Reviewerly/exHarmony huggingface dataset:
Implementasi K-Means Clustering Untuk Mengelompokkan Hasil Pertanian Kacang Kedelai (Ha) Berdasarkan Provinsi

Soybeans are one of the types of legumes which are the basic ingredients of many foods that are useful for body health, this plant has also been cultivated since 3500 years ago. Judging from the data yield of soybean (Ha) obtained from various provinces, the yield varies from year to year. But at this time the government is still lacking information in getting an information about the grouping of agricultural yield data from various provinces in Indonesia, therefore, the authors conducted a study aimed at grouping the harvested area of soybean (Ha) in each province in Indonesia with using the K-Means Clustering algorithm. The data will be divided or clustered into 3 clusters where cluster 1 is a group of provinces with high potential for agricultural output with a yield of 1 province, cluster 2 is a province with medium agricultural yield with a yield of 5 provinces, while cluster 3 is a province with low agricultural yield potential with yields of 27 provinces. The results of this study are as a way to assist the government in establishing soybean farming development areas (Ha) which is an opportunity for the government to develop and improve the provincial economy. And it is hoped that this research can be used as a material for policy making to increase soybean yields in each province in the future so that it can help maximize government programs in soybean farming.
Implementasi Algoritma Backpropagation Dalam Memprediksi Jumlah Penduduk Usia Produktif Pada Kota Pematangsiantar

The productive age itself is a population in the age group between 15 to 64 years, whether they work, go to school, and take care of the household, in this case individuals who are in the scope of productive age are people who can still work well to produce a product and services. This study uses an Artificial Neural Network (ANN) with the backpropgation method. The backpropagation algorithm is one of the existing methods of neural networks as a prediction, estimation, classification, and pattern recognition algorithm. The research data is secondary data sourced from the Central Statistics Agency (BPS) from 2013 to 2015. The data is divided into 2 parts, namely training and testing data. There are 5 architectural models used in this study. 2-20-1, 2-21-1, 2-22-1, 2-23-1, 2-24-1. Of the 5 architectural models used, the best 1 model is obtained, namely 2-24-1 with an accuracy level of 80%, MSE 0.00085177 and epoch 100. So this model is good for predicting the number of productive age population in the city of Pematangsiantar in the future
Perbandingan Antara SQLite, Room, dan RBDLiTe Dalam Pembuatan Basis Data pada Aplikasi Android

Android is one of the largest mobile operating system platforms today. Amid the ever-increasing needs of users, Android programmers are still lacking to meet the current market needs. One of the problems that causes this is the difficulty of creating an internal database, so many people give up to learn to make Android applications. Android's internal database is hard to create because the entire data structure on that database should be built with the query executed in the created program code. Some of the common internal databases currently used are SQLiTe and Room. Both databases are quite difficult to learn where SQLite should build everything from scratch while Room should study the structure and systematics of of the library. Therefore, in this article, the author proposes library and template named Relational Database Library and Template which will be referred to as RBDLiTe which can create an internal database for Android applications easily which will also be compared with SQLiTe and Room in its use.
CONTRASTIVE ANALYSIS BETWEEN ENGLISH AND INDONESIAN PRONOUNS THROUGH SEMANTIC COMPONENTS

The purposes of this study are to discover the similarities and differences between English and Indonesian pronouns based on semantic components, to predict the possible difficulties faced by Indonesian students in learning English pronouns, and to find out the implications for language teaching. In this study, the writer used the descriptivequalitative method. In collecting and validating the data, the writer applied the triangulation technique. It used documentation, observation, and interview techniques. Based on the findings, it was found that they were eight similarities and three differences between English and Indonesian pronouns through semantic components; three possible difficulties problems faced by Indonesian students in learning English pronouns; and two implications for language teaching.
Phase error analysis and compensation for motion in high-speed phase measurement profilometry

High-speed three-dimensional (3D) measurement is increasingly important in many fields. Phase measurement profilometry (PMP) based on the binary defocusing technique has been applied to the high-speed 3D measurement scene for its higher measurement resolution and precision, and breaking the speed limitations of projector. However, because the PMP needs three phase-shifting (3-PS) patterns, motion error is inevitable to measuring dynamic objects. In this research, we construct a complete high-speed 3-PS PMP system, and re-derive two clearer motion error models than those in Weise’s research [ Conference on Computer Vision and Pattern Recognition (CVPR) ( IEEE , 2007 ), pp. 1 10.1109/CVPR.2007.383291 ]. Then, we theoretically analyze the effects of the truncation error on the model accuracy, especially when the motion error is higher. To this end, a polynominal-based motion error model by fitting coefficient matrix of pre-simulation is proposed. Meanwhile, its corresponding error compensation method based on local domain estimation of the Nelder-Mead algorithm is developed. Finally, both simulations and quantitative and qualitative experiments verify the accuracy and effectiveness of the proposed method, as well as demonstrate the proposed method has improvements compared with the Weise’s research.
Culturally Ostracized Emoji: A Semiotic Analysis of Emojis and Emoticons

The worldwide usage of Emoji is a source to assess the globalization of the Japanese popular culture in the struggle to promote cultural literacy and multiculturalism.  This new visual writing system of Emoji reveals prejudice among its users across the global village. The cultural diversity have made it more complex and unreadable, hence it requires to be used with conventional modes of expression to evade misunderstandings. This rise of Emoji icons was acknowledged in 2015 by Oxford Dictionary by declaring Face with Tear of Joy Emoji as the word of the year. The present research aims to explore the visual practices employed to propagate different ideologies in the culturally banned Emoji icons and Emoticons.  This research is carried out with a proposed semiotic reading of Emoji icons and Emoticons inspired by Marcel Danesi’s the Semiotic of Emoji: The Rise of Visual Language in the Age of Internet.
Analisis kesulitan membaca pemahaman pada peserta didik kelas VD SD Djama’atul Ichwan Surakarta

&lt;p&gt;This study aims to describe the difficulties of students in the VD class of Djama'atul Ichwan Elementary School in the 2020/2021 academic year in reading comprehension. This study used a qualitative descriptive method where the data collection techniques used observation, interviews, and written tests to 6 respondents. Based on the results of data analysis and discussion, this study found difficulties in reading comprehension in students. Difficulty reading comprehension in students is shown through indicators of students' abilities in answering questions about reading content, finding main ideas, making reading conclusions, determining mandates, and the ability to retell the content of the reading. Data analysis in the discussion provides broad and in-depth information about the difficulties of different students regarding reading comprehension.&lt;/p&gt;
Design of DMD Projection Lens for Structured Light 3D Measurement

To obtain 3D information of an object, the object must be measured. As a non-contact and active measurement method, structured light-based 3D measurement technology has a wide range of applications. The image quality of the projection lens determines whether the projection grating can be clearly projected on the detection object in the 3D measurement, which directly affects the detection effect. In this paper, a DMD projection imaging lens suitable for 3D measurement of structured light is designed. The effective focal length is 33.9 mm, F/# is 2.3, and the total length of the optical system is 120 mm. At a lens resolution of 93 lp/mm, the MTF values of all fields of view are greater than 0.5, the maximum distortion of the full field of view is less than 1%, the field curvature is less than 0.05 mm, and the imaging quality is good enough for 3D measurement.
EYE CONTROL WHEELCHAIR

Nowadays cost effective system is implemented for the physically impaired people. An eye controlled based wheelchair system. The aim of Eye movement based control electric wheelchair is to eliminate the need of the help required for the disabled person. And it provides great opportunity of the disabled to feel of independent accessible life. The implemented system will allow the disabled person to regulate the wheelchair without assistance from other persons. In this system controlling of wheelchair administered by Eye movements. The camera is mounted ahead of the user, to capture the image of anybody of the attention (either left or right) and tracks the position of eye pupil with the utilization of Image processing techniques. Consistent with the position of eye, wheelchair motor are going to be directed to maneuver left, right and forward. Additionally to the present, for the security purposeultrasonic sensor is mounted ahead of wheelchair to detect the obstacles and automatically stop the wheelchair movement. to form system cost effective for monitoring, a Raspberry pi board allowed to access the system without display
Celebration of the new phase of the National Centre for Research Methods

In January 2020 NCRM entered a new phase with an ESRC award for 5 years. This event is an online celebration of the new phase of NCRM. The video launch lasts 60 min and the programme includes: • Introduction and new phase overview by Professor Gabriele Durrant, Director of NCRM• New NCRM branding and introduction to the functionality and design of the new NCRM portal by Professor David Martin, Co-Director of NCRM, Eva Nedbalova, NCRM Communication Manager • The future of research methods - a funder’s perspective, a talk by Professor Alison Park, Director of Research at the ESRC• New ‘In Conversation’ video podcast with Professor Danny Dorling, Halford Mackinder Professor of Geography, University of Oxford, and Professor Vernon Gayle, University of Edinburgh.
The Impact of Covid-19: From a Culture of Teaching Towards a Culture of Learning

The year 2020 will be remembered for Covid-19 – the period of ‘forced’ critical reflection upon ourselves, others and the society around us. This paper presents the positive and negative practices during this period by focusing on the educational system at the tertiary level where traditional teaching was substituted by e-learning. Based on personal experience and pilot research conducted with the students of South Slavic Studies,the paper further discusses the advantages and disadvantages of e-learning, paying special attention to the arts. Finally, it is concluded that e-learning will remain one of the educational approaches in future.
A Collaborative Imperative? Libraries and the Emerging Scholarly Communication Future

We’re in a period of rapid transition. Libraries are focusing on decisions, strategies, and choices that are best for their home institutions, yet also driving change by collaborating in energetic new ways. This panel will review key new trends and challenges, including collaborative collections, transformative open access agreements, and consortial experimentation, highlighting opportunities for both libraries and consortia.
Facetas para a disseminação de folhetos de cordel: acesso aberto, a experiência da Fundação Casa de Rui Barbosa

Cordel literature is one of the most relevant popular manifestations in Brazil. Its importance, in the last decades, has been strengthening among researchers from different areas of knowledge. The Casa de Rui Barbosa Foundation cordel collection is considered the most important in Latin America, being the most researched at the institution. The availability of this collection in the Rui Barbosa Repository of Cultural Information (RUBI) enabled broad and democratic access to researchers. However, because it is a material considered non-traditional, it has required a long and thorough process in technical procedures until release in the repository.
Neural Nets Distributed On Microcontrollers Using Metaheuristic Parallel Optimization Algorithm

Metaheuristic algorithms are powerful methods for solving compute intensive problems. neural Networks, when trained well, are great at prediction and classification type of problems. Backpropagation is the most popular method utilized to obtain the weights of Neural Nets though it has some limitations of slow convergence and getting stuck in a local minimum. In order to overcome these limitations, in this paper, a hybrid method combining the parallel distributed bat algorithm with backpropagation is proposed to compute the weights of the Neural Nets. The aim is to use the hybrid method in applications of a distributed nature. Our study uses the Matlab® software and Arduino® microcontrollers as a testbed. To test the performance of the testbed, an application in the area of speech recognition is carried out. Due to the resource limitations of Arduino microcontrollers, the core speech pre-processing of LPC (linear predictive coding) feature extractions are done in Matlab® and only the LPC parameters are passed to the Neural Nets, which are implemented on Arduino microcontrollers. The experimental results show that the proposed scheme does produce promising results.
Pengembangan Apartemen Cherax quadricarinatus Menuju Industri Akuakultur 4.0

Razanah ND, Girsang GE, Pangaribuan J, Manullang ME, Natalia N, Mukti RC. 2020. Cherax quadricarinatus apartement development towards the aquaculture industry 4.0. In : Herlinda S et al. ( Eds .), Prosiding Seminar Nasional Lahan Suboptimal ke-8 Tahun 2020, Palembang 20 Oktober 2020. pp. xx.  Palembang: Penerbit & Percetakan Universitas Sriwijaya (UNSRI). Red Claw ( Cherax quadricarinatus ) culture has problems, namely the narrower land for cultivation and controlling water quality. This study aims to develop Red Claw cultivation through an apartment system in a small area, to facilitate water quality control and increase the production of Red Claw. The writing method in this study uses the literature study method. The results of the study explain the comparison between the production of Red Claw using an apartment system and the cultivation of Red Claw using pond or aquarium. To produce as many as 20 Red Claw requires a pond with a size of 2m × 1m × 1m, while lobster cultivation using an apartment system only requires land measuring 1.5m × 0.17m × 0.79m. In addition, the cultivation of Red Claw with an apartment system can improve water quality for the better because it uses the RAS (Recirculating Aquaculture System) system, which is the use of water repeatedly through several stages of filtration to break down ammonia. So that the study of Red Claw cultivation through this apartment system can be used as a solution to developing and increasing the production and production of Red Claw.
Using background model and shallow convolutional neural network to detect moving vehicles from satellite videos

In recent years, the Earth-observing satellites have obtained the ability to capture city-scale videos, which enable potential vehicle monitoring. Because of the broad field-of-view, the moving vehicles in satellite videos are very small, making it difficult to differentiate true objects from noise. This paper proposes a terse framework that can effectively suppress false targets while keeping a high detection ratio. The framework first applies the K-nearest neighbor (KNN) background subtraction model to produce preliminary detection results at high recall but with low accuracy, and then uses a shallow convolutional neural network (CNN) to eliminate false targets, increasing the detection accuracy. The experiments and evaluations demonstrate that our method can largely improve the accuracy at the expense of a slight reduction of recall.
How To Utilize Search Intent In Your Content Creation

The goal of any website is to get traffic, but there are different types of traffic online that you should be aware of. These different types of traffic ...
Effect of Parenting Parents, the Concept of Self and Motivation Achievement of Student Achievement

Education has now become a benchmark of the progress of a country. Education in Indonesia has become the attention of the State to provide compulsory education. It is expected to provide the best quality to produce quality learners. This study aims to identify and analyze, 1. Parenting Parents to Student Achievement, 2. Self-concept of the learning achievement of students and 3. Achievement Motivation on Student Achievement. From this research, it has another purpose which is to acquire knowledge and test theories about Parenting Parents, Self-Concept, Achievement Motivation, and Learning Achievement. This research was conducted in Jakarta in high school (SMA) X. In a study of data needed to be collected using questionnaires and the dissemination of data processing researchers used data processing program SPSS (Statistical Package for Social Science). The results of this study indicate that there is an influence of Parenting Parents on Student Achievement.
Система відслідковування об’єктів на відеопослідовностях у інфрачервоному та видимому діапазонах на основі канально-незалежного просторово-регуляризованого дискримінантного кореляційного фільтра

The method of visual object tracking intended for the application on multispectral video sequences is considered.Introduction. The possible techniques of multispectral information fusion for visual object tracking are considered and the use of feature based fusion approach is justified. The tracker is suggested to be implemented using the discriminative correlation filters (DCF), since this approach is known to provide the compromise in terms of tracking quality and speed.Theoretic results. The method for channel-independent discriminative correlation filter with spatial regularization calculation based on the use of alternating direction method of multipliers (ADMM) is proposed. The calculation of DCF filter and the object localization is suggested to be performed in special feature space, which employs the multichannel FHOG features and the features that are based on the backprojection of object weighted histogram. In particular, we propose to calculate the mentioned features for each channel of the respective frame of the multispectral video sequence with subsequent concatenation of obtained features into a single tensor, which forms the joint feature space.Conclusions. Using the VOT Challenge RGBT2019 subchallenge, it was shown that the implementation of the suggested method is competitive in terms of tracking robustness with more sophisticated approaches, including the ones that are based on the convolutional neural networks. During the experiments, it was additionally established that the increasing of context-background information gives slight tracking quality improvement compared to the basic method implementation, even when only FHOG features are used.
Protection Motivation Theory Factors that Influence Undergraduates to Adopt Smartphone Security Measures

Because smartphones are ubiquitous in our society, and undergraduate students use smartphones extensively, it is necessary to understand how undergraduates can be protected from malicious hacker attacks, viruses, and malware. This quantitative study explores the influence of Protection Motivation Theory (PMT) constructs on security behaviors of undergraduate students. The primary focus of this quantitative study is to answer our primary research question: to what extent do the independent PMT variables (perceived threat severity, perceived threat vulnerability, self-efficacy, response efficacy, and response cost) explain undergraduate students’ employment of smartphone security measures? The findings suggest that although all hypotheses were not supported by the analysis; however, self-efficacy and perceived threat vulnerability showed a statistically positive association with several smartphone security measures. However, none of the constructs showed a statistically significant association with using unsecured Wi-Fi in public places. The practical implications of the findings are for industry to focus on better design of smartphone hardware and software (such as antivirus apps) to protect users, and to increase self-efficacy among smartphone undergraduate users through training and education.
User Verification by Keystroke Dynamics

In the age of massive information transfer, security and privacy are primary concerns. The most commonly used security ensuring techniques are static passwords. The high vulnerability of these techniques have led to the development of biometric techniques for user authentication. Keystroke dynamics is a part of behavioral biometrics which identifies and verifies a user based on his/her typing patterns. The authentication by keystroke dynamics does not requires additional hardware for authentication and cannot be imitated or copied easily. The aim of this paper is to demonstrate a user verification system by using keystroke dynamics.
Pemanfaatan Media Sosial Instagram Untuk Meningkatkan Keterampilan Menulis Deskripsi Mapel Bi Bagi Siswa Kelas VII SMP Muhammadiyah Pangkalan Bun

This study has two objectives, namely knowing the use of social media Instagram by students at Muhammadiyah Pangkalan Bun Middle School and knowing the improvement of writing skills of Muhammadiyah Pangkalan Bun Middle School students. This type of research uses classroom action research. This research method uses quantitative descriptive to analyze data with using numbers. The subjects in this study were students of class VIIA Muhammadiyah Pangkalan Bun Junior High School. The number of students there are 20 children, while the object in this study is the process (the implementation of the learning process of descriptive text with the help of social media Instagram in class VIIA SMP Muhammadiyah pangkalan Bun) and the results (in the form of scores obtained by students during the learning activities of writing text description skills with the help of media social Instagram). The results obtained are that all students, especially class VIIA SMP Muhammadiyah Pangkalan Bun know social media Instagram. Most students are active users of Instagram. Instagram media is not utilized properly or is not utilized for any of the media when they study. For the pre-action results in writing skills description of the average value of students 55.5. In the first cycle, the average value of 68 increased by 12.5. While in the second cycle the average value of 75.25 increased from the first cycle of 7.25.