Reviewerly/exHarmony huggingface dataset:
TINGKAT KEPUASAN LAYANAN CUSTUMER SERVICE BERDASARKAN METODE WEBQUAL 4.0 PADA PT TRITANA DENGAN PLS-SEM

In the world of business, especially for service businesses, there are many strategies to make a business successful. In addition to a reliable marketing strategy, a business also needs excellent service so that it can make consumers comfortable and happy. Each company will compete to provide the best service for its customers which makes customers satisfied so that it can improve other aspects such as sales, profit. In this study the authors analyzed aspects of the web service service available at PT Tratana, namely by analyzing the excellent service system to consumers with Using the Webqual4 model and data processing with the Pls-Sem method from the results of this study it is expected to know the extent to which the effectiveness and satisfaction of consumers after buying the products they buy from the analysis results obtained by many variables that are not significant to customer satisfaction..
The Effectiveness of Android Based Javanese Alphabet Learning Media on Student Learning Outcomes

Javanese alphabet as one of Indonesian culture gradually began to be forgotten along with the low interest of students to learn Javanese alphabet.Low student interest also affects learning outcomes.Factors affecting the suboptimal learning outcomes of Javanese alphabet there are no innovative learning media and attracting students' attention.The research method used Waterfall.The sample used 57 elementary school students in grades 4 and 5 in Kudus Regency.Data collection techniques that has been used were questionnaire, interview, pretest and posttest.The data analysis technique uses questionnaire.The result of this research, the average of pretest score is 59,925 and the average of posttest score is 77,765.It was proven that there was an increase in student learning outcomes.The conclusion of this research is Android-based Javanese alphabet learning media is effective to improve students learning outcomes in the content of Javanese language lessons in Javanese script.
Comparison of Lossless Image Formats

In recent years, a bag with image and video compression formats has been torn. However, most of them are focusedon lossy compression and only marginally support the lossless mode. In this paper, I will focus on lossless formatsand the critical question: "Which one is the most efficient?" It turned out that FLIF is currently the most efficientformat for lossless image compression. This finding is in contrast to that FLIF developers stopped its developmentin favor of JPEG XL.
The halal fashion trends for hijabi community: Ideology and consumption

The research is based on a large enough market potential for the development of the halal fashion industry in Indonesia. The hijab fashion trend is a production target that continues to develop with various technologies and innovations, which encourage the consumption of community groups to use hijab fashion to continue to increase. The study was conducted to determine the purpose of the hijab community in using halal hijab fashion as part of their identity in demonstrating the existence of the hijab group through the ideological and consumption approaches. Qualitative analysis is carried out to determine the ideological emphasis and consumption of the hijab community through open interviews to obtain a clear picture of the social situation. The results show that religious beliefs are the main basis in encouraging the use of hijab and necessity factors.
Students’ Errors in the Use of Present Participle in Translating Simple Dialog at the Eleventh Grade of SMK Taruna Masmur Pekanbaru

The research proposed a formulation of the problem: what kinds of errors were produced in the use of present participle in translating simple dialog by the students at the eleventh grade of SMK Taruna Masmur Pekanbaru. The objective of the research was to explain the kinds of students’ errors in the use of present participle in translating simple dialog at the eleventh grade students of SMK Taruna Masmur Pekanbaru. The research design is descriptive research. The population of this research was the eleventh grade students of SMK Taruna Masmur Pekanbaru in 2017/2018 academic year. It consisted of one class; the number of population was 14 students. The sample of this research was 14 students. The instrument of this research were test and documentation. The technique of analyzing data was quantitative analysis. Based on the data analysis, the researcher concluded that the percentage of all indicators were misformation (40 errors or 56.3%), omission (17 errors or 23.9%), addition (13 errors or 18.3%), and misordering (1 error or 1.4%). From the data above the most common errors produced by the eleventh grade students of SMK Taruna Masmur Pekanbaru was misformation consisting of 40 errors or 56.3%.
Metode Seleksi Fitur Untuk Klasifikasi Sentimen Menggunakan Algoritma Naive Bayes: Sebuah Literature Review

In the era of the industrial revolution 4.0 as it is today, where the internet is a necessity for people to live their daily lives. The high intensity of internet use in the community, it causes the distribution of information in it to spread widely and quickly. The rapid distribution of information on the internet is also in line with the growing growth of digital data, so that the public opinions contained therein become important things. Because, from this digital data, it can be processed with sentiment analysis in order to obtain useful information about issues that are developing in the community or to find out public opinion on a company's product. The number of studies related to sentiment analysis that applies the Naive Bayes algorithm to solve the problem, so researchers are interested in conducting research on the use of feature selection for the algorithm. Therefore, this research was conducted to determine what feature selection is the most optimal when combined with the Naive Bayes algorithm using the Systematic Literature Review (SLR) research method. The results of this study concluded that the most optimal feature selection method when combined with the Naive Bayes algorithm is the Particle Swarm Optimization (PSO) method with an average accuracy value of 89.08%.
Quantum Codes Obtained through Constacyclic Codes over Z3 + Î½Z3 + Ï‰Z3 + Î½Ï‰Z3

This paper is concerned with, structural properties and construction of quantum codes over Z3 by using constacyclic codes over the finite commutative non-chain ring R = Z3 + Î½Z3 + Ï‰Z3 + Î½Ï‰Z3 where Î½2 = 1, Ï‰2 = Ï‰, Î½Ï‰ = Î½Ï‰, and Z3 is field having 3 elements with characteristic 3. A Gray map is defined between R and Z43. The parameters of quantum codes over Z3 are obtained by decomposing constacyclic codes into cyclic and negacyclic codes over Z3. As an application, some examples of quantum codes of arbitrary length, are also obtained.
Analisys of teaching elements on technical and mathematical disciplines in modern distance education

The object of research is the quality of teaching technical and mathematical disciplines in modern distance education. One of the most problematic areas is communication, dialogue between a teacher and a student, personality problems in the teacher-student dyad, and the effectiveness of feedback. The idea of distance learning, obviously, is that the interaction between teacher and student takes place in a virtual space. The more efficiently this interaction is built by using a variety of techniques, methods, the better a teaching process. Distance teaching is essentially a person-centered form of education. This is a separate modern educational technology that provides a choice for the teacher, the ability to select educational material depending on the information needs of students. In the course of the study, the main possibilities for improving the effectiveness of feedback between the student and the teacher and the forms of implementing such communication were considered. The organizational and pedagogical conditions for the use of the system of certain elements of distance learning in the process of vocational training have been substantiated. Modern information technologies and innovative teaching methods in training specialists are described. It is proposed to use more actively such elements as an interactive whiteboard, interactive processing of students’ statements during a survey, both in the form of tests or a forum, and in the form of a «word cloud». The use of these interactive elements has proven itself in practice. As a tool for objective assessment of the level of feedback, a comparative analysis of statistical data is proposed, which concerns the distribution of marks at the beginning and at the end of the distance learning course. This data can also be interpreted as an indicator of the quality of teaching. In particular, the analysis of school preparation of students for mastering mathematical disciplines in higher education was carried out. Comparative analysis substantiated, in particular, the need for additional classes for students with poor preparation.
On the Parameterized Complexity of Polytree Learning

A Bayesian network is a directed acyclic graph that represents statistical dependencies between variables of a joint probability distribution. A fundamental task in data science is to learn a Bayesian network from observed data. Polytree Learning is the problem of learning an optimal Bayesian network that fulfills the additional property that its underlying undirected graph is a forest. In this work, we revisit the complexity of Polytree Learning. We show that Polytree Learning can be solved in single-exponential FPT time for the number of variables. Moreover, we consider the influence of d, the number of variables that might receive a nonempty parent set in the final DAG on the complexity of Polytree Learning. We show that Polytree Learning is presumably not fixed-parameter tractable for d, unlike Bayesian network learning which is fixed-parameter tractable for d. Finally, we show that if d and the maximum parent set size are bounded, then we can obtain efficient algorithms.
ADAPTING COURSE DESIGN TO FOSTER THE DEVELOPMENT OF SPATIAL ABILITIES IN ENGINEERING EDUCATION – A CASE STUDY

Spatial skills are crucial for engineering designers, particularly when interpreting views of an object represented by drawings, visualising parts, or manipulating geometry in CAD.Spatial skills can be improved through instruction, teaching, and training.Several interventions are described in the literature.Established approaches in engineering education are, for example, sketching exercises and technical drawing tasks.Emerging visualisation possibilities such as Virtual Reality, Augmented Reality or Mixed Reality is the subject of current studies in the field.However, their effect on the development of spatial skills needs further studies.In a previous study, the authors have investigated which visualisation techniques can positively influence the development of student's spatial skills.Here we want to take a more detailed look at the following question: How can we adapt an introductory engineering design course to match these findings?In this paper, we report on our experiences from using various training to develop spatial skills.First, we will show the interventions that have already been considered in the teaching concept.The use of technical sketching and CAD will be explained in detail.The findings of our previous study, which informed the modification of the course, will be summarised.This includes specific interventions and training, covering machine elements and sketching exercises and interactive e-learning content.
ULIN-D: WEB-BASED GIS SUPPORTING NEW HABITS IN THE TOURISM SECTOR IN BANDUNG CITY

Abstract. Indonesia is one of the countries that has enormous tourism potential where this sector has contributed a total of 229.5 trillion for the country's foreign exchange. However, in the current state of the COVID-19 pandemic, many businesses in the tourism sector have to stop temporarily and result in economic pressure which directly impacts the acceleration of the economic recession in Indonesia. One of the solutions to reduce the impact of economic pressure while reducing the risk of COVID-19 transmission in the tourism sector is the application of health protocols that are directly applied in tourist attractions. To do this a variety of careful preparations are needed. In this case, geospatial information technology can help the community, government, and tourism business managers in implementing health protocols in tourist attractions. Seeing the urgency of implementing health protocols in the tourism sector, we developed the ULIN-D product as a WebGIS platform that is able to visualize, plan, and evaluate the condition of health protocol facilities in various tourist locations. Some of ULIN-D's strategic functions are its ability to provide recommended visitor capacity, display the number of visitors in real-time, and display the number of hand-washing places at tourist attractions based on the profile characteristics of each tourist location. The method used in this research is the combination of various kinds of spatial data and non-spatial data in a dynamic and integrated platform. Tourism location profile information is analyzed in detail to obtain accurate scenario results in establishing a standard health protocol. ULIN-D is expected to be a solution and a reference for how geospatial technology can help improve the quality of policies in the tourism sector for the continuation of the new habits adaption.
A Hybrid Approach for Landmark Recognition using Deep Local Features and Residual Network-50

As smartphones and mobile data become universal in modern society, the opportunities to interact with the real world would grow tremendously. Latest Technologies such as Oculus Rift and Google Glass attempt to bridge the gap between the virtual and the material. With advancements in computing speed and image recognition, the idea of augmented reality (AR) becomes more tangible. However, the sheer complexity of image processing and feature recognition is an area of concern for AR. A successful AR system must distinguish among many landmarks and identify or classify the existence of new landmarks. AR algorithms naturally lend themselves to using deep learning because of the adaptability required to various factors. This paper aims to develop and refine a deep learning algorithm that can distinguish landmarks from images using a google landmark database of known landmarks. Instance-level recognition is universally used in areas of Landmark recognition and is also the upcoming research area. Instance-level recognition is the brain behind Landmark recognition. As in Landmarks, the goal is to seek an instance of a common group instead of a group, requiring new deep learning techniques. In this paper, three different VGG16, Inceptionv3, and ResNet50 models are trained using the transfer learning technique and a Pure Convolutional Neural Network (CNN) model is also trained from scratch. This paper proposes a modified version of the ResNet50 model to increase the accuracy and performance of the models used. The revised version of Resnet50 contains an additional Deep Local Features (DeLF) processing layer before generating the final output.
Learning and Planning Under Uncertainty for Green Security

Green security concerns the protection of the world's wildlife, forests, and fisheries from poaching, illegal logging, and illegal fishing. Unfortunately, conservation efforts in green security domains are constrained by the limited availability of defenders, who must patrol vast areas to protect from attackers. Artificial intelligence (AI) techniques have been developed for green security and other security settings, such as US Coast Guard patrols and airport screenings, but effective deployment of AI in these settings requires learning adversarial behavior and planning in complex environments where the true dynamics may be unknown. My research develops novel techniques in machine learning and game theory to enable the effective development and deployment of AI in these resource-constrained settings. Notably, my work has spanned the pipeline from learning in a supervised setting, planning in stochastic environments, sequential planning in uncertain environments, and deployment in the real world. The overarching goal is to optimally allocate scarce resources under uncertainty for environmental conservation.
Thirty Years’ History of International Scientific Conferences in the National Library of Ukraine named after V. I. Vernadsky

Since the great historical event - the proclamation of the Act of Independence of Ukraine, the country has been expanding international cooperation in librarianship. The main areas of international cooperation, which is a priority in research institutions in the library business, are: conducting joint research; organization of international conferences, symposia, congresses and other events. Scientific conferences are one of the forms of dissemination of new information. In the modern information space, scientific institutions play an essential role in developing science, education and culture. Therefore, when evaluating a scientific institution, the number of international scientific and practical seminars, conferences, other events organized by the scientific institution, and materials (including collections of abstracts) of conferences are considered. Among the research institutions of Ukraine, which study the problems of library science, bibliography, bibliology, source studies, document science, archival science, biography, codicology and discography, history of book culture, computer science, social communications, the leading position is held by the most extensive library of Ukraine – the National Library of Ukraine, named after V. I. Vernadsky. Furthermore, the article analyzes the specifics of the organization of scientific conferences in a scientific institution, studies the directions and thematic content of such events, forms of conduct, their frequency during 1991-2021.
Wall Climbing Glass Cleaner Robot

The main motive of glass climbing robot is to climb and move on glass surface.To achieve this purpose efficient attachment and detachment is an important aspect.Centrifugal impeller is used which generation the low-pressure area for proper adhesion on the wall surface.This type of robot can take place of humans to carry out hazardous work such as cleaning of glass.
A RFE- Optimised Method for Predicting the Malignancy of the Breast Cancer

Breast cancer has the most mortality rate in the case of cancer after the skin cancer. Early detection of the tumour cells would help in different therapeutic treatments. In our study, RFE (recursive feature elimination) is implemented for selecting the optimal set of features which could help on characterizing the tumor cells. The feature size has been reduced to half making the algorithm faster. The combination of RFE has been implemented with different types of classifiers and the best result was obtained in the case of logistic regression with an accuracy of 96.5% and an auc score of 0.98. This study could help in the automation of the prediction of the breast cancer type and make the process more accurate.
Sports and hate speech messages on Instagram

The Internet and social media should serve as outlets for people to share their stories and to communicate with others. The tensions between the great possibilities of user participation and the lack of strategies or resources by the authorities offer an almost perfect scenario for the growth of some types of hate speech, especially in the case of sports. However, hate speech is one of the most important scourges users must live with nowadays, particularly in the case of soccer. In this chapter, several issues will be covered, such as the theory of the Internet, social media and hate speech with a longitudinal analysis of the bibliography in this field and data, legislation and examples of sentences that illustrate hate speech. In addition, to explore the hate speech phenomenon, the authors will analyse the specific case of the Seville Football Club (@sevillafc) Instagram account. A compilation of the most frequently used insults will be displayed and commented on and studied in-depth. All the results will be shown in graphs and tables. This chapter wants to provide a broader and deeper understanding of the media ecosystem and their greatest challenges.
Learning Progression: How should we teach about disease to determine students’ level of understanding?

Strengthening Learning Progression (LP) for students' reasoning abilities is important, especially learning about diseases in Indonesia. This study aimed to map the learning progression of disease in Indonesia, compare and analyze its similarities and differences with the LP designed by National Reseaarch Council (NRC). This qualitative research to map LP, using the analysis documen method by comparing the content analysis of Basic Competencies of Curriculum 13 with benchmark analysis from the NRC 2007 on Science and Biology textbooks published in 2016, 2017, and 2018 at the elementary, junior high, and high school levels published by the Ministry of Education and Culture of the Republic of Indonesia. The findings are the LP on disease in the curriculum and life science textbooks in Indonesia has not met the benchmarks, especially in three categories, namely; pathogens, the immune system, and infection spanning learning from K-2 (elementary) to K-12 (high school). Therefore, it is necessary to categorize LP topics in diseases based on conceptual abilities from the simplest to the most complex.
LMC-SMCA: A New Active Learning Method in ASR

In Automatic Speech Recognition (ASR), transcribed data take substantial effort to obtain. It is worthwhile to explore how to selective the samples with more information from un-transcribed datapool to get a better model with the limited cost. Therefore, active learning in ASR becomes a research topic. In this manuscript, we proposed two new methods of active learning. One is Signal-Model Committee Approach (SMCA) and the other is LM-based Certainty Approach (LMCA). These two methods respectively evaluate the information amount of samples from different angles and can be applied together for joint sampling in some scenarios. We conducted many comparative experiments on Listen, Attend and Spell (LAS) model according to different demands. In experiments, we compared our approach with the random sampling and another state-of-the-art committee-based approach: heterogeneous neural networks (HNN) based approach. We examined our approach in CER in Chinese Mandarin speech recognition task. The results show that proposed approach is not only simple to use, but also has the best performance.