Reviewerly/exHarmony huggingface dataset:
Issues Faced by Minority Ethnic Groups’ Students Reflected in Their Writing

This research attempted to determine issues faced by minority ethnic groups’ students in English Language Education Department in private university in Malang, and whether ethnicity and social aspects played significant roles in the students’ language proficiency reflected in their vocabulary in writing class. The researcher analysed writing samples taken from 16 students from both minority and majority ethnic groups by utilising Voyant Tools which focused on vocabulary density and average words per sentence. Followed with spreading questionnaires to eight students of minority ethnic groups and interviewing two of them who earned highest scored based on Voyant Tools. Those sessions were analysed with Thick Description to focus on related issues regarding vocabulary proficiency and ethnicities. The results taken from Voyant Tools indicated that students from minority ethnic groups were lesser than the students from majority one’s. Those results depicted the vocabulary proficiency of students from minority ethnic groups in writing, and those results were affected by educational deprived in their origins, and verbal abuse regarding their ethnicity. The researcher discovered that verbal abuse towards ethnicity regarded as individual discrimination that strengthens the majority’s idea to emphasise their superiority over the inferior. People tend to overlook the fact that verbal abuse among students was existed in universities and it affecting students’ performance. This notion was supported by the result taken from Voyant Tools in which the result shown that the minority ethnic groups were lesser than majority one’s and the effect were reflected at their writing, notably their vocabulary proficiency.
Comparison of Optimization Techniques for Process Recognition Using Deep Neural Network

This paper brings the topic of comparison of optimization techniques using gradient descent, gradient descent with momentum, Adam and learning rate decay in combination with previous optimization algorithms for face recognition using deep neural network. This paper compares several settings of these techniques as well as techniques among themselves with combination of regularization techniques varying in using no regularization, L2 regularization and dropout to successfully recognize the sex of a person captured. The result of the evaluation is taken in a matter of successfully recognized face rate for train data and test data, cost and deep neural network learning time.
Differentiating the Curriculum to Achieve "Learner Growth" when using 1:1 Mobile Devices for Learning

With the increasing use of 1:1 mobile devices within the curriculum space, differentiating its use to support "learner growth" has become an important discussion amongst policy makers, researchers, educators and learners.This research study provides an insight into how learners are using their 1:1 mobile device to support their learning process.The premise of the discussion begins with the notion that a learner's success is dependent on the curriculum design been sufficiently differentiated using resources and scaffolding.Differentiating to develop technical skills that will lead to the production of artefacts as evidence of learning and creativity.This research study highlights the role of the digitally literate educational leader who can apply self-directed differentiation learning theory to model the use of 1:1 mobile devices to support "learner growth".The research study reveals learners come with pre, during and post learning perceptions, and understandings about how 1:1 mobile devices can be used to support their "learning growth".These perceptions and motivations for learning will need to be considered along with self-directed learning theory and applied to the delivery of linear and non-linear curriculum design.
Features of Students’ Interaction in Multicultural Educational Environment

The article is devoted to the analysis of relationships within the children's multicultural team.Due to the large migration flows, the contemporary research focuses on studying the features of the educational process when participants are representatives of different cultures.Particular attention is focused on the relationships between students in the multicultural school community.The key goal of this study is to identify the understanding of the category of tolerance by the school students, as well as to analyse the specifics of the atmosphere in a multicultural class through the peculiarities of the students themselves interacting with each other and showing their interest in other cultures.Another objective of the study was to identify the possible students' stereotypes concerning other cultures.
Aplikasi Media Pembelajaran Aksara Sunda Berbasis Android

The Sundanese script is the work of orthography of Sundanese people since around the 5th century AD until today. However, the lack of interesting and motivating media to learn scripts, both printed and electronic, makes the Sundanese script endangered. With the rapid development of technology and the era of digitalization as today, most Indonesian people have smartphones with Android operating systems that are easy to carry anywhere. Android is not only used as a communication and entertainment tool, but also as a method that can be developed as a learning medium that can convey learning material textually, and audio-visually. The purpose of this research is to design an easy-to-use Sundanese script learning media application and to implement an Android-based Sundanese script learning media application so that the public is interested in learning Sundanese script. The method used for application development is MDLC (Multimedia Development Life Cycle) multimedia application in education which consists of 6 stages, including Concept, Design, Material Collecting, Assembly, Testing and Distribution. The result obtained from this study is the Android-based application of Sundanese script learning media. The application has been tested with alpha test and from the results of the test, it can be concluded that the public can easily learn the Sundanese script with an attractive appearance because this application is equipped with audio pronunciation of the Sundanese script.
PortraitAI: A Deep Learning-Based Approach for Generating User Portrait for Online Dating Website

User portrait is an important technique which could be widely adopted in many real-world applications.It refers to the task of estimating user"s attributes containing their potential preferences and thus could be used to make better recommendations.Online dating Website is one of the most popular web applications which usually has more than 100 million users.Users of such Website are usually required to write down a brief selfintroduction as well as fill in important attributes which are then used to make the friend recommendation.However, such data generally contains a good number of missing data or fake information.To cope with this challenge, this paper proposes a deep learning-based approach to generate user portrait merely from user"s self-introduction.Then, a multi-task deep neural network is adopted to simultaneously estimate five kinds of attributes, e.g., age, gender, education, salary and characteristics, from the input textual data.The experimental dataset is collected from one famous dating Website in China.Both the proposed approach as well as three benchmark approaches are implemented and the results are reported.The performance of the proposed approach is superior to the compared method with respect to accuracy.
Similar but Superior: Rhetoric of Coexistence Employed by Religions in Jeju Island, Korea

Religions in Jeju, South Korea, have sometimes been in conflict with each other, but have generally coexisted peacefully. In a situation where diverse religions share an island that is isolated from the mainland, they have emphasized that they are similar yet superior to their rivals. Religions that were imported to Jeju, including Confucianism, Buddhism, and Christianity, have tried to make themselves look familiar to Jeju people on the basis of people’s knowledge of preexisting religions. These religions sometimes embraced rituals of preexisting religions to which people were strongly attached. The Jeju indigenous religion has also acknowledged that the ideas and practices of Buddhism and Confucianism have remarkable similarities to those of its own. Simultaneously, each religion in Jeju has claimed its superiority over others. Religions in Jeju have argued that other religions’ partial truth and limited value are in sharp contrast with the complete truth and superior value of their own. They have asserted that only they can provide the proper way of keeping the order of the universe or attaining salvation of human beings. This common rhetoric that “my religion is similar but superior to other religions” has been repeated in Jeju, in order to persuade people outside the religion to accept or at least approve it on the one hand, and to maintain the peaceful coexistence with other religions on the other hand.
Increasing communication efficiency among teachers and parents by using ClassDojo

This research aim is to investigate what is the impact ClassDojo of application on teachers and parents' communication about students' behavior and performances during school activities.54 parents participated in this research, females (N=46) and males (N=8) and two teachers, both female, who use ClassDojo in their daily activities, on a regular basis.The research methodology was based on applying a questionnaire through the Google Forms channel in order to identify the advantages and the disadvantages parents and teachers emphasize based on the ClassDojo usage.Results proved that the usage of the application brings a lot of positive aspects during teachers-parents communication relation, making this relation more efficient and having good implications in managing pupils` behavior during primary school level.
Reconnaissance Geochemical Exploration in Kaiama, North Central, Nigeria

Reconnaissance exploration for ore mineralization in Kaiama and environ have been carried out using integrated geological mapping and geochemical survey of soils, stream sediments and exposure of pegmatite/quartz veins.This was done in order to define the ore forming elements distribution and recognising type and area of possible mineralization in Kaiama and environ.. Eighteen samples were collected and analyzed for major and trace elements by x-ray fluorescence (XRF) and particle induced x-ray emission (PIXE) methods.Petrological description of thin sections of rocks was also carried out under the petrological microscope.The rocks underlying Kaiama consist of amphibolites, mica schists and granites along with fracture controlled mostly sheared mineralised pegmatite and quartz veins The fractured filled veins mainly trend NW-SE, NNE-SSW and E-W, N-S as to compare closely to the general trend of structures resulting from Pan-African orogeny.The mineralisation notably includes columbite-tantalite, rutile, cassiterites, ilmenites, wolframites, gold and gem stones.Geochemically, the trace elements concentrations shows significant anomalous concentrations of Sn, S, Ti, W, Au, Cu, Ti and Nb in the soil and stream sediments and Sn, W, and Nb in the veins.In addition, Zn, Cr, Co, Ni, Cd, Sb, Mo, V, As, Pb, Rb occurs in less significant anomalous concentrations in all the geologic media.The anomalous magnitude however decreases from soil to stream sediments and least in the veins.Further exploration work should be concentrated on soils and stream sediments towards delineating the possible ore deposit in the area of Kaiama and environs.
The Image Annotation Method by Convolutional Features from Intermediate Layer of Deep Learning Based on Internet of Things

Existing image annotation methods that employ convolutional features of deep learning methods from the Internet of Things (IoT) have a number of limitations, including complex training and high space/time expenses associated with the image annotation procedure. Accordingly, this paper proposes an innovative method in which the visual features of the image are presented by the intermediate layer features of deep learning, while semantic concepts are represented by mean vectors of positive samples. Firstly, the convolutional result is directly output in the form of low-level visual features through the mid-level of the pre-trained deep learning model, with the image being represented by sparse coding in the IoT. Secondly, the positive mean vector method is used to construct visual feature vectors for each text vocabulary item, so that a visual feature vector database is created. Finally, the visual feature vector similarity between the testing image and all text vocabulary is calculated, and the vocabulary with the largest similarity is taken from the IoT as the words used for annotation. Experiments on multiple datasets demonstrate the effectiveness of the proposed method; in terms of F1 score, the proposed method's performance on the Corel5k and IAPR TC-12 datasets is superior to that of MBRM, JEC-AF, JEC-DF, and 2PKNN with end-to-end deep features.
Blasphemy law, mental illness and the potential for injustice: a cautionary tale from Indonesia

This article highlights troubling recent cases in Pakistan and Indonesia involving the preferring of the criminal charge of blasphemy. It gives particular scrutiny to the charges of blasphemy and blasphemous libel brought against Suzethe Margaret, a Catholic woman with schizophrenia in Indonesia in 2019. While it applauds the fact that in February 2020 she was acquitted by the Cibinong District Court, it expresses concern about the period of time she was held in detention without resolution of her circum stances and the risk that the decision could have been less legally rigorous. It utilises the case to reflect on the risks inherent in the subjectivity in the charge of blasphemy and the particular dangers when the accused person suffers from a mental illness that may either preclude their fitness to be tried or raise the potential for them to be not guilty by reason of mental impairment/insanity.
Island Loss for Improving the Classification of Facial Attributes with Transfer Learning on Deep Convolutional Neural Network

Classification task on the human facial attribute is hard because of the similarities in between classes.For example, emotion classification and age estimation are two important applications.There are very little changes between the different emotions of a person and a different person has a different way of expressing the same emotion.Same for age classification.There is little difference between consecutive ages.Another problem is the image resolution.Small images contain less information and large image requires a large model and lots of data to train properly.To solve both of these problems this work proposes using transfer learning on a pre-trained model combining a custom loss function called Island Loss to reduce the intra-class variation and increase the inter-class variation.The experiments have shown impressive results on both of the application with this method and achieved higher accuracies compared to previous methods on several benchmark datasets.
Analysing installation scenarios of Debian packages

Abstract The Debian distribution includes more than 28 thousand maintainer scripts, almost all of them are written in P osix shell. These scripts are executed with root privileges at installation, update, and removal of a package, which make them critical for system maintenance. While Debian policy provides guidance for package maintainers producing the scripts, few tools exist to check the compliance of a script to it. We report on the application of a formal verification approach based on symbolic execution to find violations of some non-trivial properties required by Debian policy in maintainer scripts. We present our methodology and give an overview of our toolchain. We obtained promising results: our toolchain is effective in analysing a large set of Debian maintainer scripts and it pointed out over 150 policy violations that lead to reports (more than half already fixed) on the Debian Bug Tracking system.
IMPACT VISION SYSTEM ON ACROBATICS GYMNASTS’ BALANCE STABILITY

Acrobatics gymnastics is a discipline that is one of the best examples of the ability of human body to maintain balance.Therefore, the high level of balance stability of acrobatics gymnasts is very important in order to achieve high level of results in this sport.The aim of present study is to determine what is the impact of vision on acrobatics gymnasts' balance stability.Methods.12 gymnast national level gymnasts (females) aged 15 (SD ±3) were involved in this study.Validate force platform (Huurnink et al., 2013) "Nintendo Wii Balance board" (WBB) were used.The parameterization of center of pressure (CoP) trajectories changes, ellipse area, were measured.After individual warm up ten tests, 30 seconds each, plus two tests 10 seconds (twelve in total), were performed on a WBB.Compare analyze showed significant differences between COP EA (eyes open and eyes closed) tests.Individual tests showed up three to four times lower results, exception for test №7 and №8 (handstand).Conclusion: COP -Ellipse area increased with significant difference, average 26,53 cm^2 or 214% between eyes open and eyes closed tests.More than two times lower results of the balance stability without vision (eyes closed).Total path Len (TPL) also increased with significant difference, average 143,52 cm. or 116% between EO and EC tests.More than one times longer TPL, which confirm the results of COP EA also.Results of the present study is a starting point for further research in regard of the development of new accelerating methodologies of training in balance exercises in acrobatics gymnastics.
Hiding Compressed and Encrypted Data by using a Technique of Steganography

The steganography is a technique which hide the text data in the color and gray images .We can use different type of steganography techniques.Some Techniques are used in spatial Domain Technique.Some techniques are used in frequency Domain.Some steganography techniques are very popular like LSB, MSB and 7 bits in hiding the invisible information in various file formats images.In this paper, Steganography and Cryptography is combined for hiding and unhiding a text file into an image file.Data Compression is also used in this technique.LSB insertion technique is used for Steganography and LZ algorithm is used for Data Compression.Cryptography is done with RSA algorithm
$$\mathsf {GOOSE}$$: A Secure Framework for Graph Outsourcing and SPARQL Evaluation

We address the security concerns that occur when outsourcing graph data and query evaluation to an honest-but-curious cloud i.e., that executes tasks dutifully, but tries to gain as much information as possible. We present $$\mathsf {GOOSE}$$, a secure framework for Graph OutsOurcing and SPARQL Evaluation. $$\mathsf {GOOSE}$$ relies on cryptographic schemes and secure multi-party computation to achieve desirable security properties: (i) no cloud node can learn the graph, (ii) no cloud node can learn at the same time the query and the query answers, and (iii) an external network observer cannot learn the graph, the query, or the query answers. As query language, $$\mathsf {GOOSE}$$ supports Unions of Conjunctions of Regular Path Queries ($$\mathsf {UCRPQ}$$) that are at the core of the W3C’s SPARQL 1.1, including recursive queries. We show that the overhead due to cryptographic schemes is linear in the input’s and output’s size. We empirically show the scalability of $$\mathsf {GOOSE}$$ via a large-scale experimental study.
Association Rules Algorithms for Data Mining Process Based on Multi Agent System

In this paper, we present a collaborative multi-agent based system for data mining. We have used two data mining model functions, clustering of variables in order to build homogeneous groups of attributes, association rules inside each of these groups and a multi-agent approach to integrate the both data mining techniques. For the association rules extraction, we use both apriori algorithm and genetic algorithm. The main goal of this paper is the evaluation of the association rules obtained by running apriori and genetic algorithm using quantitative datasets in multi agent environment.
Improving Fishermens Welfare with Fuel-Saving Technology

The problem of energy for fishermen is indeed very complex. When fuel prices rise, it is very worrying that the poor in Indonesia will increase. The study aimed to find out the development of fishermen, as well as the benefits of using Brown’s Gas Electrolyzer (BG-E) on a fishing boat in Indonesia. This type of data is secondary and sourced from second parties (Government Office and others). Analysis, synthesis methods, and alternative problem solving are prepared based on data, information, and observations to solve fisherman's problems based on research objectives. The application of BG-E technology can be applied to small-scale fishing boats, is Outboard Motorboats and 5-30 GT Motorboats. BG-E is made according to the ship's power requirements. The way it works through an electrolysis process to decompose compounds in the form of solutions melts, or ordinary liquids by the electric current flowing through the compound. From the results of the electrolysis process, it produces oxyhydrogen which will react with gasoline in the boat engine. This reaction will produce an explosion to move the piston on the ship's engine so that the engine can live. With the implementation of BG-E, it can save fuel oil consumption and improve the welfare of Indonesian fishermen. The originality of the research is related to the method used in the framework of estimating Fishermen fuel savings in Indonesia, so that the study will become novelty in the future.
Intention Detection Based On Bert-Bilstm in Taskoriented Dialogue System

As an important module of intelligent dialogue system, intention detection has become an important research direction of man-machine dialogue at present. However, in the taskoriented dialogue, there are still problems that users’ intention detection accuracy is low because of users’ non-standard expression and excessive implied intentions. In order to solve the above problem, this paper proposes to use BERT launched by Google as a pre-training model, and use BiLSTM to build intention detection model of the task-oriented human-machine dialogue. With the Cambridge University Restaurant Reservation Corpus as the dataset, the accuracy of the intention detection model can reach 92.39% finally. Which provides a feasible solution for detecting users’ intention in task-oriented man-machine dialogue system.
Implementation of Document Management System using Levenshtein Distance Algorithm

The document archiving in PT SIU is still manually so it takes a long time in the process of storing and searching an archive document.Document Management System is a process or activity that starts from the making, receiving, collecting, organizing, controlling, maintaining, maintaining and storing which can be used as a solution in order to solve the problems that occur.With this research, previously manual storage and search became computerized so that the process of storing and searching for information related to document archiving systems became easier, and faster.