Reviewerly/exHarmony huggingface dataset:
REGISTER BAHASA KOMENTATOR MOBILE LEGENDS DALAM TURNAMEN MPL SEASON 5

Register is a variety of languages ​​used based on usage, such as online game players who have certain types and functions of registers that distinguish the gamers profession from other professions. Mobile legends is an online game that is played in groups. In a Mobile Legends tournament, not only players are involved in a match but there will also be commentators who will guide and provide comments on the match. The purpose of this study is to analyze the form of the Register Language used by the Mobile Legends game commentator in the MPL season 5 tournament. This research is a qualitative descriptive study. Data collection was done by observing the data by replaying the MPL season 5 grand final video many times, then transcribing the video script based on the expressions used and matching the script directly. The data analysis carried out consisted of three processes, namely data selection, data processing, and conclusions. The results of this study found that there was a use of register language that came from a foreign language, namely English which was used by Mobile Legends commentators such as the words first blood, retreat, recall, and play off.
Improving the sub-image classification of invasive ductal carcinoma in histology images

Whole &lt;span&gt;slide image (WSI) processing is a common technique used in the analysis process performed by pathologists. Identifying precise and accurate regions of cancerous in the tissue is an important process in the disease diagnosis modality. This work proposes an automated technique for identifying invasive ductal carcinoma (IDC) in histology images using. An image is divided into small non-overlapped patches (or image windows). Then, the task is to classify the image patches into different classes, i.e., i) IDC and ii) non-IDC. We employ a two-stage classification-based to classify the patches, as to identify IDC regions in the tissue. In the first stage (patch-level classification), image patch classification is carried out using a conventional handcrafted feature and deep-learning technique are explored. The second stage (post-processing) undergoes a refinement process, which considers the spatial relationships between the neighboring patches. This stage aims to amend some of miss-classified patches. Markov random field (MRF) is implemented in this stage to examine the relationships of the patches and their neighborhoods. The experiments are conducted on public dataset. The experimental results show the post-processing can improve the performance of the classification in the first stage using the handcrafted-based technique and deep learning.&lt;/span&gt;
TEACHING TECHNIQUE FOR WRITING SKILL AT THE FOURTH SEMESTER STUDENTS OF BALIKPAPAN FOREIGN LANGUAGE ACADEMY IN THE ACADEMIC YEAR 2020/2021

This study aims to describe teaching techniques for writing skills in The Fourth Semester Balikpapan Foreign Language Academy. This type of research is descriptive qualitative research. Sources of research data are events, informants, and documents. Collecting data from observations, interviews, and documents. Data is analyzed by reducing data, displaying data and verifying data. To show the truth of the data using triangulation data. The results showed that the techniques used by lecturers at Balikpapan Foreign Language Academy in teaching writing skills were using pictures, discussions, making groups and corrections, and presentations. The purpose of using techniques can make it easier for students to develop writing skills. The students' responses to each technique were interested and happy. Problems faced by lecturers such as passive students, vocabulary and writing structure problems, students’ difficulty developing paragraphs, and time constraints. Solutions for teaching writing skills include the lecturer encouraging students to be active, repeating the teaching of language and vocabulary structure, giving examples of making paragraphs using the correct tenses, motivating students to increase vocabulary, and the lecturer providing opportunities for students to practice writing not only once.
Smart Surveillance System Real-Time Multi-Person Multi-Camera Tracking at the Edge

Abstract: Nowadays, new Artificial Intelligence (AI) and Deep Learning based processing methods are replacing traditional computer vision algorithms. On the other hand, the rise of the Internet of Things (IoT) and edge computing, has led to many research works that propose distributed video-surveillance systems based on this notion. Usually, the advanced systems process massive volumes of data in different computing facilities. Instead, this paper presents a system that incorporates AI algorithms into low-power embedded devices. The computer vision technique, which is commonly used in surveillance applications, is designed to identify, count, and monitor people's movements in the area. A distributed camera system is required for this application. The proposed AI system detects people in the monitored area using a MobileNet-SSD architecture. This algorithm can keep track of people in the surveillance providing the number of people present in the frame. The proposed framework is both privacy-aware and scalable supporting a processing pipeline on the edge consisting of person detection, tracking and robust person re-identification. The expected results show the usefulness of deploying this smart camera node throughout a distributed surveillance system. Keywords: Edge Analytics, Person detection, Person re-identification, Deep learning, embedded systems, artificial intelligence
Job search during COVID: A new librarian navigating a new normal

For nearly the last two years, we have faced new challenges in unprecedented ways due to the COVID-19 pandemic.Thanks to current technology, however, we have been able to get creative to keep things moving as much as possible and find new ways to do things, including searching for jobs.Like many others, I found myself having to traverse a job search process that involved doing only virtual interviews.In my case, however, I am a new librarian (class of 2018) and this was my first full job search in the profession.Previously, I was fortunate to have landed a job as a direct hire visiting professor of library services, which was extended to two years due to COVID.This allowed me to put my foot in the door and get the experience I needed to be competitive during the job search process.But I had only experienced one other interview for a resident position, so I had no idea what to fully expect.Of course, having to do this completely virtually added a whole new level of difficulty.Along the way, there were a lot of lessons learned and experience earned that I want to share with both interviewers and interviewees.Especially because I do not see virtual interviews going away as we adjust to the new normal that COVID is creating for us.And while I know many will disagree with some of my points, I do see a lot of advantages to continuing virtual interviews for everyone involved.
Hybrid Image Steganography Method with Random Embedding of Encrypted Message

The main challenge for embedding encrypted message in an input image is to get better the security of the confidential information through hybrid-based image steganography method. Moreover, earlier LSB based solutions existed in which either secret information embedded without encryption or embedded un-randomly in an image and existing MSB based information concealing solutions minimizes information capacity and image quality too. Most of existing steganographic systems either based on LSB or MSB but only some hybrid solutions are available in which either the confidential message is not encoded before embedding it into the image and the embedding system is also not random based. The existing well known hybrid based image steganography techniques are not only deficient in performance but also deficient in embedding of encoded data in an image. To overcome these issues, a Hybrid-LSB-MSB based image steganography and multi-operation data encryption method is proposed in this article. Proposed method is not only randomly embeds the confidential information in a cover image but also provided the facility to encode the confidential information before substituting. The Hybrid-LSB-MSB based proposed image steganography method is compared with earlier Hybrid based image steganography method by using Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) values including payload capacity. Higher PSNR and Lower MSE values signify effective steganography quality. The experimental results show that proposed method retains higher PSNR and lesser MSE values as contrasted to the existing methods thereby effective in steganographic properties.
WHEN LEARNING MEDIA PLAYS ROLES IN TEFL: HOME-VISITING STUDY CASE DURING COVID 19

This study describes the implementation of learning media during the program of “home visit”. The activity involved 15 students of 6th grade of MI Unwaanul Falah, South Tangerang, as the subjects of the research. A qualitative-descriptive method was applied in this study. The researchers collected the data through observation, students’ assignment results and documentary pictures. The techniques in analyzing the data included data reduction, data display, and also conclusion and verification. The results of the research showed that the students responded to lessons better when the learning process was carried out in an interesting and interactive way, such as the used of diverse and concrete learning media which created enjoyable and appealing learning process during the COVID-19 pandemic.
e-Logbook Application Design for Job Training During the Covid-19 Pandemic (Case Study: Business Administration Department of Politeknik Negeri Samarinda)

This research was conducted to design an e-Logbook Application Design for Job Training.The application that will be built in this research is an e-Logbook, the goal is to make it easier for final year students to do job training.This application will then be used by Practitioner Lecturer and Supervisor to monitor the student progress and assess students' daily activities when carrying out job trainings.The system to be built is simpler, easier to understand and use.starting from attendance to final assessment when students have finished carrying out job trainings.The method used for the development of this system is the SDLC method, which is a system development methodology, the roles and skills required for systems analysts, the basic characteristics of object-oriented systems.
DDoS ATTACK MITIGATION WITH INTRUSION DETECTION SYSTEM (IDS) USING TELEGRAM BOTS

In the current IS/IT era, service to consumers is an absolute must to be prepared to survive in business competition. Physical and logical attacks with the aim of disrupting information technology services for individuals/agencies/companies or reducing the performance of IS/IT used. The development of IoT in the industrial revolution 4.0, which is all online, is a challenge in itself, from a negative point of view, all of them are able to carry out attacks on ISP servers, often carried out by hackers. DDoS (Distributed Denial of Service) attacks are the most common attacks. The development of software for DDoS attacks is very much on the internet, including UDP Unicorn software to attack very easily and can be done by anyone. Software for real-time monitoring of DDoS attacks, one of which is the Telegram bot. Telegram is a messaging system centered on security and confidentiality, while bots are computer programs that do certain jobs automatically. Telegram bot is free, lightweight and multiplatform. In the case study, this research contains 10 access points to the internet that will be mitigated from DDoS attacks. In this study, it was found that DDoS attacks caused traffic to become very high/congested by fulfilling upload traffic so that legitimate traffic users could not access the internet, connection to the internet was slow, the traffic was also unnatural, making it unable to connect to wireless devices and making Mikrotik login page becomes unable to appear. The purpose of this study is to mitigate DDoS attacks with the help of telegram bots so as to facilitate the notification of DDoS attacks in the event of an attack so that it is fast to deal with and find the perpetrators of the attack. The conclusion of this study is that DDoS attacks using UDP unicorn software resulted in a traffic spike of 53.5 Mbps on the upload traffic side, causing traffic for legitimate/authenticated users to slow down. By using telegram bots to know DDoS attacks occur in real time with a success rate of attack detection up to 100% notifications on telegram bots. Mitigation of DDoS attacks takes steps to track users using the torch feature on the routerboard interface menu, trace internet connection lines using wired or wireless transmission media, and ensure always monitoring the proxy interface from winbox.
Passenger’s Behavior Recognition System Using Computer Vision

One of the problems that occurs inside public transport is that passengers often overlook or ignore public transport’s rules such as in regards to eat and drink. Eating foods and drinks are not even allowed in public transport in avoiding excessive littering and drink spills which could potentially cause unwanted accidents. This system aims to recognize two actions such as eating and drinking through image processing in real-time environment. It also aims to classify and label the behavior of the passengers. This research is on a passengers behavior recognition system using computer vision (PBRSUCV) as a prototyping model. The method consists of image processing with a faster region-based convolutional neural networks (faster R-CNN) classification project that can be implemented in public transport to solve the stated problem. The system consists of a camera and laptop. The camera is used as a sensor to detect the targeted behaviors while the laptop will be the main device where every image processing takes place. The system was tested in real-time and is able to detect and label the eating and drinking behavior correctly with 99% accuracy on a single and two people in the image frame. It is certain that this system is capable to accurately recognize and classify the targeted behaviors in the public transport without any problem with the help of the faster R-CNN deep neural network.
A PCA-based Data Prediction Method

The problem of choosing appropriate values for missing data is often encountered in the data science.We describe a novel method containing both traditional mathematics and machine learning elements for prediction (imputation) of missing data.This method is based on the notion of distance between shifted linear subspaces representing the existing data and candidate sets.The existing data set is represented by the subspace spanned by its first principal components.Solutions for the case of the Euclidean metric are given.
OpenFEAT: Improving Speaker Identification by Open-Set Few-Shot Embedding Adaptation with Transformer

Household speaker identification with few enrollment utterances is an important yet challenging problem, especially when household members share similar voice characteristics and room acoustics. A common embedding space learned from a large number of speakers is not universally applicable for the optimal identification of every speaker in a household. In this work, we first formulate household speaker identification as a few-shot open-set recognition task and then propose a novel embedding adaptation framework to adapt speaker representations from the given universal embedding space to a household-specific embedding space using a set-to-set function, yielding better household speaker identification performance. With our algorithm, Open-set Few-shot Embedding Adaptation with Transformer (openFEAT), we observe that the speaker identification equal error rate (IEER) on simulated households with 2 to 7 hard-to-discriminate speakers is reduced by 23% to 31% relative.
PROFESSIONAL CULTURE IN THE TEACHER’S INTELLIGENCE SYSTEM

the article is devoted to the study of the role and place of professional culture of a teacher in the general system of his intelligence. Intelligence itself appears as a holistic formation and systemic unity of its multifactorial and multifunctional nature of activity and personality of the teacher, his professionalism, general and professional culture. The intelligence of the teacher is one of his important personal characteristics and a powerful source of purposeful pedagogical influence on students. In addition, the intelligence of the teacher is a significant stimulus to his constant self-development and self-improvement. The importance of professionalism and professional culture as integral parts of the intelligentsia and the teacher and his students is confirmed by the results of experimental research.
The Effect Of �The Venn Diagram� As A Cooperative Learning Strategy to Improve Reading Comprehension in Legal Description Texts During the Covid-19 Pandemic Period

The research was to find the simple effect of a graphic organizer which is one of the cooperative learning strategies by using Venn diagrams to improve reading comprehension of descriptive texts in English class for Law IAIN Bengkulu. The Venn Diagram has a positive effect on students. The research is Quays experimental with a non-equivalent control group design in English Specific Purpose for Law. The populations were second-semester students of the Faculty of Law. They are class A consisting of 16 students as an experimental class (international class) and class B consisting of 16 students (international class) as a control class. The totality sample is used, the researcher took the sixth step, namely; first, students were given Pre-Test for both classes to determine the experimental and the control class. Second, giving treatment for three meetings in the experimental and control classes. Third, the researcher conducted a Post-Test, in the experimental and control classes to determine the effect of the Venn Diagram. Fourth, the researcher analyzed the test using the assessment criteria. Fifth, the researcher used the t-test formula to determine the significance of the use of it from the experimental class. Sixth discusses conclusions based on the data. The results indicate that Venn Diagrams can improve students' understanding of reading descriptive texts. It can be seen after being calculated by the T-test formula that the T-Count is higher than the T-table (2.25 &gt; 2.0423) and the average value of the two classes increased by about 9.68 points for the experimental class and 2.19 points for the control class that it has a positive effect on students' law. Furthermore, suggested that the Venn diagram is applied by students for reading comprehension.
Study of Job Satisfaction and Work Performance of Teacher Retention for Vocational Education in Sichuan of China

Education development in private higher vocational colleges had achieved remarkable results and became a significant force in promoting education and education in higher vocational colleges. However, due to subjective and objective reasons, the development of private vocational colleges would still not be optimistic. One of the main problems the development of education in private vocational colleges faced was the severe loss of teachers and the teachers’ team’s lack of stability and professionalism. For private vocational schools, teachers were the critical factor in their development. Job satisfaction and teachers’ work performance would be the main reason that influences the rate of teacher turnover.
Fresh Graduate Students� Difficulties in Writing Research Articles

Writing research article is one of requirement for a student�s university to be fulfilled before graduate. However, writing research article is not easy for the student. This research aimed to find out the difficulties in writing research article, the cause of the difficulties in writing research article and the way to overcome the difficulties in writing research article. The respondents of this research were 4 fresh graduate students who graduated in 2020 and the data ware obtained through interview. This research used descriptive qualitative method by using the procedures from Miles and Huberman (1994). The result of this study shows that the difficulties in writing research article were in finding references and struggle in using correct grammar, the worry about feedback from the readers was the cause of the difficulties and the fresh graduate had their own solution to overcome the difficulties in writing research article. In conclusion, the fresh graduate of the English Education Study Program of Bengkulu University faced various difficulties in writing research article and had cause of the difficulties in writing research article, but they had solution to deal with such difficulties.
An Analysis of Code Mixing Used by English Department Students of Universitas Riau on Instagram

This study has an objective to find out the code mixing types used in Instragram bythe English Department students -Universitas Riau. The respondents of thisresearch were all related students in2016/2017 academic year. The researcherused descriptive qualitative research design and the data were collected from documents as the instrument. Then, Hoffman‟s theory (1991) was used for data analysis to find out the types of code mixing used by these students. Thus the research finding has revealed that all of the three types of code mixing appearedin the captions or comments written by the students as suggested by Hoffman. There were twenty-nine data classified into intra- sentential, two data classified into intra-lexical code mixing, two data classified into involving a change of pronunciation and two data classified into both intra-sentential code mixing and intra- lexical code mixing.&#x0D; Key Words: Analysis, Code Mixing, Instagram.
Analyzing Students� Obstacles of Online Learning for UIB English Class

Online learning is used because of the Covid-19 virus outbreak and the lecturers and students must use online platform to teach the students. As for the learning, online platforms may have some benefits and problems either for students and lecturers. UIB have implemented the online learning by using Microsoft Teams and Moodle. This research are sought to find what are the students obstacles with online learning in UIB. The subjects of this research are 335 UIB students from 1st semester English class 1 students batch 2020/2021. This research used quantitative approach which of collecting data that yield results such as words or pictures. The data collection used questionnaire that spreaded to 335 UIB students from all major via social media: Whatsapp, Line, etc. This research has 6 lists of obstacles from various researchers which are: Lack of interest, Lack of motivation, Lack of digital devices, Lack of competence in using technology, Role of motivation, and English curriculum. The list of obstacles will be explained in this research to find the similarly comparison from the various researchers with this research. The result of the research could become a suggestion from the students' view for the UIB in conducting the online learning. The suggestions for UIB are repair the LMS server so that the students can submit or download the learning materials without any problem. Then, maybe for the LMS application can add some new features such as notification for the assignment deadline; sort and separate the list of learning materials and assignment from all major so the students can find the learning materials and their assignment easily. Also, increase the file capacity for submitting assignment, material file or video assignment will make the students easier to submit their assignment without have to redo the work to adjust the size of file to submit it on LMS.