Reviewerly/exHarmony huggingface dataset:
Assisting authors to convert raw products into polished prose

Being a notoriously complex problem, writing is generally decomposed into a series of subtasks: idea generation, expression, revision, etc. Given some goal, the author generates a set of ideas (brainstorming), which he integrates into some skeleton (outline, text plan, outline). This leads to a first draft which is submitted then for revision possibly yielding changes at various levels (content, structure, form). Having made a draft, authors usually revise, edit, and proofread their documents.We confine ourselves here only to academic writing, focusing on sentence production. While there has been quite some work on this topic, most writing assistance has mainly dealt with grammatical errors, editing and proofreading, the goal being the correction of surface-level problems such as typography, spelling, or grammatical errors.We broaden the scope by also including cases where the entire sentence needs to be rewritten in order to express properly all of the information planned. Hence, Sentence-level Revision (SentRev) becomes part of our writing assistance task.Obviously, systems performing well in this task can be of considerable help for inexperienced authors by producing fluent, well-formed sentences based on the user’s drafts.In order to evaluate our SentRev model, we have built a new, freely available crowdsourced evaluation dataset which consists of a set of incomplete sentences produced by nonnative writers paired with final version sentences extracted from published academic papers. We also used this dataset to establish baseline performance on SentRev.
New Extraction Technologies Lining Up to Be Game-Changers

The first installment of this column examines the development of various extraction technologies.
LibGuides: Getting to Know the Human Body: Home

This guide is to help 5th grade students studying the human body at Tyro Elementary with their research projects.
LibGuides: Cloud and Networking Infrastructure Management: Specialized Databases

This guide is for the NCU specialization Cloud and Networking Infrastructure Management. It contains resources available in the NCU Library.
Library Guides: Collaborative Research Tools: Tips for Remote Collaborative Research

This guide features library resources and other freely-available products that students can use to collaborate remotely.
On the applicability of software attestation techniques to embedded systems.

Software has been developed around any aspect of technology in the last few years. It has become a core part of every device, not only for personal use but also in industrial and automotive environments. A direct raise in security issues has come with its spread, particularly for programs executing in third-party contexts. A company's income might rely on software operating on devices it does not own (take smartphones for example). If physical control is not an option, an attacker can open the device, attach a debugger and potentially tamper its software. The only possible defense is to detect these attacks and take the proper countermeasures. Software attestation is a technique through which the integrity of a program can be monitored remotely. A valid example of software attestation procedure is the ASPIRE project's remote attestator. This project offers a complete framework for binary protection, but its structure and its dependencies create a problem in terms of portability. This paper elaborates on two issues. The first regards the possibility of solving the ASPIRE remote attestator's portability problems. A standalone test version of the remote attestator was extracted from the ASPIRE project. This detachment removes some dependencies and increases its portability. The second point is an analysis of the extent to which this attestation procedure can be ported to different platforms. The attestator's requirements were discussed and analyzed during this work. The results suggest that the attestator should be adaptable to most of the embedded operating systems on the market. The attestator alone does not provide complete protection of the binary since there are various methods to bypass its checks. Nevertheless, it is a valuable option to add along with other protection mechanisms. This study also shows it is portable to embedded systems, which makes it a remarkably valuable technique.
Real-time Learning and Planning in Environments with Swarms: A Hierarchical and a Parameter-based Simulation Approach

Swarms can be applied in many relevant domains, such as patrolling or rescue. They usually follow simple local rules, leading to complex emergent behavior. Given their wide applicability, an agent may need to take decisions in an environment containing a swarm that is not under its control, and that may even be an antagonist. Predicting the behavior of each swarm member is a great challenge, and must be done under real time constraints, since they usually move constantly following quick reactive algorithms. We propose the first two solutions for this novel problem, showing integrated on-line learning and planning for decision-making with unknown swarms: (i) we learn an ellipse abstraction of the swarm based on statistical models, and predict its future parameters using time-series; (ii) we learn algorithm parameters followed by each swarm member, in order to directly simulate them. We find in our experiments that we are significantly faster to reach an objective than local repulsive forces, at the cost of success rate in some situations. Additionally, we show that this is a challenging problem for reinforcement learning.
Penerapan Model Picture And Picture dalam Meningkatkan Aktivitas dan Hasil Belajar Pembelajaran Tematik Siswa Kelas II SD

This study aims to improve the activities and learning outcomes of thematic learning in grade II elementary school students through the application of picture and picture models. The research method used was classroom action research (clascroom action research) with a cycle of Kemmis and Taggart using 4 stages namely planning, action, observation, reflection. Research subjects with 27 students consisting of 14 men and 13 women. The results of the study stated that an increase in student activity and learning outcomes in thematic learning in class II, this can be seen from the increase in the average acquisition of student activity scores in the first cycle obtained an average score of 31 increased to 35.5 with a good category in the second cycle. Then the learning outcomes are proven from the average value and the percentage of student learning in the form of cognitive, affective and psychomotor values. Cognitive Value The highest average value is in the natural science subjects at 84.16 with the percentage of student learning reaching 100% and the lowest average value in mathematics subjects at 80.83 with the percentage of student learning only reaching 83.39%. Affective value, the highest percentage of criteria namely in SBK, Natural Sciences and Civics reached 88.88% or as many as 24 people and the lowest percentage of criteria namely in mathematics subjects only reached 81.48% or as many as 22 people. Psychomotor scores, the highest percentage of criteria namely SBK, Natural Sciences and Civics reached 88.88% or as many as 24 people and the lowest percentage of criteria namely in Mathematics and Social Sciences subjects only reached 85.18% or as many as 23 people. The conclusion is that the application of picture and picture models in grade II elementary schools can increase the activities and learning outcomes of thematic learning.
Guides @ UF: Course Reserves for George A. Smathers Libraries: Warning of Copyright Restrictions

Learn about Course Reserves and how they can contribute to your teaching and learning experiences.
LibGuides: Guide to Searching: Overview

Develop a search strategy using keywords and boolean operators. Dig deeper to learn about different ways to search and locate information.
Privacy, Data Protection and Security in the Context of Direct-to-Consumer Genetic Testing Services

This chapter provides a broad overview of privacy, data protection and security issues raised by DTC services. This includes discussion of the EU’s General Data Protection Regulation (GDPR), the UK’s Data Protection Legislation, and a brief discussion of US and Canadian Privacy Law. It also covers secondary use of genetic databases, the Future of Privacy Forum’s Privacy Best Practices for Consumer Genetic Testing Services, and Indigenous Peoples and Data Sovereignty.
Writing articles about tourism destination to promote wandernesia website at PT Korina Prima Sinergi

ABSTRAKThe purposes of this report are to describe my internship program activities, the problems that I faced, and the solutions. I had produced 41 articles of  tourism destination. To produce good articles, I did three steps in my writing process. The steps are choosing the place, collecting the reference and data, and writing.The problems that I faced during writing articles were grammar and diction. I had the solutions for those problems. I was looking for grammar and vocabulary using some dictionaries. I also ask help from my friend who had an internship program in the same place with me to revise and give suggestion for my translation.
How To Change The Name Of Your iPhone Or iPad

Are you happy with the name of your iPhone? Does it have a generic name or a unique name that truly represents you? In this blog post, I will tell you ...
Prior-Knowledge Addition to Spatial and Temporal Classification Models with Demonstration on Hand Shape and Gesture Classification

The neural networks have been extensively used for tasks based on image sensors. These models have, in the past decade, consistently performed better than other machine learning methods on tasks of computer vision. It is understood that methods for transfer learning from neural networks trained on large datasets can reduce the total data requirement while training new neural network models. These methods tend not to perform well when the data recording sensor or the recording environment is unique from the existing large datasets. The machine learning literature provides various methods for prior-information inclusion in a learning model. Such methods employ methods like designing biases into the data representation vectors, enforcing priors or physical constraints on the models. Including such information into neural networks for the image frames and image-sequence classification is hard because of the very high dimensional neural network mapping function and little information about the relation between the neural network parameters. In this thesis, we introduce methods for evaluating the statistically learned data representation and combining these information descriptors. We have introduced methods for including information into neural networks. In a series of experiments, we have demonstrated methods for adding the existing model or task information to neural networks. This is done by 1) Adding architectural constraints based on the physical shape information of the input data, 2) including weight priors on neural networks by training them to mimic statistical and physical properties of the data (hand shapes), and 3) by including the knowledge about the classes involved in the classification tasks to modify the neural network outputs. These methods are demonstrated, and their positive influence on the hand shape and hand gesture classification tasks are reported. This thesis also proposes methods for combination of statistical and physical models with parametrized learning models and show improved performances with constant data size. Eventually, these proposals are tied together to develop an in-car hand-shape and hand-gesture classifier based on a Time of Flight sensor.
Game Training In Mathematics Of Elementary School Students

The training games have a considerable developing effect because they form in children’s thinking accurately certain, designed in advance logical structures and also the general and specific intellectual actions by means of which the child will be able to solve both standard, and non-standard mathematical tasks (they are developed exactly for this purpose). In the article the content of a regional component of the all-professional and special disciplines determining professional motivation of students in the game training in mathematics in the Republic of Tatarstan is disclosed. Also the theoretical justification and experimental approbation of system of the training games creating prerequisites to mastering school students in further training the major mathematical concepts (a variable, compliance, function, the equation, negative and positive numbers), the ideas of informatics (an algorithm, the flowchart, the count, the computer) and logicians (true and false statements, a justification problem, the proof) is presented. Forms of classroom work with students promoting their effective professionally motivating training such as academic competitions, tournaments, contests, quizzes, mathematical sophisms, tasks-jokes, illusions, modeling, entertaining tasks (historical and logical), logical mini-tasks, logical endings, mathematical labyrinths, mathematical excursions and practical works on the area are present-ed. In general, results of experimental and development work allow telling about relevance of the offered regional component content of the professional focusing training of students in discipline for choice Game training in mathematics.
A mixed-methods approach to characterize Knowledge-Rich Contexts for specialized translation

The notion of Knowledge Rich Context has proved efficient for various aspects of terminological analysis. However, such contexts are not very often displayed in resources available to users. Following the growing interest among the translation research community for user-oriented empirical studies, we investigated how KRCs, in combination with other resources, are used during the translation process, in particular through two experiments carried out in 2014, involving 42 trainee translators. The unusually large number of participants and the amount and diversity of the data gathered allowed us to ponder over the usefulness of a “mixed-methods approach”. Although the combination of both approaches led us to some conclusive findings regarding, for instance, the design of the interface or the type of KRC most wished for by translators, it also had some limitations that need to be discussed, such as its time-consuming side and the need for coherent criteria to deal with the very heterogeneous data. This finally leads us to draw some conclusions on the qualification of KRCs when applied to translation.
Samsung One UI Home Is Great – Find Out Why

In this blog post, I will explain what is Samsung One UI and I will tell you everything you need to know about it. If you ...
LibGuides: School Safety: Websites

This guide is for the subject of School Safety. It contains resources available in the NCU Library.
A Digital Platform Design for Supply Chain of Existing Fish Market in Bangladesh

The research was conducted to reveal the scenario of the supply chain of the existing fish market in Bangladesh. Fish is one of the great sources of protein for the people in Bangladesh. But unfortunately, the quality of the fishes that we are buying from markets is often questionable, and the price is also very high. The current supply chain consists of so-called middlemen who are controlling the entire fish market, and they are one of the significant reasons for overpricing of fishes. The fishermen, who are the actual provider of the fishes, are not getting sustainable profit comparing to the market price. To ensure the exact scenario, we surveyed both fishermen and consumers. The primary data of this research was collected directly through survey questionnaires. In this paper, we have proposed an infrastructure that will eliminate all the middleman from the market and provide a direct connection between fishermen and consumers through a real-time app. Our proposed system will minimize the cost of fishes and provide the best quality fish from the river to the consumers. Besides, our designed system will help the fishermen to earn more and make more profit than before.
The Virtual Market Place : Connecting Women-Owned Small and Medium Sized Enterprises to E-Commerce Platforms in Middle East and North Africa Region

This Brief is part of the Solutions for Youth Employment (S4YE) Knowledge Brief series focusing on the design and implementation of youth employment programs. This Brief builds on S4YE’s 2018 annual report, Digital Jobs for Youth: Young Women in the Digital Economy, which highlighted new and emerging strategies for practitioners designing digital jobs interventions for youth. In this Knowledge Brief, authors examine how the World Bank’s ‘E-Commerce for Women-Led SMEs’ project addresses the constraints faced by small, and medium-sized enterprises (SMEs) run or managed by women operating in: Algeria; Djibouti; the Arab Republic of Egypt; Jordan; Lebanon; Morocco; and Tunisia. The authors specifically highlight how the World Bank seeks to support women-led SMEs (WSMEs) in the Middle East North Africa region (MENA) in accessing global markets through e-commerce platforms, and the strategies used to help WSMEs to access financial resources, develop capacity, and increase sales. Driving the jobs agenda of the World Bank, the Jobs Group has developed a paradigm that focuses not only on creating more jobs, but also on creating better and more inclusive jobs. The authors showcase the ‘E-Commerce for Women-Led SMEs’ project to illustrate how projects can achieve key jobs outcomes by helping young, female entrepreneurs to increase their income and productivity. The MENA e-commerce Project is part of the World Bank Group’s Women Entrepreneurs Finance Initiative (We-Fi), a joint global initiative of the World Bank and International Finance Corporation that tests innovations and scales up successful pilots under three thematic pillars, strengthening entrepreneurial ecosystems, expanding financial services, and improving market access, and includes research, investment, advice, partnerships and peer-learning efforts. The program aims to reach 43,000 women entrepreneurs and catalyze 40,000 loans to WSMEs.
Research Guides: Remote Cowles Library Resources & Support: Instructor Resources

Resources and services to assist with remote learning and instruction during the COVID-19 crisis
LibGuides: Library Research Navigator: Destination 1: Pre-Proposal Stage: Idea Development

Your preliminary source of information and guidance as you begin or continue with your research journey.
Internet of Things-Based Smart Security Provisioning Using Voice-Controlled Door Locking System

The use of Internet of things (IoT) allows transformation of a conventional door locking into an automated door locking system that leads to smart security system at home. The IoT-based door locking system can detect home user, monitors for authentication, manage locking/unlocking the door, and alert home users if any intruder is identified. To ensure the smart security, a double-layer security has been proposed that includes user authentication and voice recognition. At the first layer, a user will be authenticated using his own smartphone and his body dimension using Kinect sensor. At the second layer, user will be authenticated using his voice, as well as the system will control the door using his voice command. The system includes a mobile application that will be used to alert home user in case of unauthorized access to home. A system architecture has been proposed and demonstrated to validate the system.
UCC LibGuides: Game Design and Development: Finding Books

This guide is designed for students in the Game Design and Development A.A.S. (Associate in Applied Science) program.
ANALYSIS OF CLASSIFICATION PROCESS FOR VIDEO SCENE UNDERSTANDING

Scene understanding is a process observing scenes which humans are used as models to understand them. This project is focused on analyzing the classification process for video scene. The algorithm used in this project will later be evaluated to see its performance. The process starts with human action video obtained from KTH dataset as the input for video processing. In the frame process, important information will be extracted from the video images accordance to frame sequence where Spatial Temporal -Interest-Point (STIP) is used based on Harris’ Corner detection. The human motions will then be classified by utilizing K-Nearest Neighbor (K-NN) method into their desired group of actions such as walking, running, or clapping. K-NN is an effective classifier since it works well with small datasets. However, K-NN does not work well with large datasets because it required longer timeframe.
Research Guides: Asian Library Remote Resources and Services: Home

This guide supports Asian Library users as they study, teach and conduct research from home.
Multi-channel system of quantum key distribution with frequency coding based on the AMPM-PMAM electro-optical scheme

In this paper, we propose the option of constructing a multi-channel system of quantum key distribution with frequency coding based on the AMPM-PMAM electro-optical scheme, using a Comb generator, multiplexer and demultiplexer to form a set of parallel quantum subchannels. The AMPM-PMAM work of the QKD system is based on the modulation conversion of the photon carrier based on the Ilyin-Morozov method and its one- and two-modulator implementations. The application of this scheme will significantly increase the transmission speed of the quantum key, allow the use of several levels of cryptographic protection, reduce the likelihood of achieving a positive result in PNS attacks of Eve (illegal subscriber) by eliminating the carrier from the structure of the signal transmitted through the quantum key distribution channel, and splitting information about key to different independent quantum channels.
Research Guides: Watch, learn & discover: Ask a Librarian

Upgrade your skills and hear stories from our reference desk with these videos. There are four series to explore: Ask a Librarian, Our Online Collections, Tech Tips and Creators.
Important Features Extraction by using POS Tag Pattern of Dependency Relation for Online Movie Reviews

With the emerging of web technologies, online reviews become trending and lead to the progression of sentiment analysis research. Feature extraction is the most important task in sentiment analysis of online reviews. This task is enable to help researcher to differentiate between relevant and irrelevant features in sentiments. The relevant features will kept for later process while the irrelevant features will be discarded. Dependency relation is one technique that can be used in features extraction process. By manipulating the dependency relation between words in reviews, the most important features can be identified. However, not all types of dependency relation are able to extract the important features. In this paper, the most useful of specific types of dependency relation with POS tag pattern for extracting the important features from movie reviews dataset is proposed. The proposed pattern will be used to filter out the relevant features that later will send to the classification process. By doing this, it will increase the classification accuracy as well as decrease the time taken for classification process.