Reviewerly/exHarmony huggingface dataset:
Machine Learning on Cloud with Blockchain: A Secure, Verifiable and Fair Approach to Outsource the Linear Regression.

Linear Regression (LR) is a classical machine learning algorithm which has many applications in the cyber physical social systems (CPSS) to shape and simplify the way we live, work and communicate. This paper focuses on the data analysis for CPSS when the Linear Regression is applied. The training process of LR is time-consuming since it involves complex matrix operations, especially when it gets a large scale training dataset In the CPSS. Thus, how to enable devices to efficiently perform the training process of the Linear Regression is of significant importance. To address this issue, in this paper, we present a secure, verifiable and fair approach to outsource LR to an untrustworthy cloud-server. In the proposed scheme, computation inputs/outputs are obscured so that the privacy of sensitive information is protected against cloud-server. Meanwhile, computation result from cloud-server is verifiable. Also, fairness is guaranteed by the blockchain, which ensures that the cloud gets paid only if he correctly performed the outsourced workload. Based on the presented approach, we exploited the fair, secure outsourcing system on the Ethereum blockchain. We analysed our presented scheme on theoretical and experimental, all of which indicate that the presented scheme is valid, secure and efficient.
FPGA Based on airflow Noise Cancelling of mechanical ventilation

The traditional de-noising method used by classical hardware equipments can’t achieve successful de-noising effect and the software-only method never meets a high real time capability. Based on the Undecimated Wavelet Transform (UWT) which is an effective technique for de-noising signals corrupted by non-stationary noises, we propose implementing the UWT method on the field programmable gate array (FPGA) to realize a digital electronic circuit to de-noise the airflow of mechanical ventilation. The experiment results obtained was done regarding signal to noise ratio (SNR) and the requirement of real-time signal processing.
Correction to: Advanced Methods for Processing and Visualizing the Renewable Energy

The original version of the book was inadvertently published with incorrect affiliation (city name) of the editors in the frontmatter, which has now been corrected from “Seri Iskandar, Selangor, Malaysia” to “Seri Iskandar, Perak, Malaysia”. The erratum book has been updated with the changes.
Android Based Application Using Google Maps API for Tourism Travel Guide

This research aims to design, build, and implement an application that able to increase knowledge and interest of society to tourism of Jakarta by providing various information about tourist location in DKI Jakarta as well as giving guide of travel route to tourist location, as guide in doing tourism activity to location – location of tourism in DKI Jakarta. This application development method uses waterfall system development methodology that has 5 phases of communication, planning, modeling, construction, and deployment. This application is built using Android Studio IDE, Java programming language, SQLite as database, and utilize Google Maps API to display the map. With this application, people who want to find information about Jakarta tourism can obtain various tourist information and guide the route to tourist locations in Jakarta more quickly and easily.
Cross-Domain Using Composing of Selected DCT Coefficients Strategy with Quantization Tables for Reversible Data Hiding in JPEG Image

Reversible data hiding (RDH) techniques for JPEG images have big challenges in order to improve the capacity, quality, and flexible embedding method. In this paper, we propose a new RDH algorithm using combination of selected DCT coefficients strategy with quantization tables. In order to further reduce the distortion, we survey the effect of quantized process on DCT coefficients for making the strategy of selection the embedding DCT coefficients. Compared to the conventional method, our experimental results show that our proposed method has better performance in terms of both the increasing capacity and improving the quality of embedded JPEG images after data embedding.
Closing the Planning-Learning Loop with Application to Autonomous Driving in a Crowd.

Imagine an autonomous robot vehicle driving in dense, possibly unregulated urban traffic. To contend with an uncertain, interactive environment with heterogeneous traffic of cars, motorcycles, buses, ..., the robot vehicle has to plan in both short and long terms in order to drive effectively and approach human-level performance. Planning explicitly over a long time horizon, however, incurs prohibitive computational cost and is impractical under real-time constraints. To achieve real-time performance for large-scale planning, this work introduces Learning from Tree Search for Driving (LeTS-Drive), which integrates planning and learning in a closed loop. LeTS-Drive learns a driving policy from a planner, which is based on sparsely sampled tree search. The learned policy in turn guides online planning for real-time vehicle control. These two steps are repeated to form a closed loop so that the planner and the learner inform each other and improve in synchrony. The entire system can learn on its own in a self-supervised manner, without human effort on explicit data labeling. We applied LeTSDrive to autonomous driving in crowded urban environments in simulation. Experimental results show clearly that LeTS-Drive outperforms either planning or learning alone, as well as open-loop integration of planning and learning.
Exploring the relationship between social media usage and academic performances

Social media and academic grades are two of the most important things in an average student’s life. Several factors play an important role in determining whether he achieves first class, second class, third class, or distinction. This study aims to find out the extent to which Social Media impacts the student’s academic results. Using Pearson’s Correlation test, the study determined that there was a negative impact of social media usage on academic performance. Furthermore, Pearson’s Correlation test also showed us that the distraction caused by social media impact their academic performance. There is a high need to include various beneficial aspects of social media in a classroom’s teachings. Instead of outright condemning social media usage by students, education systems and academics should try and make it a part of the educational curriculum. The longer the academicians try and stick to the age-old teaching method from a constraint boundary of class and books, the more we unequip students from the necessary skillsets required to bring a change and lead.
Discussing the Risks of Adaptive Virtual Environments for User Autonomy

Adaptive virtual environments are an opportunity to support users and increase their flow, presence, immersion, and overall experience. Possible fields of application are adaptive individual education, gameplay adjustment, professional work, and personalized content. But who benefits more from this adaptivity, the users who can enjoy a greater user experience or the companies or governments who are completely in control of the provided content. While the user autonomy decreases for individuals, the power of institutions raises, and the risk exists that personal opinions are precisely controlled. In this position paper, we will argue that researchers should not only propose the benefits of their work but also critically discuss what are possible abusive use cases. Therefore, we will examine two use cases in the fields of professional work and personalized content and show possible abusive use.
Pengembangan Media Pembelajaran Berbasis Website Tema 6 Subtema 1 Kelas IV

Abstract: This research aims to find out the feasibility, practicality, and effectiveness of the development of website-based learning media theme 6 subtheme 1 grade IV. The research method used by researchers is development research and using ADDIE (Analysis, Development, Design, Implementation, and Evaluate) models. The test subjects were 20 grade IV students at SDN 1 Argosuko. Instruments used for data collection are questionnaires and documentation. The questionnaire consists of a questionnaire of material experts, media experts, language experts, practitioners (teachers) and student response questionnaires. technical data analysis using quantitative and qualitative descriptive. The results of the study were obtained from the feasibility test on average a percentage of 80% of the lecturers of materials experts, 91% of the lecturers of media experts, and 82.6% of the lecturers of language experts. Practicality tests obtained 91.2% from teachers and 91.7% from students. The Effectiveness Test obtained an average score of 81. Based on the results of the data, website-based media is said to be feasible for elementary school level. Researchers hope the study can add new experiences to learning and can be used as a reference for other similar studies.
Blockchain Technology for Tracking Chain Supply

The adequate technology was the architecture that was distributed through the block chain technology which had authorizations for securing data storage and for accessing any piece of information anytime and anywhere. The objective of this study was to find out whether the issues of the supply chains and the block chain were able to be solved. The hypothesis of this study was suitable for the supply chain management in the block chain architectures. In this study, a survey was conducted to validate the issues of supply chain management and to obtain the requirement for a supply chain software system. Keywords: Supply Chain, Supply Chain Management, Blockchain, Distributed Architecture, Security, Traceability, Information Integration, Interoperability
The Influence of Outdoor Learning Method Towards Learning Outcomes and Interests

This study aims to analyze using outdoor learning methods on learning outcomes and interest in learning physics. This study uses a quasi-experimental method. This study involved 60 students from two classes, namely class XA and XB. The instruments used in this study were the pretest-posttest questions and the interest in learning questionnaire. Data analysis techniques used independent sample t-test, N-gain, and multivariate analysis of variance (MANOVA). The analysis results show that the treatment has a significant effect on learning outcomes and can improve learning outcomes compared to conventional learning. The outdoor learning method makes students more interested in learning physics. The conclusion that can be drawn is the outdoor learning method has a significant effect on learning outcomes and interest in learning physics in high school.
Multi-Image Steganography Using Deep Neural Networks

Steganography is the science of hiding a secret message within an ordinary public message. Over the years, steganography has been used to encode a lower resolution image into a higher resolution image by simple methods like LSB manipulation. We aim to utilize deep neural networks for the encoding and decoding of multiple secret images inside a single cover image of the same resolution.
The Development of Pocketbook Learning Media based on Mind Mapping in Introductory Economics Course

Economic learning at the tertiary level, especially in the introductory economics course at the Faculty of Economics, is still limited to textbooks or foreign translations.They are structurally difficult for students to understand because they use case studies that do not follow local reality conditions in Indonesia, especially those which are related to data and economic phenomena.Therefore, we need a book that is interesting, innovative, concise, and easy to learn.This study focused on developing a handbook as learning media based on mind mapping on the introductory economics course and assessing the feasibility of the mind mapping-based learning media book for use in an introductory course to economics, primarily on necessary economic concept study contents.This research used Research and Development (R & D) model in developing a mind mapping-based economics pocketbook as learning media.The development of a mind mapping-based pocketbook will make students easier to study in the introductory economics course because the small pocketbook will make students easy to study anywhere and anytime.The development of the pocketbook product consisted of five stages: analysis, design, development, implementation, and evaluation.Based on the validation conducted by the content experts and media experts on content and linguistic feasibility, the mind mapping-based pocketbook on the introductory economics course at the Faculty of Economics at Universitas Negeri Makassar was in a very feasible category.The product trial results showed that mind mapping based pocketbook was very viable in terms of content, linguistic, presentation, and graphic so that the pocketbook that has been tested was ready to be published.
Digital Ethics: Rhetoric and Responsibility in Online Aggression

Digital research is not only methodologically complex, but it also exposes researchers to numerous risks, demands emotional labor, and presents complicated and unpredictable ethical quandaries, all...
An Experimental Evaluation of Transformer-based Language Models in the Biomedical Domain

With the growing amount of text in health data, there have been rapid advances in large pre-trained models that can be applied to a wide variety of biomedical tasks with minimal task-specific modifications. Emphasizing the cost of these models, which renders technical replication challenging, this paper summarizes experiments conducted in replicating BioBERT and further pre-training and careful fine-tuning in the biomedical domain. We also investigate the effectiveness of domain-specific and domain-agnostic pre-trained models across downstream biomedical NLP tasks. Our finding confirms that pre-trained models can be impactful in some downstream NLP tasks (QA and NER) in the biomedical domain; however, this improvement may not justify the high cost of domain-specific pre-training.
Cookpad Parsed Corpus: Linguistic Annotations of Japanese Recipes

It has become increasingly common for people to share cooking recipes on the Internet. Along with the increase in the number of shared recipes, there have been corresponding increases in recipe-related studies and datasets. However, there are still few datasets that provide linguistic annotations for the recipe-related studies even though such annotations should form the basis of the studies. This paper introduces a novel recipe-related dataset, named Cookpad Parsed Corpus, which contains linguistic annotations for Japanese recipes. We randomly extracted 500 recipes from the largest recipe-related dataset, the Cookpad Recipe Dataset, and annotated 4; 738 sentences in the recipes with morphemes, named entities, and dependency relations. This paper also reports benchmark results on our corpus for Japanese morphological analysis, named entity recognition, and dependency parsing. We show that there is still room for improvement in the analyses of recipes.
Digital Educational Environment as a Tool of Complex Changes of the Teacher's Pedagogical Activity

The authors of the article identified four basic functions of the use of information technology in the course of training future representatives of a profession: information and training, forming, evaluation and correction, research.n It is noted that these functions do not operate separately, but as elements of a single system, depending on the conditions determined by the features of the information EE. The analysis allows the authors of the article to assert that at this stage of the educational process evolution the main task is to create a methodology related to the use of information management technologies in the development of electronic materials of educational nature and their implementation in the context of pedagogical activity.
Childcare teachers awareness and demands on STEAM education: focused on STEAM education related teachers

본 연구는 STEAM 관련 교육을 받은 경험이 있는 유아교사 198명을 대상으로 유아 STEAM 교육에 대한 인식 및 교사교육 내용에 대한 요구도를 살펴보고, 이를 통해 유아 STEAM 교육의 현장 적용성을 높이기 위한 방안을 모색하고자 하였다. 그 결과 STEAM 교육에 대한 이해와 필요성에 대한 인식은 전체적으로 높게 나타났으나, ‘통합과 융합에 대한 이해도’가 다소 낮게 나타났다. 유아 STEAM 교육의 내용 요구도에서는 교사대 아동비율, 또래관계증진, 창의성, 과학에 대한 성취, 실생활관련 내용에 대한 부분이 보다 높게 나타났으며, 현장 적용성을 위한 환경 요구도에서는 프로그램 개발 및 지도안, 원장, 교사의 의지와 신념, 학부모의 인식, 지속적인 교사교육이 필요함을 나타냈다. 이러한 결과는 유아 STEAM 교육을 실행하는데 물리적 환경개선을 위한 유아교육학계의 노력과 정책적 지원방안이 모색되어야 함을 시사한다.The purpose of this study is to find out the need for awareness of infant STEAM education and the contents of teacher education, and to seek ways to enhance the on-site applicability of infant STEAM education. 198 infant teachers with experience in STEAM-related education took part in this research. The result of the study showed that STEAM education and the awareness of the need were high overall, but the level of understanding of integration and convergence was somewhat low. In the section of the demands of STEAM education for infants, the teachers replied that teacher-infant ratio, the promotion of peer relationship, creativity, achievement in science, and real life-related content were relatively insufficient. And in the section of the environmental demands for field applicability, the teachers replied that the program development and guidance, the attitude and belief of directors and teachers, awareness of parents, and continuing teacher education were needed. These results suggest that the efforts of the pedagogic circle to improve the physical environment and the educational policy level support should be sought to implement the infant STEAM education.
Research Guides: Information Literacy Toolkit: Information Literacy Toolkit

Resources to help with planning or implementing information literacy concepts and assignments in classes.
Implementasi Fuzzy Dalam Menentukan Dampak Belajar Online Pada Masa Pandemi Covid-19

The purpose of this study was to identify the impact of online learning during the Covid-19 pandemic. As we know that the epidemic caused by a virus called corona has an impact on all aspects of people's lives, especially education. Teaching and learning activities that are usually done directly must also be stopped and replaced with online learning at home. In determining the impact of online learning the need for a support system, where the support system used is the Fuzzy Tsukamoto method with 4 variables namely tasks, costs, networks and the impact of online learning during the Covid-19 pandemic. For the calculation of data will go through stages of fuzzification, inference, and defuzzification. Identification is done by entering existing parameters so that conclusions can be obtained how big the impact of online learning during the Covid-19 pandemic. Keywords : Fuzzy Tsukamoto, Dampak Belajar Online, Pandemi Covid-19
Clear Sky Irradiance Year-to-Year Variations and Trends

Solar radiation data for seven SURFRAD stations for the period 1996-2018 show an increase in irradiance under clear skies over the period, but the increase was not constant and shorter periods may have even experienced decreases in irradiance. A popular implementation of a clear sky model provided modeled irradiances for comparison with the SURFRAD data under conditions screened for clear skies. The use of the clear sky model, which did not consider year-to-year variances in atmospheric turbidity, was found problematic for resolving small changes in irradiance important for determining PV system degradation over three or five years, but less problematic for a period of ten years.
Cloud Computing: A Boon for Education System

Traditional lecturing and tutoring based teaching learning method which is commonly used in universities will not fulfill need of students in the 21st century. Universities and Colleges from around the world have understand needs to acclimate novel teaching learning methods to meet student’s various needs. Cloud computing can be used to enhance the teaching quality of educational organizations by utilizing IT services at very low cost and power. Cloud computing could let students on other continents in fact use those facilities and collect their own data. Higher education stands to gather significant advantages from cloud computing by creating settings that opens understudies to the “tools of the trade” in a varied choice of disciplines. The access to specific resources via cloud computing, can allow institutions or organizations to extend the possibility of their educational plans. The emerging networked information economy creates distinct opportunities for universities and colleges to justify their extremely distributed IT resources and to induce bigger, their institutional footprint. In this paper we represent a cloud-based architecture that can be used to enrich teaching methodology to meet current student’s requirements and also discuss some challenges that should be known to educational institutes for acclimating cloud computing into the teaching-learning environment.
Fuzzy Based Adaptive Deblocking Filters at Low-Bitrate HEVC Videos for Communication Networks

In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding (HEVC) frames and improves its subjective visual quality in multimedia services over communication networks.However, on faster processing of the complex videos at a low bitrate, some visible artifacts considerably degrade the picture quality.In this paper, we proposed a four-step fuzzy based adaptive deblocking filter selection technique.The proposed method removes the quantization noise, blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate.We have considered Y (luma), U (chromablue), and V (chroma-red) components parallelly.Finally, we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants, namely up 45 • , down 45 • , up 135 • , and down 135 • across horizontal and vertical block boundaries.In this context, experimentation is done on a wide variety of videos.An objective and subjective analysis is carried out with MATLAB software and Human Visual System (HVS).The proposed method substantially outperforms existing postprocessing deblocking techniques in terms of YPSNR and BD_rate.In the proposed method, we achieved 0.32-0.97dB values of YPSNR.Our method achieved a BD_rate of +1.69% for the luma component, -0.18% (U) and -1.99% (V) for chroma components, respectively, with respect to the stateof-the-art methods.The proposed method proves to have low computational complexity and has better parallel processing, hence suitable for a real-time system in the near future.
Some fast algorithms multiplying a matrix by its adjoint

We present a non-commutative algorithm for the multiplication of a 2 × 2 block-matrix by its adjoint, defined by a matrix ring anti-homomorphism. This algorithm uses 5 block products (3 recursive calls and 2 general products). It works unconditionally in positive characteristic, or over the complex field with transposition, but for instance not over the complex field with conjugate-transpose. The resulting algorithm for arbitrary dimensions is a reduction of multiplication of a matrix by its adjoint to general matrix product, improving by a constant factor previously known reductions. We prove also that there is no algorithm derived from bilinear forms using only four products and the adjoint of one of them. Second we give novel dedicated algorithms for the complex field and the quaternions to compute the multiplication alternatively, taking advantage of the structure of the involved matrix-polynomial arithmetic. We then analyze the respective ranges of predominance of the two strategies. Finally we propose schedules with low memory footprint that support a fast and memory efficient practical implementation over a prime field.