Reviewerly/exHarmony huggingface dataset:
Pengaruh Matakuliah Matematika Dasar dan Strategi Belajar Mengajar terhadap Matakuliah Micro Teaching

Education students must be someone who is intelligent and able to think creatively in the future as an educator. But in reality it is not small when students are tested to perform properly like a teacher. Microteaching courses can be used as a solution for students to learn how to work as educators. Not only in the microteaching course, students can learn how to become good educators, other subjects that support basic mathematics and teaching and learning strategies, so the purpose of this study is to determine the effect of basic mathematics and teaching and learning strategies on microteaching subjects. This study uses a purposive sampling technique with a sample of research determined by students of class E T.A 2015/2016. This study uses linear regression calculations and correlations with Ms. Excel in order to find out which of the 2 courses that have been taken is the one that most influences the appearance of students in the microteaching course. The results showed that the teaching and learning strategy subjects had the most influence on the appearance of students in the microteaching course with a correlation value (0.20).
PCN177 CHARACTERIZING LUNG CANCER PATIENTS IN CHINA USING EHR DATA FROM MULTIPLE HOSPITALS

Electronic health records (EHRs) systems have been implemented widely in China and EHRs data has become the most important part of real-world data for clinical research. The National Cancer Center of China has started building a National Cancer Big Data Platform (NCBDP) since 2016, by collecting EHRs data from all cancer hospitals in China. The purpose of this study is to characterize patients of lung caner, the leading cause of tumor death in China, by using EHRs data collected from multiple hospitals through NCBDP. Both structured and unstructured EHRs data were collected from individual hospitals and converted into the OHDSI Common data Model (CDM), to support the generation of reliable evidence. Structured data such as diagnoses and medications were mapped to Chinese coding standards ICD-10-CN and NCCD (Normalized Chinese Clinical Drugs). Natural language processing was used to extract additional details that was embedded in clinical narratives. A cohort of lung cancer patients were extracted using ICD10 codes C33-C34. Demographics, diagnosis and treatment information were extracted and used for the analysis. 47,499 lung cancer patients were identified from 12 hospitals. The median age was 61 years old and 29,953(63.06%) were male. Among patients with TNM staging, 2046(8.94%), 2012(8.79%), 6159(26.91%) and 12672 (55.36%) of these patients are Stage I,II,III,IV, respectively. Among patients who received drug therapy (n = 25,427), 23,741(93.37%), 5,069(19.94%), and 9 (0.04%) received chemotherapy, targeted therapy, and immunotherapy, respectively. We believe that EHRs data, after careful cleaning and normalization, can be used to characterize lung cancer patients in China, by providing real-world evidence to answer important questions such as how they are treated and what their responses are. It may also help us monitor and understand how new treatments such as immunotherapy grow. Nevertheless, there are still issues such as data diversity and incompleteness that need to be addressed.
Concerning the Issue of the Logic of Maqom Composition

The phenomenon of maqom composition takes up a central position in the maqom musical tradition. Its comprehension is assisted by maqom thinking, which, unfortunately, is gradually becoming extinct. This is stipulated by the weakening of the maqom canons, the changes of the process of cognition of the maqom and the methodological notions of the traditional school of ustod-shogird. The treatise “Bayozi Shashmaqom” by the famous Tajik maqom player Fazliddin Shakhobov (1911–1974) presents a most important source containing a classical interpretation of this question. It is the only work written during the Soviet period by a representative of the classic school of the Shashmaqom. The merit of Fazliddin Shakhobov’s position lies in that it brings a procedural interpretation of the maqom scalar modes in a maqom composition, demonstrating the logic of its formation. The main conditions of its development are represented by the ability and skill of using maqom scalar modes in the maqom dramaturgy. With the aid of several examples, the article demonstrates a procedural interpretation of maqom composition in adherence with the canons of modality, rhythm and form-generation. The information contained in Shakhobov’s treatise serves as a foundation for drawing conclusions that the chief compositional method in maqom is the asl-far. This method hearkens back into medieval traditions, the hidden theory of the maqom, and profound knowledge of the parda/maqom. It is the asl-far in particular which is capable of reviving maqom musical thinking. Keywords: the musical culture of Tajikistan, Shashmaqom, maqom, asl-far, Khororang, Chorgokh-Mukhayar, Uzzolrang, farsaqil, aslparda.
Personal resources and burnout: evidence from a study among librarians of Moscow region

Purpose. The paper is aimed to study the level of burnout and its relations to personal resources in librarians of Moscow region. Method. The sample is comprised of 504 respondents, ranging from 17 to 72 years old. The most of the participants is women (96%). To measure burnout, a model proposed by V. Shaufeli and S. Desart was used. The main constructs of personal resources were optimism, hardiness and self-efficacy. As the main method of analysis, multi-level regression was used,which is the most preferable when analyzing clustered data, so that the contribution of any variablesis not overestimated. As a preliminary analysis, a measurement model of burnout was validated using confirmatory factor analysis (with first and second order factors). Findings. It was shown, that the respondents’ level of burnout is quite low, personal resources are strongly and negatively related to burnout (rs = - .64, p < .01). The effect of personal resources varies across libraries (β = - .08, 95% CI[- .04; - .12]), however, is the same amongst rural and urban library workers (β = .03, 95% CI [- .15;.21]). In addition to personal resources, age was a significant predictor of the level of burnout (β = - .10,95% CI [- .18; - .02]), while the work experience turned out to be insignificant. Value of the results. In conclusion, the results of the paper are discussed with previous studies, as well as the possibility of professional development of librarians, considering their psychological state.
MOTIVATION OF THE MAIN CHARACTER IN SUE MONK KIDD’S SECRET LIFE OF BEES

This research to used know form motivation and special figure character in novel Secret Life of Bees by Sue Monk Kidd’s. Research type is qualitative. This study was conducted to analyze the motivation of the main protagonist in the novel Secret Life of Bees work of Sue Monk Kidd and try to connect with the sociological approach. To obtain more data about the character in the novel, library research was also conducted by the writer. The writer collected some journals, articles, and some significant notes that could be used 5as references to investigate this research. And the characters were arranged systematically, in addition to the novel itself, additional data from literature supporters, the data of journals, articles, and data from the internet. Result of research indicates that in analyzing novel Secret Life of Bees by Sue Monk Kidd’s, that character of the special figure in novel that is Lily Owen covering character: they are love, fear of failure, hope for reward, and religious feeling. And motivation in the main character’s life. The four of them make her successful to achieve her goal. Lily is successful to get away from her cruel father and goes to Tiburon with Rosaleen to know about her mother’s death in order to learn about herself. Having analyzed some motivation of the main character in the novel Secret Life of Bees , it shows that the motivations make some results for the main character. Furthermore, the writer analyzes the result of her motivation that will be accepted by the main character. Penelitian ini digunakan untuk mengetahui bentuk motivasi dan karakter tokoh khusus dalam novel Secret Life of Bees karya Sue Monk Kidd. Jenis penelitian adalah kualitatif. Penelitian ini dilakukan untuk menganalisis motivasi protagonis utama dalam novel Secret Life of Bees karya Sue Monk Kidd dan mencoba untuk terhubung dengan pendekatan sosiologis. Untuk mendapatkan lebih banyak data tentang karakter dalam novel, penelitian perpustakaan juga dilakukan oleh penulis. Penulis mengumpulkan beberapa jurnal, artikel, dan beberapa catatan penting yang dapat digunakan sebagai referensi untuk menyelidiki penelitian ini. Dan karakter disusun secara sistematis, selain novel itu sendiri, data tambahan dari literatur pendukung, data jurnal, artikel, dan data dari internet. Hasil penelitian menunjukkan bahwa dalam menganalisis novel Secret Life of Bees karya Sue Monk Kidd, karakter tokoh utama dalam novel itu adalah karakter Lily Owencovering: mereka adalah cinta, ketakutan akan kegagalan, harapan akan hadiah, dan perasaan religius. Dan motivasi dalam kehidupan karakter utama. Keempatnya membuatnya sukses untuk mencapai tujuannya. Lily berhasil melarikan diri dari ayahnya yang kejam dan pergi ke Tiburon bersama Rosaleen untuk mengetahui tentang kematian ibunya untuk mengetahui tentang dirinya sendiri. Setelah menganalisis beberapa motivasi karakter utama dalam novel Secret Life of Bees, itu menunjukkan bahwa motivasi membuat beberapa hasil untuk karakter utama. Selanjutnya, penulis menganalisis hasil motivasinya yang akan diterima oleh tokoh utama.
Thermal-aware job scheduling in data centers: an optimization approach

Data centers are becoming more and more vital for every day life: they are huge computational beasts that run google queries, keep facebook profiles, and store our data in the cloud. As a result, research has focused the last decade on making the computing halls that host data centers more energy efficient. This thesis focuses on thermal management and control techniques that balance the thermal load in the data center, using knowledge of the thermal flows and leakages among the server equipment. For maximal utility, the controllers are extended to allow operation at the operating boundary. The results are completed by simulating a combination of thermal-aware controllers designed in this thesis, and power-aware controllers designed elsewhere. It is shown that a smart combination of both techniques results in greater energy reductions than implementing a single-purpose controller. Finally this thesis provides a method for characterizing the thermal map of any data center. With this identification method, it is possible to apply the controllers designed in this thesis to any existing data center.
A Discussion on the Ways to Improve Pupil Well-being

As the topic of mental health has become increasingly popular recently in education, psychology and several other social science disciplines, well-being of young students has raised great concerns worldwide.This paper aims to explore the ways to improve pupil well-being by reviewing literatures.The first part describes the definition of pupil well-being and a theoretical model.Then a number of empirical studies on pupil well-being focusing on schools, teachers, social relationship and pupils themselves were reviewed.According to the definition, theoretical model and the empirical evidence, the ways of improving pupil well-being are discussed in the final parts of discussion and conclusion.
Deep Convolutional Neural Network Based Facial Keypoints Detection

Facial keypoints (FKP) detection is considered as a challenging task in the field of computer vision, as facial features vary from individual to individual. It becomes a more challenging proposition as the same person facial image may also vary due to change in position, size, pose, expression etc. Some methods exist in literature for detection of FKPs. In this paper, a deep architecture is used to locate the keypoints on gray-scale images. As baseline method one hidden layer neural network and convolutional neural networks are built in the proposed work. Additionally, a block of pretrained Inception module is used to extract the intermediate features. Specifically, the sparse structure of Inception model reduces the computational cost of the proposed method significantly. The methods are evaluated on standard dataset and compared with existing state-of-the-art CNN based methods. The obtained results are promising and also bring out the efficiency of the proposed work.
Письмо как властная практика в средней школе: от ручки к кейборду

Dysgraphia is a specific historical phenomenon, it came into the view of society recently. Dysgraphia is caused by the necessity of universal literacy of the population. The hypothesis of the study: if dysgraphia is caused by certain technologies (this handwritten writing), overcoming dysgraphia can also be connected with the change of technology of production of the text: this refers to the departure from the handwritten writing to printing (in milder forms of dysgraphia) and use of programs of speech recognition, sound files, etc. In other words, the use of new media makes it possible to correct the manifestations of normalizing sanctions against the dysgraphics on the part of teachers and classmates. The object of the study were secondary school students-dysgraphics in Samara. The aim is to find out how the disciplinary practices of writing within the school environment repress this category of students, forcing them to meet certain educational standards.
Performance of Classifiers on MFCC-Based Phoneme Recognition for Language Identification

The automatic identification of language from voice clips is known as automatic language identification. It is very important for a multi lingual country like India where people use more than a single language while talking making speech recognition challenging. An automatic language identifier can help to invoke the language specific speech recognizers making voice interactive systems more user friendly and simplifying their implementation. Phonemes are unique atomic sounds which are combined to constitute the words of a language. In this paper, the performance of different classifiers is presented for the task of phoneme recognition to aid in automatic language identification as well as speech recognition. We have used Mel Frequency Cepstral Coefficient (MFCC) based features to characterize Bangla Swarabarna phonemes and obtained an accuracy of 98.17% on a database of 3710 utterances by 53 speakers.
Slow Science for a Sustainable Agriculture

“Data is the lifeblood of decision-making and the raw material for accountability.” (Food and Agricultural Organisation of the United Nations) Agriculture depends on living organisms: the resources that we grow and harvest (crops, livestock), the many naturally-occurring organisms that support agro-ecosystem services and those that are considered pests. Biodiversity represents the pool of resources upon which production systems are based. This ecosystem-based understanding of agriculture is fast replacing the simplistic input-output paradigm that was once prevalent. Reflecting this trend, the Food and Agricultural Organisation of the United Nations created a Department of Climate, Biodiversity, Land and Water in 2016. This shift is also perceived in trends in research supporting agriculture, where research towards fast fixes (eg. genetic engineering) for food security and production sustainability, is steadily losing ground to more systemic approaches and “Slow Science”. This includes information derived from observation-based, long-term, multi-location data gathering from, for example, newly-termed Living Laboratories or Genomic Observatories. These activities generate a diverse set of data types complemented with extensive physical-chemical and climate data to enable more comprehensive and scientifically defensible assessments of biodiversity for policy and regulatory decision-making. However, the data associated with these entities can be very large, raising several challenges. First, a robust IT infrastructure must exist and persist to both store the data and to facilitate analysis often associated with high-performance computing. Next, this infrastructure must be supported by a data management policy, which responsibly dictates what data is preserved and for what time period as most institutions must be cognisant of their limited IT resources. The data, where not sensitive, must typically be openly shared to allow for use in other projects from local to global scale. This sharing relies on global data standards managed by a multitude of standard bodies and spread across a diverse set of data types. However, this new paradigm, especially with the constant advent of new technologies such as those implemented in genomic observatories and precision agriculture, has challenged standards bodies to keep up. Another challenge lies in the analysis and management of this big data, which relies on a new set of skills not traditionally found in agricultural science including data scientists and data curators. Finally, a major challenge to this “Slow Science” approach are the research funding models themselves that are not highly supportive of long-term, and often non-hypothesis-driven research. We will discuss these challenges and provide some examples of progress being made to embrace this new “Slow Science” agricultural paradigm.
Analyzing

Shudong Hao, Michael J. Paul. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
Characterization of a High-Brightness, Laser-Cooled Li + Ion Source

Ion sources based on laser cooling have recently provided new pathways to high-resolution microscopy, ion milling, and ion implantation. Here, we present the design and detailed characterization of a 7Li magneto-optical trap ion source (MOTIS) with a peak brightness of (1.2 ± 0.2) × 105 A m-2 sr-1 eV-1 and a maximum continuous current over 1 nA. These values significantly surpass previous Li MOTIS performance benchmarks. Using simple models, we discuss how the performance of this system relates to fundamental operating limits. This source will support a range of projects using lithium ion beams for surface microscopy and nanostructure characterization, including Li+ implantation for studies of ionic transport in energy storage materials.
Interferometric measurement of shape with spatially incoherent light

Get PDF Email Share Share with Facebook Tweet This Post on reddit Share with LinkedIn Add to CiteULike Add to Mendeley Add to BibSonomy Get Citation Copy Citation Text M. Sjödahl and K. Ramser, "Interferometric measurement of shape with spatially incoherent light," in Digital Holography and Three-Dimensional Imaging 2019, OSA Technical Digest (Optica Publishing Group, 2019), paper Tu4B.6. Export Citation BibTex Endnote (RIS) HTML Plain Text Citation alert Save article
Comparative Study for Text Document Classification Using Different Machine Learning Algorithms

Classification is a supervised learning method: the goal is finding the labels of the unknown object. In the real world, the tedious amounts of manual works are required to label the unknown documents. The system is initially trained by labeled documents by using one of the supervise machine learning algorithm and then applied trained model to predict the label of the unknown documents.  The framework of text document classification consists of: input text document, pre-processing, feature extraction and classification. The analysis four common classification methods are performed: Naive Bayes, Decision Tree, Support Vector Machine and K-nearest neighbors for text document classification. The main focus of this paper is to present comparative study of different exiting classification methods for text document classification. The experiment performed different classification methods on the Enron Email Dataset and measure classification accuracy, true positive, true negative, false positive and false negative to compare the performance of different classification methods.
Ориентация сельских старшеклассников на высшее образование в современной России

The major research objective is to clarify rural schoolchildren’ orientations to higher education in modern Russia. Methodology: Higher education has been considered from the standpoint of institutional and axiological approaches. The research methodology combines qualitative and quantitative methods. Methods of collecting primary data were the questionnaire and interview. 206 rural schoolchildren were questioned. Interviews with experts (20 experts) are used to identify main problems and the causes of low assessment of education values by schoolchildren. Findings and discussion: The study has shown that higher education is an instrumental value for the majority of rural schoolchildren and their parents, which is associated with improving future social status, getting better job after graduation and relocating to cities. The dominant status-prestige value of higher education will probably retain its leading position in the nearest future, sharing it, perhaps, with economic (material) value. The lack of conditions for schoolchildren’s self-realization increases the number of defectors in the village. Meanwhile, the orientation of schoolchildren towards the profession of a teacher and doctor tells us about the potential return of young people to the village if there is a developed infrastructure there (hospitals, schools, secondary vocational educational institutions, etc.). However, only 30.0% of the respondents do not return to their villages after graduation of the university. The study has revealed different access to higher education among rural students. It turned out that living in rural areas has a much stronger influence on further life course than personal plans of young people, including admission to different types of educational institutions (or preservation of general secondary education). Key words:  rural schoolchildren, higher education, orientations to higher education, compulsory schooling value, instrumental value.
Energy-efficient fuzzy-based approach for dynamic virtual machine consolidation

In cloud environments, the overload leads to performance degradation and Service Level Agreement (SLA) violation while underload results in inefficient utilisation of resources and needless energy consumption. Dynamic Virtual Machine (VM) consolidation is considered as an effective solution to deal with both overload and underload problems. However, dynamic VM consolidation is not a trivial solution as it can also lead to violation of negotiated SLA due to runtime overheads in VM migration. Further, dynamic VM consolidation approaches need to answer many questions such as (i) when to migrate a VM? (ii) which VM is to be migrated? and (iii) where to migrate the selected VM? In this work, efforts are made to develop a comprehensive approach to achieve better solution to above discussed problems. In the proposed approach, future forecasting methods for host overload detection are explored; a fuzzy logic based VM selection approach that enhances the performance of VM selection strategy is developed; and a VM placement algorithm based on destination CPU utilisation is also developed. The performance evaluation of the proposed approaches is carried out on CloudSim toolkit using PlanetLab data set. The simulation results have exhibited significant improvement in the number of VM migrations, energy consumption, and SLA violations.