Reviewerly/exHarmony huggingface dataset:
Does the dataset meet your expectations? Explaining sample representation in image data

Since the behavior of a neural network model is adversely affected by a lack of diversity in training data, we present a method that identifies and explains such deficiencies. When a dataset is labeled, we note that annotations alone are capable of providing a human interpretable summary of sample diversity. This allows explaining any lack of diversity as the mismatch found when comparing the \textit{actual} distribution of annotations in the dataset with an \textit{expected} distribution of annotations, specified manually to capture essential label diversity. While, in many practical cases, labeling (samples $\rightarrow$ annotations) is expensive, its inverse, simulation (annotations $\rightarrow$ samples) can be cheaper. By mapping the expected distribution of annotations into test samples using parametric simulation, we present a method that explains sample representation using the mismatch in diversity between simulated and collected data. We then apply the method to examine a dataset of geometric shapes to qualitatively and quantitatively explain sample representation in terms of comprehensible aspects such as size, position, and pixel brightness.
NGO Data Protection using Ethereum Blockchain Technology

A growing stream of research finds several relations between the economic growth and corruption. Government implements various strategies to diminish the corruption and also technology often plays a dominant role to face it. Among various technologies alterations, Block-chain technology that becomes an effective and efficient way to resolve these issues related to corruption. This paper represents a brief knowledge related to the Block-Chain technology as it is a kind of distributed database or public ledger of all transactions that have been executed and shared among participating parties. Each and every transaction in the public ledger is verified by a majority of the participants registered in the system. The possible risk related to current scenario and give brief idea for resolving that problem with the help of blockchain technology. Non-Governmental Organization (NGOs) which aim is to tackle some of the issues faced by the society. NGO faces difficulty in terms of maintaining and gaining the support from donors in terms of funds. In recent decades there have been multiple examples of corruption misconduct scandals impacting the public image and reputation of NGOs. It is clear that trust of the people in NGOs is affected adversely by such events. Doubts arise in terms of where does the donation ends up? Who is leading the organization? Is donated money are used in a proper direction? So as a part of it, a need is raised to solve such issues for the betterment of the society. For the above stated problem regarding management of funds in NGOs, we propose a solution by using the Blockchain technology among various technologies alteration available. Blockchain offers the way to eliminate the doubts by providing data security, immutability and transparency. So, Blockchain Technology can offer the NGO industry to regain the trust of public.
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction

This paper investigates how to effectively incorporate a pre-trained masked language model (MLM), such as BERT, into an encoder-decoder (EncDec) model for grammatical error correction (GEC). The answer to this question is not as straightforward as one might expect because the previous common methods for incorporating a MLM into an EncDec model have potential drawbacks when applied to GEC. For example, the distribution of the inputs to a GEC model can be considerably different (erroneous, clumsy, etc.) from that of the corpora used for pre-training MLMs; however, this issue is not addressed in the previous methods. Our experiments show that our proposed method, where we first fine-tune a MLM with a given GEC corpus and then use the output of the fine-tuned MLM as additional features in the GEC model, maximizes the benefit of the MLM. The best-performing model achieves state-of-the-art performances on the BEA-2019 and CoNLL-2014 benchmarks. Our code is publicly available at: https://github.com/kanekomasahiro/bert-gec.
Multi-agent navigation based on deep reinforcement learning and traditional pathfinding algorithm

We develop a new framework for multi-agent collision avoidance problem. The framework combined traditional pathfinding algorithm and reinforcement learning. In our approach, the agents learn whether to be navigated or to take simple actions to avoid their partners via a deep neural network trained by reinforcement learning at each time step. This framework makes it possible for agents to arrive terminal points in abstract new scenarios. In our experiments, we use Unity3D and Tensorflow to build the model and environment for our scenarios. We analyze the results and modify the parameters to approach a well-behaved strategy for our agents. Our strategy could be attached in different environments under different cases, especially when the scale is large.
Evaluating Dialogue Generation Systems via Response Selection

Existing automatic evaluation metrics for open-domain dialogue response generation systems correlate poorly with human evaluation. We focus on evaluating response generation systems via response selection. To evaluate systems properly via response selection, we propose the method to construct response selection test sets with well-chosen false candidates. Specifically, we propose to construct test sets filtering out some types of false candidates: (i) those unrelated to the ground-truth response and (ii) those acceptable as appropriate responses. Through experiments, we demonstrate that evaluating systems via response selection with the test sets developed by our method correlates more strongly with human evaluation, compared with widely used automatic evaluation metrics such as BLEU.
Practice in the System of Training the Future Educator: Opportunities and Advantages

Horizon Research Publishing,USA (HRPUB) is a worldwide open access publisher serving the academic research and scientific communities by launching peer-reviewed journals covering a wide range of academic disciplines. As an international academic organization for researchers & scientists, we aim to provide researchers, writers, academic professors and students the most advanced research achievements in a broad range of areas, and to facilitate the academic exchange between them.
Development of Module and Augmented Reality Based Android Aplication Computer Assembly For Vocational High School Student

&lt;p&gt;Based on observation in class X TKJ SMK Negeri 1 Sawit. Students had some problem when learning computer assembly. That happens because lack of equipment and learning media. They need a learning media that can be used to study computer assembly not only inside a school but outside as well. We propose to solve that problem with developing a new learning media that can help students learn independently. We develop a module and android based augmented reality application called ARRAKOM . when ARRAKOM detect a marker in the module. It can display a 3-dimensional model in real time. Learning media is created using ADDIE consist of Analysis, Design, Development, Implementation, and Evaluation. In the development stage, we are using an incremental model and created 2 prototypes of ARRAKOM. In result of the feasibility test, Arrakom gets measured with a Likert scale from expert media get percentage 75% very good, 25% good, 0% bad, 0% very bad. for expert material get percentage 57% very good, 43% good, 0% bad, 0% very bad. And from user get percentage 47% very good, 43% good, 3% bad and 0% very bad.&lt;/p&gt;
SALA-An Integrated Framework for Speech Recognition Using Lexical Analyzer

First and foremost method of communication between humans is through speech. Speech is the most powerful communication tool if it is used in an appropriate way. These days English has become the most prominent and most used language for interaction between literates. Good communication is possible only if vocabulary of the preferred language is used appropriately. We have found need of a system which analyzes the vocabulary used in the spoken audio which is referred to as speech. This system developed an Integrated Framework for Speech Analysis using Lexical Analyzer (SALA). This system is used in several areas of concern such as in teaching, employment, communication skills, one's dexterity in English vocabulary. The proposed SALA takes input an audio which consists of English speech. This audio is parallelly recorded and also converted into text and is passed through tokenizer and lexical analyzer, then compared with GSL to create a report of the vocabulary levels used by the speaker in the input audio. This system uses the most popular Speech to Text Conversion to analyze the speech which is a peculiar branch of Artificial Intelligence.
EXPLORING ENGLISH STUDENT TEACHERS’ READING HABITS AND PREFERENCES

The vast benefits of reading in both the first and the target language makes reading essential for English Language Teaching Department students who are not only English language learners but also English teacher candidates. This study explores English student teachers’ reading habits and preferences. An open-ended and closed-ended questionnaire and interviews were used to collect information on 88 English student teachers’ reading habits and preferences. The participants’ reading habits were predicted by their attitudes towards reading, reading frequency, and reading material preferences. The findings suggest that although student teachers mostly displayed positive attitudes towards reading and acknowledged the importance of reading, they didn’t really invest in personal reading. In terms of reading preferences, most of the student teachers chose fiction books and online materials as the most preferred reading materials. When it comes to language preferences, most of them preferred to read in their first language (Indonesian) instead of the language they are currently learning (English) for both academic reading and reading for pleasure.
PENGARUH PENERAPAN METODE READING GUIDE TERHADAP PRESTASI AL-QURAN HADITS

Motivation for student learning is often with classroom management so the better the teacher doing classroom management has the potential to develop student interest and attractiveness. This study discusses student motivation due to the correlation between the management of PAI in SMA Wali Songo Sukobendu High School in 2019/2020. With a focus of research as follows: How is the management of PAI class XII  at SMA Wali Songo Sukobendu High School in 2019/2020 . What is the motivation for learning the PAI subjects in class XII at SMA Wali Songo Sukobendu High School in 2019/2020 . What is the correlation between classroom management and learning motivation of PAI subjects in class XII at SMA Wali Songo Sukobendu High School in 2019/2020 . This research uses quantitative methods with a sample of 39 respondents. While the data collection technique uses a questionnaire method (questionnaire) and data analysis uses the Pearson product moment correlation formula from the SPSS 20 application. With results, including: Class management at SMA Wali Songo Sukobendu High School is classified as good with a value interpretation of 68.7% because it is between the interval values of 51% - 75%. the motivation to learn ing PAI in SMA Wali Songo Sukobendu High School is classified as good with the interpretation of values which is 66.5% because it is between the interval values of 51% - 75%. The results of testing the research hypothesis show that there is a correlation between classroom management and learning motivation of PAI subjects in class XII in SMA Wali Songo Sukobendu High School in 2019/2020: A correlation of 0.370 can be obtained with a significant 0.020 ˂ 0.05 meaning that there is a significant correlation between classroom management variable (X) with learning motivation (Y) then Ho is rejected and Ha is accepted; Based on the price of a positive correlation coefficient of 0.370, the direction of the relationship is positive.
An adaptive algorithm for embedding information into compressed JPEG images using the QIM method

The widespread use of JPEG images makes them good covers for secret messages storing and transmitting. This paper proposes a new algorithm for embedding information in JPEG images based on the steganographic QIM method. The main problem of such embedding is the vulnerability to statistical steganalysis. To solve this problem, it is proposed to use a variable quantization step, which is adaptively selected for each block of the JPEG cover image. Experimental results show that the proposed approach successfully increases the security of embedding.
IDENTIFYING THE FEATURES OF TEACHERS’ VERBAL VIOLENCE IN ACEH SCHOOL

The present study identifies the features of verbal violence uttered by the teachers to students in two schools in Lhokseumawe Aceh. The design of this study was qualitative research with a phenomenology paradigm. The data of this study were in the oral utterances of teachers to students who represented verbal violence in learning at school. The data collection methods were observation and in-depth interviews to find out directly the features of teacher's violent words and phrases to students at school. The findings of this study indicated that verbal violence of teachers to the students ranged from insulting on the human body parts, addressing nicknames on animals and spirits, harassing, threatening, and cursing the students. The practical implication of the study for language teachers or students in Aceh and other parts of Indonesia is that teachers’ spoken language should communicate especially in educational settings at school.
Enhanced Framework of Quantum Approximate Optimization Algorithm and Its Parameter Setting Strategy

An enhanced framework of quantum approximate optimization algorithm (QAOA) is introduced and the parameter setting strategies are analyzed. The enhanced QAOA is as effective as the QAOA but exhibits greater computing power and flexibility, and with proper parameters, it can arrive at the optimal solution faster. Moreover, based on the analysis of this framework, strategies are provided to select the parameter at a cost of $O(1)$. Simulations are conducted on randomly generated 3-satisfiability (3-SAT) of scale of 20 qubits and the optimal solution can be found with a high probability in iterations much less than $O(\sqrt{N})$
Usuários dos arquivos: uma análise dos congressos nacionais de arquivologia

The scientific events in archival science are a space for reflection on the theoretical and practical aspects of the archivist’s professional practice. Through an exploratory research, addressing the qualitative and quantitative aspects, the points of discussion about users in the editions of the national archival science conference were analyzed, showing a very small participation.Keywords: archives; researcher; scientific event.
SECURITY OF DATA` IN CLOUD COMPUTING BASED ON ADVANCED SECRET SHARING KEY MANAGEMENT SCHEME

Cloud Computing (CC) is a worldwide concept and there are no boundaries define with in the cloud computer which is used to access and store user data can be located anywhere on the global nework, depending on where the capacities that are required are available in the global computer networks used for cloud computing.Because of the efficient features of (CC) many Organization are using cloud storage for storing their essential information.The data can be stored remotely in the cloud computing environment by the user and can be retrieved by the client at the time of need.Data security is the major concern in cloud computing.Data Storage is risky because of use of internet by cloud based services which means less control over the store data.Essential elements of cloud is how do we grab all the benefit of the cloud while maintain security controls over the organization assets.Our aim is to propose a more reliable, decentralized light weight keymanagement scheme (KMS) techniques for cloud system which provide more efficient data security.
Improving Performance of the VerCors Program Verifier

As program verification tools are becoming more powerful, and are used on larger programs, their performance also becomes more and more important. In this paper we investigate performance bottlenecks in the VerCors program verifier. Moreover, we also discuss two solutions to the identified performance bottlenecks: an improved encoding of arrays, as well as a technique to automatically generate trigger expressions to guide the underlying prover when reasoning about quantifiers. For both solutions we measure the effect on the performance. We see that the new encoding vastly reduces the verification time of certain programs, while other programs keep showing comparable times. This effect remains when moving to newer backends for VerCors.
Depth estimation on embedded computers for robot swarms in forest

Robot swarms to date are not prepared for autonomous navigation such as path planning and obstacle detection in forest floor, unable to achieve low-cost. The development of depth sensing and embedded computing hardware paves the way for swarm of terrestrial robots. The goal of this research is to improve this situation by developing low cost vision system for small ground robots to rapidly perceive terrain. We develop two depth estimation models and evaluate their performance on Raspberry Pi 4 and Jetson Nano in terms of accuracy, runtime and model size of depth estimation models, as well as memory consumption, power draw, temperature, and cost of above two embedded on-board computers. Our research demonstrated that auto-encoder network deployed on Raspberry Pi 4 runs at a power consumption of 3.4 W, memory consumption of about 200 MB, and mean runtime of 13 ms. This can be to meet our requirement for low-cost swarm of robots. Moreover, our analysis also indicated multi-scale deep network performs better for predicting depth map from blurred RGB images caused by camera motion. This paper mainly describes depth estimation models trained on our own dataset recorded in forest, and their performance on embedded on-board computers.
Adapting the Human: Leveraging Wearable Technology in HRI

Adhering to current HRI paradigms, all of the sensors, visualisation and legibility of actions and motions are borne by the robot or its working cell. This necessarily makes robots more complex or confines them into specialised, structured environments. We propose leveraging the state of the art of wearable technologies, such as augmented reality head mounted displays, smart watches, sensor tags and radio-frequency ranging, to "adapt" the human and reduce the requirements and complexity of robots.
E-Sharing : Developing a Web Based Online Donation System

Nowadays there are so many people who are surviving on only one meal per day. Especially in developing countries, it is one of the major problems. On the other hand, there is so much wastage of food every day. Some poor people need clothes and vessels, and children need some books and study kits. Solution to this is that we only need to donate the leftover food to needy people, charities, and our old stuff. For that to happen, we need some sort of platform. This could be any online platform like a website/web application. In Saudi Arabia, there are so many people who are capable of making donations and also there are so many Nongovernmental Organizations (NGOs) which are helping poor and needy people of Saudi Arabia. But to connection gap is not as blur as it should be. There has to be some simple, fast, intuitive and secure way of doing such online donations so that users can donate easily with just a click. The aim of this work is to design and develop a Web Based Online charitable Donation System. Where, the charitable website will collect the charitable donations (such as clothes, toys, school tools) and delivers it to the children who need it. The proposed system will provide voluntary opportunities for those wishing to be volunteer in delivering the donations to the homes of the poor for free. The proposed work was designed and developed using the Unified Modeling Language (UML), SQL Server for implemented the database, and ASP.net and Visual basic programming languages.
Transformation Of The Teacher’s Role In Digital Age (Russia &amp; France)

Rapid changes in the country’s socio-economic development and the adoption of digital technologies as its main component are two aspects that the education system cannot ignore. In order to increase the country’s competitiveness in the field of education, it is necessary to train highly qualified specialists who will be able to take responsibility for operating modern technologies and new methods of education in the digital age. In addition, future specialists must be ready for continuing education, and this requires a high-quality information and communication base. Current conditions in the digital age dictate new requirements for the organization of training, changing the content, forms and methods of teaching. School education management is gradually being digitized. All this leads to the fact that the role of the teacher in timely conditions is fundamentally changing. In addition, in the context of globalization, there is an interest in foreign practices in education. The article contains a comparison of the evolution of Informatization of education in Russia and in France. Attention is drawn to the formation of digital competencies in future teachers and the emergence of new teaching professions, such as e-learning tutor, distance learning teacher consultant, etc., which arose in response to the needs of society and are associated with the spread of digital technologies in the educational process.
Pengembangan Sistem Online Pendaftaran Santri Baru untuk Penguatan Manajemen Informasi Pondok Pesantren Islamiyah Syafi’iyah Situbondo

New Santri Admission (Penerimaan Santri Baru) is an administrative process for the selection of new student candidates. The PSB process is always carried out manually at each school institution, especially the Islamic Boarding Schools, which will cause various difficulties from several related parties. Therefore the New Santri Admission System was created online or the term can be called the online PSB. . An idea emerged to create a new student admission information system based on the SQL database. With this system, pesantren or administrators can manage the implementation of student registration for web technology using the PHP programming language and new languages. such as rapid registration and announcements.
Gesture control of UAV using radio frequency

With the ever-increasing reliance on electronic gadgets and equipment, the technology has reached its peak but with the increase in features and functions of the gadgets, the complexity of the user interface also increases. As such are the problems faced by drones that have almost unlimited untapped potential but due to the complex interfacing between conventional controls and the use of a lot of the drones are still limited. This paper puts light on the steps to create an aerial vehicle capable of being controlled by easy gestures, to reduce complications in controls, more instantaneous and instinctive control of the aerial vehicle. This technology can be currently used in flying drones and can further be applied to military, rescue, and relief operations in times of distress.