Reviewerly/exHarmony huggingface dataset:
Computational Analysis of an Electrodynamic Speaker and Implementation in 3D Printing

This article presents the use of two technologies as a methodology to design, study, and fabrication of electrodynamic speakers. The experiment setup consisted first in modeling and simulated the classical physical structure circular of a loudspeaker using ANSYS® and solved by the finite element method (FEM), the second part was manufacturing the loudspeaker using 3D printing technics and standard materials in this industry. The simulations, the physical structure implementation and the measurements of frequency response.
Collaborative work and reflective practice to improve teacher’s performance

In search of improving the teaching-learning process in higher education, a Teacher's Performance Assessment Model was designed by answering six questions (What for? Who? When? How? Expected problems? Expected outcome?). This model emphasizes collaborative work and reflective practice among teachers, students and managers, and applies performance indexes that are generated using information provided by the management staff and students’ opinion collected by a web system built for it. Finally, management staff and teachers use these indexes to design general and individual strategies to improve teachers’ performance. The proposed Assessment Model is described here, including the assessment process, its advantages and problems, and results obtained during its application in a University in Sothern Mexico.
An analysis of teachers’ perception on the implementation of the 2015 revised English curriculum: Focusing on elementary school Grades 3-4

This study examines teachers’ perception on the implementation of the 2015 revised English curriculum in elementary school Grades 3 and 4. Teachers who taught Grades 3 and 4 English in 2018 or 2019 were given a survey to complete and interviews were conducted. The results indicate that the majority of the respondents said that the English subject competencies introduced in the 2015 revised national curriculum were suitable for application in elementary schools and that the difficulty level and amount of English learning content in elementary school Grades 3 and 4 were appropriate. However, there were also many responses indicating that the listening part was easy and the writing part was difficult; additionally, the reading and writing parts were short based on the amount of learning. In terms of the difficulty of teaching third and fourth grade English, the majority of the respondents stated that it was the most difficult to manage classes considering the individual differences of students. To manage classes considering these differences, most respondents indicated that it was necessary to provide support personnel. However, interviews also suggested concerns for supporting assistant teachers. Based on these results, support measures were proposed to improve the difficulties in the field.
The Effects of Child Care Teachers’ Emotional Labor on Interaction with Children : Focusing on the mediating effect of ego-resilience

본 연구는 보육교사가 지각하고 있는 감정노동이 교사-유아와의 상호작용에 미치는 영향을 살펴보고, 이들 사이의 관계에서 자아탄력성의 매개효과를 검증하는데 연구의 목적이 있다. 본 연구의 대상은 서울, 경기지역의 어린이집에서 근무 중인 보육교사 302명을 대상으로 조사를 실시하였으며, 연구결과는 다음과 같다. 첫째, 보육교사의 감정노동, 유아와의 상호작용, 자아탄력성 간의 상관관계 분석 결과 감정노동과 유아와의 정서적, 언어적, 행동적 상호작용 간에는 부적 상관관계가 나타났다. 유아와의 상호작용과 자아탄력성간의 상관관계 결과 정적 상관관계가 나타났다. 둘째, 보육교사의 감정노동이 유아와의 상호작용에 미치는 영향을 살펴본 결과 감정노동이 유아의 정서적 상호작용, 언어적 상호작용, 행동적 상호작용에 영향을 미치는 요인으로 나타났다. 감정노동인 표면적, 내면적 행동을 낮게 지각할수록 유아와의 정서적, 언어적, 행동적 상호작용을 높게 지각하고 있는 것으로 나타났다. 마지막으로 보육교사의 감정노동이 유아와의 상호작용에 미치는 영향에서 자아탄력성의 매개효과 검증 결과 부분매개효과를 미치는 것으로 나타났으며, sobel test에서도 매개효과의 유의성이 검증되었다. 따라서 보육교사의 감정노동을 조절하고, 자아탄력성을 증진과 관련하여 보육교사 대상 교육, 상담 프로그램과 연계하여 활용할 수 있는 점에서 연구의 의의를 둘 수 있다.The purpose of this study is to examine how the emotional labor that child care teachers have formed are associated with their interaction with children and verify the mediating effect of ego-resilience in their correlation. A survey was conducted to 302 child care teachers working in daycare centers located in Seoul or Gyeonggi, and this researcher has reached following results: First, according to the results of correlation analysis between child care teachers’ adult emotional labor, ego-resilience, and interaction with children, there was negative correlation found between emotional labor, ego-resilience, and interaction with children. Second, looking at the effect of child care teachers emotional labor on the interaction with children, the results showed that emotional labor was a factor affecting the emotional, verbal and behavioral interactions of children. Lastly, according to the results of examining the mediating effect of ego-resilience in correlation between child care teachers’ emotional labor and interaction with children, partly mediating effect was found in it, and in the sobel test, too, the significance of mediating effect has been verified.
A novel experimental preparation of Gaussian modulated coherent state based on dual-drive Mach-Zehnder modulator in continuous variable quantum key distribution

In this paper, a novel experimental preparation scheme of Gaussian modulated coherent state (GMCS) in continuous variable quantum key distribution (CVQKD) system is proposed based on dual-drive Mach-Zehnder modulator (DDMZM). The experimental implementation of the proposed GMCS preparation scheme only depends on a DDMZM instead of an AM and a PM in conventional CVQKD, which simplifies the experimental setup and reduces the costs of the CVQKD system. Moreover, the sum-difference signals of the Rayleigh distribution and uniform distribution are applied on two parallel electrodes of the DDMZM, respectively, getting rid of the accurate time-delay alignment between the AM and the PM in conventional Gaussian modulation scheme. Besides, the measurement method of the prepared GMCS is experimentally demonstrated based on heterodyne detection, and both quadrature (X and P) are simultaneously measured to verify the proposed GMCS preparation scheme.
Log-log linearity of the asymptotic distribution - a valid indicator of multi-fractality?

&amp;lt;p&amp;gt;The asymptotic shape of the marginal frequency distribution of geochemical variables has been proposed as indicator of multi-fractality. Transition into a certain statistical regime as inferred from the distribution function may be considered as criterion to delineate geochemical anomalies, including mineral resources or pollutants such as radioactive fallout or geogenic radon.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The argument is that asymptotic linearity in log-log scale, log(F(z)) = a - b log(z) as z&amp;amp;#8594;&amp;amp;#8734;, b&amp;gt;0 a constant, indicates multi-fractality.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We discuss this with respect to two issues:&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;(1) What are the consequences of estimating the slope b for non-ergodic, in particular non-representative and preferential sampling schemes, as often the case in geochemical or pollution surveys?&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;(2) Frequently in geochemistry, multiplicative cascades are considered valid generators of multifractal fields, corroborated by observed f(&amp;amp;#945;) functions and variograms (Mat&amp;amp;#232;rn or power, for low lags). This generator leads to marginally asymptotically (high cascade orders) log-normal distributions, which in log-log scale are asymptotically (high z) parabolic, not linear.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Theoretical aspects are addressed as well as examples given.&amp;lt;/p&amp;gt;
Characterizing ResNet Filters to Identify Positive and Negative Findings in Breast MRI Sequences

Training of deep learning models requires large and properly labeled datasets, which make unfeasible using it for developing computer-aided diagnosis systems in medical imaging. As an alternative, transfer learning has shown to be useful to extract deep features using architectures previously trained. In this paper, a new method for classification of breast lesions in magnetic resonance imaging is proposed, which uses the pre-trained ResNet-50 architecture for extracting a set of image features that are then used by an SVM model for differentiating between positive and negative findings. We take advantage of the ResNet-50 architecture for introducing volumetric lesion information by including three consecutive slices per lesion. Filters used as feature descriptors were selected using a multiple kernel learning method, which allows identifying those filters that provide the most relevant information for the classification task. Additionally, instead of using raw filters as features, we propose to characterize it using statistical moments, which improves the classification performance. The evaluation was conducted using a set of 146 ROIs extracted from three sequences proposed for designing abbreviated breast MRI protocols (DCE, ADC, and T2-Vista). Positive findings were identified with an AUC of 82.4 using a DCE image, and 81.08 fusing features from the three sequences.
Hybrid Sequence to Sequence Model for Video Object Segmentation.

One-shot Video Object Segmentation (VOS) is the task of pixel-wise trackingan object of interest within a video sequence, where the segmentation mask ofthe first frame is given at inference time. In recent years, Recurrent NeuralNetworks (RNNs) have been widely used for VOS tasks, but they often suffer fromlimitations such as drift and error propagation. In this work, we study anRNN-based architecture and address some of these issues by proposing a hybridsequence-to-sequence architecture named HS2S, utilizing a hybrid maskpropagation strategy that allows incorporating the information obtained fromcorrespondence matching. Our experiments show that augmenting the RNN withcorrespondence matching is a highly effective solution to reduce the driftproblem. The additional information helps the model to predict more accuratemasks and makes it robust against error propagation. We evaluate our HS2S modelon the DAVIS2017 dataset as well as Youtube-VOS. On the latter, we achieve animprovement of 11.2pp in the overall segmentation accuracy over RNN-basedstate-of-the-art methods in VOS. We analyze our model's behavior in challengingcases such as occlusion and long sequences and show that our hybridarchitecture significantly enhances the segmentation quality in these difficultscenarios.
PERANCANGAN LOGIKA FUZZY METODE SUGENO UNTUK MENENTUKAN DOSEN PEMBIMBING SKRIPSI BERDASARKAN SPESIFIKASI KEAHLIAN DOSEN

Thesis preparation in Study Program of Informatics Engineering, Faculty of Engineering, University of Muhammadiyah Prof. DR. HAMKA is composed by students and guided by thesis supervisors. Process of determining the thesis supervisor is conducted by students, by asking information about the specifications of supervisors expertise to the alumnus. The process is not accurate because the determination of the supervisor is based on personal opinion and not based on the actual specifications of the supervisors's expertise. In this study, author used the Sugeno Fuzzy Logic Method to determine the thesis supervisor. The results obtained in this study are the Sugeno Fuzzy Logic Method can be applied to determine the thesis supervisor by using four input variables namely Software Engineering, Network and Security, and Multimedia. And using the output variables (alternative) on this system are Software Engineering, Network and Security, and Multimedia. Based on the questionnaire that has been done there are 14 supervisors data with an average value for z score of Software Engineering is 1.642 (Enough), the average value for z score of Network and Security is 1.50 (Enough), and the average value for z Multimedia score is 1.50 (Enough).
Multi-Array Multi-Phase Back-Projection: Improving the imaging of earthquake rupture complexities

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;We present a back-projection method capable of being parameterized with multiples arrays. The rupture imaging is weighted to restrict uncertainties induced by non-symmetric azimuthal coverage of seismic arrays. The strategy also exploits the differences in time delays between&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;em&amp;gt;&amp;lt;span&amp;gt;P&amp;lt;/span&amp;gt;&amp;lt;/em&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;and depth phase (&amp;lt;/span&amp;gt;&amp;lt;em&amp;gt;&amp;lt;span&amp;gt;pP)&amp;lt;/span&amp;gt;&amp;lt;/em&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;waveforms by assuming them as proxies of the rupture that can be simultaneously back-projected. Surprisingly, this helps to improve the final results, even when depth phases overlap with the direct arrivals due to the rupture time exceeding the &amp;lt;em&amp;gt;pP-P&amp;lt;/em&amp;gt; delay. Thus, the approach heightens the spatiotemporal resolvability enough to image rupture complexities. The rupture image of two large events demonstrates its robustness. The first one is the 14 November 2007 Mw 7.7 Tocopilla earthquake in northern Chile. The high-frequency rupture (0.5 - 2.0 Hz) encircles two asperities while the short-period energy radiated predominates up-dip of the coseismic slip. We propose the contribution of asperity rupture complexities and along-dip barriers to high-frequency emissions beyond the megathrust frictional structure. The second one is the Mw 7.5 Palu strike-slip earthquake, which occurred on 28 September 2018 in Sulawesi island. The back-projection reveals a prominent supershear rupture at a speed of 4.5 km/s. The result correlates with space geodesy data highlighting the successful recovery of fault structures. Finally, we discuss the potential and challenges of automating this analysis for near-real-time applications&amp;lt;/span&amp;gt;, including near-source back-projection with strong-motion data.&amp;lt;/p&amp;gt;
SCUTMA: Selecting Components for Unit Testing in Mobile Applications

Context The source code of a mobile application has several components (i.e., code units) and they have a cost (e.g., test creation and execution) and benefit (e.g., find bug) value for performing unit testing.Problem Choosing in which components unit tests should be done, in order to increase the benefit (effectiveness) and decrease the cost of this activity.Proposal This study presents an approach that supports the selection of components for unit test creation in Android mobile applications.The SCUTMA approach allows the selection of components with respect to the following criteria, which can be combined: Cost of future maintenance, propensity to defects, frequency of call, risk of failure, market vulnerability and business value.Results Two empirical studies were performed to evaluate SCUTMA.The first study aimed at analyzing the correlation between the metrics that represent the criteria described above, where the result showed the possibility of using the metrics Cost of Future Maintenance (CFM), Code Smell (CS), Frequency of Calls (FC), Fault Risk (FR), Market Vulnerability (MV) and Business Value (BV) combined in a solution for component selection.The second study aimed to evaluate the effectiveness of using the SCUTMA approach.The result indicates that SCUTMA selected more components with error (58.33%) than the selection performed by specialists (40%).Conclusions The SCUTMA approach is effective in selecting components for creating unit tests in Android mobile applications.
PENGARUH KEAKTIFAN DAN FASILITAS BELAJAR TERHADAP HASIL BELAJAR SISWA KELAS XII SMK N 1 BANYUDONO 2019/2020

The purpose of this research was to determine:  (1) the influence of student’s activeness; (2) the influence of learning facilities on the learning outcomes; and (3) the influence of student activeness and learning facilities together toward the learning outcomes at twelveth grade of Personnel Administration subject at SMK N 1 Banyudono Academic Year 2019/2020. This research is a quantitative research with correlational method. The sample taken were 60 students, using Slovin formula, and random sampling technique. The results of the research indicate: 1) significant positive effect of student activity on student’s learning outcomes, t_count> t_table (5.303> 2,00030) significance (0,000 ttable (5,071> 2,00030) significance (0,000 Ftable (59,209> 3.15) significance (0,000 <0.05), so Ho is rejected and Ha received; and 4) multiple linear regression equations obtained Ŷ = 30.955 + 0.199 X1 + 0.387 X2. These results indicate that the higher activeness and complete learning facilities together, the better student’s learning outcomes achieved by students at twelveth grade at SMK Negeri 1 Banyudono Academic Year 2019/2020.
Patent Inventorship and Ownership Issues on Inventions Developed by Humans Using Artificial Intelligence (人工知能を用いて人が生み出した発明についての 発明者適格と権利帰属問題)

English Abstract: Artificial intelligence (AI) is immensely capable of questioning this human ‘self-awareness’ by replicating the human potential to think, sense and also to make decisions in any knowledge field. Advanced research in AI has identified increasingly diverse applications of AI all over the globe. One of the crucial aspects of these AI programs is; even though the instructions have been given by the programmers, the final creative output is sometimes generated by intelligent machines by taking decisions by themselves based on the dense neural networks. In view of the above, some argue that the inventorship rights for such inventions should be owned by intelligent machines. Nevertheless, researchers and legal experts suggest that the inventions developed by machines will always need human intervention and creative input. In this regard, this research focuses on inventorship and ownership issues in relation to inventions developed by humans using AI. This report has tried to resolve these issues by analyzing the statutes and case laws of US, UK, India and Japan. In addition, this report provides the opinions of technological and legal experts. Lastly, the report provides author's suggestions and recommendations which have proposed a framework model that would be helpful to decide the ownership and inventorship of inventions developed by humans using AI.Japanese Abstract: 人工知能(A I)は、どのような知的分野であれ、思考し、知覚し、また決定を下 す人間の潜在的な能力を再現することで、人間のこの『自己認識』を大きく揺る がす可能性がある。AIに関する先進的な研究により、世界中でAIの応用方法がい っそう多様化していることが判明した。これらのA Iプログラムの決定的に重要な 側面の一つが、命令を与えるのがプログラマーであるにしても、最終的かつ創造 的な出力は、インテリジェントマシンが、高密度のニューラルネットワークに基 づき、時には自ら決定を行うことにより生成するということである。上記の点を 考慮し、そのような発明の発明者としての権利を知的機械に帰属させるべきであ ると主張する人々もいる。とはいえ、研究者や法律の専門家は、機械により開発 された発明には今後も常に人間の介入と創造的な情報の提供が必要だと示唆して いる。この点について、本研究では、人間がA Iを用いて開発した発明の発明者適 格及び権利帰属の問題に着目する。本報告書では、米国、英国、インド、日本の 法令及び裁判例を分析することで、これらの疑問に答えようとしている。さらに、 本報告書では、技術及び法律分野の専門家の意見も明らかにしている。最後に、 本報告書では、執筆者の意見と提言を述べる。それは、人間がAIを用いて開発し た発明の権利帰属と発明者適格を決定する助けになるような枠組みモデルを提案 するものである。
Recursos Educativos Abiertos (REA) en la docencia universitaria. Jornada REDUNETE

Webinar about Open Educational Resources (OER): what they are, where they can be identified, how to reuse and remix them, how to create new OERs and how to share them. Some Spanish OER iniciatives will be also presented.
The Unexpected Problem of Classroom Video Conferencing: An Analysis and Solution for Google Hangouts and Jitsi Meet

The paper looks at a multi-classroom video conferencing activity case study from the perspective of EFL classroom practitioner action research. The practitioners had identified an unknown usage limitation problem when simultaneously using large numbers of video conferencing tools. The research took place at a tech focused university campus in Tokyo, Japan, during June and November 2019. The problem had actually manifested because the practitioners had a high degree of confidence in their WI-FI and broader network environment. The research identified and subsequently isolated the specific problem through A/B testing, and the findings were supported by linear regression analysis. On the basis of the findings, the research successfully trialled a solution. However, it became apparent that this was not a localised problem and that the identified issue was relatively generalisable to other school environments. The issue will eventually be faced by other schools as 5G and improved WI-FI are rolled out worldwide. The reaction to the COVID-19 lockdown is likely to speed up the process and mean the identified solution will be required sooner rather than later.
End-to-End Blurry Template Matching Method Based on Siamese Networks

Template matching is a classic problem in computer vision, but most matching methods simply assume the ideal inputs without real-world degradation, such as blur. For blurry template matching, existing methods either have low accuracy or low time efficiency, this paper proposes an end-to-end network BMNet based on siamese networks. When the blurry template image and the clear reference image are input in pairs, the siamese networks are used to extract features respectively, then the two feature maps are transformed and sent to two branches for the classification of the target scene/background and the regression of the coordinates’ offsets. Through the multi-task learning, a trained BMNet can accurately output the coordinates of the template image in the reference image. Extensive experiments demonstrate that our method significantly outperforms state-of-the art on accuracy, speed and robustness.
CREATING TESTS WITH GOOGLE FORMS

The article introduces Google Forms as a part of the G Suite for Education applications for creating and administrating of tests. The article introduces the settings, with different the options for asking questions and providing various types of answers, inserting additional elements (text, video, images), sharing the form and collaborating with it, as well as evaluating and providing the tests’ results.
Cryptocurrencies — An Assessment of Global Adoption Trends

Government and state approaches to any venture first begin with regulations being kept in place to safeguard its interests as well as those of its citizens. Cryptocurrency adoption on a global scale has been led by major players such as the U.S. and China, while some smaller countries have achieved comparable success. In this chapter, we analyze and assess a country’s level of cryptocurrency adoption on the basis of its regulatory framework. We then classify this approach according to the business function that regulates the use of these cryptocurrencies. We also derive a gradual approach to cryptocurrency adoption and regulation, which can be used by fledgling countries new to cryptocurrency.
MENINGKATKAN KETERAMPILAN BERBICARA DENGAN METODE PAIRED STORY TELLING (BERCERITA BERPASANGAN) PADA SISWA KELAS IV DI SDN 4 CAKRANEGARA TAHUN PELAJARAN 2015/2016

This Classroom Action Research aims to increase students’ speaking skill through method Paired Story Telling at grade IV SDN 4 Cakranegara Academic Year 2015/2016. This research was conducted in two cycles. Data collecting Method used were observation, test and documentation whereas, method of data analysis were descriptive quantitaive and qualitative. Based on data analysis result held in cycle 1, classical mean score was 67 with the number of successful studens were 20 and failed students were 12. Highest score was 75 and the lowest score was 50. So that the classical successful students in cycle 1 was 62,5%. The result of reflection in cycle 1 showed that remedial action in next cycle was required. Based on analysis conducted in cycle 2, the number of successful students were 28 and failed students were 4, with the higherst score was 95 and the lowest score was 60. The classical mean score was 77 with classical successful was 87.5 %. That result showed that the application of method paired story telling could increse speaking skill of grade IV students at SDN 4 Cakranegara Academic Year 2015/2016.