Reviewerly/exHarmony huggingface dataset:
STEAM-deaf learning model assisted by rube goldberg machine for deaf student in junior special needs school

Abstract The 2013 curriculum has been applied in Special Needs School. STEAM can be taught in deaf classrooms using hands-on project for giving students experience working in cooperative team. This paper provides the research of STEAM-Deaf model learning and utilization of Rube Goldberg Machine (RGM). It is aimed to determines characteristic, effectiveness and practical of this model. The method uses Research and Development with single participant design. This research was conducted at SLB Ungaran. The result of research shows that the characteristic STEAM-Deaf consist of syntax with six phases namely observation, research, planning, application, analyze, and evaluation. The support system was STEAM lesson plans, RGM, and worksheet. The reaction system was teachers playing a role as a guide, facilitator, and motivator. The instructional effect showed that the enhanced student’ understanding in cognitive aspect and growing students’ science creativity skill. The nurturant effect showed that students dare to do experiment, independent, and build good team work. The effectiveness of models’ to be analyze with effect size (d). The mean of deaf students’ understanding in cognitive ≥ 0.2 with high criteria. The percentage of science creativity skill, with very good and good criteria. The practical results obtained a percentage average based on deaf student and teacher with practical criteria. Based on the result of this study, it can be concluded that STEAM-Deaf model learning with utilization of RGM is practical and effective for enhancing deaf student’s cognitive aspect and for growing their science creativity skill.
Design of the Study

This chapter discusses issues concerning the design and implementation of the research project dealing with the changes in the levels of willingness to communicate, motivation, boredom and language anxiety, their relationships and factors influencing them in the course of the participants’ visits to the virtual world Second Life.
Feed the Beast: Getting Data into R

Before R can be truly useful to you, you’ll probably have to get more data inside of it than just basic arithmetic problems or greetings to the world. This can be tricky in some cases, and daunting in others. R has tremendous support for a wide variety of data types and sources, and we’ll cover the most common types and use cases in this chapter. My goal here is to
A New Approach to Supervised Data Analysis in Embedded Systems Environments: A Case Study

Nowadays, the implementation of embedded systems with sensors for massive data collection has become widely used for their flexibility and improvement in decision making. However, this process can be affected by errors in reading, attrition of systems, among others. For this, a selection approach of supervised algorithms with a prototypes selection criterion is presented, which allows an adequate embedded system performance. To do that a quality measure was established which compromises between the data reduction of the training set, algorithm processing time and the classification performance. As a result, it was determined that the algorithm for the data selection is Condensed Nearest Neighbors (CNN) and the classification algorithm is k-Nearest Neighbour (k-NN).
Neuroimage acquisition and analysis

Neuroimaging has facilitated major advances in understanding the human brain, and provides invaluable guidance for diagnosis and therapy of disease. This chapter provides a broad overview of human in-vivo neuroimaging techniques, and introduces algorithms for neuroimage processing and analysis. Covered modalities include structural, functional, and diffusion MRI (dMRI), positron emission tomography (PET), and magnetoencephalography (MEG). We discuss state-of-the-art algorithms for image registration and segmentation, for statistical analysis, and for predictive modeling.
Toward unsupervised, multi-object discovery in large-scale image collections.

This paper addresses the problem of discovering the objects present in a collection of images without any supervision. We build on the optimization approach of Vo et al. (CVPR'19) with several key novelties: (1) We propose a novel saliency-based region proposal algorithm that achieves significantly higher overlap with ground-truth objects than other competitive methods. This procedure leverages off-the-shelf CNN features trained on classification tasks without any bounding box information, but is otherwise unsupervised. (2) We exploit the inherent hierarchical structure of proposals as an effective regularizer for the approach to object discovery of Vo et al., boosting its performance to significantly improve over the state of the art on several standard benchmarks. (3) We adopt a two-stage strategy to select promising proposals using small random sets of images before using the whole image collection to discover the objects it depicts, allowing us to tackle, for the first time (to the best of our knowledge), the discovery of multiple objects in each one of the pictures making up datasets with up to 20,000 images, an over five-fold increase compared to existing methods, and a first step toward true large-scale unsupervised image interpretation.
Decentralized Lightweight Detection of Eclipse Attacks on Bitcoin Clients

Clients of permissionless blockchain systems, like Bitcoin, rely on an underlying peer-to-peer network to send and receive transactions. It is critical that a client is connected to at least one honest peer, as otherwise the client can be convinced to accept a maliciously forked view of the blockchain. In such an eclipse attack, the client is unable to reliably distinguish the canonical view of the blockchain from the view provided by the attacker. The consequences of this can be catastrophic if the client makes business decisions based on a distorted view of the blockchain transactions. In this paper, we investigate the design space and propose two approaches for Bitcoin clients to detect whether an eclipse attack against them is ongoing. Each approach chooses a different trade-off between average attack detection time and network load. The first scheme is based on the detection of suspicious block timestamps. The second scheme allows blockchain clients to utilize their natural connections to the Internet (i.e., standard web activity) to gossip about their blockchain views with contacted servers and their other clients. Our proposals improve upon previously proposed eclipse attack countermeasures without introducing any dedicated infrastructure or changes to the Bitcoin protocol and network, and we discuss an implementation. We demonstrate the effectiveness of the gossip-based schemes through rigorous analysis using original Internet traffic traces and real-world deployment. The results indicate that our protocol incurs a negligible overhead and detects eclipse attacks rapidly with high probability, and is well-suited for practical deployment.
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening

We propose a novel algorithm for unsupervised graph representation learning with attributed graphs. It combines three advantages addressing some current limitations of the literature: i) The model is inductive: it can embed new graphs without re-training in the presence of new data; ii) The method takes into account both micro-structures and macro-structures by looking at the attributed graphs at different scales; iii) The model is end-to-end differentiable: it is a building block that can be plugged into deep learning pipelines and allows for back-propagation. We show that combining a coarsening method having strong theoretical guarantees with mutual information maximization suffices to produce high quality embeddings. We evaluate them on classification tasks with common benchmarks of the literature. We show that our algorithm is competitive with state of the art among unsupervised graph representation learning methods.
The hidden voices of the upright bass

This thesis will focus on the possibilities of the upright bass as a chord instrument in the genre of composed music. The author will in particular delve into the natural harmonic spectra of the upright bass, utilizing harmonics to create scales and chords in the hopes of discovering ways to seamlessly blend traditional pizzicato playing with harmonics, thus "unlocking" new ways of approaching the upright bass as an ensemble- or indeed a soloinstrument.
Social-Emotional and Ethical Learning of Younger Schoolchildren in the Formation of Civil and Historical Competence

The essence of the concepts “historical competence”, “civic competence”, “emotional literacy” is highlighted. It is substantiated that socio-emotional and ethical learning (SEE Learning) is based on three dimensions that correspond to the types of knowledge and competencies that SEE Learning seeks to transfer to students: awareness, empathy, involvement. Three levels of SEE Learning are characterized: personal, social, systemic. Four key learning trajectories have been identified and analyzed to facilitate the acquisition and internalization of knowledge and skills at each of the three levels of understanding at SEE Learning. It is established that educational trajectories are pedagogical components that broadly outline the ways of studying, critically evaluating and interna-lizing various topics and skills of socio-emotional and ethical learning.
Research on Rural Landscape Design Based on 3R Principle

Abstract In recent years, the pace of beautiful countryside construction in China has been accelerating, which has promoted the development of rural tourism industry and is of great significance to the economic development of vast rural areas. While paying attention to economic development, we should also realize the 3R principle, integrate more environmental protection concepts, and realize all-round development in rural areas. Based on the principle of 3R, this paper analyzed the rural landscape design, optimized the traditional design methods, selected more green recyclable materials, and improved the economic benefits of rural landscape design and environmental protection benefits, which provides power for the long-term development of rural areas.
Influencing Factors of the Negative Spillover Effect of Brand Scandal

This study examined causality using structural equation model for the psychological characteristics of crisis severity, ability and honesty factors on the effect of brand scandal spreading negatively.BR The structural equation was used to examine the direct effect of severity on the attitudes of the company and its competitors, and the effect of mediating ability and honesty using survey data(N=309).BR Studies have shown that the seriousness awareness of brand scandals has a directly significant negative impact not only on the attitude of the brand but also on the attitude of the rival brand,BR The discriminatory implications of the results of this study is that existing studies on the spread of brand scandals have identified that the severity factor of the scandal affects the attitudes of the company and its competitors only through parameters, while this study has found that the severity factor of the scandal can directly affect the attitudes of the company and its competitors without parameters.
THE ANALYSIS OF KNOWLEDGE MANAGEMENT PROCESS ON SOFTWARE DEVELOPMENT PROCESS: A SYSTEMATIC REVIEW

Software quality is affected by its development process. The software development process, in general, goes through several stages, including project management, system requirements analysis, architecture, and design, implementation and testing. On each of these stages it cannot be separated from the process of capturing, storing, transferring and sharing knowledge between the developer and the stakeholders. This systematic review aimed to analyze the knowledge management process in the software development process. In this systematic review we used the Preferred Reporting Item for Systematic Review and Meta-Analysis (PRISMA) guidelines. We reviewed twenty-two works of literature from several publisher sources and analyzed the knowledge management process in software development. The analysis revealed that the knowledge management process has an essential role in improving the quality of software developed. As a conclusion of this systematic review, knowledge management is one of the factors in determining software quality.
Detection and Enumeration of Parasitic Infections in Stool Samples from Tertiary Care Hospital of Rural Setting

Background: Parasitic infections are the major public concern particularly in developing countries like India. Routinely used microscopy method for the detection of parasitic infections have compromised sensitivity. Materials and Method: The study was carried out on 500 stool samples received in Department of Microbiology MMIMSR, Mullana (Haryana) for a period of 6 months (August 2017 to January 2018). Stool samples for detection of ova and cyst were included. Result: Of these 500 samples examined, 235 (47%) stool samples showed positive results for ova/cyst after the use of simple salt floatation technique while it was merely 33% (n-165) without using the salt floatation method. of the 235 positive samples 29.8% were cyst of Giardia lamblia followed by eggs of Ascarislumbricoides (Fertilized and unfertilized) and cyst of Entamoebahistolytica each of 19.1%, Ancylostomaduodenale 14.9%, Hymenolepis nana 10.6%, Entamoeba coli 4.2% and Trichuristrichiura 2.1% were also identified. Conclusion: There is a need for more tests that do not sacrifice sensitivity and that can be used in poor resource field settings.
A Brief Analysis of the Management Innovation Strategy of Undergraduate Students under the Humanistic Value

&lt;p&gt;Education is the ladder of human progress and the power for social development. With people gradually paying attention to the importance of humanistic education management mode and the humanistic education management mode on the agenda, humanistic education management mode of teachers and students not only provides a good teaching atmosphere, but also fosters talents on a solid foundation. This paper will briefly describe the management and innovation strategies for undergraduate students under the humanistic value.&lt;/p&gt;
Diverse and Styled Image Captioning Using SVD-Based Mixture of Recurrent Experts.

With great advances in vision and natural language processing, the generation of image captions becomes a need. In a recent paper, Mathews, Xie and He [1], extended a new model to generate styled captions by separating semantics and style. In continuation of this work, here a new captioning model is developed including an image encoder to extract the features, a mixture of recurrent networks to embed the set of extracted features to a set of words, and a sentence generator that combines the obtained words as a stylized sentence. The resulted system that entitled as Mixture of Recurrent Experts (MoRE), uses a new training algorithm that derives singular value decomposition (SVD) from weighting matrices of Recurrent Neural Networks (RNNs) to increase the diversity of captions. Each decomposition step depends on a distinctive factor based on the number of RNNs in MoRE. Since the used sentence generator gives a stylized language corpus without paired images, our captioning model can do the same. Besides, the styled and diverse captions are extracted without training on a densely labeled or styled dataset. To validate this captioning model, we use Microsoft COCO which is a standard factual image caption dataset. We show that the proposed captioning model can generate a diverse and stylized image captions without the necessity of extra-labeling. The results also show better descriptions in terms of content accuracy.
Research and Implementation of Real-Time Voice Control System based on Android

Abstract At present most of the mobile phone users must have to constantly change their mobile phone’s contextual model to adapt to different occasions in every busy life. In order to solve this problem. This paper designed and implemented the real time auto control system of mobile phone’ voice based on Android platform. The paper introduces the sound overall framework of real-time control system around three functional modules: the sound acquisition, getting sound’s loudness and adjusting ring and expounded key technology of the system in the implementation process. The result of experiment shows that the system can change ringtone loudness on the degree of noisy environment in real time and the system run reliably, meanwhile it has certain applicability and practical value.
CONCEPTUAL - HISTORICAL ASPECTS OF ORGANIC CHEMISTRY TEACHING (on the example of chemistry direction of Higher educational institutions)

The article reveals the historical approach on the teaching of organic chemistry in pedagogical universities. The development of modern trends and general competencies of students on the basis of historical approach, the creation of educational motivation, the focus on independent research and training of creative specialists are the most important directions. In this regard, it is important to improve the technology for organizing the educational process on the basis of historical principles in the system of training future chemistry teachers, to improve the mechanisms on the methodological support, to fulfill the system of competencies and cyclic diagnostics.
Aplikasi Pembelajaran Hukum Pidana Umum untuk Generasi Muda Berbasis Android

Law is a rule that is a norm made by aiming to regulate every human behavior for example keeping order, fairness, and preventing chaos. Today's young generation is very lack of science about the law, legal learning is a fairly elusive and boring lesson and also the science of law is considered low and many are violating or defying the law, younger generations nowadays smore often play smartphones than on reading books about the law that is so thick. So they are more interested in learning the law with Android based learning media. Game application also aims to fill free time or rest time. In addition to entertainment or pleasure games also serve as learning media and can hone skills, intelligence in overcoming a problem found in a game. Besides because this game combines the learning and playing side, this game can also be used to attract the attention of the younger generation to continue to learn about the law, especially in the case of theft game application created and designed with the aim that the generation of easily more pleased to learn law on the case of theft with learning media games.  The preparation of this research in making games with waterfall method (Reqriutment, Design, Implementation, Verification and Maintenance) and to analyze using Unified Modeling Language (UML) including Use Case Diagram, Activity Diagram, Sequence Diagram, Class Diagram. The learning games themselves will be developed based on Android or intended for mobile/Smartphone users. Method used in the creation of game applications using waterfall method. This game is played by one person in this game there are several Theory and quiz. Based on the test results of the general criminal law Learning games for Android based youth using CONSTRUCT2 software that this Game application can be inserted on smartphones with the minimum operating system Android. Keywords : android, hukum, pidana, game, kuis
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THE USE OF TEA PARTY LEARNING STRATEGY TO IMPROVE STUDENTS’ READING COMPREHENSION OF NARRATIVE TEXT (A Classroom Action Research of the Tenth Grade of MA Al-Bidayah Bandungan in the Academic Year of 2019/2020)

ABSTRACTHandayani, Irma. 2020. “The Use of Tea Party Learning Strategy to Improve Students’ Reading Comprehension of Narrative Text fot the Tenth Grade Students of MA Al-Bidayah Bandungan”. A Graduating Paper of English Education Department, Teacher Training and Education Faculty, State Institute for Islamic Studies (IAIN) Salatiga. Counselor: Dr. Mashlihatul Umami, MA.Keyword: Tea Party Learning Strategy, Reading Comprehension, narrative Text. The objectives of the study were: (1) To find out the implementation of Tea Party Learning Strategy to improve students’ reading comprehension of narrative text for the tenth grade students of MA Al-Bidayah Bandungan in the academic year of 2019/2020. (2) To find out the whether the use of Tea Party Learning Strategy to improve student reading comprehension of narrative text for the tenth grade students of MA Al-Bidayah Bandungan in the academic year of 2019/2020. (3)To identify how far the improvement of the students‘ reading comprehension of narrative text after the use of Tea Party Learning Strategy for the tenth grade students of MA Al-Bidayah Bandungan in the academic year of 2019/2020. The number of subjects of the research were 27 students of MA Al-Bidayah Bandungan. The methodologyof this research was Classroom Action Research. It was It was conducted in two cycles. Each cycles contained four steps. They were planning, action, observation, and reflection. The researcher took the role as an observer who observed everything that happened in the class while the teacher performed classroom action research for the students. The data collected through observation, pretest, post-test, and documentation. The result showed that the students‘ reading comprehension improve significantly. The T-test of cycle I was 6.15, and cycle II was 12.34, it mean that higher than T-table was 2.06. The improvement of the cycle I was 25.9% and in the cycle II was 29.5%. The passing grade was 70 and the target of passing grade was 75%. The students passed the passing grade. The target of cycle II was achieved. The data showed that the result of the T-test in the first cycle and the second cycle was higher than T-table. Based on the result, the researcher recommended using Tea Party Learning Strategy in teaching reading comprehension of narraive text.
PENGEMBANGAN BUKU AJAR INOVATIF IPA TERPADU BERBASIS INKUIRI TERBIMBING SESUAI KURIKULUM 2013 DI SMP SE-KABUPATEN TAPANULI TENGAH

This research is a research and development which is aimed to produce a certain product or develop an existing product including test its effectiveness. The research and development procedures are included in stages such as: Potential and problems; Data collection; Product design; Design validation; Design revisions; Product I trial; Product I revision; Trial usage; Product Revision II; Mass product. The data analysis resulted as follows (1) in the teaching materials that have been developed on the subject matter of additives and addictive substances based on BSNP, (a) the aspects of content worthiness is 3.65 of mean, (b) the aspects of language worthiness is 3.70 of mean, (c) the aspects of the feasibility of serving with is 3.60 of mean, those score are valid and don’t need any revision and it is very decent. (2) It is the students understanding who use the material that has been developed, it obtained an average of 80.21. However the understanding of students who did not use the teaching materials developed just obtained an average of 65.00. This result shows that the understanding of students using the developed teaching materials is higher than without using developed teaching materials.