Reviewerly/exHarmony huggingface dataset:
Can the Hypnoteaching Method Increase Students’ Speaking Ability?

The objective of this research was to invest the effect of implementation of hypnoteaching toward eleventh grade to increase students’ speaking ability. The research was facused to know the significant effect of implementation hypnoteaching method at MA YASMI DURI. The population are 42 persons of eleventh grade that consists of two classes and the sample are 16 persons of IPA 1 Class. The research design was pre-experiment with pre-test and post-test design. The are two variables, they are hypnoteaching method and speaking ability, and then to analyze the data obtained,the research used Paired sample T-test.&#x0D; &#x0D; Based on the data analysis and its result, the writer knows that mean score of students in pre – test was 50.5 and mean score of students in post-test was 67.25 and the result of paired sample T-test was Tvalue = 6,898, by df is 15. Based on the table of Tvalue, for df 15, Ttable significant 5% is 2,13 and Ttable significant 1% is 2,95.&#x0D; &#x0D; the writer can make a conclusion that implementation of hypnoteaching method toward speaking ability is categorized in “Ha” level based on the experiment classroom, and there is significant effect of implementation of hypnoteaching method toward eleventh grade student speaking ability at IPA 1 class. the result indicate that there is significant effect difference on implementation hypnoteaching method, where post-test improvement score than the pre-test score.
Smartphone-based shade analysis using hemispherical fisheye imaging for local solar energy potential

In the emerging trend of smartphone use and a rising demand for solar photovoltaic (PV) power worldwide, this master thesis project explores the potential to utilize commercially available fisheye lens optics in combination with a smartphone camera to capture and analyze local shading conditions. Photogrammetric studies involving hemispherical sky photos have since long been used for environmental studies and solar energy applications, although mostly with high-end costly equipment. This methodology is therefore developed as an alternative solution using available low-cost equipment for conducting shading analysis. The method overcomes challenging concepts such as lens distortion calibration and image segmentation to calculate plane of array (POA) irradiance from the input image. Tested for both synthetic and real on-site shading analysis the developed method shows promising results in comparison to the more well-established PV system design software SAM. Ultimately it will challenge existing techniques with a more user-friendly, accurate and cost-effective shading analysis tool. (Less)
Home containment and COVID-19: a perspective about the mental health of the geriatric population

Introduction: The COVID-19 pandemic is a major Public Health problem today. Social isolation is the main measure established so far to delay the spread of this pathology. However, the loneliness resulting from confinement can be particularly problematic in senescence. This article aimed to produce and update reflections about the impact of social isolation on the mental health of the elderly during the COVID-19 pandemic. Methodology: A search was carried out in the main data sources: Lilacs, Bireme and Pubmed, in Portuguese and English. Articles that address inclusion requirements were selected and exclude those that do not. It was also decided to perform a reverse search, in order to expand and diversify the results. Results: By crossing the keywords in the database, a total of 475 publications were found. Joining selected articles in the database and in the reverse search, the sample was composed of 21 articles in all. Conclusion: Social isolation negatively affects the mental health of the elderly. Thus, health professionals must be prepared to face an epidemic of emotional disorders arising from the confinement of this population.Keywords: elderly, mental health, pandemic, COVID-19, social isolation.
Mediating Effect of Leadership Outcomes on the Relationship between the Leadership Style of Leaders and Followers’ Administrative Creativity

This paper aims to identify and understand the mediating role of leadership outcomes (LOs) on the association that exists between leadership styles (LS) of leaders and their followers’ administrative creativity (AC) in Najran university. A random sampling technique was conducted which comprised of 342 administrative employees. SPSS tool was used and several statistical methods were involved in the data and statistical analysis including the maximum likelihood estimate. Finally, the structural model testing (SEM) was conducted using AMOS (Analysis of a Moment Structures) to test the proposed hypotheses of the study model. The results showed that leadership styles of managers have a positive relationship on followers’ leadership creativity. In addition, leadership outcomes of followers are positively mediating the relationship between transformational and transactional leadership of leaders and follower’s administrative creativity.
Push the Button: Making Security Training Fun and Interactive

As humans, we are all constantly trying to find the signal in the noise. Unfortunately, the topics and behaviors that we, as corporate security trainers, are trying to explain, teach, and reinforce are often seen as noise to those whom we are targeting. Therefore, to achieve our goals we need more than pertinent information and slick graphics; we need to find ways to stand out, capture people’s attention, and find a way to cement our desirable security behaviors with positive associations. An effective strategy to stand out, make your message more memorable, and to build a positive reputation for your security team is to incorporate interactive exhibits and activities in your security training program.
Feynman-Kac Models: Definition, Properties and Recursions

SummaryBuilding on the concepts of the previous chapter we introduce in this chapter Feynman-Kac models. This concept plays a central role in this book, as all SMC algorithms may be viewed as a Monte Carlo approximation of some underlying Feynman-Kac model.We start by giving the general definition of Feynman-Kac models, i.e., a sequence of distributions for variables X0:t obtained by applying a certain change of measure to the law of a Markov process. We highlight the connection between Feynman-Kac models and state-space models. We then work out various recursions that relate successive Feynman-Kac distributions. In particular, we cover the forward recursion, which underpins particle filtering (Chap. 10), and two types of forward-backward recursions, which underpin particle smoothing (Chap. 12).
Selling Data at an Auction under Privacy Constraints

Private data query combines mechanism design with privacy protection to produce aggregated statistics from privately-owned data records. The problem arises in a data marketplace where data owners have personalised privacy requirements and private data valuations. We focus on the case when the data owners are single-minded, i.e., they are willing to release their data only if the data broker guarantees to meet their announced privacy requirements. For a data broker who wants to purchase data from such data owners, we propose the SingleMindedQuery (SMQ) mechanism, which uses a reverse auction to select data owners and determine compensations. SMQ satisfies interim incentive compatibility, individual rationality, and budget feasibility. Moreover, it uses purchased privacy expectation maximisation as a principle to produce accurate outputs for commonly-used queries such as counting, median and linear predictor. The effectiveness of our method is empirically validated by a series of experiments.
A Comprehensive Study on Challenges in Deploying Deep Learning Based Software

Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications. These software applications, named as DL based software (in short as DL software), integrate DL models trained using a large data corpus with DL programs written based on DL frameworks such as TensorFlow and Keras. A DL program encodes the network structure of a desirable DL model and the process by which the model is trained using the training data. To help developers of DL software meet the new challenges posed by DL, enormous research efforts in software engineering have been devoted. Existing studies focus on the development of DL software and extensively analyze faults in DL programs. However, the deployment of DL software has not been comprehensively studied. To fill this knowledge gap, this paper presents a comprehensive study on understanding challenges in deploying DL software. We mine and analyze 3,023 relevant posts from Stack Overflow, a popular Q&A website for developers, and show the increasing popularity and high difficulty of DL software deployment among developers. We build a taxonomy of specific challenges encountered by developers in the process of DL software deployment through manual inspection of 769 sampled posts and report a series of actionable implications for researchers, developers, and DL framework vendors.
The Role of Isomorphism Classes in Multi-Relational Datasets

Multi-interaction systems abound in nature, from colloidal suspensions to gene regulatory circuits. These systems can produce complex dynamics and graph neural networks have been proposed as a method to extract underlying interactions and predict how systems will evolve. The current training and evaluation procedures for these models through the use of synthetic multi-relational datasets however are agnostic to interaction network isomorphism classes, which produce identical dynamics up to initial conditions. We extensively analyse how isomorphism class awareness affects these models, focusing on neural relational inference (NRI) models, which are unique in explicitly inferring interactions to predict dynamics in the unsupervised setting. Specifically, we demonstrate that isomorphism leakage overestimates performance in multi-relational inference and that sampling biases present in the multi-interaction network generation process can impair generalisation. To remedy this, we propose isomorphism-aware synthetic benchmarks for model evaluation. We use these benchmarks to test generalisation abilities and demonstrate the existence of a threshold sampling frequency of isomorphism classes for successful learning. In addition, we demonstrate that isomorphism classes can be utilised through a simple prioritisation scheme to improve model performance, stability during training and reduce training time.
An Anonymous Trust-Marking Scheme on Blockchain Systems

During the Coincheck incident, which recorded the largest damages in cryptocurrency history in 2018, it was demonstrated that using Mosaic token can have a certain effect. Although it seems attractive to employ tokens as countermeasures for cryptocurrency leakage, Mosaic is a specific token for the New Economy Movement (NEM) cryptocurrency and is not employed for other blockchain systems or cryptocurrencies. Moreover, although some volunteers tracked leaked NEM using Mosaic in the CoinCheck incident, it would be better to verify that the volunteers can be trusted. Simultaneously, if someone (e.g., who stole cryptocurrencies) can identify the volunteers, then that person or organization may be targets of them. In this paper, we propose an anonymous trust-marking scheme on blockchain systems that is universally applicable to any cryptocurrency. In our scheme, entities called token admitters are allowed to generate tokens adding trustworthiness or untrustworthiness to addresses. Anyone can anonymously verify whether these tokens were issued by a token admitter. Simultaneously, only the designated auditor and no one else, including nondesignated auditors, can identify the token admitters. Our scheme is based on accountable ring signatures and commitment, and is implemented on an elliptic curve called Curve25519, and we confirm that both cryptographic tools are efficient. Moreover, we also confirm that our scheme is applicable to Bitcoin, Ethereum, and NEM.
Swell noise suppression via correntropy based robust sparsity-promoting method

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2020Swell noise suppression via correntropy based robust sparsity-promoting methodAuthors: Weiwei XuYanhui ZhouXiaokai WangWenchao ChenWeiwei XuXi’an Jiaotong UniversitySearch for more papers by this author, Yanhui ZhouXi’an Jiaotong UniversitySearch for more papers by this author, Xiaokai WangXi’an Jiaotong UniversitySearch for more papers by this author, and Wenchao ChenXi’an Jiaotong UniversitySearch for more papers by this authorhttps://doi.org/10.1190/segam2020-3427492.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail AbstractSwell noise, which is characterized by high-amplitude and low-frequency content, can mask the useful signals in seismic data and severely affect the fidelity of subsequent seismic processing. In this abstract, we presented a novel correntropy based robust sparsity-promoting method for swell noise suppression. Unlike traditional least-squares sparsity-promoting methods making use of the norm, which is extremely sensitive to swell noise, our method leveraged the superiority of correntropy induced metric (CIM) to adaptively assign weights for noisy data depending on the swell noise level. And also, the sparse prior is imposed on the CIM to learn robust and sparse representations. Using the Half-Quadratic optimization technique, the correntropy based optimization can be transformed into an -constrained quadratic problem, which can be efficiently solved by a standard optimization method. We applied our presented method to real marine seismic data which is largely contaminated by swell noise, and the results turns out that the swell noise is suppressed successfully and the useful signals are well preserved. 2 l 1 lPresentation Date: Wednesday, October 14, 2020Session Start Time: 9:20 AMPresentation Time: 9:45 AMLocation: Poster Station 13Presentation Type: PosterKeywords: noise, signal processing, prestack, marine, optimizationPermalink: https://doi.org/10.1190/segam2020-3427492.1FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2020ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2020 Pages: 3887 publication data© 2020 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 30 Sep 2020 CITATION INFORMATION Weiwei Xu, Yanhui Zhou, Xiaokai Wang, and Wenchao Chen, (2020), "Swell noise suppression via correntropy based robust sparsity-promoting method," SEG Technical Program Expanded Abstracts : 3269-3273. https://doi.org/10.1190/segam2020-3427492.1 Plain-Language Summary Keywordsnoisesignal processingprestackmarineoptimizationPDF DownloadLoading ...
Production and Characterization of Bioplastic from Phycocolloids

Plastic that is made partly or wholly from polymer derived from biological sources such as sugarcane, potato or starch is called bioplastic. It is bio based, biodegradable or features both the properties. The use of Bio plastic is growing rapidly because of their clear advantage over traditionally used plastic. Bio plastic can be used in packaging industries, in the making of capsules and pills, mobile cases, for making baby toys, etc. The main aim of this study was to identify the potential use of agar (Phycocolloids) in the making of bio plastic. The term phycocolloid is used to described a colloid derived from seaweed; a colloid in turn is defined as a non crystalline substance with very large molecules. A phycocolloid is thus simply a seaweed gum. The results of current study show that agar can be successfully used for making bio plastic.
Bitcoin and its impact on the economy

The purpose of this paper is to review the concept of cryptocurrencies in our economy. First, Bitcoin and alternative cryptocurrencies' histories are analyzed. We then study the implementation of Bitcoin in the airline and real estate industries. Our study finds that many Bitcoin companies partner with airlines in order to decrease processing times, to provide ease of access for spending in international airports, and to reduce fees on foreign exchanges for fuel expenses, maintenance, and flight operations. Bitcoin transactions have occurred in the real estate industry, but many businesses are concerned with Bitcoin's potential interference with the U.S. government and its high volatility. As Bitcoin's price has been growing rapidly, we assessed Bitcoin's real value; Bitcoin derives value from its scarcity, utility, and public trust. In the conclusion, we discuss Bitcoin's future and conclude that Bitcoin may change from a short-term profit investment to a more steady industry as we identify Bitcoin with the "greater fool theory", and as the number of available Bitcoins to be mined dwindles and technology becomes more expensive.
No quantum speedup over gradient descent for non-smooth convex optimization

We study the first-order convex optimization problem, where we have black-box access to a (not necessarily smooth) function $f:\mathbb{R}^n \to \mathbb{R}$ and its (sub)gradient. Our goal is to find an $ε$-approximate minimum of $f$ starting from a point that is distance at most $R$ from the true minimum. If $f$ is $G$-Lipschitz, then the classic gradient descent algorithm solves this problem with $O((GR/ε)^{2})$ queries. Importantly, the number of queries is independent of the dimension $n$ and gradient descent is optimal in this regard: No deterministic or randomized algorithm can achieve better complexity that is still independent of the dimension $n$. In this paper we reprove the randomized lower bound of $Ω((GR/ε)^{2})$ using a simpler argument than previous lower bounds. We then show that although the function family used in the lower bound is hard for randomized algorithms, it can be solved using $O(GR/ε)$ quantum queries. We then show an improved lower bound against quantum algorithms using a different set of instances and establish our main result that in general even quantum algorithms need $Ω((GR/ε)^2)$ queries to solve the problem. Hence there is no quantum speedup over gradient descent for black-box first-order convex optimization without further assumptions on the function family.
Paradoxes of The Technogenic Society. On Nikolai Tverdynin’s Book Technics In the Literature of Different Countries and Periods: an Essay Monograph

The review on the book of a former Emergency Ministry official and a philosophy professor Nikolai Mikhailovich Tverdynin published in 2020 in ANO Dialog Kul’tur publishing house analyses views on technology and technics that are manifested by acknowledged people across the globe. Two major beliefs are as follows: technophobic and technocratic. Dr. Tverdynin provides an unbiased description of their application to practice, as it becomes clear that technological threat awareness is a key feature of both attitudes. The book suggests that modern technical boom and its increasing involvement in education and personal development shall remain a vital, but not central method of acquiring new skills, as direct experience teaches not only to operate, but also to be a qualified worker and an individual even in sciences. Despite this and other opinion messages (remember the author’s past service), the book is not a journalist, but a scientific work, as it is void of ideology that accompanies technology. Overall, the book serves as an example of a rare accurate review of such an urgent issue and on such a thorough source collection.
The Influence of International Pre-Service Teaching Program Towards Students’ Speaking Ability at University of Muhammadiyah Makassar

The objective of the research is to find out the influence of International Pre-service Teaching Program toward students’ speaking English ability at Makassar Muhammadiyah University. The researcher applied descriptive qualitative research. The population of the research was the students who join International Pre-service Teaching Program (P2K International) at Makassar Muhammadiyah University. The researcher used total sampling technique. The population consisted of 15 students who joined in 2014 and 13 students who joined in 2015. The result of the research data showed that there were 25.31% students chose Strongly Agree from 237 items in positive statement and 37.14% Agree, 27.85% Undecided, 5.90% Disagree, and then 3.80% students chose Strongly Agree. While 1.57% students chose Strongly Agree from 254 items in negative statement and 10.24% Agree, 21.26% Undecided, 23.63% Disagree, and then 43.30% students chose Strongly Agree. In self-confidence aspect they feel no worry anymore to speak in public, in grammar they can not deny that their grammar become better, in fluently their English speaking is not slow as beginner, and their vocabulary significantly enriched after the program. All these aspects lead the students to become speaker especially in English. Having analyzed the data, it can be concluded that Pre-service teaching international program has significantly influence and improved the students’ English speaking ability at Makassar Muhammadiyah University.
Investigating English Teacher Candidate’s Use of Instructional Media During the Teaching Practicum: A Case Study

This study analyzes the English teacher candidate’s use of instructional media in the teaching practicum. The English teacher candidate who became the participant in this study was doing their teaching practicum in MTsN 5 Jember. This study applied the qualitative case study design. Interview and observation were done one time to select the participant. The four-times classroom observations and questionnaires were used in order to collect the data. This study employed the model of Creswell in analyzing the data. The findings of this study showed that the English teacher candidate applied one type of instructional media namely Visual Media. Those were Picture and Whiteboard. The way the teacher candidate implemented the instructional media was almost the same in each meeting of the teaching and learning process. However, the students’ participation and response were not always the same in every meeting. It depended on the way the teacher candidate managed the class activity.
Great UI Can Promote the “Do Everything Ourselves” Economy

As user experience designers know, great UI design isn’t just a frill. It isn’t just about aesthetics, and isn’t just about efficiency or convenience. But what designers might not yet appreciate, is that great UI might actually hold the key to solving some of the major social problems of our time – like poverty, inequality, war, and climate change.It might do so through an unusual route – enabling end-users to solve problems themselves that would otherwise require interactions with large industrial organizations. Great UI is now enabling “Do it Yourself” (DIY) culture, from home repair videos, to the Maker movement enabled by 3D printers. What if we could evolve these developments into a “Do Everything Ourselves” (DEO) economy? This could form the foundation of a more sustainable, more equitable economy for the new age of Artificial Intelligence and Personal Manufacturing.