Reviewerly/exHarmony huggingface dataset:
SpeakerNet for Cross-lingual Text-Independent Speaker Verification

Biometrics provide an alternative to passwords and pins for authentication.The emergence of machine learning algorithms provides an easy and economical solution to authentication problems.The phases of speaker verification protocol are training, enrollment of speakers and evaluation of unknown voice.In this paper, we addressed text independent speaker verification using Siamese convolutional network.Siamese networks are twin networks with shared weights.Feature space can be learnt easily by training these networks even if similar observations are placed in proximity.Extracted features from Siamese then can be classified using difference or correlation measures.We have implemented a customized scoring scheme that utilizes Siamese' capability of applying distance measures with the convolutional learning.Experiments made on cross language audios of multi-lingual speakers confirm the capability of our architecture to handle gender, age and language independent speaker verification.Moreover, our designed Siamese network, SpeakerNet, provided better results than the existing speaker verification approaches by decreasing the equal error rate to 0.02.
Decision Making System to Determine Childbirth Process with NaÃ¯ve Bayes and Forward Chaining Methods

Childbirth is the last stage before the infant comes into the world. There may be incidents that could cause death in the process of childbirth for mothers and infants. Lack of knowledge and attention to the labor process can increase maternal mortality rate. Maternal mortality rate in Indonesia was recorded at 190 per 100,000 live births on 2015. The figure is still far from the fifth Millennium Development Goals target of 102 per 100,000. The increasing development of technology in health informatics to provide health care more effective can be used to help overcome the problems of pregnant women. To reduce maternal mortality rates, a web-based expert system is perfect one for use. NaA¯ve Bayes method is a simple, fast and high accuracy method. Forward Chaining method is a inference method that performs a fact or statement that starts from the condition (IF) then to the conclusion (THEN). Based on analysis of the method obtained with 233 patients data on childbirth process using expert system, the NaA¯ve Bayes method has accuracy in diagnosing by 90,987124463519% while Forward Chaining method accuracy is 86.69527897%.
Compact Generation of a Large Scale Square-grid Cluster State in the Quantum Optical Frequency Comb

We showed theoretically that the phase modulation of the output of a single optical parametric oscillator can be used to generate a square-grid cluster state, a key resource for universal quantum computing.
Perancangan Robot Maze Solving Berbasis Arduino

The maze solving robot is the development of the line follower robot. Where the robot can trace a path that has an intersection, in tracing a maze, apart from finding a way out / finish, it will be more efficient if the robot can find a shorter path through the maze. From the maze samples made, the robot can explore a maze and find the shortest path. When the mapping process is carried out, the robot traces 12 path codes; after the path simplification process is carried out, the robot can shorten the path it takes to 6.
Automatic Q.A-Pair Generation for Incident Tickets Handling: An Application of NLP

Chatbots answer customer questions by mostly manually crafted Question Answer (Q.A.)-pairs. If organizations process vast numbers of questions, manual Q.A. pair generation and maintenance become very ex-pensive and complicated. To reduce cost and increase efficiency, in this study, we propose a low threshold QA-pair generation system that can automatically identify unique problems and their solutions from a large incident ticket dataset of an I.T. Shared Service Center. The system has four components: categorical clustering for structuring the semantic meaning of ticket information, intent identification, action recommendation, and reinforcement learning. For categorical clustering, we use a Latent Semantic Indexing (LSI) algorithm, and for the intent identification, we apply the Latent Dirichlet Allocation (LDA), both Natural Language Processing techniques. The actions are cleaned and clustered and resulting Q.A. pairs are stored in a knowledge base with reinforcement learning capabilities. The system can produce Q.A. pairs from which about 55% are useful and correct. This percentage is likely to in-crease significantly with feedback in its usage stage. By this study, we contribute to a further understanding of the development of automatic service processes.
Self-Actualization of the Main Character in Novel Daun Yang Jatuh Tidak Pernah Membenci Angin Tere Liye Works

This study aims to describe the process of achieving self-actualization of the main character (Tania) in the novel of daun yang jatuh tidak pernah membenci angin Tere Liye works . The method used in this research is descriptive qualitative with a literary psychology approach. The research data is in the form of the self-actualization process of the main character (Tania) based on Abraham Maslow's humanistic psychological theory and the data source is a novel daun yang jatuh tidak pernah membenci angin by Tere Liye. The data collection technique used in this research is content analysis (document). The validity of the data used theoretical triangulation. The results showed that the main character (Tania) succeeded in achieving self-actualization. The process of achieving self-actualization is carried out by meeting other needs, such as physiology, safety and security, love and belonging, self-esteem, and self-actualization.
Development Of Adaptive, Spritual, Academic And Social (ASAS) Programs In Revitalizing Social Interactions Of Students

If the diversity of a community is not managed properly, it will cause various problems that can lead to disharmony in the interaction patterns in that community. The diversity of students of the Faculty of Social Science and Christian Humaniora (FISHK) of IAKN Tarutung leads to a tendency to cause grouping and even create competition, which greatly affects the patterns of interactions among students. The purpose of this research is to develop the ASAS programs in revitalizing the social interaction patterns of students of the Faculty of Social Science and Christian Humaniora (FISHK) of IAKN Tarutung. This research method uses a quantitative description, which aims to explain events that are described in the form of Figures containing useful numbers. The four indicators for the Adaptive Program (A) show that 31.13% of respondents strongly agree to hold adaptive programs, 61.13% of respondents agree, 6.78% disagree, and 0.88% of respondents strongly disagree. The seven indicators for the Spiritual Program (S) show that 38.14% of respondents strongly agree to hold spiritual activities, 56.71% of respondents agree, 5.14% of respondents disagree, and no one strongly disagrees. The five indicators for the Academic Program (A) show that 29.4% of respondents strongly agree to hold an academic program, 61.6% of the respondents agree, 8.4% of respondents disagree, and 0.6% of the respondents strongly disagree. The four indicators for the Spiritual Program (S) show that 30.75% of respondents strongly agree to hold social activities, 60% of the respondents agree, 8.75% of respondents disagree, and less than one percent (0.5%) of respondents strongly disagree. From all the indicators in the ASAS program that have been implemented, it can be concluded that the ASAS (Adaptive, Spiritual, Academic and Social) programs can be as solutions in revitalizing interaction patterns among students and those can become references for readers or others in overcoming disharmony issues in a community.
Towards grading automation of open questions using machine learning

Assessing the academic capabilities of students should play a key role in both stimulating their learning process (formative assessment) and in the accurate evaluation of their knowledge and capabilities in relation to a topic (summative assessment). Therefore, according to the principle of constructive alignment, any form of assessment needs to be carefully designed to match the learning outcomes of a course and needs to be delivered in an appropriate format (paper-based vs. computer-based) and graded in a suitable manner. However, this is a challenging task, due to the substantial amount of time teachers need to spend on grading open questions. From our experience, this results in using less appropriate assessment methods (e.g.: Multiple Choice questions) or in less time spent by teachers on innovating their courses (e.g.: implementation of formative assessment). Inspired by recent developments in academia and practice, we propose to investigate the application of machine learning technology for supporting grading of open questions, with a focus on summative assessment and exploring possibilities for formative assessment. Our expected results include the design of a method for supporting grading of open questions with machine learning, an investigation into the most suitable machine learning algorithms for small samples of tests.
A study on the implications of a non-professional interpreting case for interpreting education – Focusing on Sharon Choi’s interpreting.

Sharon Choi became an instant celebrity in both Korea and beyond as the videos of her eloquent English interpreting for the Academy-winning Parasite’s director Bong Joon-Ho, went viral on social media. The study aims to explore the possibility and implication of using Sharon Choi’s interpreting case for education purpose, although she is a non-professional or a non-certified interpreter. Using the videos of Sharon Choi’s interpreting on social media, 53 graduate students majoring in interpretation and translation in Korea participated in survey, which was conducted to look into how students evaluated Sharon Choi’s interpreting at the beginning of semesters of 2020. The survey results show that Sharon Choi helped students to better understand the role of interpreter and interpreter competence for outstanding consecutive interpreting service, despite her limitation as a non-professional interpreter. The survey has also provided unique opportunity for discussion on the conditions for successful interpreting as well as competitive edge students should have as they launch and continue their training at an accredited graduate school to become professional interpreters and translators.
Pendeteksian Tepi Citra untuk Menentukan Kualitas Beras Berdasarkan Jenis Menggunakan Metode Laplacian of Gaussian

Rice is a staple food for most Indonesian people. Rice consumption in Indonesia is increasing every year along with the increasing population of Indonesia. The high dependence of the Indonesian people on rice will be a problem if the availability of rice cannot be fulfilled. The Laplacian of Gaussian method can detect edges more accurately especially on steep edges. In addition, it can be said to be more accurate because it can reduce the appearance of false edges, because the image is filtered first with a Gaussian function. This Laplacian method has been widely implemented to analyze various problems. The purpose of this study is to detect the edges of rice images and determine their quality more accurately using the Laplacian of Gaussian method
Social Recommendation Model with User Trust and Item Ratings Using Collaborative Filtering Technique in Hotel Application

A trust-based recommendation model is regularized with user trust and item ratings called TrustSVD. Trust networks are large-world networks where many users are socially linked, suggesting the assumption of trust in recommendation systems. An item rating downloaded from the OSN Server can be viewed by the user. If the information is accessible on the server, all the adjacent devices are enabled and a peer to peer mode of communication is initiated. User reviews from a graphical forum are shown. It focuses on the rating prediction role in the current framework and has shown that integrating user social confidence data will boost the output of recommendations. The strategy builds on the SVD++ state-of-the-art model. The data sparsity and cold start issues are resolved in the friend of friend recommendation model used. The mining method generates the user's overall rating in graphical representations and illustrates the overall rating. This model increases the utility of data by exchanging neighborhoods to protect security and privacy issues. One of the most common techniques for implementing a recommendation scheme is Collaborative filtering (CF).
Expanding Belnap 2: the dual category in depth

Bilattices, which provide an algebraic tool for simultaneously modelling knowledge and truth, were introduced by N.D. Belnap in a 1977 paper entitled How a computer should think. Prioritised default bilattices include not only Belnap’s four values, for ‘true’ (t), ‘false’(f), ‘contradiction’(⊤) and ‘no information’ (⊥), but also indexed families of default values for simultaneously modelling degrees of knowledge and truth. Prioritised default bilattices have applications in a number of areas including artificial intelligence. In our companion paper, we introduced a new family of prioritised default bilattices, Jn, for n ⩾ 0, with J0 being Belnap’s seminal example. We gave a duality for the variety Vn generated by Jn, with the dual category Xn consisting of multi-sorted topological structures. Here we study the dual category in depth. We axiomatise the category Xn and show that it is isomorphic to a category Yn of single-sorted topological structures. The objects of Yn are ranked Priestley spaces endowed with a continuous retraction. We show how to construct the Priestley dual of the underlying bounded distributive lattice of an algebra in Vn via its dual in Yn; as an application we show that the size of the free algebra FVn(1) is given by a polynomial in n of degree 6.
The Relationship between Burnout and Learning Motivation in Full-day School Students at SMPN 34 Padang

This research was conducted because it saw problems that occur in full day school students who experience boredom of learning so that it affects the students' motivation to learn low. This study aims to examine the relationship of learning motivation with full day student learning saturation. The number of samples was 222 students of 34 Padang Junior High Schools selected by using simple random sampling. The instrument used was a Likert scale model, as well as data processed using SPSS version 19 '. The results obtained from this study are that there is a significant negative relationship between learning motivation and learning saturation with a correlation coefficient of -0.512 which is at a significance level of 0.000 with a strong enough category. This means that the higher the motivation to learn, the lower the saturation of student learning. With this finding it is hoped that counselors or counseling teachers can provide guidance and counseling services such as information services, individual counseling services, group guidance services, and group counseling services. To increase learning motivation and to reduce boredom in full day school students.
Investigating Teacher’s Reluctance in Using Mobile Technology in ELT: An Indonesian Context

Along with the changing times, learning techniques and methods have shifted from traditional patterns that are teacher-center to technology-based learning that promotes student centered learning. Therefore, mobile-assisted language learning has become a rapidly developing trend in English language teaching. Mobile devices are believed to help the teachers makes the learning process easier through sharing the material, asking the students to do online exercise, uploading and submitting assignments, and so on. However, some teachers are still reluctant to integrate mobile device technology in classroom practices. This paper attempts to investigate the teacher’s reluctance in using mobile device technology in ELT. Three English teachers from different universities in Yogyakarta have been interviewed to explore the reason of teacher’s reluctance. The result can be categorized into three patterns, (1) lack of time, (2) lack of competence in operating mobile apps, and (3) worrying of students’ understanding of the material.
Challenges in Individual Representation of GP Classification

Abstract Genetic Programming (GP) is an evolutionary programming strategy that automatically solves complex problems through computer programs. The field of Data Mining has got engrossed towards GP, due to its advantages in automatic evolution of programs with optimized solutions without prior knowledge on data. The classification technique is among the most studied Data Mining task through GP. GP, despite being used for classification for long time due to its numerous outstanding abilities, still suffers from certain limitations. Hence, this paper focuses on various Individual Representation challenges of GP Classification. Keywords: genetic programming, data mining, classification, classification issues
MENINGKATKAN KEMAMPUAN GURU MENGGUNAKAN APLIKASI PENGOLAHAN NILAI BERBASIS EXCEL BAGI GURU KELAS MELALUI IN HOUSE TRAINING DI SD NEGERI 1 BERAMBAI MAKMUR KECAMATAN PANGKALAN BANTENG TAHUN AJARAN 2019/2020

The low ability of teachers in using excel-based value processing applications at SDN I in Berambai Makmur, Pangkalan Banteng District is the background of this research. The method used is In House Training. The subjects of this study were six teachers who worked at SDN I Berambai Makmur. This research was conducted on October 17-December 2019. The author also used three research procedures, namely Pre-Research, Cycle I and Cycle II, which consisted of planning, observation, implementation and reflection. In addition, the data collection techniques used were observation, questionnaires and interviews. Based on the research results it was found that (1). The results of the study were to improve the ability of teachers to use excel-based value processing applications there was an increase after the In House Training activities were carried out. (2). There is a positive trend or increase in teacher scores from the results of the Pre-Cycle to Cycle II assessments.
SOCIAL DEMAND FOR A TEACHER-INNOVATOR

One of the necessary condition for the implementation of the concepts of democratization and humanization of education is the scientific and creative ability of teacher to self-development and selfimprovement. In this context, we note that according to experts, the following global phenomena significantly grow the need to increase the scientific capacity of the pedagogical process: informatization, digitalization, internationalization, virtualization of education, etc., where the teacherinnovator can introduce his own scientifically based opinion in the relevant scientific discourse, to develop and propose a new pedagogical technology or model of organization of managerial or educational work for implementation.
Interactional Metadiscourse used in Bloomberg International Debate

In delivering an argument, several things must be known, such as the theme, the purpose, and the content of the argument in a debate. Since debate demands critical thinking, debaters need to consider their words’ choice in delivering their argument. In that case, this research aims to analyze the uses of interactional metadiscourse markers that are applied in the Bloomberg International Debate. In doing the analysis, the writers used the descriptive method and proposed Hyland’s theory (2005). As the result of the research, it shows that the most speaker who is producing interactional metadiscourse markers is Ella Cox, followed by John Allan and then Ndidie Okezie and finally Auday and Rus Ma. Although there are three speakers in each team (both proposition and opposition), it seems that the third person on each team only as support and the one who then summarizes the result of the debate for each team. Further, related to the uses of interactional metadiscourse, the most used of the interactional dimension markers is self-mention, followed by booster, hedges, and booster.Keywords: Bloomberg, critical thinking, debate, interactional metadiscourse, metadiscourse markers
Letter From the Editor: Inaugural Address

As this is our inaugural issue, I think it’s only appropriate to share how we got here and to thank all those who helped bring our student open access journal to fruition. For the past few years, the professional librarians in the Learning Resource Centre have been working with Faculty to fully develop the digital information literacy competencies of our students – to help students succeed in their academic lives, their future healthcare professional lives, and as life-long learners.  Having a critical approach, understanding the value of information creation and dissemination, recognizing authoritative sources, and approaching literature searches like strategic exploration are all elements of the framework for the conversation of scholarship and are all competencies we seek to instill in our students through our digital information literacy workshops and consultations.  It was in the course of this work that a faculty member came to us, commenting on the increased quality of the assignments being submitted by her students as a result of the LRC workshops and lamenting the lack of venue where our students writing and other works could be showcased.  We had also been discussing our students’ research capacity – and how to help prepare them for their roles in furthering their professions through scholarly communications.  Why not develop an open access journal, shepherded by the LRC and focused on the contributions of Michener students to showcase their work?  Thus Mich: The Student Journal of the Michener Institute was born.   Of course, nothing is that easy.  Graham Lavender, our Associate Librarian, was essential in negotiating the OJS platform on which the journal is built.  Tom Blennerhassett came on board as our Scholarly Communications Librarian to manage the OAJ project.  Michener Faculty embraced the idea of promoting our students’ best work – and were the first step in the production by nominating the student articles that came forward.  Several Michener staff members served as our project team, the editorial committee – and general sounding board.  And, of course, the Michener students who were excited by the opportunity to share their scholarship were essential to this inaugural issue.  (P.S. It was the Michener students who chose the name Mich for this journal!  It is truly their work.)-Juanita RichardsonManager, Learning Resource Centre
Research and Design of Stream Computing Framework Based on Storm

Firstly this paper introduces the basic concept of stream computing, studies the relevant characteristics of stream data and analyzes the differences between the stream processing system and the traditional data processing system in detail. Secondly, the composition, operation mechanism and characteristics of the typical stream computing system storm are analyzed in detail and the structure of storm cluster is studied. Finally, the workflow of storm cluster architecture is studied.