phones that have evolved into smartphones (Ira, 2012), allowing the internet to be accessed all the time. Economic aspects soon followed, assimilated in cyberspace into E-commerce that allows transactions of goods and services in cyberspace (Botha et at., 2008). In the world of tourism, the use of modern technology has become a necessity for many destinations to remain competitive and attractive to modern tourists. A form of new technology that is increasingly being used in public spaces is Augmented Reality (AR). Augmented reality technology allows users to receive information in the form of a display that contains a combination of real and virtual objects in the real world in real time. Technology is accessed via an app that is installed on a smartphone.This research aims to analyze the role of behavioral intention based on augmented reality applications in mediating the effect of perceived usefulness and perceived ease of use on the actual system use in bamboo bar Sanur. An augmented reality prototype application was developed specifically for this research. Quantification of human behavior is possible by combining the branch of psychology theory of planned behavior with e-commerce based mobile computing context (Imielinski &amp; Korth, 1996).&#x0D; Keywords: behavioral intention, aplikasi, augmented reality, smartphone, e-commerce, TAM, Mobile computing Text
Experimental Study of Digipass Go3 and the Security of Authentication

Based on the analysis of 6-digit one-time passwords (OTP) generated by DIGIPASS GO3 we were able to reconstruct the synchronization system of the token, the OTP generating algorithm and the verification protocol in details necessary for an attack. The OTPs are more predictable than expected. A forgery attack is described. We argue the attack success probability is much higher than it may be expected if all the digits are independently and uniformly distributed. The implications for the security of authentication are discussed and open questions are formulated.
BULLING: DOMESTIC AND FOREIGN EXPERIENCE

Purpose: The article aims to show the importance of the problem of bullying in modern conditions, which requires a solution by improving the methods of adjusting behavior taking into account existing foreign experience. Methodology: To solve the problem of bullying, the studies of foreign and domestic scientists were analyzed, a number of recommendations were proposed that can be used in precautionary measures to counter bullying and help victims. Results: In a scientific article, bullying was studied as a negative socio-psychological-pedagogical phenomenon that can occur in any children's team and which affects and affects all participants, leading to a violation of the educational process, causes long-term consequences for the individual, sometimes remote in time, overcoming of which is largely possible with specialists with certain theoretical knowledge, special skills. Scientific novelty: studies were conducted on the best practices of collecting information and conducting surveys of victims of bullying to form modern methodological approaches to provide psychological assistance to participants in bullying and to counter the phenomenon of bullying in educational institutions in general. Practical relevance: Research results can be used in the work of services or departments that develop methodological materials for psychological and pedagogical assistance, the Ministry of Education and Science, the Ministry of Health to improve preventive and supportive measures against bullying in schools and colleges.
Fog Concentration Grade Judgment for Meter Reading Based on SVM

Robot reading energy meter devices automatically is a basic task for smart grid. Unfortunately, the predicted accuracy is influenced by environment dramatically. In order to solve the problem, we propose a method which can metric fog concentration in environment before meter reading. Moreover, based on the characteristics of image and fog influence, joint features and SVM are used to discriminate the concentration level of foggy image. Specially, Contrast feature and DFT feature are extracted as joint features to describe the foggy image and SVM is used to study and train the joint feature. Finally the fog concentration level is discriminated naturally. The experimental results demonstrate the effectiveness of proposed method in term of judging the meter image with five level.
Topological and Multi-Topological Frames in the Context of Intuitionistic Modal Logic

We present three examples of topological semantics for intuitionistic modal logic with one modal operator □. We show that it is possible to treat neighborhood models, introduced earlier, as topological or multi-topological. From the neighborhood point of view, our method is based on differences between properties of minimal and maximal neighborhoods. Also we propose transformation of multitopological spaces into the neighborhood structures.