Reviewerly/exHarmony huggingface dataset:
Design and Feasibility of EXE Learning Media on the Topic of Chemical Bonding

The transformation on the industrial era 4.0 has greatly influenced changes in the way students learn who are more dominantly use gadgets both online and offline. This research aims to develop an e-Learning XHTML Editor (EXE) learning media which is feasible to be used in chemistry learning on the topic of Chemical Bonding, and also to test the validity and practicality of the media. The study used a research and development (R & D) design by adapting Hannafin and Peck’s model. The steps are limited to the design of EXE learning media. The feasibility of the EXE learning media is tested in terms of validity and practicality. The instrument used are validation questionnaire and students’ response questionnaire. The data were obtained and analyzed by using descriptive percentage. The results of the feasibility test conducted by the material experts, media experts, and teachers obtained an average of 89% with very feasible category. Meanwhile, the practicality test was obtained from the results of students’ response questionnaire from SMAN 8 Samarinda and SMAN 3 Tenggarong, showing the practicality value is 87% with the category of very practice and easy to operate and useful. It means the EXE learning media is feasible and practice to be used as chemistry learning media on the topic of Chemistry Bonding.
Reduksi Noise Salt And Pepper Pada Citra Pankromatik Menggunakan Metode Contraharmonic Mean Filter

A panchromatic image is an image that uses the entire spectrum visible to the eye from red to purple. The capture power of a panchromatic image recording device is almost the same as the sensitivity of the human eye. Taking images or pictures when using a camera often experiences noise or noise in the image caused by a bad camera lens or camera position when taking images so that it can cause noise in the image. resulting from. Noise or noise in the image greatly affects the clarity of an image where the image results are less clear when seen by the eye, therefore noise in the image must be removed so that the image can be clearer and have much better quality. The contraharmonic mean filter method is a filtering technique that works by replacing the intensity of a pixel with the average pixel value of the neighboring pixels, with the contraharmonic noise method in the image can be reduced so that the image is clearer than before. The contraharmonic method is very well used to remove noise in the panchromatic image so that the noise in the panchromatic image can be reduced by using the contraharmonic method which has a good role in reducing salt and pepper noise
Application of the Naïve Bayes Algorithm in Predicting Acceptance of Family Hope Program Assistance (PKH)

PKH is one of the programs for providing conditional social assistance to Poor Families which are designated as recipient families, PKH benefits with the aim of relieving the economy of those who are less fortunate. However, in its implementation, especially in the community, this program has not run well and optimally due to the unevenness of the PKH program. This is of course very influential on the welfare of the community where the programs that should be received by the poor have not been well realized. The concept of data mining can be used to provide solutions to problems at hand, the Naive Bayes Method is a method which can predict an opportunity from previous experience. The variables used include; Disability, children under five, school children and the elderly, where this variable is a requirement of a family as PKH recipients with additional criteria classified as a poor family with variables of occupation, income and residence status. Then the variable data is processed in the R language to determine the prediction results on the eligibility of PKH recipient families. The results of this study can be used as benchmarks and help in the optimization of the PKH program, from the experiments conducted, the results obtained were two households with id Test24 and Test44 which had the status of a recipient that was predicted to be non-recipient, with an Accuracy of 96%, 100% Sensitivity, and Specivicity 92%.
The Effect of Job Satisfaction and Self-efficiency on Goal Orientation Depending on Personality Traits of Employees in Beauty Industry

Amid the 4th industrial revolution, the beauty industry creates creative trends and develops new technologies and sensibilities. In particular, the beauty service industry, which is highly dependent on human labor, requires professional skills and artistic creativity. The labor-intensive beauty services industry requires professional skills and artistic creativity, so personal competence and role are critical. It is necessary to nurture beauty professionals with professional knowledge, technology, and practical experience to strengthen human competitiveness. Therefore, the individual
THE EVALUATION OF ENGLISH TEACHING LEARNING PROCESS USING CIPP MODEL

This research purposed to evaluate the English teaching learning process at SMPN 1 Majenang using CIPP Model. A total of 20 English teachers and 50 students in the Academic Year of 2020/2021 participated in the study. The research is based on a questionnaire applied to teachers and students. The percentage of CIPP components’ items is used for analyzing the data. Results of the study indicated that from the teachers’ point of view, the process of English teaching and learning is in the highest percentage; 25% but the product is the lowest. It is only 22%. And from students’ point of view, the input is in the highest percentage; 22% but the context is the lowest. It is only 20%
An Empirical Study of Waste Heat Re-utilization in Thermal Power Plant Using Advanced Fuzzy –PID Technology

Many industrial heating operations create waste energy, particularly boiler exhaust gas, aiming to minimize global warming. The waste heat from the exhaust gas can be utilized to warm the entering gas. This is one of the most basic waste heat recovery technologies. As a result, the object of this study is how to recover heat waste from boiler exhaust gas using a shell and tube heat exchanger and improve the boiler's efficiency. Methods for recovering the heat from flue gases from boilers included water warmed and air preheated. The goal of this article is to improve the performance of control circuits used in heat exchangers to get the optimum solution; the Fuzzy ID controller will replace the PID with the Fuzzy controller. This article examines traditional intelligent controllers with the goal of controlling the yield fluid temperature of a shell. Experimental plant data is used to do mathematical of the process to satisfy the control target. A traditional PID control may be utilized to regulate output fluid. By fine-tuning the practical problem, you may get improved settling time, rising time, and overshoot. Engineers have significant problems in improving timing parameters to maintain optimal control over the operation. In this search work, suitable intelligent through the proper controller is proposed for improving the operational beehive. It proves that overshoot is good in PID, settling time, and overshoot both in fuzzy controller &further improvement can be obtained through a neuro-fuzzy genetic controller.Power generating is becoming a more complex undertaking throughout the world. A power station is a multivariable controlled facility, independent of cutting-edge technology and techniques for unit performance, operation, flexibility, and availability; economic optimization and software that position state-of-the-art approaches are among the demands imposed on Control & Instrumentation engineers. As a result, fuzzy methods are being investigated to achieve resilience, tractability, and cheap cost by using tolerance for imprecision, ambiguity, and partial truth. Traditionally, control is focused on modeling the plant to be managed. The controller's performance may be unacceptably poor if the model is inaccurate.Furthermore, to create control actions, these traditional controllers rely on comprehensive data collection, including sensory information and parameter values. Program instructions and data are often integrated into the controller's memory. If the model parameters and other required data are not entirely known, such as a result of sensing issues, then appropriate estimates have to be made.Furthermore, if the supplied data is ambiguous, qualitative, or imprecise, these crisp controllers based on limited data are unlikely to produce satisfying results.
Learning Task Sampling Policy for Multitask Learning

It has been shown that training multi-task models with auxiliary tasks can improve the target task quality through cross-task transfer. However, the importance of each auxiliary task to the primary task is likely not known a priori. While the importance weights of auxiliary tasks can be manually tuned, it becomes practically infeasible with the number of tasks scaling up. To address this, we propose a search method that automatically assigns importance weights. We formulate it as a reinforcement learning problem and learn a task sampling schedule based on the evaluation accuracy of the multi-task model. Our empirical evaluation on XNLI and GLUE shows that our method outperforms uniform sampling and the corresponding single-task baseline.
ВЛИЯНИЕ ДИДАКТИЧЕСКИХ МАТЕРИАЛОВ НА ПОЗНАВАТЕЛЬНУЮ СПОСОБНОСТЬ УЧЕНИКОВ

The article presents research materials on the use of didactic materials in enhancing students' cognitive abilities and the role of didactic games in aesthetic education in biology lessons. Also reviewed the scientific and pedagogical foundations of the use of types and directions of didactic materials and their playing forms during the lesson. Didactic materials are intended for independent work of students who help to visually study the subject of study. With the proper formulation of the work of the teacher, students are much easier to memorize the lessons. Educational materials mainly include visual natural materials – pictures, tables, various schemes, diagrams, models, models, models. The use of didactic material helps to enhance the cognitive ability of students and save study time. Currently, technical means are often used – a microscope, an interactive whiteboard, projectors and presentation slides, transparencies, disks. In the experiment, of all 84 students, 44.0 % retained interest in the classes, while 16.7 % of the students had no interest. Also, 39.3 % of students in this survey were neutral.
Development of an Android-Based Dictionary of Electronic Components at the University of Muhammadiyah Sidoarjo

This study aims to determine the process of developing an android-based electronic component dictionary in the electronics course of the Information Technology Education Study Program, Muhammadiyah University of Sidoarjo. This research is a research and development (R&D) development research with a 4-D development model (Define, Design, Development and Disseminate). Development research was carried out on students of the Information Technology Education Study Program at the Muhammadiyah University of Sidoarjo. The data collection instruments were observation and questionnaires. The appropriateness of this study aid was assessed by media experts, material experts and students. The data analysis in this study used the Likert scale. Based on the results of the analysis, the percentage of 95% was obtained with the very feasible category by the media expert, 89% with the very feasible category by the material expert and the students obtained an average validity of 83.43% with the feasible category. So it can be concluded that the development of an android-based electronic component dictionary is very suitable for use both outside and in learning electronics courses.
АНАЛІЗ МЕТОДІВ ЗАХИСТУ ДАНИХ В МЕРЕЖІ INTERNET OF THINGS

With the constant increase in the number of smart devices, the vulnerability of data also increases. There are a number of vulnerabilities between them on the Internet of Things that can be exploited by attackers. The paper considers various methods of solving these weaknesses. An effective IoT connection with Blockchain is presented. As a result, a complete or partial solution to the existing problems of the Internet of Things.
Classification of prefeature extracted images with deep convolutional neural network in facial emotion recognition of vehicle driver

Chapter Contents: Abstract 10.1 Introduction and related work 10.2 Proposed models 10.2.1 Datasets 10.2.2 Preprocessing 10.2.3 Prefeature extraction 10.2.3.1 Gaussian Canny filter 10.2.3.2 Bit plan slicing method 10.2.3.3 Gabor filter as a feature extractor 10.2.4 Convolutional neural networks 10.2.5 Model design 10.2.6 Metrics 10.2.6.1 Accuracy 10.2.6.2 Cross-entropy loss 10.2.7 System configuration 10.3 Experiments and results 10.4 Vehicle driver emotion recognition experimental setup, results, and discussion 10.5 Conclusion Acknowledgments References
Evaluation of Content Analysis of Central and State University Library Websites in Bihar

A University library website is a set of Web Pages, Images, Videos, Digital Contents, E-Content, YouTube, Twitter, Instagram, Facebook, Telegram and other many Apps which are addressed to a Universal of its web addresses i.e. Universal Resource Locator. It provides a wide range of resources and services which are useful to visitors on University library websites. Websites are the popular way to interact with users without physical appearance and are performing an important role in accumulating and disseminating information to the users in the field of Higher Education System. Library is being the social institution and also need to be presence over the websites and show their resources and services as well as interaction with users also. This research paper analyses the content of Library related information provides on websites of Central and State Universities of Bihar from different dimensions to fulfill and satisfy the information needs of users.
Perancangan Aplikasi Istilah Olahraga Berbasis Mobile dengan Penerapan Algoritma Apostolico-Giancarlo

In this era of globalization, it is very necessary to have an information system that is fast and ready to use due to increasingly sophisticated human civilization and humans themselves are required to be able to adapt to these developments. Especially in the development of sports in information technology. The application design process carried out is still difficult to find the meaning of certain sports terms in sports. In order to overcome this problem, the author applies the apostolico-giancarlo algorithm to the application of mobile-based sports terms that can facilitate the information search process, compared to those who still have to search for books which require a relatively long time in searching for the meaning of sport. With the program design that has been made by the author for the general public, especially sportsmen, it is hoped that it can help in the process of finding information. The program in the form of Eclipse Juno consists of several searching, biodata, and closing
A Corpus Based Method for Evaluating the Teaching Effect of Electronic Engineering English

The existing evaluation methods have the problem of imperfect teaching effect evaluation model, which leads to the low reliability of the evaluation index. This paper designs a corpus based quantitative analysis method for teaching effect evaluation of Electronic Engineering English. Based on the mathematical principle of radial basis function, this paper uses corpus to analyze the distribution characteristics of Electronic Engineering English courses quantitatively, and uses association rules algorithm to build an English teaching effect evaluation model to comprehensively judge the importance of each factor. Experimental results: the average reliability of the two existing evaluation methods is 1.0751 and 0.5455 respectively, and the average reliability of the evaluation method is 0.7983, which shows that the reliability of the evaluation method is closer to the standard value of 0.8, which proves that the evaluation method of Electronic Engineering English teaching effect integrated with quantitative analysis of corpus has better practical application performance good.
Photonics for Neuromorphic Computing and Artificial Intelligence

Neuromorphic photonics exploit optical device physics for neuron models, and optical interconnects for distributed, parallel, and analog processing for high-bandwidth, low-latency and low switching energy applications in artificial intelligence and neuromorphic computing.
A 2-FACTOR SECURE AUTHORIZED DEDUPLICATION USING HARD LOGARITHM CRYPTOGRAPHY IN CLOUDS

Here in this paper a new and efficient technique for the Data Deduplication over Hybrid Cloud is proposed using 2-Factor Authentication between Data Owner and Trusted Third Party. Here for 2-Factor Authentication Token Based Authentication is used and Hard Logarithmic Cryptography such as Elliptic Curves are used for the Encryption of Data. The planned tactic implemented here is an efficient technique in comparison to the existing approach implemented for Data Deduplication. The Experimental analysis shows the performance of the planned method.
De-anthropocentrising healthcare design

In design research and design practice we can see new ideas emerging around deanthropocentrising design in order to rebalance our place and sustainability within the global ecosystem. Ideas including Posthumanism, Actor Network Theory, Object Orientated Ontology, Xenodesign, and Multi Species Design begin to show new perspectives for how we design and where we place humans in value chains. Current healthcare design models put the human at the top of the pyramid with effects on the wider downstream ecosystem through negative outputs like medical waste being one of the consequences. Here we ask how this challenges the future of design in healthcare and begin to explore the new types of methods and thinking that we may need to adopt in order to realise the potential of this new approach. Our conclusions raise a number of key questions for meta level healthcare design approaches, ethics, value chains and gaps in new methods and practices that need to be considered for adoption.
Unveiling the Truth in Liquid Democracy with Misinformed Voters

This paper investigates the so-called ODP-problem that has been formulated by Caragiannis and Micha []. This problem considers a setting with two election alternatives out of which one is assumed to be correct. In ODP, the goal is to organise the delegations in a social network in order to maximize the probability that the correct alternative is elected. While the problem is known to be computationally hard, we strengthen existing hardness results and show that the approximation hardness of ODP highly depends on the connectivity of the social network and the individual accuracies. Interestingly, under some assumptions, on either the accuracies of voters or the connectivity of the network, we obtain a polynomial-time 1/2-approximation algorithm. Lastly, we run extensive simulations and observe that simple algorithms relying on the abilities of liquid democracy outperform direct democracy on a large class of instances.
Application Of Clustering Using The K-Means Method In Indonesian Provinces Based On Infrastructure Data In 2020

National development cannot be separated from infrastructure development. Infrastructure development that continues to be carried out by the government is expected to have a positive impact on Indonesia's economic growth. In Indonesia, infrastructure development can be said to be uneven in various provinces. This study aims to group provinces in Indonesia into several clusters based on infrastructure data in 2020. This research was conducted using K-Means Clustering method. The examination was conducted and it was obtained that the data is representative and there is no multicollinearity. Obtained results i.e. provinces in Indonesia can be grouped into 3 clusters. Cluster 1 belongs to the low category consisting of 22 provinces, cluster 2 belongs to the medium category consisting of 9 provinces, and cluster 3 belongs to the high category consisting of 3 provinces.
Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity.

Quality-Diversity (QD) is a concept from Neuroevolution with some intriguing applications to Reinforcement Learning. It facilitates learning a population of agents where each member is optimized to simultaneously accumulate high task-returns and exhibit behavioral diversity compared to other members. In this paper, we build on a recent kernel-based method for training a QD policy ensemble with Stein variational gradient descent. With kernels based on $f$-divergence between the stationary distributions of policies, we convert the problem to that of efficient estimation of the ratio of these stationary distributions. We then study various distribution ratio estimators used previously for off-policy evaluation and imitation and re-purpose them to compute the gradients for policies in an ensemble such that the resultant population is diverse and of high-quality.
The Impact of Virtual Reality Nature Environments on Calmness, Arousal and Energy: a Multi-Method Study

Virtual Reality is the current media's epitome of Immersiveness, Presence and Suspension of Disbelief.Both research and gaming industry communities have been building on this in order to exhaustively research and explore feelings of high-adrenaline, scariness, panic and other visceral and instinctive feelings.We take the opposite approach and try to prove that Virtual Reality can also be used to induce feelings of relaxation and soothingness effectively and strongly.Therefore, it could be used to improve the mental health of people who cannot be exposed to situations that induce said feelings.In our experiments, we found that Virtual Reality can be used to induce a strong sense of Calmness and to reduce the sense of Arousal and Energy, with a high degree of significance, having an effect with short-duration exposures.We also found hints that Virtual Reality may have an effect in the circadian cycle's regulation by exposing the subjects to a virtual sunset.
A Question of Trust: Facebook Libra as Money in the Economic and Legal Sense

This article examines the use of Facebook’s Libra as a substitute for fiat money. It considers Libra’s prospects for success in light of the fact that it purports to substitute trust in a technology for the traditional legal supports that bolster public trust in traditional fiat currencies. The legal doctrines that support fiat currencies do so for the purposes of recognizing the economic functions that money performs and are also meant to support public policies that promote monetary stability, protect consumers and help to enforce anti money laundering statutes. It is argued that Libra will result in unintended challenges for monetary authorities that will subject the world financial system to greater consumer transaction risks, increase systemic risks, and make it more difficult to combat money laundering efforts. The ultimate question is whether the public can place its trust in Facebook and its partners to manage a global currency, or is that trust better placed in the hands of central banks?