Reviewerly/exHarmony huggingface dataset:
WASSA@IITK at WASSA 2021: Multi-task Learning and Transformer Finetuning for Emotion Classification and Empathy Prediction.

This paper describes our contribution to the WASSA 2021 shared task on Empathy Prediction and Emotion Classification. The broad goal of this task was to model an empathy score, a distress score and the overall level of emotion of an essay written in response to a newspaper article associated with harm to someone. We have used the ELECTRA model abundantly and also advanced deep learning approaches like multi-task learning. Additionally, we also leveraged standard machine learning techniques like ensembling. Our system achieves a Pearson Correlation Coefficient of 0.533 on sub-task I and a macro F1 score of 0.5528 on sub-task II. We ranked 1st in Emotion Classification sub-task and 3rd in Empathy Prediction sub-task.
Evaluating multi-core graph algorithm frameworks

Multi-core and GPU-based systems offer unprecedented computational power. They are, however, challenging to utilize effectively, especially when processing irregular data such as graphs. Graphs are of great interest, as they are now used to model geographic-, social- andneural networks. Several interesting programming frameworks for graph processing have therefore been developed these past few years.In this work, we highlight the strengths and weaknesses of the Galois, GraphBLAST, Gunrock and Ligra graph frameworks through benchmarking their single source shortest path (SSSP) implementations using the SuiteSparse Matrix Collection. Tests were done on an Nvidia DGX2 system, except for Ligra, which only provides a multi-core framework. D-IrGL, built on Galois, also provided a multi-GPU option for SSSP. We also look at program size, documentation and overall ease of use.High performance generally comes at the price of high complexity. D-IrGL shows its strength on the very largest graphs, where it achieved the best run-time, while Gunrock processed most other large sets the fastest. However, GraphBLAST, with a relatively low-complexity interface, achieves the greatest median throughput across all our test cases. This despite that its SSSP implementation size is only 1/10th of Gunrock, which for our tests has the highest peak throughput and the fastest run-time in most cases. Ligra had less computational resources available, and consequently performed worse in most cases, but it is also a very compact and easy to use framework. Futher analyses and some suggestions for future work are also included.
Does Fear of Covid-19 Trigger Fear Of Bitcoin?

This study aims that Bitcoin prices are considered as dependent variables, and the total number of Coronavirus cases in the world, Ethereum Prices, Gold Prices, Coronavirus Google Trend Index, and Crypto Money Google Trend Index are considered as independent variables. Using the ARDL model, it was analyzed with a daily data set between 21.01.2020 - 04.04.2020. It is concluded that the relationship between the variables included in the analysis and Bitcoin prices exists co-integrated in the long term. Within the framework of the findings, investors' fears were interpreted by associating them with Bitcoin and Covid-19.
Improving The Quality And Effectiveness Of The Educational Process

The article provides the social essence of an innovative pedagogical approach. Innovativetechnologies have been revealed, the relevance of the issue has been highlighted, the goals andobjectives have been outlined, the practical significance has been laid.
The Model of Modern Entrepreneurial University: Has It Been Created in Russia?

The competitive edge of national economic systems is largely determined by the activities of higher education institutions. In the modern world, universities carry out not only educational functions, but also generate actively new knowledge and innovations. Both in industrially developed economies and developing countries, universities are often the sources of new technologies for business, and there is numerous evidence of the consolidation of this role of the university sector.
Principles of gas sampling: TOS with critical challenges

Sampling and analysis of materials in the gas phase is not covered in general sampling standards and guides, due to the complex nature of the subject matter. Most gas-phase materials exist in the region from ambient temperatures (~300 K) to combustion temperatures typically around ~1200 K. Common to both temperature range margins, though predominantly for hot gases, is the fact that continuous reactions often take place in material that is moving at high speeds, presenting less than trivial challenges to conventional Theory of Sampling (TOS). The purposes of representative gas sampling are many, but three standard cases are presented, covering the most dominating scenarios met with in science, technology and industry.
Creating and Evaluating Resources for Sentiment Analysis in the Low-resource Language: Sindhi.

In this paper, we develop Sindhi subjective lexicon using a merger of existing English resources: NRC lexicon, list of opinion words, SentiWordNet, Sindhi-English bilingual dictionary, and collection of Sindhi modifiers. The positive or negative sentiment score is assigned to each Sindhi opinion word. Afterwards, we determine the coverage of the proposed lexicon with subjectivity analysis. Moreover, we crawl multi-domain tweet corpus of news, sports, and finance. The crawled corpus is annotated by experienced annotators using the Doccano text annotation tool. The sentiment annotated corpus is evaluated by employing support vector machine (SVM), recurrent neural network (RNN) variants, and convolutional neural network (CNN).
Diabetes Prediction Using Feature Selection

Neural network is one of the pattern classification techniques, which has been widely used in many fields application. The multilayer perceptron in a training process has an accuracy impact. The selection of features is another factor that influences classification accuracy. The objective of this research is to optimize simultaneously parameters and subset of functionalities in order to increase multilayer perceptron accuracy. A genetic algorithm approach is presented in order to characterize selection and optimization parameters that serve as input to the multilayer perceptron classifier. The proposed algorithm can scan irrelevant information in PIMA database and obtain better accuracy. The results of this experience show that the proposed algorithm can provide a significant performance gain in terms of accuracy and training speed for the multilayer perceptron classification.
Arabic Emoji Sentiment Lexicon (Arab-ESL): A Comparison between Arabic and European Emoji Sentiment Lexicons

Emoji (the popular digital pictograms) are sometimes seen as a new kind of artificial and universally usable and consistent writing code. In spite of their assumed universality, there is some evidence that the sense of an emoji, specifically in regard to sentiment, may change from language to language and culture to culture. This paper investigates whether contextual emoji sentiment analysis is consistent across Arabic and European languages. To conduct this investigation, we, first, created the Arabic emoji sentiment lexicon (Arab-ESL). Then, we exploited an existing European emoji sentiment lexicon to compare the sentiment conveyed in each of the two families of language and culture (Arabic and European). The results show that the pairwise correlation between the two lexicons is consistent for emoji that represent, for instance, hearts, facial expressions, and body language. However, for a subset of emoji (those that represent objects, nature, symbols, and some human activities), there are large differences in the sentiment conveyed. More interestingly, an extremely high level of inconsistency has been shown with food emoji.
Implementasi Algoritma Approximate Pada Aplikasi Paritta Suci Pada Kitab Tripitaka Berbasis Android

The word Paritta in Paliatau Pirit, literally means full of protection. Buddhas on various occasions with the holy pali language compose Paritta or Pirit, there must be a misunderstanding that equates Paritta as a mysterious blessing or mantra, but actually there are genuine advocates that are ethical and contain philosophical values from Buddhism, which are related to aspects of the Dhamma. And the Tripitaka is a Buddhist scripture which is a collection of sermons, statements, parables, and conversations that the Buddha had done with his students and followers. Likewise with the Paritta Suci part of the Book of Tripitaka which is very necessary in the search for verses from the word Paritta Suci. Making it easier for users to read from the book. For that we need an application that can help users in translating a language that is easy to carry and can be used anytime and anywhere. The application is in the form of an android application that can be installed on a mobile phone. The book Tripitaka application requires a search process that supports the performance of the application so that the search process can shorten the time in the search itself. In this study Approximate Levensthein Distance Algorithm is an algorithm that can be used to calculate distance differences between two strings. Distance or distance is the minimum number of delete operations, insert or substitution needed to change the origin string (s) to the target string (t). And Algorithm Approximate string matching is matching strings with the basis of similarity in terms of writing (number of characters, arrangement of characters in the document). So that it can help users of the application in searching for words from the book.
MOTIVASI BELAJAR MAHASISWA DENGAN PENERAPAN MODEL PEMBELAJARAN MOBILE LEARNING DI MASA PENCEGAHAN PENYEBARAN COVID-19

One of the prevention and spread of Covid-19 is to carry out physical distancing. Physical distancing is keeping a minimum distance from one person to another, and staying away from crowd points, because if this is not done, the spread of covid-19 will be very fast, the number of patients in the hospital will explode so that health facilities will be overwhelmed to handle it. Lectures conducted online will break the chain of the spread of covid-19. The purpose of this study is to look at student learning motivation in artificial intelligence courses in the odd semester of TA. 2019/2020 by applying the mobile learning model for one semester, whether there is an increase or a decrease. The method used in the research was to spread closed questionnaires to all students who took artificial intelligence courses at the PTIK FTIK IAIN Bukittinggi Study Program, then the questionnaires were analyzed. The mobile learning model is one of the alternative learning models during this pandemic. The results showed that the mobile learning model increased student learning motivation, independent learning, more active and effective communication between fellow students and also between students and their lecturers. On average, student learning motivation, especially in the artificial intelligence course, is at a value of 8.13%, which means it is included in the good criteria of the 42 questionnaire items filled by students. The learning motivation of female students was higher (mean rank: 157.15) than boys (mean rank: 104.35).
Adverbial clauses in translation : Translation of finite and non-finite (-ing, -ed and to-infinitive) adverbial clauses from English to Swedish in popular science

This study investigates adverbial clauses in a translation of a popular science text from English to Swedish. The clauses investigated are both finite and non-finite adverbial clauses. The non-fini ...
Cloud Computing for MATLAB and R Users: Part I – Creation of Virtual Computing Instance Using Amazon Web Services

Cloud-based computing has tremendous potential for academia in general and researchers in particular. The ability to store, read and manipulate large dataset is increasingly important to be on the cutting-edge of research. While most researchers have extensive programming skills, they generally are not computer scientists. A number of cloud-based and virtual work spaces have been developed which can bring enormous computing advantages over any desktop or laptop. However, the instructions to get up and running in the cloud are often overwhelming, and require a significant investment of time. There is an initial steep learning curve associated with developing a high performance computing environment that several times becomes an obstacle that prevents many to benefit the most from using the cloud. This paper seeks to demystify the process and get the reader up and running very quickly. Once this initial process is over and the reader is proficient on these issues, performing computational chores that would take days on a desktop can be done in minutes. We next show the way the readers can implement their research using two well-known computer programs: MATLAB and R.
Perbandingan Metode Cost Sensitive pada Decision Tree dan Naïve Bayes untuk Klasifikasi Data Multiclass

Abstrak – Knowledge discovery is the method of extracting information from data in making informed decisions. Seeing as classifiers do have a lot of learning patterns in the data, testing an imbalanced dataset becomes a major classification issue. The cost-sensitive approach on the decision tree C4.5 and nave Bayes is used to solve the rule of misclassification. The glass, lympografi, vehicle, thyroid, and wine datasets were collected from the UCI Repository and included in this analysis. Preprocessing attribute selection with particle swarm optimization was used to process the data collection. Besides, the cost-sensitive decision tree C4.5  and the cost-sensitive naive Bayes method were used in the research. On the glass, lympografi, vehicle, thyroid, and wine datasets, the accuracy of the test results was 72.34 %, 68.22 %, 75.68 %, 93.82 %, and 93.95 %, respectively, using the cost-sensitive decision tree C4.5. While the cost-sensitive naive Bayes method outperforms the others by 32.24 %, 82.61 %, 25.53 %, 97.67 %, and 94.94 % on the dataset, respectively.
LibGuides: Makerspace: Donation Guidelines

Information about the ECTC Library Makerspace.. Guidelines for making in-kind donations to the Makerspace
Advancing food web modelling capabilities to analyse global ocean futures

Institute for the Oceans and Fisheries (IOF) Seminar Series, The University of British Columbia (UBC), 22 November, 2019
IMPLEMENTASI DAN KONFIGURASI VPN SERVER MENGGUNAKAN JUNIPER

The internet network in Bengkalis district has been evenly distributed in every sub-district and offices in Bengkalis district. And one of them is at the population and civil registration office (DUKCAPIL). Currently the internet network in this office still uses Mikotik in daily work operations and for VPN Servers still using mikrotik, but over time the use of data and information is very high, causing several security problems in the network because that is to overcome these security problems need a VPN Server. Research and design of a VPN Server using Juniper and will be applied in the Bengkalis Regency Population and Civil Registry Office is a literature study, and a field survey to obtain valid data about the Civil Service Server.   Keywords: Juniper, VPN Server, Configuration
Rigorous evaluation of vector-associated model performance (REVAMP)

DevOps engineers take many factors into account when assessing the suitability of AI/ML algorithms for operations. They rely on documentation about data requirements, parameter settings, theoretical limits, and operating characteristics to anticipate how well an algorithm will perform in the field prior to writing a single line of code. However, the USAF currently lacks code quality and documentation standards for AI/ML, which forces downstream consumers to make assumptions about the behavior of algorithms that often lead to unexpected results and wasted efforts. Therefore, we present a preliminary set of criteria by which to judge the maturity of word embedding algorithms in terms of reproducibility, testability, and documentation quality. We hope the criteria will grow into a set of quality requirements that govern how the DoD procures AI/ML capabilities, and eventually motivate the need for an ML development maturity model. Our nascent evaluation criteria surfaced during our own struggles with trying to replicate and compare the performance between a well-known word embedding algorithm (Word2Vec) and a custom graph embedding algorithm (IRI2Vec), procured specifically for the purpose of connecting missions across ATOs. We walk through two case studies in which we applied our evaluation criteria to assess the maturity of both Word2Vec and IRI2Vec
Iraqi Food Image Detection Using Convolutional Neural Network Classification Method

A restaurant is a public place, and it is open to everyone to take a drinks and food against money. The restaurant offers service of food and drinks desires to satisfy the customer. At the moment, the payment process at restaurants is still manual and ineffective because it uses a cash record. A cashier will check what foods are required, then calculate them with the cash record, and this process will take a long time and be ineffective. In this paper, design application for Iraqi food detection and also reduces long queues at certain hours in restaurants and estimate food costs automatically applying the convolutional neural network (CNN) classification method. The results of the application are can detect six types of food on 80% data partition training data and 20% test data, with the image taken in storage. The accuracy of the appley of CNN reaches 100% with a detection time of 3.59 s.
Paper ID IJMS0519-015 TEACHERS COMPLIANCE OF REPUBLIC ACT 6713 AND THEIR PERFORMANCE LEVEL: BASIS FOR FACULTY ENHANCEMENT PROGRAM

The study was conducted to determine the teachers compliance of Republic Act 6713 or the Code ofConduct and Ethical Standards for Government Officials and Employees and its effects on teaching performance ofthe secondary teachers of national high schools in the Division of Cagayan de Oro. The respondents of the studywere the 300 secondary teachers of the 22 national high schools of Cagayan de Oro City, both in District I andDistrict II. The descriptive method of research was used in this study. Thus, the study involved populations withalmost similar demographic attributes with common outstanding features that distinguishes them from other groupsin a specific location. The questionnaires were items taken from Republic Act 6713 otherwise known as the Code ofConduct and Ethical Standards for Public Officials and Employees, National Competency Based Standards forTeachers and the STAR Observation Technique. Stratified random sampling was used to determine the number ofrespondents. The weighted mean of each item of the questionnaires was determined; The null hypothesis of therelationship between the variables of the study were tested by means of the Pearson r Product Moment Coefficientof Correlation; T-test was used to find out if there is a significant difference between the respondents' profile andtheir compliance with RA 6713 and their teaching performance. On the basis of results and findings, respondents’profile as to gender, age, teaching experience, teaching position’ educational qualification and family monthlyincome did not differ significantly to the level of teachers’ compliance to RA 6713. Therefore, regardless of gender,age, experience, teaching position, educational qualification and family background, they do not differ on theirperformance. They relatively have the same performance. As the statistic shows, there is a positive and significantrelationship between the teachers’ compliance to RA 6713 with respect to Commitment to public interest;Professionalism; Justness and sincerity; Political neutrality; Responsiveness to the public; Nationalism andpatriotism; Commitment to democracy; and Simple living. Which means, the higher the level of the professionalismamong teachers it is expected that there is also a higher the compliance among teachers to RA 6713 respectively.This is also true with the other indicators as stated in the said Republic Act.
Segmentasi Citra Spektrum Menggunakan Algoritma Region Growing

Image segmentation is a process shown to get the objects contained in the image or to divide the image into several areas with each object or area having similar attributes. The Region growing algorithm is a procedure that groups pixels or sub-regions into larger areas based on defined criteria. The basic approach starts from the set of starting points, then the area is enlarged by adding each neighboring pixel point that has similar properties to that point, for example the range specification intensity or color. The purpose of region-based segmentation (region) is to divide an image into several regions, this is done by grouping parts of the image that have the same characteristics in the form of color changes between adjacent points. The application of the Region Growing algorithm can be used in analyzing the segmentation of Infrared Spectrum Image in detecting image edges based on the growth area with the image segmentation process using the Region Growing algorithm
STUDENTS’ VOICES ON ACADEMIC WRITING ACTIVITIES AT TERTIARY LEVEL

&lt;p&gt;Academic writing activities play an important role for students at the tertiary level. Because students are required to be mastered to write academically. The aim of this research was to know-how is the teaching of writing for academic purposes, to know how students perceive the teaching of writing for academic purposes, and to know how a teacher perceives the teaching of writing for academic purposes. Case study was used as the research design in the paradigm of the qualitative and 20 students (in the 5th semester) and 1 teacher from Bogor Ibn Khaldun University were invited as a research participant. Observation, interview, photovoice, voice recorder, and documents were used as a research instrument to get the data. The result of this study showed the teacher taught the materials before each student was required to write an essay. The teacher provided feedback and comment on their essay in the process of writing an essay. Students did the revising process to make their essays better. The students also had a positive perception of the teaching of writing for academic purposes. There were three aspects that students perceive on the teaching writing for academic purposes those were the teaching practice, teachers’ feedback, and students’ problems or challenges. Besides, the teacher perceives there were some problems encountered in the teaching of writing for academic purposes. The problems encountered were students’ level proficiency, students’ motivation, technical problems in the classroom, the production of the students’ essay, and the support from the leader.&lt;/p&gt;
Pembelajaran Jarak Jauh Bagi Anak Tunarungu Pada Masa Pandemi Covid-19 di SLB Al Azhar Bukittinggi

The background of this research found problems in the learning system in schools from face-to-face learning to distance learning due to the Covid-19 pandemic, both regular schools and special schools (SLB). This study aims to describe how the planning, implementation, supporting factors and inhibiting factors for the implementation of distance learning for deaf children in SLB Al Azhar Bukittinggi. This study used descriptive qualitative method. The results showed that: 1) Planning by compiling a program includes essential materials and the ability of teachers to use technology, 2) Implementation using online and offline methods with a strategy of utilizing technology, 3) Supporting factors include collaboration between schools and parents, assistance from the school and free quota assistance from the government, 4) The inhibiting factors for implementing distance learning are parents who have permanent jobs, parents who do not understand the task, and where students live who find it difficult to get an internet network.