Reviewerly/exHarmony huggingface dataset:
Kemampuan Menspesifikasi Topik Sebagai Bentuk Perwujudan Keterampilan Menulis Esai

Essay writing has the characteristic of focusing the discussion on one thing. The focus of the problem chosen is discussed widely and thoroughly. This research is a qualitative study conducted in the 2018/2019 academic year and funded by the Ministry of Research and Technology with the Beginner Lecturer Research scheme in 2019. The research was conducted at Musi Charitas Catholic University with a population of 382 writings and a sample of 180 random samples. The study was conducted with pen and paper based text, which provides writing texts to students studied. The students studied were asked to read the predetermined news text, analyze the topics contained in the news, then write a simple essay text based on the results of the analysis. The student's writing is then assessed by two people and the final grade is determined by calculating the average of the scores of the two assessors. This paper discusses the ability of students in writing specified on the character of the essay which is a reaction or statement of one's views on the topic discussed. Therefore, the expected text only focuses on one topic from a number of topics presented in the main text (news). The results showed 79.4% of students studied were not able to write essays that had one single topic. Students still explain the topics contained in the first text and do not strengthen their argument with evidence, but only explain the topics in the first text. There are only 12.2% of students who are able to write essay texts that describe one topic and complete it with supporting arguments and evidence.
Current philosophical problems of modern scientific knowledge

The article provides a philosophical analysis of the problems of modern science. It is noted that global problems come to the fore in terms of their importance and coverage of the population. Problems of a scientific nature among all global problems should be singled out in a special block. The authors distinguish between problems of science and problems in science. Problems of science are formulated in relation to science as an integral education and can be attributed to the philosophy of science. Problems in science are formulated within the Sciences as problems of their leading edge of development. The authors focus on the problems of the philosophy of science (its internal problems and philosophical problems of science as a certain integrity) and on the philosophical problems of individual sciences that attract attention by their special fundamental nature.
LibGuides: Thesis Collection: Finding Theses

The Pratt Institute Libraries have graduate theses produced by Pratt students going back to the 1960s.
Improving Methodological System for the Development of Managerial Competence of Heads of Higher Educational Institutions

This article discusses about the development of management skills and leadership potential of the higher education institutions and these establishments play an important role in improving the quality of education, effective organization of scientific and innovative activities in the country. Priorities have been identified for the development of proposals and recommendations on the meaningful and targeted organization of work on training, retraining, advanced training and development of scientific and innovative activities of teachers in the higher education system.
Analisis Pemanfaatan Media Pembelajaran Berbasis TIK di Sekolah Dasar Negeri Pengadilan 5 Kota Bogor

This study aims to determine the use of ICT-based learning media at SDN Negeri 5 Bogor City. The approach used in this study is qualitative with descriptive analysis. Data sources consist of school principals, teachers, and students. Data collection techniques performed Data collection is done by observation (in the form of a checklist), interviews, and documentation. The researcher tested the validity of the data by means of further observations, and triangulation of data. The results showed that the six aspects studied were (1) teacher knowledge of low category ICT-based media, (2) ability to use medium-based ICT media, (3) ability to create low-category ICT-based media, (4) relevance of media-based use ICT with low category learning objectives, (5) relevance of the use of ICT-based media with medium category learning material, and (6) relevance to the characteristics of high category students. Based on the results of research that has been carried out it can be concluded that the use of ICT-based learning media in SD Negeri Pengadialn 5, Bogor City is in the low category. Thus it is necessary for teachers and schools to conduct training in order to increase knowledge about technology-based media in accordance with the times. Kata kunci: Media Pembelajaran dan TIK
GEOPHYSICAL INTERPRETATION AND MODELLING OF THE SOUTHERN MCARTHUR BASIN, NORTHERN AUSTRALIA: IMPLICATIONS FOR SUB-BASIN DEVELOPMENT AND BASE METALS MINERALISATION

The Palaeo- to Mesoproterozoic McArthur Basin located in the north-east of the Northern Territory (Australia) is highly prospective for sediment hosted Zn-Pb-Ag mineralisation. Mineralisation is hosted within structurally controlled sub-basins, and several world-class deposits (e.g., McArthur River and Teena) have been discovered in the 50-80 km wide structural corridor known as the Batten Fault Zone. The Batten Fault Zone preserves a complex stratigraphic and fault architecture that developed during multiple episodes of extension and mild crustal shortening. The complex architecture and poor exposure of the basin has made recognition of sub-basins challenging. To better understand the regional structural architecture and sub-basin development, this study integrated geophysical interpretation and modelling with detailed sedimentology and sequence stratigraphy. Interpretation of gravity, magnetic, radiometric and AEM data helped to delineate the spatial distribution of sedimentary rocks and determine the extent and overprinting relationship of faults. Seven forward models of the gravity and magnetic data constrained by available seismic data were produced to understand the geometry of major faults and broad scale variations in the preserved thickness of stratigraphy. Integration of these results with a newly developed stratigraphic framework allowed observations of depositional cycles and shifting depocentres to be placed in context of the structural framework of the basin. Results from this integrated geophysical and geological analysis suggest two styles of sub-basins developed within the Batten Fault Zone under broadly north-south directed extension. These include transtensional sub-basins, which developed between segments of the north–northwest-trending Emu Fault Zone, and east–west-trending sub-basins developed adjacent to east–west-trending normal and north–northwest-trending transfer faults. Forward modelling of the gravity data also suggests the presence of a thick mafic volcanic pile located within basal sequences of the McArthur Basin. These volcanics are located proximal to known Pb-Zn-Ag deposits in the region and may have been an important source for base metals.
Research through Design (or Tokens, Trinkets and other Transitional Things)

This masterclass is focused on RtD as a strategy for developing games and other types of playfulness. We will consider the underlying ethos of speculative engagements and discuss how the building of props and other research products might allow different kinds of knowledge to emerge. The class will be online and as interactive as we can manage with the technology and situation at hand.
Controlling the entropic uncertainty and quantum discord in two two-level systems by an ancilla in dissipative environments*

The uncertainty principle is a crucial aspect of quantum mechanics. It has been shown that the uncertainty principle can be tightened by quantum discord and classical correlation in the presence of quantum memory. We investigate the control of the entropic uncertainty and quantum discord in two two-level systems by an ancilla in dissipative environment. Our results show that the entropic uncertainty of an observed system can be reduced and the quantum discord between the observed system and the quantum memory system can be enhanced in the steady state of the system by adding an dissipative ancilla. Particularly, via preparing the state of the system to the highest excited state with hight fidelity, the entropic uncertainty can be reduced markedly and the quantum discord can be enhanced obviously. We explain these results using the definition of state fidelity. Furthermore, we present an effective strategy to further reduce the the entropic uncertainty and to enhance the the quantum discord via quantum-jump-based feedback control. Therefore, our results may be of importance in the context of quantum information technologies.
Information Technology of Data Mining and Forecasting of Nonlinear Non-Stationary Processes

The article is devoted to the actual task - the information technology development for the data intellectual analysis and nonlinear non-stationary processes (NNP) forecasting. The study object are non-linear non-stationary processes in ecology, economics and finance. The necessity of development of information technology for data mining and forecasting of nonlinear non-stationary physical processes of different nature is grounded in order to increase the adequacy of mathematical models of nonlinear non-stationary processes and improve the quality of prediction estimates that are calculated using available models. The rules of its application are described. The mathematical apparatus used in the composition of information technology for solving problems of various nature data analysis is presented for the purpose nonlinear nonstationary processes forecasting. The results of information technology application for forecasting of such processes are resulted. The linguistic modeling method is described in detail. The content and mathematical formulation of the task of finding linguistic images of time series is formulated. The concept of linguistic modeling was introduced and the method of applying this approach was gradually described to solve the problem of prediction of nonlinear non-stationary physical processes of different nature. Also, for a more complete consideration of the roblem, additional subtasks were introduced, their mathematical statements were described, and examples of their execution were given. In the scientific researches course, nonlinearities and nonstationary aspects types were identified in modern environmental, financial and economic processes. NNP classification is made, the existing information technologies for the research of NNP analysis is carried out; processes for research are selected; the necessary statistics are collected; the forecasting function is constructed and estimates of forecasts for the selected processes are calculated. The the practical verification results of the use of the developed information technology for prediction of nonlinear non-stationary processes with the help of the linguistic modeling method are presented. The results of the comparative analysis of the developed method adequacy with some existing ones are analyzed and the quality of the obtained predictive values is analyzed. The analysis showed the high adequacy of the results obtained with the help of the developed information technology and high quality of the received forecasts.
Introduction to AR-Bot, an AR system for robot navigation

We introduce a system to assign navigation tasks to a self-moving robot using an Augmented Reality (AR) application running on a smartphone. The system relies on a robot controller and a central server hosted on a PC. The user points at a target location in the phone camera view and the robot moves accordingly. The robot and the phone are independently located in the 3D space thanks to registration methods running on the server, hence they do not need to be spatially registered to each other nor in direct line of sight.
Comparing Segmentation Approaches for Learning-Aware Wireframe Generation on Human Model

Abstract Wireframe has been proved very useful for learning human body from semantic parameters. However, the definition of the wireframe is highly dependent on the anthropological experiences of experts in previous works. Hence it is usually not easy to obtain a well-defined wireframe for a new set of human models in the available database. To overcome such difficulty, an automated wireframe generation method would be very helpful in relieving the need for manual anthropometric definition. In order to find such an automated wireframe designing method, a natural way is using automatic segmentation methods to divide the human body model into small mesh patches. Nevertheless, different segmentation approaches could have various segmented patches, thus resulting in various wireframes. How these wireframes affect human body learning performance? In this paper, we attempt to answer this research question by comparing different segmentation methods. Different wireframes are generated with the mesh segmentation methods, and then we use these wireframes as an intermediate agent to learn the relationship between the human body mesh models and the semantic parameters. We compared the reconstruction accuracy with different generated wireframe sets and summarized several meaningful design guidelines for developing an automatic wireframe-aware segmentation method for human body learning.
예비영어교사 교사교육 연구 동향 고찰: 학교현장실습을 중심으로

This article presents a systematic review of the studies on the field experience of both elementary and secondary preservice teachers of English as a foreign language (EFL) in Korea over the last 20 years (1999-2018). A total of 30 empirical studies were analyzed according to their publication date, educational level, methodology, and research themes. The results demonstrated that the field experience of preservice EFL teachers has gained prominence as a research topic since the mid- 2000s in the field of TESOL in Korea－with numerous studies being published during this period. More studies were conducted on the practicum of secondary preservice teachers than that of elementary preservice teachers. In investigating their field experience, diverse research methodologies were incorporated-ranging from quantitative to qualitative and mixed methods. A large number of the studies examined the overall experience of preservice teachers in the field, exploring their successes and challenges. There were also studies that examined the influence of the practicum on preservice teachers'' beliefs, perceptions, and teaching efficacy. Other themes such as preservice teachers'' reflective practice during their placement in the field and the learning community approach as a strategy to support preservice teachers were also examined. Research and educational implications are suggested based on the results of this review.
Comparison of Different Models for Clothing Images Classification Studies

In this paper, we employed three machine learning models, i.e., pure 5-layer convolutional neural network, VGG-16 model, and XGBoost algorithm model. We trained and tested these models on the Fashion-MNIST dataset. By comparing the classification accuracy and the training time, the results show that 1) the pure convolutional neural network is a very effective method for clothing images classification; 2) The complex structure of VGG 16 increases the training time, and the risk of overfitting; 3) XGBoost does not show the efficiency benefits of multi-threading on this issue.
Interactive Robot Art : A turn-based system for painting together with a robot

A large amount of people suffer from mental illnesses such as depression and autism. Receiving the care they need can be a very difficult process, with long queues and expensive bills. Automating p ...
YALESCHEME: Stata module providing a modern Stata scheme for Yale University-branded data visualizations

The Yale Stata scheme provides a quick set of options for modern-looking graphs from Stata using Yale colors. The scheme is designed for use by the Yale Economic Growth Center's Research Team when designing visualizations for presentations and social media. There are no restrictions on its use.
Key Technologies of Virtual Reality Fusion and Interactive Operation for Intelligent Learning in Network Environment

With the globalization development of educational informatization, information technologies such as Internet of Things, cloud computing and big data are constantly emerging. As the core and fundamental cornerstone of wisdom education, intelligent learning has come into people’s vision and received great attention from many foreign countries. However, the study of wisdom learning in China has just started. Based on this, this paper studies the further development of wisdom learning by combining the key technologies of virtual and real fusion and interactive operation. This paper firstly analyzes the research status of intelligent learning, discusses various interaction technologies, and proposes virtual and real interaction methods based on Kinect sensor instruction type and multi-channel type. These interaction methods can effectively control virtual objects and improve the stability, real-time and authenticity of the augmented reality interaction system. Then, this paper combined with the network learning platform to carry out an experiment on the scheme, the results show that the scheme effectively improves the learning efficiency of students in the network intelligent learning platform, the attendance rate increased by 11.27%.
A Specificity Effect Related to the Discourse Connectivity of Weak Crossover Phenomena

In this paper, I propose that the specificity effect is able to improve or override weak crossover (WCO) phenomena, since [+specific] features associated with D-linking elements overtly move in wh-questions. These crossover configurations have been described in terms of syntactic factors. Postal (1971, 1993) and Wasow (1979) both refer to these kinds of crossover phenomena. Strong Crossover (SCO) violates the crossover principle or Binding Condition C. In contrast, WCO phenomena have remained marginal. The local constraints are not available to explain the variation associated with discourse connectivity, which includes WCO phenomena, or to capture pragmatic variation in context. From the perspective of semantic and pragmatic approaches, I suggest that specificity related to discourse context is able to explain the degree of the grammatical acceptability of wh-phrases in WCO configuration.
Dynamic Query Processing for Hidden Web Data Extraction From Academic Domain

The web documents lying on WWW can be classified as hidden web and surface web. The web documents from surface web are indexable as well as crawlable by the search engines and hence they can be displayed to users as per their input query. In contrast to this, hidden web documents are neither indexable nor crawlable by the traditional search engines due to disconnected URL’s, no-index tag, user authentication, web form processing. Also, since the information is scattered across multiple web pages, users find it difficult to hop between multiple pages to find the desired information. Hence, there is dire need of hidden web crawlers which could extract the data from hidden web databases and uncover this big part of WWW. In this research, a novel framework “Dynamic Query Processing for Hidden Web Data Extraction (DQPHDE)” has been proposed to extract such hidden web data and integrate it with the data from surface web to meet user’s requirements. DQPHDE makes use of clustering, semantic based text mining and fuzzy rule based system to carry out the desired task. The results of the proposed work were compared with the existing academic search engines like ‘Microsoft Academic’ and ‘Academia.edu’ etc, and our proposed work outperforms them in fetching the information and then integrating the related information for other pages.
Discriminative Multi-label Model Reuse for Multi-label Learning

Traditional Chinese Medicine (TCM) with diagnosis scales is a holistic way for diagnosing Parkinson’s Disease, where symptoms can be represented as multiple labels. To solve this problem, multi-label learning provides a framework for handling such task and has exhibited excellent performance. Besides, it is a challenging issue of how to effectively utilize label correlations in multi-label learning. In this paper, we propose a novel algorithm named Discriminative Multi-label Model Reuse (DMLMR) for multi-label learning, which exploits label correlations with model reuse, instance distribution adaptation and label distribution adaptation. Experiments on real-world dataset of Parkinson’s disease demonstrate the superiority of DMLMR for diagnosing PD. To prove the effectiveness of the proposed DMLMR, extensive experiments on four benchmark multi-label datasets show that DMLMR significantly outperforms other state-of-the-art multi-label learning algorithms.
Improving testing reusability and automation for software product lines

Software product lines are widely used in industrial environments for developing complex software systems. One of the main advantages deriving from the adoption of this software engineering develop ...
An Attention-oriented U-Net Model and Global Feature for Medical Image Segmentation

ABSTRACTAiming at the problem that medical images are easily disturbed by various factors, resulting in uneven gray scale and blurred boundary, which increases the difﬁculty of segmentation. In this paper, we propose an attention-oriented U-Net model for medical image segmentation. The original convolutional layer is replaced by reside-density module, and the transpose convolution and scaling convolution modules are used for up-sampling. Meanwhile, the feature layers at different levels are processed by attention mechanism, which can extract more features and promote network convergence. Experimental results show that the proposed U-Net structure can improve the precision and efﬁciency of medical image segmentation.
Micro MICRO STRUCTURE ANALYSIS, LIGNIN CONTENT AND HEMICELLULOSE FIBER FROM PALM OIL DUE TO ALKALI TREATMENT:

The use of natural fibers from palm frond fibers in the manufacture of composite materials has its advantages,including high specific strength and modulus, low price, low density, lower population emissions, and is common or recyclable. The production of the material starts from the natural decomposition of the palm frond fibers. After the palm fronds have rotted, the process of extracting fibers is carried out using a cloth brush or beating them against the board so that the dirt is removed so that it gets the best fiber. Furthermore, the fibers were soaked in 5% NaOH solution for 1,2,3,4 hours and without NaOH treatment, after that, they were dried using an oven at 105 ° C. Tests carried out the lignin and hemicellulose content and the microstructure of the palm frond fibers with the effect of 5% NaOH treatment and without treatment. From the test results, it was found that the lowest lignin content was in 5% NaOH treatment for 4 hours 22.1030%, and the highest lignin content was in 5% NaOH treatment for 1 hour 29,8694%, and the highest hemicellulose was found without NaOH treatment, namely 26.6343% and the lowest was the need for NaOH for 1 hour 22,1164%. As well as the results of research on the microstructure of palm frond fibers without treatment and with 5% NaOH treatment for 1,2,3, and 4 hours, there were cavities in the fibers. The longer the treatment, the cavities become more open