Reviewerly/exHarmony huggingface dataset:
Student-Centric Network Learning for Improved Knowledge Transfer

In the context of model compression using the student-teacher paradigm, we propose the idea of student-centric learning, where the student is less constrained by the teacher and able to learn on its own. We believe the student should have more flexibility during training. Towards student-centric learning, we propose two approaches: correlation-based learning and self-guided learning. In correlation-based learning, we propose to guide the student with two types of correlations between activations: the correlation between different channels and the correlation between different spatial locations. In self-guided learning, we propose to give the student network the opportunity to learn by itself in the form of additional self-taught neurons. We empirically validate our approaches on benchmark datasets, producing state-of-the-art results. Notably, our approaches can train a smaller and shallower student network with only 5 layers that outperforms a larger and deeper teacher network with 11 layers by nearly 1% on CIFAR-100.
Competing risks model for clustered data based on the subdistribution hazards with spatial random effects

In some applications, the clustered survival data are arranged spatially such as clinical centers or geographical regions. Incorporating spatial variation in these data not only can improve the accuracy and efficiency of the parameter estimation, but it also investigates the spatial patterns of survivorship for identifying high-risk areas. Competing risks in survival data concern a situation where there is more than one cause of failure, but only the occurrence of the first one is observable. In this paper, we considered Bayesian subdistribution hazard regression models with spatial random effects for the clustered HIV/AIDS data. An intrinsic conditional autoregressive (ICAR) distribution was employed to model the areal spatial random effects. Comparison among competing models was performed by the deviance information criterion. We illustrated the gains of our model through application to the HIV/AIDS data and the simulation studies.
Penerapan Algoritma K-Means Dalam Pengelompokan Penerimaan Imunisasi Dasar Lengkap Menurut Provinsi

Immunization is a form of immune system or immune to disease. The process of giving immunizations gives the body immunity to be immune to disease. With routine immunization improves the quality of children's health. According to data from the official Government website, the lowest percentage of children aged from 12 to 23 months who received immunization is 40% at the provincial level in Indonesia. This research was conducted by grouping the minimum level of immunization from 2015 to 2018 using the K-means method. The data obtained are grouped into 2 Clusters starting from the lowest and highest. The author obtains data from the official website of Government which addresses https://bps.go.id. The conclusion of this study concludes that there is still a lack of child immunization in Indonesia, so that there is an expectation that the Government in every region in Indonesia be more active for the welfare of children's health.
DESIGNING AN ENGLISH VOCABULARY WORKBOOK FOR HOSPITALITY STUDENTS BASED ON CORPUS-BASED APPROACH

The research about the use of corpus-based approach in teaching English for Specific Purposes (ESP) to improve the students' vocabulary mastery has been conducted by many researchers. However, the product of the materials in teaching and learning vocabulary which laverages the use of corpus is very limited. For that reason, this study is aimed to design a prototype of English vocabulary workbook for Hospitality students based on corpus-based approach in determining the content, task, and activities carried out. This research uses Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model as the procedure to create a valid, practical, and effective English vocabulary workbook for Hospitality students and corpus-based approach will be used in determining the target words, task, and activities in the workbook. Based on the result of analysis using Wilcoxon test, it can be seen that the Asymp.Sig (2-tailed) is 0.000. As the value of 0.000 is smaller than 0.05, it can be concluded that there is a significant difference between the results of student learning before and after using the workbook developed.
THE CORRELATION BETWEEN INTERPERSONAL INTELLIGENCE AND STUDENTS’ READING COMPREHENSION

The purpose of this study was to find out whether there is a correlation between students 'interpersonal intelligence and students' reading comprehension. The research design used in this research was quantitative correlational research. The populations in this study were 40 students of fourth semester at English Department in Academic Year 2019/2020. The population was selected by simple random sampling technique. The sample in this research was 29 students. Interpersonal Intelligence Questionnaire and Reading Comprehension Test were used as instruments of this study after the validity and reliability tests of the two instruments were conducted. The data normality test used in this study was Kolmogorov Smirnov. The researcher analyzed the correlation using the Pearson Product Moment formula to find out correlation between Students’ Interpersonal Intelligence and Students’ Reading Comprehension. The research found out that there was a significant correlation between Students' Interpersonal Intelligence and Students' Reading Comprehension of fourth semester at English department Universitas Riau Kepulauan in Academic Year 2019/2020. Suggestions were taken by researcher, namely that teachers must be aware of the importance of interpersonal intelligence in students to assist students in honing students 'interpersonal intelligence and students must realize and hone interpersonal intelligence that is in themselves.
TEACHING MATERIALS IN THE TEXTBOOK ENTITLED, “WHEN ENGLISH RINGS THE BELL” FOR JUNIOR HIGH SCHOOL STUDENTS YEAR VII

This study was a descriptive study aimed at describing the the quality of the textbook entitled, “When English Rings The Bell” for Junior High School Students Year VII in providing English teaching material to improve students’ English Knowledge competence.The researcher analyse this book based on the theory from Howard and Major (2010) about good teaching material in English language teaching. The subject of this study is the textbook entitled, “When English Rings The Bell” for Junior High School Students Year VII”. The sources of data of this study were collected by questionnaire and interview from respondents. The respondents were one english teachers from SMP 1 Padang and SMP 31 Padang. The result of this study showed that the respondents had same perception that the quality of the textbook entitled, “When English Rings The Bell” for Junior High School Students Year VII was poor in providing the English Teaching Material to improve students’ knowledge about WH questions.
Abnormal WBC Scattergrams by Sysmex XN550, A Supplementary Diagnostic Tool for Malaria to the Conventional Methods

Background: In India, malaria has a major impact on health system. It is usually diagnosed based on symptomatology, parasite detection in the peripheral smear (PS) or rapid diagnostic tests (RDT) such as malaria antigen test (MAT). Detection of malaria by MAT is considered as the gold standard. A rapid, cost effective screening of malaria can be done with the automated analyzers. The present study was undertaken to assess the efficacy of WBC scattergram generated by Sysmex XN 550 hematology analyzer to diagnose malaria.&#x0D; Methods: A prospective study was conducted over a period of 4 months from August to November 2019, after obtaining institutional ethical clearance. All cases diagnosed as Plasmodium vivax / Plasmodium falciparum infections on malaria antigen test (MAT) were included. Their hemogram and WBC scattergrams obtained from Sysmex XN 550 were studied. Thick &amp; thin Smears were made and stained with Leishman’s stain for microscopy.&#x0D; Results: A total of 101 cases were diagnosed as malaria positive by MAT and thick smear. Ninety-seven were positive by Leishman’s stain. Abnormal scattergrams were 81 out of 101 malaria positive cases. The commonest pattern was double neutrophil zone (n=22) followed by double neutrophil with less space between neutrophil and eosinophil (n=17). An abnormal event on X axis was observed in 16 patients. Gray zone and double eosinophil areas were observed in 11 and 4 cases respectively. The sensitivity of the analyzer was found to be 80.19%.&#x0D; Conclusion: Scattergram of automated haematology analyser (Sysmex XN 550) has good sensitivity, which can be increased to a better level if combined with thrombocytopenia and symptomatology of the patients.
Improving 3D Object Detection via Joint Attribute-oriented 3D Loss.

3D object detection has become a hot topic in intelligent vehicle applications in recent years. Generally, deep learning has been the primary framework used in 3D object detection, and regression of the object location and classification of the objectness are the two indispensable components. In the process of training, the $\ell_{n} (n=1,2)$ and the focal loss are considered as the frequent solutions to minimize the regression and classification loss, respectively. However, there are two problems to be solved in the existing methods. For regression component, there is a gap between evaluation metrics, e.g., 3D Intersection over Union (IoU), and the traditional regression loss. As for the classification component, confidence score exists ambiguous due to the binary label assignment of target. To solve these problems, we propose a loss by jointing 3D IoU and other geometric attributes (named as jointed attribute-oriented 3D loss), which can be directly used in optimizing the regression component. In addition, the jointed attribute-oriented 3D loss can assign a soft label for supervising the training of the classification. By incorporating the proposed loss function into several state-of-the-art 3D object detection methods, the significant performance improvement has been achieved on the KITTI benchmark.
Using Feed-Forward Network for Fast Arbitrary Style Transfer with Contextual Loss

Image style transfer is a method that extracts its style from the style image and applies this style to content image. Since the introduction of neural style transfer, the field of style transfer has developed rapidly, and many new methods have been proposed. There are also some methods based on feed-forward networks, but these methods can usually only transfer one style or several styles. And these methods usually use feature gram matrix to calculate style loss. However, due to the global nature of the gram matrix, some local details cannot be stylized well, which is prone to distortion and artifacts. In this work, we propose an arbitrary style transfer method based on feed-forward network, in which the gram matrix and feature similarity are used together to calculate the style loss. The loss calculated by the similarity between features (called contextual loss in this paper) is minimized to produce stylized images with better details and fewer artifacts. Experimental results and user study prove that our method has achieved the state-of-the-art performance compared with existing arbitrary style transfer methods.
Edición crítica, problemas textuales y de autoría: métrica y ortología en Lope de Vega

Through examples taken from comedies recently attributed to Lope de Vega, this article deals with certain problems that should be considered when studying or editing plays of doubtful authorship. The analysis focuses on methods traditionally used to resolve problematic attributions, such as the study of versification, orthoepy and syllable counting. The conclusion argues that all of these tools —as well as the landmark works by Morley and Bruerton or W. Poesse — still offer great surprises and challenges for researchers. Thus, the development of new methods, such as stylometry, should not impel us to dismiss the classic approaches. Quite the opposite: old and new methods inform one another.
A Framework Establishment of the Reciprocal Teaching in English Learning of After-School Tutoring Institutions

The reciprocal teaching, compromising a series of reading strategies, is always being conducted in plentiful regular educational institutions, concerning reading comprehension enforcement among students of all levels. This paper intends to discuss the practice of applying the reciprocal teaching in English class of the after-school tutoring institutions, the entities supplementing regular school education; and more importantly, to establish a framework guiding the relevant matters from preparatory work to class activities, from implementation appraisal to system maintenance.
애니메이션 녹음 활동의 영어 발음 및 말하기 능력 향상 효과 연구

The purpose of this study is to investigate whether and how the effects of animation recording activities assisted explicit pronunciation instruction on second grade Korean middle school students'' English pronunciation and speaking proficiency. To this end, three research questions were posed, and answers to the research questions were examined using a total of 30 Korean second grade middle school students. The results demonstrate that the implementation of the animation recording activity was effective in improving the overall English pronunciation of students, particularly on pronunciation features as deletion, reduction. linking, and intonation. Furthermore, this implementation has positively affected students'' attitudes and perceptions toward English learning. Although the animation recording activity did not significantly affect the overall speaking proficiency of students, it positively influenced students'' speaking fluency. Research implications were also discussed.
MEDIA DISCOURSE IN THE LENS OF TRANSITIVITY ANALYSIS

This study aimed at analysing the implementation of marketing strategies in Academic Libraries in Developing Countries in the era of Information and Communication Technologies (ICTs). The objectives of the study were to; identify the marketing strategies implemented by academic libraries in Cameroon, determine the efficiency of marketing strategies implemented by academic libraries and to investigate the challenges faced by academic libraries in marketing their services. The study used elements from the Marketing Communication Mix Theory and employed an exploratory research design. Data were collected using an interview guide which was validated by subject experts in the information and marketing professions. Participants were selected from 2 Academic Libraries in Fako Division of the South West Region of Cameroon. Data collected were analysed thematically. The findings indicated that several electronic and non-electronic marketing strategies are used by these libraries, but these are inefficient and there is need for exploitation of more technological means of marketing. One of the recommendations of this study was that current Information and Communication Technology trends be adopted in marketing of academic libraries and that working documents be implemented in an all-inclusive manner to include staff at the operational, tactical and strategic levels who should be well trained to survive in the electronic environment
Android & Ios Covid19 Data Clustering Application Using Flutter with K-Means Algorithm

In the current pandemic, Covid19 has a tremendous impact on the survival of mankind. The government has made efforts to spread Covid19 so that it does not spread much in Indonesia, and now it is in the process of being called PSBB (Large-Scale Social Restrictions) but many Indonesians still violate and ignore the program. There are still many who travel to the Mall, Coffe shop, and even abroad. In this 2020 Era, mobile technology is now an important component of human life, so it is possible to harness the power of mobile technology to make the Indonesian people who still want to violate the program of this government aimed at reducing the spread of COVID-19. So the author aims to create an application that can be accessed through Android & Ios
Influence of Storytelling Method and Information Communication Technology on Learning Public Speaking in Communication Science Students in the City of Pekanbaru

Public speaking courses increasingly encourage renewal efforts in utilizing public speaking material through the mastery of information and communication technology. The material presented must be renewable according to current developments. Sources from the internet and social media make students of communication science confidence appear in the practice of public speaking as a model of storytelling in conquering their audience. Although not a few who are ignorant of information through global developments through information and communication technology (ICT) today, those who share life experiences such as, will experience overwhelmed in looking for improvisation in appearing as a good speaker. This study is to determine the effect of learning methods of Storytelling and Information and Communication Technology on the ability of Public Speaking Students of Communication Studies in Pekanbaru City. This research uses a quantitative method with population and the sample of this research is Communication Science students in Communication Studies study programs in all universities in the city of Pekanbaru with the condition that they have received material and experience in public speaking courses. The results showed that: the storytelling model in the practice of public speaking for communication science students was very influential. The results also show the use of communication and information technology as a source of information influences public speaking communication science students in Pekanbaru.n
DiffAutoML: Differentiable Joint Optimization for Efficient End-to-End Automated Machine Learning

The automated machine learning (AutoML) pipeline comprises several crucial components such as automated data augmentation (DA), neural architecture search (NAS) and hyper-parameter optimization (HPO). Although many strategies have been developed for automating each component in separation, joint optimization of these components remains challenging due to the largely increased search dimension and different input types required for each component. While conducting these components in sequence is usually adopted as a workaround, it often requires careful coordination by human experts and may lead to sub-optimal results. In parallel to this, the common practice of searching for the optimal architecture first and then retraining it before deployment in NAS often suffers from architecture performance difference in the search and retraining stages. An end-to-end solution that integrates the two stages and returns a ready-to-use model at the end of the search is desirable. In view of these, we propose a differentiable joint optimization solution for efficient end-to-end AutoML (DiffAutoML). Our method performs co-optimization of the neural architectures, training hyper-parameters and data augmentation policies in an end-to-end fashion without the need of model retraining. Experiments show that DiffAutoML achieves state-of-the-art results on ImageNet compared with end-to-end AutoML algorithms, and achieves superior performance compared with multi-stage AutoML algorithms with higher computational efficiency. To the best of our knowledge, we are the first to jointly optimize automated DA, NAS and HPO in an en-to-end manner without retraining.
LibGuides: Online Teaching and Learning Resource Guide For Faculty: Sharing Content

This guide is intended to help faculty learn about library services and resources available during remote learning
USE OF REGRESSION ANALYSIS TO IDENTIFY THE RELATIONSHIP BETWEEN TRAINING AND REAL PROFITS FOR SUDANESE BANKS FOR THE PERIOD (2001-2014)

Training is considered as a method for raising the efficiency of humanresources and providing them with information so as to realize thewarranted balance between the goals and the training results. Thus, theresearch is aimed at studying the relationship between training and thereal profits for the Sudanese banks during the period (2001-2014). Thestudy used the descriptive and empirical methods and the ordinaryleast squares method to the data collected from three banks selected inthe sample of the study (Farmer’s Commercial bank, Al-Niline bankand Faisal Islamic bank). The results showed that the selected bankscare for training, however, the Farmer’s Commercial bank gives moreattention to training than Faisal and Al-Niline banks. There was a bigvariation in the real profits in Farmer’s Commercial bank and Al-Niline bank, while the real profits in Faisal Islamic bank werehomogeneous. The number of trainees in the Farmer’s Commercialand Faisal Islamic banks was increasing but it was decreasing in Al-Niline bank. It was also revealed that the real profits caused andincreased the real expenditure on training in Al-Niline bank. Thenumber of trainees in Al-Niline bank caused an increase in realprofits. The study recommended that there should be greater care fortraining in the Sudanese banks and specific and continuous budgetsshould be devoted to training.
Towards Understanding Multimodal Interaction for Visual Data Analysis

Multimodal interaction for visual data analysis and exploration provides new opportunities for empowering users to engage with data. However, it is not well understood which input modalities should be leveraged for certain information visualization (InfoVis) operations and how user would prefer to utilize them during data analysis and exploration. In order to close this research gap, we performed an user-elicitation study to examine how users utilize touch, speech, mid-air hand gestures and a combination of those for various InfoVis operations on large interactive displays. We believe this analysis will help us identify associated challenges and provide knowledge for the development of systems that provide multimodal interaction capabilities for visual data analysis and exploration.