Reviewerly/exHarmony huggingface dataset:
UNVEILING THE LAYERS OF L.O.L. SURPRISE: AN ANALYSIS THROUGH THE GRAMMAR OF VISUAL DESIGN

The L.O.L. Surprise doll was created in 2016 by MGA Entertainment inspired by theYouTube trend of “unboxing” videos, in which children and adults open toyspackages, or other objects, and show to the viewers how it works or what it does.Being a collectible toy with the possibility of more than a hundred surprise dolls,L.O.L. Surprise, which is a best seller, explores playing from the unwrapping of theseveral layers involved in the unboxing of the doll’s package. The marketing of L.O.L.Surprise does not involve TV advertisements and all its strategy is focused onYouTube videos showing kids unboxing the toy. It is possible to perceive that openingthe package, and consequently finding the doll, is part of the experience/play ofL.O.L. Surprise. Since the rise of the North American doll L.O.L. is a trend not only inBrazil but all around the world (FROMM, 2019), it is a rising successful trend in lastyears (GREEN, 2018), this study aims at describing and analyzing the multimodalfeatures of the layers of the doll’s package, perceiving how the surprise element isconstructed through it. Therefore, to analyze the layers of the package, we will drawon Kress & Van Leeuwen’s Grammar of Visual Design (2006) and its visualmetafunctions, which derive from Halliday’s Systemic Functional Linguistics (1978).The description and analysis reveal a stimulus to children’s curiosity, enhanced bythe interactive aspect perceived through the verbal and visual language, as well as atendency towards consumerism and social media engagement
Isabelle/Spartan -- A Dependent Type Theory Framework for Isabelle

This paper introduces Isabelle/Spartan, an implementation of intensional dependent type theory with cumulative universes as an object logic in the Isabelle proof assistant. In contrast to other systems supporting dependent type theory, Isabelle is based on simple type theory -- yet I show how its existing logical framework infrastructure is able to handle automation tasks that are typically implemented on the source code level of dependently-typed systems. I also go some way in integrating the propositions-as-types paradigm with the declarative Isar proof language. Isabelle/Spartan supports book HoTT and the univalence axiom, and its capabilities are demonstrated by the formalization of foundational results from the Homotopy Type Theory book.
Benchmarking qubit quality and critical subroutines on IBM's 20 qubit device

As superconducting qubits continue to advance technologically, the realization of quantum algorithms from theoretical abstraction to physical implementation requires knowledge of both quantum circuit construction as well as hardware limitations. In this study we present results from experiments run on IBM's 20-qubit `Poughkeepsie' architecture, with the goal of demonstrating various qubit qualities and challenges that arise in designing quantum algorithms. These include experimentally measuring $T_1$ and $T_2$ coherence times, gate fidelities, sequential CNOT gates, techniques for handling ancilla qubits, and finally CCNOT and QFT$^{\dagger}$ circuits implemented on several different qubit geometries. Our results demonstrate various techniques for improving quantum circuits which must compensate for limited connectivity, either through the use of SWAP gates or additional ancilla qubits.
LibGuides: ACL 2020: Beyond All Limits!: Dining in Wichita

A guide to all things ACL 2020 Annual Conference at Newman University in Wichita, Kansas. We look forward to hosting the conference at our school and we are ready to welcome you to our school and our community. A guide to local favorites
KESIAPAN BELAJAR SISWA MENJALANI SEKOLAH LIMA HARI DI KOTA SAMPIT

To undergo a five-day school there is a need for learning readiness from the students concerned. This research was conducted to determine the learning readiness of students undergoing five-day school in Sampit 1 Junior High School.The population in this study were students of the 8th grade 2018/2019 Middle School 1 grade, which numbered 278 students and were taken as a sample of 72 students using the Proportional Random Sampling technique. The results of quantitative descriptive analysis show that the readiness of students to undergo a five-day school in SMP Negeri 1 Sampit has a high category with a percentage of 23.61%, a medium category with a percentage of 62.50% and a low category with a percentage of 13.89%.
TEACHERS’ STRATEGIES IN TEACHING SPEAKING AT SMP NEGERI 18 MEDAN

This research is aimed to find the teachers’ strategies in teaching English. This study was conducted to the eight grade students of SMP N 18 Medan. The research was conducted by using descriptive qualitative research design. The intruments used in this research were observation and interviewd. The researchers needed few days in collecting the data. From the data analysis, the researchers found that the strategies used by the teachers in teaching speaking were role play, drill and listen and repeat strategy.
Image Alignment and Stitching: A Tutorial

This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. This tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It ends with a discussion of open research problems in the area.
Analyzing Character Education in EnglishReading Material

This research is aimed to find out the character education values in readingmaterials of English textbook in MAN 2 Model Banjarmasin which ispublished by Yudhistira and Tiga Serangkai. This research used the textbookthat is used by the eleventh grade of Senior High School as a handbook. Thisstudy is a descriptive qualitative research by doing content analysis. Inconducting the research, the researcher analyzed the reading materialsprovided in the textbook by analyzing the material and determined the genreand character education value of the text. Then, the researcher interviewed theteachers to define assessment for character education value in teaching andlearning English. Throughout the analysis, the researcher found 16 charactereducation values are inserted in reading text material, involve: religious,honest, tolerance, discipline, work hard, creative, independent, democratic,curiosity, the spirit of Nationality, love homeland, rewarding achievement,friendly/communicative, love peace, joy of reading, environmental care, socialcare, and responsibility. The teachers assess the character education valuesdirectly and joined with other evaluation, in the form of Affective. Therefore,the finding of this research is expected to the teacher could define or createtheir own rubric score to assess character education value in teaching reading
BERT Can See Out of the Box: On the Cross-modal Transferability of Text Representations.

Pre-trained language models such as BERT have recently contributed to significant advances in Natural Language Processing tasks. Interestingly, while multilingual BERT models have demonstrated impressive results, recent works have shown how monolingual BERT can also be competitive in zero-shot cross-lingual settings. This suggests that the abstractions learned by these models can transfer across languages, even when trained on monolingual data. In this paper, we investigate whether such generalization potential applies to other modalities, such as vision: does BERT contain abstractions that generalize beyond text? We introduce BERT-gen, an architecture for text generation based on BERT, able to leverage on either mono- or multi- modal representations. The results reported under different configurations indicate a positive answer to our research question, and the proposed model obtains substantial improvements over the state-of-the-art on two established Visual Question Generation datasets.
Intelligent Bilingual Data Extraction and Rebuilding Using Data Mining for Big Data

In today’s World there exists various source of data in various formats (file formats), different structure, different types and etc. which is a hug collection of unstructured over the internet or social media. This gives rise to categorization of data as unstructured, semi structured and structured data. Data that exist in irregular manner without any particular schema are referred as unstructured data which is very difficult to process as it consists of irregularities and ambiguities. So, we are focused on Intelligent Processing Unit which converts unstructured big data into intelligent meaningful information. Intelligent text extraction is a technique that automatically identifies and extracts text from file format. The system consists of different stages which include the pre-processing, keyphase extraction techniques and transformation for the text extraction and retrieve structured data from unstructured data. The system consists multiple method/approach give better result. We are currently working in various file formats and converting the file format into DOCX which will come in the form of the un-structure Form, and then we will obtain that file in the structure form with the help of intelligent Pre-processing. The pre-process stages that triggers the unstructured data/corpus into structured data converting into meaning full. The Initial stage is the system remove the stop word, unwanted symbols noisy data and line spacing. The second stage is Data Extraction from various sources of file or types of files into proper format plain text. The then in third stage we transform the data or information from one format to another for the user to understand the data. The final step is rebuilding the file in its original format maintaining tag of the files. The large size files are divided into sub small size file to executed the parallel processing algorithms for fast processing of larger files and data. Parallel processing is a very important concept for text extraction and with its help; the big file breaks in a small file and improves the result. Extraction of data is done in Bilingual language, and represent the most relevant information contained in the document. Key-phase extraction is an important problem of data mining, Knowledge retrieval and natural speech processing. Keyword Extraction technique has been used to abstract keywords that exclusively recognize a document. Rebuilding is an important part of this project and we will use the entire concept in that file format and in the last, we need the same format which we have done in that file. This concept is being widely used but not much work of the work has been done in the area of developing many functionalities under one tool, so this makes us feel the requirement of such a tool which can easily and efficiently convert unstructured files into structured one.
Constructing Multiple Teaching System of Instrumental Analysis Experiment Based on Network Platform

There are several problems in the current experimental teaching of instrumental analysis. Students are not motivated to preview the experiment and have rare opportunities to practice. The student achievement assessment and teaching evaluation cannot be well quantified. To solve these problems, the multiple teaching system of instrumental analysis experiment was constructed for students based on a network platform from previewing the experiment to practicing in scientific research. A number of teaching stages have been implemented, including the exam, setting papers for examination, instrument booking for research purpose, and examination paper analysis to find out the weak link of teaching. It is necessary for the “question-answer” teaching in laboratory and network platform aided teaching to be combined together. Through practice researching, the average score of the students taught by the reform method was increased by 2.26 points. The multiple teaching system based on the network platform can play a positive role in training innovative and application-minded talents.
Detection of Cervical Cancer Based on Learning Vector Quantization and Wavelet Transform

Cervical cancer has became the common women dsease in the world. Mostly, cervical cancer has been already known lately, because it is very dificult to detect this in early stage. In this work, a computer based software using Learning Vector Quantization (LVQ) has been designed as the early cervical cancer detection aid tool. There are six methods before the detection is performed, namely preprocessing, contrast stretching, median filtering, morphology operation, image segmentation, and Wavelet Transform based feature extraction. In tihis work, 73 cervical cell images that consist of 50 normal images and 23 cancer images are used. 35 normal images and 14 cancer images are used to train the LVQ. Then, 23 normal images and 9 cancer images are used in the testing process. Our results show 88,89 % cancer image can be detected correctly (sensitivity), 100 % normal image can be detected corerctly (specificity), and 95,83 % for overall detection (accuracy).
THE USE OF INFORMATION GAP METHOD IN SPEAKING CLASS AT MTS RIYADLUL MUHTADIN PEGANTENAN PAMEKASAN IN THE ACADEMIC YEAR OF 2018/2019

This study is focus on the implementation of information gap method and the students` response to the implementation of information gap method in teaching speaking skill by one english teacher who taught twenty one students in IX IPS class at MTs Riyadlul Muhtadin Pegantenan Pamekasan. This study was aimed to describe the the use of Information Gap method in teaching speaking by considering the implementation of group work, choosing interesting material and applying some procedures, then they did the activities consisted of incomplete information in the form of text. Then each groups performed asking and question in front of the class to completing the task. This study also describe the students` response to Information gap method, there were 90.47 % of the students were attracted to learn by using Information Gap Method. Furthermore, the information-gap activities could grab the students’ attentions, make them enjoyed the material during the class, and enthusiastically joined the teaching and learning activities.
A cryptographic cloud-based approach for the mitigation of the airline cargo cancellation problem

In order to keep in good long-term relationships with their main customers, Airline Cargo companies do not impose any fee for last minute cancellations of shipments. As a result, customers can book the same shipment on several cargo companies. Cargo companies try to balance cancellations by a corresponding volume of overbooking. However, the considerable uncertainty in the number of cancellations does not allow to fine-tune the optimal overbooking level, causing losses. In this work, we show how the deployment of cryptographic techniques, enabling the computation on private information of customers and companies data can improve the overall service chain, allowing for striking and enforcing better agreements. We propose a query system based on proxy re-encryption and show how the relevant information can be extracted, still preserving the privacy of customers’ data. Furthermore, we provide a Game Theoretic model of the use case scenario and show that it allows a more accurate estimate of the cancellation rates. This supports the reduction of the uncertainty and allows to better tune the overbooking level.
Blockchain-Based Multi-UAV Surveillance System

This paper describes a framework for a Multi-UAV surveillance system based on a blockchain allowing to coordinate the UAVs and to manage financial exchanges between the different users. The objective of the system is to allow a set of Points-Of-Interest (POI) to be surveyed by a set of autonomous UAVs which cooperate to minimize the time between successive visits while having an unpredictable behavior to prevent external agents from learning their movements. The system can be seen as a marketplace where the UAVs are the service providers and the POIs are the service seekers. It is based on a blockchain embedded on the UAVs and on some nodes on the ground which has two main functionalities. The first one is to organize the routes of each UAV through an efficient Game Theoretical decision algorithm implemented in a smart contract. The second one is to allow financial transactions between the system and its users: the POIs subscribe to surveillance services by buying tokens and the UAVs are paid in tokens for the provided services. The first implementation tests show that the IOTA blockchain could be a good blockchain candidate to be integrated in the multi-UAV surveillance system already developed in our lab.
Automatic Spam Detection on Twitter Based on Content and Online Social Interaction

Twitter is one among the principal normal little blogging administrations, that is for the most part familiarised offer news and updates through short messages. At present, in general consecration a cross breed approach for sleuthing programmed spammers by amalgamating network principally based choices with various element classes, explicitly metadata-, content, and collaboration based choices. The oddity of the anticipated methodology exists in the portrayal of clients bolstered their co-operations with their adherents up to a client will avoid choices that zone unit related with his/her own exercises, anyway evasion those upheld the supporters is inconvenient. Nineteen very surprising alternatives, just as six new plot choices and two reclassified choices, zone unit known for learning three classifiers, in particular, random forest, call tree, and Bayesian network, on a genuine dataset that contains kind clients and spammers.
Penerapan Model Pembelajaran Cooperative Learning untuk Meningkatkan Motivasi Belajar pada Mata Kuliah Kapita Selekta Pendidikan Mahasiswa FKIP UNISRI

Learning is a daily activity for students. there are also learning activities that do not include lecturer designs, because of the students' own desires. There are several motivational theories, among others: encouragement theory, intensive theory, achievement motivation theory, competency motivation theory, and motivation needs theory. cooperative learning system or cooperative learning is a teaching system that provides opportunities for fellow students to work together on structured tasks. Cooperative learning is known as group learning. This research is a Classroom Action Research (CAR) which can also be called development research. The study was conducted in 2 cycles, by applying methods in cooperative learning. Based on the discussion that has been done in the previous chapter, in general, it can be concluded that the application of STAD type cooperative learning methods can increase student motivation in the Capita Selekta Education Course. This was evidenced by the average student motivation in the high category in both Cycles I and Cycle II with a percentage of 56.25 and 62.50%. With an increase in student motivation significantly also affect the results of learning evaluations with a complete score category&gt; 75.&#x0D;
A Bilingual Ontology Mapping and Enrichment Method for Domain Ontologies in E-learning

English language is accepted as international language for publishing research in e-learning and Semantic Web area, but people are needed from representing data and knowledge in his native language.This paper proposes an approach for mapping and enrichment of domain ontologies, labeled in two natural languages (bilingual ontologies).Our approach combines syntactical, structural and semantic mapping.It also can reuse existing mappings and use learner's or expert's feedback to improve mapping.We discuss the application of our approach for mapping ontologies describing e-learning content.
Deep Neural Networks for Out-of-sample Classification of Nonlinear Manifolds

In information processing domains, high dimensional data poses several challenges in terms of storage, visualization, and retrieval. There are several instances where, even though the data points are of high dimension, the data actually resides on a lower dimensional space. Dimensionality reduction methods attempt to find meaningful representation of data which is present in the lower dimension leading to better visualization, removal of noisy features and redundant information. Traditional linear dimensionality reduction techniques are incapable of dealing with nonlinear datasets. Nonlinear dimensionality reduction methods like Isomap work well for such datasets, but suffer from the issue of out-of-sample extension. In this paper, a solution for out-of-sample problem of Isomap method and extended Isomap method is put forward by employing neural networks. Out-of-sample extensions of Isomap and extended Isomap using deep neural network (DNN) are proposed. The proposed method is tested using AT&T face database, Yale face database, and MNIST handwritten digit database. The proposed technique is compared with the existing out-of-sample extension method using general regression neural network (GRNN).
LibGuides: LIS 2004 Research Strategies for College Students: Module One

LIS 2004 is a one-credit hour course. The course focuses on methods of accessing information resources available through the Internet. Adapted from: Author/Creator (Digital Rights Manager) Helene Gold [goldh], goldh@tcc.fl.edu Topic Selection and Keywords
The Kaizen Agent : A self-driving car continuously learns by imagination

For an agent to autonomously interact in a real world environment, it needs tolearn how to behave in the different scenarios that it may face. There are differentapproaches of modeling an artificia ...
Vibration Measurement Accuracy of Time-averaged Digital Holographic Interferometry

In this research, I confirmed the accuracy of vibration mode measurement of copper plate for application measurement of time-averaged pulse strobe digital holography interferometry. Laser displacement meter and time-averaged pulse strobe digital holographic interferometry were used to confirm the accuracy of the amplitude quantity. Time-averaged pulse strobe digital holography interferometry can record the maximum displacement of vibration and can visualize the displacement state by using a light chopper with a duty ratio of 50%. The test piece is fixed in a cantilevered manner, and the vibration mode is excited by direct vibration by the vibrator. The displacement of this method was compared with the displacement of the laser displacement meter to confirm the vibration measurement accuracy of this method. The vibration modes of the copper plate were measured from the first to fifth modes. As a result of comparing each measurement data, a difference of about 0.5 μm occurred at the maximum.