Reviewerly/exHarmony huggingface dataset:
Practice Analysis on the Teaching Theory and Skills of English Translation

As a universal language, English makes a better communication between China and the developed countries, English language teaching has become increasingly important in more and more Chinese Schools. At the beginning, when Chinese students start to learn a second language, they need to translate the second language such as English into Chinese in the first hand, and this procedure will help them to understand and learn English better. For English language translation teachers, they need to research and create the suitable、effective method of learning English translation for most students constantly in order to improve the English translation learning efficiency of the Chinese students. The local culture of China is quite different from the culture of other English speaking countries. When our Chinese students study English language translation, at the same time, they need to learn the different culture in different countries and learn how to accept and face up the cultural background difference between our country and the other English speaking countries. In the meantime, during the time of teaching English translation, the English translation subject teachers need to guide the students to learn and understand the difference in practice, and help them to establish a comprehensive and correct idea of learning English translation (through teaching right and different translation skills.
Ted Nelson's Junk Mail

Ted Nelson invented hypertext and spent years developing and promoting Xanadu , a digital repository scheme for world-wide electronic publishing. Using modern web technology you can read his old junk mail.
LibGuides: COMM 2025: Fundamentals of Communication: Library Resources

A course guide for students in COMM 2025: Fundamentals of Communication. This guide will assist students in locating information in the JSCC Library for their speeches.
Identification needs and placement location of conservation building in upstream area with geographical information system

The upper course of water catchment areas is buffer area for conservation at the watershed. In upstream area there are also regions where also suitable for planting a variety of agriculture commodities. The activity can cause the accurence of erosion and land degradation, so as to encourage of the flow of sediment to major rivers. The sediment carried by the flow of run off is to downstream so that causes silting-up of the grooves river due to sedimentation, that decrease capacity of flow the river and causes overflow of the river so there was a flood. Base on the problem, required building for conservation there is retaining sediment building on a grooves at the upperstream to hold and controling the flow of sediment. Therefor reguired to identification of the needs and right location to exact placement of the retaining sediment building. Because the nature of the land on the upstream area are hilly condition used geographical information system (GIS) to assist in identification of the needs and to determination of site the retaining sediment building. The purpose of the research is to prevent and control the flow of sediment that accur in upstream area and flow into the major river. The objective of the study is to understand the needs and appropriate location to placement of retaining sediment building in the watershed. Research methods that used is using geographical information system which combined with class and level of erosion and the technical requirement of retaining sediment building. The result showing that geographical information system can help in assignment the appropriate site of retaining sediment building in the grooves of upstream areas. According 29 catchment areas in the watershed, 17 of the region in accordance to putting retaining sediment building and 12 region other not appropriate. The number of retaining sediment building that can built in the watershed there was 22 location/points.
Retrospective study to assess the impact of ranibizumab 0.5mg in the visual acuity of patients with macular diseases in a real life context

A melhora
Data governance and the emerging university

Knowledge and information governance questions are tractable primarily in institutional terms, rather than in terms of knowledge itself or individual or social interests. This Chapter offers the modern research university as an example. Practices of data-intensive research by university-based researchers, sometimes reduced to the popular phrase “Big Data,” pose governance challenges for the university. The Chapter argues that the new salience of data exposes emerging shifts in the social, cultural, and economic identities of the university, from missions defined in terms of distinctions between basic knowledge (research) and applied knowledge (suitable for technology transfer and commercialization), on the one hand, to missions now defined in terms of data and evidence, on the other hand. The concept of the data-intensive university offers a general outline of a new paradigm for aligning the university as an institution with social goals associated with information law and policy.
QUALITATIVE COMPARISONS OF ELICITATION TECHNIQUES INREQUIREMENT ENGINEERING

It is often emphasized that the quality of elicited requirement is mostly influenced by the elicitation techniquesemployed to gather software requirements. Many elicitation techniques have been presented in requirement engineering butthey are hardly adopted in practice as the available empirical and comparative evaluations are inadequate to guide thesoftware industry on which technique is better. Classifying a selection of seven requirement elicitation techniques ascollaborative, individual or contextual, this study compares the popular techniques using two groups of qualitative criteria -terms of information collection and quality of feedback information. The evaluation results are tabulated and the findingsare depicted by spider diagrams. The study concludes that each technique has its strengths and weaknesses, the factorssoftware engineers should weigh when selecting appropriate techniques for requirement elicitation.
The Journey from Entropy to Generalized Maximum Entropy

Currently we are witnessing the revaluation of huge data recourses that should be analyzed carefully to draw the right decisions about the world problems. Such big data are statistically risky since we know that the data are combination of (useful) signals and (useless) noise, which considered as unorganized facts that need to be filtered and processed. Using the signals only and discarding the noise means that the data restructured and reorganized to be useful and it is called information. So for any data set, we need only the information. In context of information theory, the entropy is used as a statistical measure to quantify the maximum amount of information in a random event.
A Case Study on Anxiety of University English Teachers as Visiting Scholars in Their Collaborative Learning

The study is to explore the test anxiety of three university English teachers in their collaborative learning community when they do their visiting scholar program.The research questions are about the representations of test anxiety of the college English teacher collaborative learning community as visiting scholars, and the interaction between anxiety and their collaborative learning.The main data collection includes deep interview, field observation, online chatting, etc.The research finds that at the three stages of their learning, the participant shows various representations of test anxiety from cognitive, affective and behavioral perspectives, and collaborative learning community facilitates the participant have better execution in learning, more pressure released and much cognitive enhancement achieved.In contrast, lack of collaborative learning environment in her working university and the specific anxiety for marriage in female participant are two additional findings in the study, which may prove the positive effect of collaborative learning on anxiety from another point of view.
Memetic Algorithm for Stochastic Inventory Optimization with Seasonal Demand

Due to the increasing complexity of logistics networks driven by rapid globalization and technological transformation, a naive inventory management leads to serious damage to both the business and its supply chain. Therefore, achieving and maintaining the optimal balance between cost reduction and customer service has become an important strategic concern for all types of organizations.In this thesis, we study a single item, single-echelon inventory replenishment system with stochastic seasonal demand and stochastic lead time. Our objective is to ﬁnd a time-varying, periodic review (T, Rt, Qt) policy that minimizes holding, ordering, reviewing and purchasing costs under a minimum ﬁll rate constraint. We propose a simulation-based stochastic optimization framework based on a new Memetic Algorithm (MA), which combines a Genetic Algorithm (GA) with a gradient-free Local Search Algorithm (LSA). The performance of the MA has been validated by solving a benchmark experiment with 18 diﬀerent test instances and by comparing the solution quality with a benchmark model. Furthermore, its performance and robustness have been evaluated with extensive tests and numerical analyses. Our computational experiments show that the proposed MA obtains signiﬁcantly better solutions than the benchmark method and that it is robust to problem parameters and inventory structures.
Organisation of the project – CYRail project

WP1 - Project Management WP2 - Operational Context and Scenarios WP3 - Security Assessment WP4 - Threat analysis, attack detection and early warning WP5 - Mitigation and Countermeasures…
A study and further development of nonlinear unsupervised methods : With applications to financial data

The main focus for this thesis is nonlinear dimensionality reduction. When analysing data of high dimension it is often vital to find a lower dimension representation of the data, while preserving ...
ANALYZING THE QUALITY OF FISRT ENGLISH SIMULATION TEST FOR NINTH GRADERS IN ACADEMIC YEAR 2016/2017

This research was used to know the quality of first English simulation test for ninth graders in academic year 2016/2017 in SMPN 7 Pasuruan. The quality consists of validity, reliability, item difficulty, discrimnating power, and item distractors.This research was designed into descriptive quantitative which produced the result by expressing numbers. The subject of this study were 258 ninth grade learners. The data was collected on 17th February 2017 using documentation. The result of this research was Code 1 had 96% as good validity, had 0.67 as high relability, had 52% moderate items of item difficulty, had more satisfactory items of discriminating power (26%), had 71% unworkable distractors in upper group and 57% in lower group, and had 21% inappropriate distractors. Code 2 had 100% as good validity, had 0.64 as high reliability, had 44% moderate items of item difficulty, had more satisfactory items of discriminating power (46%), had 72% unworkable distractors in upper group and 45% in lower group, and had 17% inappropriate distactors. Code 3 had 100% as good validity, had 0.37 as low reliability, had 48% moderate items of item difficulty, had more satisfactory items of discriminating power (38%), had 45% unworkable distractors in upper group and 30% in lower group, and had 26% inappropriate distactors. In conclusion, the researcher stated that each code had one lack to fulfill characteristics as a good test. Code 1 and Code 2 could not fulfill workable distractors. In other hand, Code 3 did not have high reliability. Keywords : discrimnating power, item difficulty, item distractors, reliability, validity.
Exact Kalman Filter for Binary Time Series

Non-Gaussian state-space models arise routinely in several applications. Within this framework, the binary time series setting provides a source of constant interest due to its relevance in a variety of studies. However, unlike Gaussian state-space models---where filtering and predictive distributions are available in closed form---binary state-space models require either approximations or sequential Monte Carlo strategies for inference and prediction. This is due to the apparent absence of conjugacy between the Gaussian states and the probit or logistic likelihood induced by the observation equation for the binary data. In this article we prove that the filtering and predictive distributions of dynamic probit models with Gaussian state variables belong to the class of unified skew-normals (SUN) and the associated parameters can be updated recursively via analytical expressions. Also the functionals of these filtering and predictive distributions depend on known functions, but their calculation requires Monte Carlo integration. Leveraging the SUN results, we address this point by proposing methods to draw independent and identically distributed samples from filtering and predictive distributions, thereby improving state-of-the-art approximate or sequential Monte Carlo inference in small-to-moderate dimensional dynamic models. A scalable and optimal particle filter which exploits SUN properties is also developed and additional exact expressions for the smoothing distribution are provided.
EVALUATION OF FORMATION OF LEGAL CULTURE IN THE EDUCATIONAL ENVIRONMENT BOARDING SCHOOL

The article deals with the problem of organization of the process aimed at the education of orphans to the culture of law in the space of boarding school. The results presented in this article - theoretical analysis and study of scientific approaches of teachers and scientists evaluation indicators of legal culture, development and scientific justification of criteria to measure the components of legal culture in orphans and children left without parental care. The methodological basis consists of system, personal, cultural, activity, polysubject (dialogical) approaches to the study of social and pedagogical phenomena; pedagogical ideas of humanization of education. As research methods used, empirical-observation, individual and group conversations, interviews, questionnaires, testing, study of school documentation (personal files of students, class journals, minutes of meetings, meetings) and pedagogical experiment; theoretical - analysis of philosophical and pedagogical literature. To determine the level of legal culture, the optional legal culture of the individual was introduced. Activity approach to the study of the concept of legal culture allowed to develop evaluation and criteria tools of levels of formation of legal culture of orphans and children left without parental care. Taking into account the analysis of the main approaches to the study of levels, indicators and criteria at the theoretical level, the article also presents the author's approach to the method of determining the criteria, indicators and levels of formation of legal culture in the educational space of the institution for orphans and children left without legal culture at the practical level. Criteria, indicators of formation of legal culture which are introduced and tested in educational process of boarding school are scientifically proved and developed. The proposed criteria and indicators can be used in various types of educational institutions to assess the level of education of legal culture of young people.
Stereo Matching through Squeeze Deep Neural Networks

Visual depth recognition through Stereo Matching is an active field of research due to the numerous applications in robotics, autonomous driving, user interfaces, etc. Multiple techniques have been developed in the last two decades to achieve accurate disparity maps in short time. With the arrival of Deep Leaning architectures, different fields of Artificial Vision, but mainly on image recognition, have achieved a great progress due to their easier training capabilities and reduction of parameters. This type of networks brought the attention of the Stereo Matching researchers who successfully applied the same concept to generate disparity maps. Even though multiple approaches have been taken towards the minimization of the execution time and errors in the results, most of the time the number of parameters of the networks is neither taken into consideration nor optimized. Inspired on the Squeeze-Nets developed for image recognition, we developed a Stereo Matching Squeeze neural network architecture capable of providing disparity maps with a highly reduced network size without a significant impact on quality and execution time compared with state of the art architectures. In addition, with the purpose of improving the quality of the solution and get solutions closer to real time, an extra refinement module is proposed and several tests are performed using different input size reductions.
High-Speed Free-Flight Wind Tunnel Experiment With A Compromised Quadrotor: Creating A Dataset Suitable For Identification Of Aerodynamic Forces and Moments

To aid in the continued effort of making unmanned flight safer, this paper presents the experimenting effort towards determining aerodynamic forces on a off-the-shelf quad-rotor under compromised circumstances. For the first time an Incremented Nonlinear Dynamic Inversion controller is used for compromised flight in wind tunnel conditions. For the Parrot Bebop v1, five aerodynamically different configurations were tested. These configurations include reduced rotor effectiveness on one or two rotors and the inclusion of one or two bumpers. In order to gather a suitable dataset for these highly dynamic models, free-flight model identification is deemed necessary. To facilitate free-flight aerodynamic model identification, data was provided by the on-board inertial sensors and a motion-tracking OptiTrack system. Sensor fusion through Extended Kalman Filtering was chosen to counter frame vibrations and sensor bias. A sufficient convergence rate was found for estimating the biases. Further modeling efforts are required to validate these results. A rotor rate Kalman Filter was also designed to improve rotor rate differentiation. Excitation of the system was performed with position-controlled doublets, designed to observe theoretical modes from existing quadrotor models. This resulted in five main types of excitation, designed to maximize yawing motions, thrust variation and drag effects. The differences seen for each configuration show interesting behavior, and further investigation is recommended. The resulting dataset is considered uniquely suitable for estimating coupled dynamics with saturated actuators and loss of yaw control.
Acceleration of expensive computations in Bayesian statistics using vector operations.

Many applications in Bayesian statistics are extremely computationally intensive. However, they are also often inherently parallel, making them prime targets for modern massively parallel central processing unit (CPU) architectures. While the use of multi-core and distributed computing is widely applied in the Bayesian community, very little attention has been given to fine-grain parallelisation using single instruction multiple data (SIMD) operations that are available on most modern commodity CPUs. Rather, most fine-grain tuning in the literature has centred around general purpose graphics processing units (GPGPUs). Since the effective utilisation of GPGPUs typically requires specialised programming languages, such technologies are not ideal for the wider Bayesian community. In this work, we practically demonstrate, using standard programming libraries, the utility of the SIMD approach for several topical Bayesian applications. In particular, we consider sampling of the prior predictive distribution for approximate Bayesian computation (ABC), the computation of Bayesian $p$-values for testing prior weak informativeness, and inference on a computationally challenging econometrics model. Through minor code alterations, we show that SIMD operations can improve the floating point arithmetic performance resulting in up to $6\times$ improvement in the overall serial algorithm performance. Furthermore $4$-way parallel versions can lead to almost $19\times$ improvement over a na\{i}ve serial implementation. We illustrate the potential of SIMD operations for accelerating Bayesian computations and provide the reader with essential implementation techniques required to exploit modern massively parallel processing environments using standard software development tools.
Semi-supervised feature sharing for efficient video segmentation

In robot sensing and automotive driving domains, producing precise semantic segmentationmasks for images can help greatly with environment understanding and,as a result, better interaction with it. These tasks usually need to be processed forimages with more the 2 object’s classes. Moreover, semantic segmentation should bedone for a short period. Almost all approaches that try to solve this task used heavyweightend-to-end deep neural network or external blocks like GRU [14], LSTM[25]or optical flow [1]. In this work, we provide a deep neural network architecture forlearning to extract global high-level features and propagate them among the imagesthat describe the same video’s scene, for speeding up image processing. We providea propagation strategy without any external blocks. We also provide loss functionfor training such network with the dataset, where the vast number of images don’thave a segmentation mask.
Conference report: innovation, interaction … and a lot of data: first time reflections on Internet Librarian International, UK 2018

Purpose The purpose of this paper is to summarise a number of presentations at Day 1 of the Internet Librarian International conference, London, UK (16 October 2018). This was the 20th conference in the series, and the three key themes included were the next-gen library and librarian; understanding users, usage and user experience; and inclusion and inspiration: libraries making a difference. Design/methodology/approach This paper reports from the viewpoint of a first-time attendee of the conference. This summarises the main issues raised by each presentation and draws out the key learning points for practical situations. Findings The conference covered a variety of practical ways in which libraries can use technology to support users and make decisions about services. These include developing interactive physical spaces which include augmented reality; introducing “chat-bots” to support users; using new techniques to analyse data; and piloting new ways to engage users (such as coding clubs). A key theme was how we use and harness data in a way that is ethical, effective and relevant to library services. Originality/value This conference focussed on practical examples of how library and information services across sectors and countries are innovating in a period of huge change. The conference gave delegates numerous useful ideas and examples of best practice and demonstrated the strength of the profession in adapting to new technologies and developments.
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Securing student records from closed Texas charter schools via the Texas Records Exchange (TREx)

PDF Version DATE: February 21, 2019 SUBJECT: Securing student records from closed Texas charter schools via the Texas Records Exchange (TREx) CATEGORY: New Resource Available
The Dynamic Earth, Earthquakes in Germany

In the early morning of April 13, 1992, the residents of the German-Dutch border area between Roermond and Düren, and as far as Cologne and Bonn, awakened from their sleep by tremors that caused bookshelves to tumble, cups to clank in the cupboards and tiles to fall from the roofs.
14. Redefining Reader and Writer, Remixing Copyright: Experimental Publishing at if:book Australia

His current research addresses the way the copyright regime impacts how memory institutions enable access to and use of our shared cultural heritage, online and across borders.In addition, he develops