Reviewerly/exHarmony huggingface dataset:
Determining higher order periods of the Logistic equation using a Chebyshev Transform

The Logistic Equation is an iterative equation which exhibits complicated dynamics when the control parameter r is varied. When r is in between 3 and 3.57, a period doubling phenomena occurs in which periods of 2N is observed, where N∈(1,∞). The Time Series of the Logistic Equation can be interpreted using Power Spectrum analysis method in which one can determine the periods present with a given r value. A popular method in determining the Power Spectrum is the Fast Fourier Transform (FFT). A difficulty encountered by the FFT however is presenting the Power Spectrum of higher order periods since the lower order periods have larger magnitudes, making the higher periods barely visible in the plot. In this paper, we explore the possibility of determining the Power Spectrum of the Logistic Equation using a Chebyshev Transform. The transform was constructed with the help of a package in Matlab called Chebfun in extracting the Chebyshev coefficients. The coefficients together with the scaled frequency bin was used in comparison to the power spectrum of the FFT. It was seen that the Chebyshev Transform had larger peaks compared to that of the FFT and had better numerical accuracy when it comes to determining the periods of the time series.
Eye fixation frequency affects visual memory performance

Visual memories depend on visual input in the most fundamental way. Until recently however, little attention has been paid to the role of visual exploration in generating coherent memory representations. In an attempt to fill this gap, we first identified scanning characteristics related to memory by collecting eye tracking data in a picture memory task performed by 968 healthy subjects. We found that the number of fixations in semantically informative regions during picture viewing was related to later memory performance. Using fMRI, we further report a positive linear relationship of the number of such fixations with functional brain activation in regions primarily related to vision and memory, including bilateral precuneus, cingulum, orbitofrontal cortex, left inferiorparietal cortex, right cerebellum and the medial temporal lobe. In a further study using experimental manipulation of fixation frequency, we could establish a causal link between the number of fixations and memory performance. The findings demonstrate individual differences in visual exploration, which are susceptible to instructed viewing conditions and which impact memory processing.
A Reexamination of Luther’s Reformation and the Origin of Mass Education

오늘날 모든 사람에게 균등한 교육의 기회를 제공하기 위해 실시되는 대중교육은 민주주의적 가치와 부합되는 장점을 지니면서도 질적 저하의 한계를 지닌다는 문제의식을 가지고 그 기원을 비판적으로 고찰하였다. 이를 위해 종교개혁과 함께 교육개혁을 시도한 루터의 교육 사상 및 활동, 그의 교육 사상의 신학적 배경 및 인문주의적 배경에 대하여 살펴보았다. 개성의 해방과 현세적 삶의 향유를 강조하였던 이탈리아 르네상스 등의 배경 위에 진행된 루터의 종교개혁은 도덕적·종교적·신중심적인 운동이었음에도 불구하고 중세의 聖과 俗의 이층 구조를 무너뜨리면서 점점 세속화의 길로 나아가게 하였고, 교육을 신성한 것으로 여겼던 사상에서도 멀어지게 하였다. 이 과정에서 도입된 대중교육은 시간이 흐르면서 군주에 의해 빈민을 대상으로 국가의 이익을 추구하기 위한 수단이 되기도 하면서 오우크쇼트의 주장대로 본래의 교육을 침해하는 방향으로 진행되어 나갔다. 이러한 대중교육은 옛 동양의 선현들처럼 높은 경지를 믿고 추구한다든가 고대 그리스 철학자들처럼 이데아의 세계를 인식하려 한다든가 하는 교육적 의도에서 멀어지게 하였음을 비판하였다. 이에 대한 대안으로 교육의 神聖性을 회복하여 세속화의 과정에서 잊혀져왔던 성의 세계, 즉 초월 세계의 존재를 믿고 높은 경지를 추구하며 살아가게 할 것을 제안하였다.Many scholars in education have expressed some concerns with the quality of today’s education, believing that it was in many part brought about by the mass education system. The mass education system was used by the rulers of Western nations as menas of instructing the poor subjects to increase the well-being and human capital of nations in the 17th century. This system has invaded the original idea of education as an initiation into an inheritance of human understandings as Oakeshott lamented. Searching for the origin of the mass education system, the author reached the religious reformer Martin Luther. In order to understand the religious and social context in which the mass education system was called for, the author critically examined Luther’s educational thoughts and activities, theological thoughts, and the renaissance humanism and the biblical humanism. As a result, the author ascertained, first, that Luther’s Reformation was influenced by Italian renaissance that emphasized the emancipation of the individuality and enjoying the present-day life. Second, the author found out that Luther’s Reformation, although it was moral, religious, and God-centered movement, disintegrated the divine-secular double structure and moved people away not only from the divine world of middle ages, but also from the thought that education is divine. The author argued that the mass education system has made people gradually move away from such educational models as ancient oriental sages who believed in and pursued the absolute knowledge and self-realization that are too high to reach during one’s life time and as ancient Greek philosophers who tried to recognize The Idea of the Good. The author suggests that educators revive the awareness of an absolute that looks upward to the eternal and divine and have students believe in and pursue the divine, transcendental world that has been forgotten in the course of secularization during the past half of a millenium.
Benchmarking big data recommendation algorithms using Hadoop orApache Spark

Recommender or recommendation systems have gained popularity in recent years, and big data is the driving force behind recommendation systems. Recommendation systems changed the way websites communicate with the users by providing a recommendation based on users history such as purchases and searches. Recommendation systems are used in a variety of areas such as movies, music, research articles and social tags. For example, recommendation system in Facebook “People you may know,” Netflix “Because you watched” and YouTube “Recommend for you.” These systems usually produce a list of recommendations in two ways: collaborative and content-based (CB) filtering. Collaborative filtering (CF) is based on a model of prior user behavior, which can be constructed from sole user&apos;s action or from the actions of other users who have similar behaviors, while content-based filtering constructs a recommendation on user&apos;s behavior such as by using historical browsing information. Apart from these, the hybrid approach can be used by combining two models. While designing, such systems require compute function values at several thousand points and thus are computationally quite extensive. These systems need parallel computations to speed up the search for an acceptable solution that can be recommended through nature-inspired computation. There are many factors that are essential while designing accurate recommendation algorithms. Some of these factors are diversity, recommender persistence, privacy, user demographics, trust and labeling. Recommendation system cannot perform its job without data, and big data supplies the amount of user&apos;s data such as past purchase history, browsing history [1,2]. In fact, efficient recommendation system requires big data. The best solution is Hadoop; it is a platform used to store, generate, manage and distribute big data easily around several large server nodes [3-5]. Hadoop offers Hadoop distributed file system (HDFS), which distributes all the data in different clusters and performs parallel operations. This chapter will explore big data issues and specific in Hadoop and HDFS.
LibGuides: Tips and Resources on Writing Well in Seminary: Online Writing Resources

This guide offers basic writing tips to help students make the transition to seminary education. Additional resources are listed for more indepth work.
A COMPARABLE FOUNDATION FOR ITS RESEARCH LOOP AND SUBFIELDS

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1402-1409ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0425Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
New Tools, Gadgets, and Devices in Libraries

The internet explosions, proliferation of online resources, and the advent of free and open access resources in the last two decades provided the much-needed impetus for libraries to inject new energy into providing quality delivery of its services. More and more applications and databases are being provided to the libraries as mobile products. This chapter summarizes, to some extent and expatiate to a large extent, the various new tools, devices, and gadgets operational and adaptable to various aspects of librarianship. After an exploration of how these devices and tools work, and the different types, the author provided a comparison of current popular products, followed by a look at some of the new tools, gadgets and devices that we have available (to and around us). With the awareness that we are in the midst of an ongoing information revolution, the internet and personal computing have tremendous potential to transform library services. All tools, devices, and gadgets will be analyzed with an eye towards the future, cost-effectiveness, performance, and functionality.
Perceptions on EFL Writing Peer Feedback by Two Proficiency Groups: Focusing on Personality and Comparing Giving and Receiving Feedback

Based on a lack of research about the impact of personality on peer feedback in EFL writing, this study investigated relevant research questions with two proficiency groups of college students. The study also focused on the differing effects when giving and receiving peer feedback. The findings included the following: First, lower proficiency seemed to play a role in giving higher satisfaction when receiving feedback. Second, motivation was significantly correlated with effectiveness in the Lower group. Third, participants strengthened their ability and confidence more when receiving feedback. Fourth, the effectiveness of extroverts was higher when receiving feedback, particularly in the Higher group. Lastly, personality affected the preference of peer type of Higher group. Based on these findings, pedagogical implications and suggestions for future research are discussed.
Parallel Convolutional Networks for Image Recognition via a Discriminator

In this paper, we introduce a simple but quite effective recognition framework dubbed D-PCN, aiming at enhancing feature extracting ability of CNN. The framework consists of two parallel CNNs, a discriminator and an extra classifier which takes integrated features from parallel networks and gives final prediction. The discriminator is core which drives parallel networks to focus on different regions and learn different representations. The corresponding training strategy is introduced to ensures utilization of discriminator. We validate D-PCN with several CNN models on benchmark datasets: CIFAR-100, and ImageNet, D-PCN enhances all models. In particular it yields state of the art performance on CIFAR-100 compared with related works. We also conduct visualization experiment on fine-grained Stanford Dogs dataset to verify our motivation. Additionally, we apply D-PCN for segmentation on PASCAL VOC 2012 and also find promotion.
A Case Study on a College Short-Term English Abroad Program for Holistic Learning

This study aims to qualitatively explore the holistic nature of a short-term English abroad program for college students during their one-month stay...
LAYANAN INFORMASI MENINGKATKAN PERCAYA DIRI SISWA DALAM MENGEMUKAKAN PENDAPAT DI MAN 3 BANJARMASIN

This research is motivated by the lack of confidence of students in expressing opinions in the school environment or society. Confidence in expressing opinions makes students active in the teaching and learning process, daring to express their opinions, dare to reject something that is considered incorrect, not hesitating in attitude. By increasing students' confidence in expressing their opinions, it is expected that students can become individuals who are confident in their abilities.The method used in this study is a quantitative method using the Pre-Expansion Designs design in the form of a Pretest-Posttest group. this design to find out the results of the treatment more accurately, in this study conducted 2 observations (measurements), namely comparing the conditions before and after being treated.The results of the research obtained by the Pre-test Results of the sample showed that the average percentage of self-confidence before joining the Information Service increased students' self-confidence by 35.64% which was included in the medium category. After getting the treatment experience an increase and fall into the medium category. The post test results showed that the average percentage of self-confidence after taking treatment in the form of information services increased students' confidence in expressing opinions by 64.04%, which was included in the High category.The conclusion of this study is that there is a positive change in the form of increasing students' self-confidence after being treated with information services in expressing their opinions.
Tanimoto coefficient based Word Sense Disambiguation

In many NLP applications such as machine translation, content analysis, and information retrieval, Word Sense Disambiguation (WSD) is an important technique. Word sense disambiguation is the essence of communication in a natural language. WSD process is useful for automatically identifying the correct meaning of an ambiguous word in the sentence or the query when it has multiple meanings. So, this system proposes as the Tanimoto coefficient based word sense disambiguation system to increase the precision of the NLP application. This system provides additional semantic as conceptually related words with the help of glosses to each keyword in the inputted sentence by disambiguating their meanings. This system uses the WordNet as the lexical resource that encodes concepts of each term.
Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the prior knowledge, involving the accurate model, sufficient information of the noise distribution and the suitable initialization. To address these problems, in this paper, a new adaptive factor together with a fuzzy logic system is proposed for online adjusting the process and the measurement noise covariance matrices simultaneously. In the core of the proposed algorithm, the fault detection procedure is also adopted to reduce the computational time. The theoretical developments are investigated by simulations, which indicate the effectiveness of the proposed filter in DBT problem.
Localization in Fractonic Random Circuits

Random quantum circuits with fractonic charges, which exhibit restricted mobility, fail to thermalize after a long time, thus showing a new mechanism for achieving many-body localization.
TUTORING AND COACHING THE STUDENTS IN CLASS DURING THE FIRST 4 MONTHS AT THE UNIVERSITY

1 University of the Basque Country UPV/EHU; TECNALIA R&I (SPAIN)2 University of the Basque Country UPV/EHU (SPAIN)
RANCANGAN SISTEM INFORMASI PENGADAAN BARANG PADA KOPERASI KARYAWAN AQUA GROUP DENGAN METODOLOGI BERORIENTASI OBYEK

Recent computer technology will be very effective if it is applied to a cooperative both large scale and small scale, where in addition to providing convenience for users, of course, it will be easier to improve operational. operations in the procurement system still using the system manually, so often the reports are sent to the cooperative chairman and often write errors and incomplete . Based on the data above and the urgency of the need for a computerized new goods procurement system, the authors help solve existing problems by designing information systems for procurement of goods. With the use of a computerized system in the company, the authors expect that the system of procurement of goods works efficiently, so as to increase the competitiveness of the company in the future.
Automated Item Difficulty Modeling with Test Item Representations.

This work presents a study that used distributed language representations of test items to model test item difficulty. Distributed language representations are low-dimensional numeric representations of written language inspired and generated by artificial neural network architecture. The research begins with a discussion of the importance of item difficulty modeling in the context of psychometric measurement. A review of the literature synthesizes the most recent automated approaches to item difficulty modeling, introduces distributed language representations, and presents relevant predictive modeling methods. The present study used an item bank from a certification examination in a scientific field as its data set. The study first generated and assessed the quality of distributed item representations with a multi-class similarity comparison. Then, the distributed item representations were used to train and test predictive models. The multi-class similarity task showed that the distributed representations of items were more similar on average to items within their content domain versus outside of their domain in 14 out of 25 domains. The prediction task did not produce any meaningful predictions from the distributed representations. The study ends with a discussion of limitations and potential avenues for future research.
Obscuro: A bitcoin mixer using trusted execution environments

Bitcoin provides only pseudo-anonymous transactions, which can be exploited to link payers and payees -- defeating the goal of anonymous payments. To thwart such attacks, several Bitcoin mixers have been proposed, with the objective of providing unlinkability between payers and payees. However, existing Bitcoin mixers can be regarded as either insecure or inefficient. We present Obscuro, a highly efficient and secure Bitcoin mixer that utilizes trusted execution environments (TEEs). With the TEE's confidentiality and integrity guarantees for code and data, our mixer design ensures the correct mixing operations and the protection of sensitive data (i.e., private keys and mixing logs), ruling out coin theft and address linking attacks by a malicious service provider. Yet, the TEE-based implementation does not prevent the manipulation of inputs (e.g., deposit submissions, blockchain feeds) to the mixer, hence Obscuro is designed to overcome such limitations: it (1) offers an indirect deposit mechanism to prevent a malicious service provider from rejecting benign user deposits; and (2) scrutinizes blockchain feeds to prevent deposits from being mixed more than once (thus degrading anonymity) while being eclipsed from the main blockchain branch. In addition, Obscuro provides several unique anonymity features (e.g., minimum mixing set size guarantee, resistant to dropping user deposits) that are not available in existing centralized and decentralized mixers. Our prototype of Obscuro is built using Intel SGX and we demonstrate its effectiveness in Bitcoin Testnet. Our implementation mixes 1000 inputs in just 6.49 seconds, which vastly outperforms all of the existing decentralized mixers.
Reducing Subjectivity and Bias in an Officer's Analysis of Suspicion in Drug Interdiction Stops

Police officers must daily determine whether they have justification to detain cars they have stopped for ordinary traffic investigations for further investigation. Yet these determinations involve the interpretation of very fact-specific case law that does not yield predictions for subsequent cases and are fraught with subjectivity if not actual bias. Artificially intelligent systems hold the potential to lessen the impact of implicit biases by assisting officers in making these decisions with greater consistency on the basis of factors relevant to suspicion. Using patented text recognition algorithms in order to identify content of interest, or relevant language, our prototype is capable of reading case law and police reports to identify factors relevant to suspicion. With this information, the likelihood a court will approve a search or detention can be assessed. Police reports identifying the bases for fruitful and unsuccessful searches will then permit the system to assess the odds that drugs are present. Deployment will further allow the collection of more detailed data about the basis of successful and unsuccessful stops, improving the system's predictive capacity.
The historical route of puppets arts experience in Iraq

Throughout the ages, the importance of puppets arts comes from the importance of the puppet. Its first function appears by using it in pagan religious rituals and magic.  The puppet has a series of functional changing. It has played different political, social, and cultural roles, by that it became out of religious field and entered the artistic field. Therefore, types of puppets arts play big roles in the different fields of life. The researcher has limited the problem of this research as that, the real existence of puppets arts in Iraq has a great deal of weakness and obscurity. As well as the specialists in this field have fogginess intellectual views, whether they are in the governmental foundations or not, and whether they have a direct contact with the puppets arts or not. The researcher has also found a clear weakness in formal and scientific documentations of the artistic efforts that have done for puppets arts. This weakness comes from the lack of awareness in dealing with these arts by describing them, as effective arts like all other arts that have the specialists' interest. Moreover, there are very limited scientific researches that shed light on these efforts by analyzing their accuracies and amounts, especially those researches about puppets arts in Iraq. This research depends on historical analysis to describe  puppets arts in Iraq during the period 1954-2017. The results show that the developing of these arts in Iraq have four phases according to artistic and educational levels, which are as the following: Initiatives phase  (1955-1966) Establishing  phase(  1967-1979) Recession and hesitating phase(1980-2000) Renaissance and dedication phase(2003-2017) The most important suggestion of this research is to dedicate the enlightenment   of the puppets arts by specialists in the formal foundation, especially Ministry of education, ministry of culture, ministry of higher education, and official media institution. As well as building national center for puppet arts in Baghdad, and establishing sub-centers for it in all cities. Puppets arts should treat as main subjects in institutes and colleges of fine arts in Iraq. Official Theatrical foundation should make for puppets arts and it can add to department of cinema and theater or department of the child's culture, and foundation of festivals specializing in puppets arts whether in theater or in cinema.
Lessons from Experts

This talk will reflect on decades of empirical research on software design in high-performing teams and by experts. The talk will present three broad perspectives: It will identify some of the particular challenges of designing software and the practices that experts use to address them. It will characterise expert software design in terms of a complex of design dialogues. It will consider how expert practice can inform how we teach software design.
THEORETICAL ASPECTS AND PROBLEMS OF THE RUSSIAN EDUCATIONAL SYSTEM MODERNIZATION

1 RUDN University (RUSSIAN FEDERATION)2 West Kazakhstan Engineering Humanitarian University (KAZAKHSTAN)