Reviewerly/exHarmony huggingface dataset:
Peer Review: A corpus study of verbs in opinion articles of The Jakarta Post and the relation with text characteristics

As one of the text categories, opinion texts have distinctivecharacteristics compared to any other texts in newspapers, including the choice of verb usage. This study then aims at preliminarily examining the verbs used in opinion articles in The Jakarta Post to find out the relation between frequency and text characteristics. This study collected the opinion articles of The Jakarta Post comprising 47.143 words. This study was assisted by Lancsbox to store the corpus of opinion section texts, to identify the verb lemmas, and to count the frequency of verbs. The verbs found in this study were then classified based on Scheibman’s main verb classification (which is based on Halliday’s and Dixon’s verb types). The results of the study show that there are three most frequent verb types used in opinion texts in The Jakarta Post; they are material, verbal, and feeling verb types. Meanwhile, the lesser frequent ones are perception, possessive/relational, relational, and cognition verbs types.Meanwhile, the least frequent verb types are existential, corporeal and perception/relational verbs types. As opinion text conveys the argument of the writer, it is plausible to find feeling verb type belongs to the third most frequent types, along with material type to show concrete actions and verbal type to report the information. These frequencies exhibit that there is a firm relationship between text characteristics and the tendencyof verb choice.Keywords: Verbs, Opinion, Corpus, Frequency, Text characteristics
Impact of Visual Noise in Activity Recognition Using Deep Neural Networks - An Experimental Approach

The popularity of deep learning methods has increased significantly, in no small part due to their impressive performance in several application scenarios. This paper focuses on recognising activities in an in-vehicle environment and measuring the impact that factors such as resolution, aspect ratio, field of view and framerate have on the performance of the model. The use of deep learning methodologies in recent years has increased the amount of data required to train and test the models. However, such data is often insufficient, unavailable, or lacks suitable properties. Publicly available action recognition datasets have been analysed, collected, and prepared to assess the classification results in such scenarios, which provides important guidance for use in a real-world setting.
Implementasi Profile Matching Pada Penerimaan Bantuan Langsung Tunai

Various problems arise when direct cash assistance from the government which is carried out in each region begins to be disbursed to people who are entitled to it. One of them is the error in selecting the target recipient of assistance, according to the regulations, residents who receive assistance must comply with applicable conditions such as Indonesian citizens, the poor, the elderly and affected by COVID-19, but there are still people who are classified as capable of being able to get the BLT due to the accumulation of data. numbered in the thousands and packaged in a manual system resulting in assistance not being channeled to the right people, with this problem the author took the initiative to create a system that was implemented with the profile matching method with criteria taken from the data on the requirements for receiving BLT from the government to provide solutions to problems by determining residents appropriate and appropriate in receiving the cash direct assistance. Data research was carried out using the prototyping concept to increase the accuracy of receiving cash transfers that were processed with a decision support system to facilitate the acceptance process so that it was more accurate and faster and did not harm related parties. This system is designed in such a way that it can be accessed by the general public and with Android devices to facilitate the admissions selection process.
Startup Kit@HKUL 2021

StartupKit@HKUL 2021Through this workshop, you will learn how to configure and install the essential software and Apps to facilitate your workflow, including:Mobile@HKUL: Quick mobile access to HKU Libraries information and services.HKUL Search Assistant: A plugin to search HKU Libraries Catalogue and other popular databases within your browser and access HKUL subscribed resources from publisher websites.Reload via HKUL: A bookmarklet to facilitate access to HKUL subscribed resources from publisher websites.Google Scholar: Link to HKUL full text subscriptions through ViewIt@HKUL.Endnote: A reference management software to organize readings and cite sources while writing a paper.
Determination of Efficient and Secured Healthcare Monitoring Based on IoT Along with Machine Learning

A Health Monitoring System (HMS) is a modern technology and an alternative to traditional patient and health management. The usage of IoT in healthcare system is playing a vital role. Using the IoT device the various health parameters of the patient can be read and stored in the cloud for various analysis purpose. The data can be analyzed using various statistical methods and machine learning algorithms. Since the data stored are of sensitive information the security of the data to be achieved. In this chapter the role of IoT, artificial intelligence or machine learning algorithms and security issues and its challenges are discussed and the research gap is identified.
Using machine learning to understand human sensitivity to noise in naturalistic images

Understanding our sensitivity to noise in naturalistic conditions will provide key clues as to the visual system's adaptations to the real world. Determining which characteristics of image noise (kind, amount, or distribution) appear particularly noisy to humans is a key first step. To examine this, we presented pairs of images (natural landscapes: m=102 shot at ground level; m=289 overhead), which were noise-added versions of the same noise-free image and had observers (n=108 total) judge, in a 2AFC paradigm, which image appeared clearer (less noisy). Varying level and kind of noise, data from 2346 image pairs were obtained. Classifiers were trained to simulate human choice data based on the values extracted for each of the image's forty-four pre-determined features. Features are local or global; local meaning over a small neighborhood around each pixel; global meaning ensemble values over the entire image. Results shown here are the averages of four algorithms (decision tree, random forest, logistic regression, SVM). Ten-fold cross-validation was used. Custom code for feature extraction was written in MATLAB; supervised machine learning was implemented on Pycharm. Our reasoning was to use machine learning to mimic human selection, then leverage the classifier to find what image features could possibly underlie human sensitivity to noise. While the all-features classifier matched (95.3±1.2%) human choice data, its performance was nearly matched by a classifier (93.0±1.3%) based on a single local feature, LocalContrastNearestNeighbor-Red – the local (red) contrast between a pixel and its nearest neighbors. The second-best (92.4±1.4%) single-feature classifier was also local. On the other hand, the best single global-feature classifiers, namely NumberOfOutlines (88.0±1.6%), HistogramMean-Red (83.3±1.9%) and HistogramSkewness-Red (82.8±1.9%) did not perform as well. Generally speaking, clearer images as judged by human observers were of lower local contrast and higher positive skewness than their noisier counterparts. Additional signatures of human-like performance are being explored.
A Note on the Exact Relation Between Mixture Likelihood and Entropy

It is interesting to note that the expected value of the log likelihood function is entropy. This note shows that there is an exact relationship between the mixture log likelihood function (ln LM) and the sum of the mixing distribution entropy (HM) and the mixture density entropy (HD). Ln LM is seen as a function exactly of four Shannon entropies, each a unique measure of uncertainty. This method, known as mixtures of linear models (MLM), is a form of empirical Bayes which uses a non-informative uniform prior and generates both confidence intervals and p-values which clinicians and regulatory agencies can use to evaluate scientific evidence. An example based on allergic rhinitis symptoms scores are given and show how easy it is to assess the fit of the model and evaluate the results of the trial.
Survival Analysis and Prognosis of Lung Cancer Patients using NHISS

폐암은 5년 이상 생존하는 환자가 10∼15%에 불과한 예후가 좋지 않은 대표적인 병이며 환자 개개인의 특성에 따라 예후가 상이한 모습을 보이므로 예후에 대한 정확한 정보 제공이 중요하다. 본 연구에서는 국민건강보험자료 공유서비스(NHISS)에서 제공하는 의료 데이터를 통해 2012년부터 2018년까지의 진료 기록이 존재하는 폐암 환자 총 100,268명에 대하여 생존분석과 예후 예측을 실시하고자 한다. 콕스 비례위험 모형, 카플란 마이어 생존 곡선, 로그순위 검정을 통해 폐암 환자의 생존분석을 실시하였으며, 콕스 비례위험 모형으로 예후에 영향을 미치는 요인들을 살펴보고 카플란 마이어 생존 곡선으로 성별과 흡연여부에 따른 예후를 비교해보았다. 또한 개별 환자들의 잔여수명을 예측하여 실제수명과의 차이를 확인하였다. 평균절대오차(MAE)와 평균 제곱근오차(RMSE)를 계산한 결과 각각 575일, 658일의 차이를 보였으며 향후 더 정확한 예측을 위한 방안이 필요할 것으로 보인다. 환자에 대한 생존 분석을 통해 생존기간에 영향을 미치는 요소들을 발견하고 이를 토대로 환자들의 예후를 개선할 수 있는 방안 마련이 기대된다.Lung cancer is a representative disease with poor prognosis, with only 10∼15% of patients surviving for more than five years and it is important to provide accurate information on prognosis because the prognosis varies depending on the characteristics of each patient. Through medical data provided by NHISS this study aims to conduct survival analysis, prognosis prediction for a total of 100,268 lung cancer patients with medical records from 2012 to 2018. Survival analysis of lung cancer patients was conducted through Cox proportional hazard model, Kaplan-Meier curve, and Log-rank test. According to the analysis, the factors that affect the prognosis through the risk ratio of variables with the Cox proportional hazard model were examined and the prognosis according to gender and smoking were compared with the Kaplan-Meier curve. In addition, the residual life of individual patients was predicted and compared to the actual life. Calculating the MAE and RMSE showed a difference of 575 days and 658 days respectively, and it seems that a plan for more accurate predictions will be needed in the future. We hope to find factors that affect the survival period through survival analysis of patients and come up with ways to improve patients’ prognosis based on them.
The effect of high fps on vision in visual presentation under active motion

In conventional video presentation system, 24-60 fps has been widely used because high fps is considered indistinguishable by humans. However, it has often been pointed out that there is a lack of reality under the fps in VR where the user's viewpoint moves. This may be because of the effect of lowering the perceptual stimulus threshold by active motion of the viewpoint. In fact, we have confirmed that the subjective resolution differs by changing the frame rate when binary images are presented in front of the eyes under active motion viewing. Therefore, we observed the binary images fixed in front of the eyes during lateral head movement using 60 fps and 1440 fps presentation fps. We then identified this effect by measuring contrast acuity using equivalent acuity judgment. The method of the experiment is to present a binary image on a screen prepared in front of the eyes, and to draw the image by moving it at the same speed as the head movement. After the image was presented, the gray image was presented once. After the image was presented, the gray image was presented once. After the images were presented, the gray image was presented once, and then the subject was asked to respond by adjusting the contrast using equivalent acuity judgment. The subjects tended to respond with lower Michelson contrast when the images were presented at 1440 fps compared to 60 fps. This perceptual difference indicates that high fps presentation, which is previously considered unnecessary because people can’t distinguish from 60 fps presentation, could present visual information more clearly in visual presentation during active motion.
ONLINE TICKET BOOKING INFORMATION SYSTEM ON CV. TAXI SIMPATI PADANGSIDIMPUAN WEB BASED

CV. Taxi Simpati is a CV that provides transportation services in the city of Padangsidimpuan. The process of processing ticket booking data on CV. Taxi Simpati is still done manually by using handwriting. With the Online Ticket Booking Information System and computerized data processing, of course the ticket ordering process and ordering data processing will be more effective, and minimize errors in writing ticket sales reports that have been done manually. For the ticket ordering information system, it includes an input design that contains the ticket sales process. Customers login to order tickets for the desired major, system transaction automatically provide proof of ticket replacement sheets at departure.
Social media platform Parler goes dark after Amazon cloud suspension

Social media platform Parler is down following Amazon Web Services' decision to suspend Parler from its cloud hosting service after Wednesday's U.S. Capitol riot.
PENGARUH PENGGUNAAN METODE DISCOVERY LEARNING TERHADAP HASIL BELAJAR SISWA PADA PELAJARAN BAHASA INDONESIA DI KELAS V SDN 091263 KARANG SARI

The problem in this study is the low activeness of students in social studies lessons. This study aims to improve student learning activity by applying a problem-based learning model. This type of research is Classroom Action Research which consists of two cycles with four stages, namely planning, action, observation and reflection. The subjects of this study were the fifth grade students of SDN 091263 Karang Sari, totaling 24 people, while the object of this research was the effect of using discovery learning methods to improve student learning outcomes in Indonesian lessons. Data collection techniques are observations and questionnaires on student learning activities. And observation of teacher teaching activities. Based on the analysis of the data obtained in the first cycle, the medium category is 4.17%, the high category is 83.30%, and the very high category is 12.50%. Then it increased in the second cycle with the percentage of high category 4.17% and very high category 95.83%.
How To Use Poster To Teach English

the aimed of this article is to develop learning media, namely poster. because poster will drive student motivation and character in learning English. The students conducted this article because there were problems in learning, the students have to understand to knowledge and have skills in learning. Students must also have good character in increasing learning motivation. So that the author makes posters to gave students improve to learn because posters in education was make students to improve student learning. These poster as a media are common among the learner and student were easy to learn, particularly in the current condition, students have to build ideas and develop knowledge through written writing. so that in this writing the poster was chosen to be used as material to develop student creativity in class learning and theauthor chose a Canva application to make learning applications to serve as classes learning materials. This research was used qualitative method with DnD model namely design, development, and evaluation. The population of this research was the English teacher SMPN 4 Kintamani with a sample all seven grade students with 32 students who were sampled in this study. the results of using these three steps can help teachers to use posters in teaching English and the results of the posters can be used as material for teaching in class.
IMPROVING STUDENTS’ VOCABULARY MASTERY THROUGH INDEX CARD MATCH STRATEGY

English is one of the subjects studied by Indonesia students' ranging from Junior High School until University. One aspect that plays an important role in learning English is vocabulary mastery. For that reason, the purpose of this study is to know whether or not there is any improvement of vocabulary mastery by using an index card match strategy. This research was conducted at SMPN 4 Cikalongwetan using the classroom action research (CAR) method with 30 students as samples. Learning using the index card match itself is considered to be able to increase vocabulary mastery as an impact of interesting and exciting learning, it can be seen from the score of post-test which is higher than the pre-test score, with a pre-test score of 64.66, post-test score cycle 1 of 79.33 and post-test score cycle-2 of 83,66. This means the index card match strategy is effective to improve students' vocabulary mastery. Keywords :  Vocabulary, Index Card Match, CAR
Feature Extraction and Classification of Segmented ECG Signals Based on Radial Basis Function and Random Forest Methodology

Agriculture is said to be the backbone of the economy. Farmers toil hard with different kinds of crops to make good and healthy food for the country. There are more existing systems but uses outdated machine-learning techniques based on RNN( Recurrent neural network) which makes the process slower and more time-consuming. Here We are proposing a new CNN(Convolutional neural network ) based system which is fast and gives accurate results within seconds. CNN is power-efficient and is more suitable for real-time implementation. In this project, we use CNN algorithms which is very much better than the RNN algorithms used in the existing system.More parameters will be taken for the consideration of prediction in the proposed system. And we use Random Forest Regression, Multiple Linear Regression
The Relevance of Academic Performance in Career Development According to the Big Five Model

A purely theoretical analysis reveals the existence of a direct relationship between academic performance and work performance. It is also expected that individuals who have registered during academic performance will develop a career in their field of academic preparation. A research of the students' academic performance contributes to the identification of the relevant factors of the academic performance with an impact on the work performance. The fundamental idea is that the performance of individuals is determined by their personality, characterized by the big five model. Known to be a positive personality ensures both academic performance and work performance and career success.
Information Literacy as a Factor of Developing Teaching Competency in Foreign Language Teachers in the People`s Republic of China

The problem of developing information literacy in modern society is urgent because the ability to use information resources is one of the ways to carry out effective professional activity. The aim of our study is to analyse the development of information literacy of foreign language teachers in the PRC. The following research methods have been used for this purpose: comparative pedagogical analysis and empirical data analysis. The obtained survey results were processed using qualimetric techniques. The results of the survey allowed determining a need to develop information literacy in Chinese foreign language teachers. For deeper analysis, observation of teachers was conducted during classes, which allowed determining areas of work with them on understanding the component of pedagogical competence as an individual professional element and the value attitude towards information resources. The main conclusions of the study provide for identification of the ways to develop information literacy in Chinese foreign language teachers. At the same time, possibilities of using modern interactive methods for information literacy in Chinese foreign language teachers were identified. Promising areas of further research may be the study of the use of interactive methods in combination with collaborative technologies to develop information literacy in Chinese foreign language teachers.
Self-Organizing Optical Matter Machines and Many-Body Forces

Optical Matter systems, particularly those created with nanoparticles, allow studying new optical physics phenomena, non-reciprocal forces and even many-body effects. This talk will introduce self-assembling nanoparticle-based optical matter machines and the inter particle electrodynamic interactions that give rise to structures that can do work. It will also introduce a new many-body mechanism for spin-to-orbital angular momentum conversion as studied by experimental measurements, electrodynamics-Langevin dynamics simulations and theory.
Pengembangan Sistem Manajemen Event Pameran Karya Mahasiswa Menggunakan Metode Extreme Programming

An event is a means for students to improve their soft skill and hard skill. In college, one kind of event that usually held regularly is an exhibition. It is usually held around the universities environtment, but in practice there are still some shortcomings, such as the registration process is done manually, attendance of participants that are not integrated with the system, and unavailability of certificates for participants who have attended the event. Since the outbreak of Covid-19, organizing the events must be done online, so we need a system that can accommodate this. Therefore, this study aims to create an event management system that can manage exhibition event data. Besides, the system is also equipped with a feature to generate an E-Certificate that has a QR Code embedded. The method used in this study is Extreme Programming, with its flexible nature toward changes to facilitate the process of system development. The testing in this study is using black box method, with the test results show that all functional in the system can run well in accordance with user expectations. The use of the Extreme Programming method produces a quality system, because users are involved during the system development process.&#x0D;
Sistem Monitoring Kesehatan Dalam Penentuan Kondisi Tubuh Dengan Metode Fuzzy Mamdani

In this study, designing a health monitoring system with an Android-based Application of Health Detector (AHD) application. The data displayed is an input for multi-sensor readings from the detection of body health. From the detected health, it will provide a determination of the body's health condition, using the fuzzy mandani algorithm. The variables calculated were age, gender, heart rate, body temperature, systolic blood pressure, diastolic blood pressure, and blood oxygen levels. The stages of the fuzzy mamdani method in determining body health conditions include the formation of fuzzy sets, application of implications functions, and composition of rules. From the results of this study, it was found that the age factor affects health conditions. Older people tend to have indications of health conditions, only some of them have indicated health conditions, and almost all of them have healthy health conditions. The level of accuracy of the fuzzy mamdani method in this study was 85.18%. This is because in this study many variables are used which causes many rules to be made so that they are prone to errors.