Reviewerly/exHarmony huggingface dataset:
Using The KWL (Know, Want and Learn) Strategy to Improve Students’ Reading Comprehension” A Classroom Action Research at The Tenth Grade of Senior High School of SMA Islam Al-Bina Cadasari

AAT HERAWATI. 142301643. 2018, “ Using The KWL (Know, Want and Learn) Strategy to Improve Students’ Reading Comprehension” A Classroom Action Research at The Tenth Grade of Senior High School of SMA Islam Al-Bina Cadasari. The researcher investigates using The KWL (Know, Want, and Learn) strategy to improve students’ reading comprehension. The researcher conducted the research based on the main problems, 1) How is students’ reading comprehension at the tenth grade students of SMA Islam Al-Bina?, 2) How are students difficulties during learning using KWL (Know, Want, Learn) Strategy?, 3) How is the effect of KWL strategy in students’ reading comprehension. The aims of the research to find out the students’ reading comprehension at the tenth grade students of SMA Islam Al-Bina, to know students’ difficulties during learning using KWL strategy and to describe the process teaching used KWL strategy in teaching reading comprehension at Senior high school of SMA Islam Al-Bina Cadasari – Pandeglang. This research uses classroom action research. The research was conducted in two cycles and covered plan, action, observing, and reflection. the subject were 15 students of class X (tenth) SMA Islam Al-Bina Cadasari in the academic year 2017/2018. In this research, the individual criteria of success was 75. The result of the research shows that there were some improvements in the student’s reading comprehension. In the first Cycle, the highest score was 93, the lowest score was 53 and average of students’ score was 76,4, for the second cycle the highest score was 100, the lowest score was 73 and the average of the students’ score was 86,4. It showed that there was significant improvement of students’ skill in reading comprehension.Learning from the result, it can be concluded that the students’ reading comprehension can be improved by using KWL strategy. Therefore, there must be other research need to be conducted in the classroom action research. However, the KWL strategy can be a very useful instructional strategy as a teaching media when it is used effectively. It may refresent as a better strategy if it is compared with other teaching media.
Research of Improved Artificial Fish Swarm Portfolio Optimization Algorithm Based on Adaptive Levy Mutation

With the rapid development of the economy, the stock market is growing like mushrooms, and a large number of enterprises and individuals invest in all kinds of securities. In the stock market, the investment itself with a certain risk, some assets have high risk, and some assets with low risk, investors must choose which securities products to makes higher income, it is particularly important for different investors. It has become very important to choose the investment plan reasonably so that investors can get the highest return on acceptable risk level, which has become the focus of many scholars. The research of portfolio theory has a very important influence on the stock market. In the process of investment market, we select appropriate proportion of investment so that reduce the risk of investment, and access to greater income. At present, most of the intelligent optimization algorithms could be used to optimize the investment portfolio model. In view of the basic artificial fish swarm algorithm is easy to fall into local extreme value and the search speed is slow, this paper combine basic artificial fish swarm algorithm with Levy mutation. Computer simulation shows the improved algorithm has better convergent performance, And this paper takes the stock exchange price data of five stocks in Shanghai stock exchange for 100 days as an example. The improved algorithm is used to solve the investment portfolio model. Experimental results show that the income is increased, and the risk is reduced.
Constructive Formal Control Synthesis through Abstraction and Decomposition

Author(s): Kim, Eric Shinwon | Advisor(s): Arcak, Murat; Seshia, Sanjit A | Abstract: Control synthesis is the problem of automatically constructing a control strategy that induces a system to exhibit a declared behavior. Synthesis algorithms vary widely across different classes of system dynamics and specifications.While continuous optimization has traditionally been used to construct stabilizing controllers for physical systems modeled with differential equations, temporal logic synthesis for finite state machines heavily leverages discrete algorithms and data structures.Hybrid systems are a class of systems that exhibit both continuous and discrete behaviors, which are necessary to capture phenomena such as impacts for legged robots and congestion shockwaves in freeways. Tractable control synthesis remains elusive because hybrid systems violate many of the fundamental topological assumptions made by prior algorithms for purely continuous or discrete systems.This thesis exploits compositionality and system structure to provide a suite of algorithmic and theoretical techniques to tackle acute computational bottlenecks in hybrid control synthesis.The first half of this thesis provides a framework for engineers to model control systems and construct algorithmic pipelines for control synthesis.By explicitly capturing system structure, this framework gives users the flexibility to rapidly iterate over and leverage a library of optimizations for control synthesis.We demonstrate this framework in the context of abstraction-based control, a synthesis workflow that translates continuous systems into finite state machines by throwing away high precision information. Different optimization techniques such as multi-scale grids, lazy abstraction, and decomposed synthesis, can all be expressed as modifications to a computational pipeline. We demonstrate computational gains while synthesizing safe motion primitives for numerous robotic examples.The second half addresses distributed control synthesis where multiple controllers act as agents that seek to jointly satisfy a specification and are restricted by some communication topology. We introduce parametric assume-guarantee contracts as a formalism to derive guarantees about the closed loop behavior of a collection of interacting components. Dynamic contracts allow contract parameters to change at runtime and enable coordination of multiple interacting sub-systems.These results are demonstrated in the context of a freeway ramp meter and an adjacent arterial network.
From relational to technological trust: How do the IoT and Blockchain technology fit in?

The construction industry is complex, fragmented andstruggles to cope with an intricate and geographicallydiverse Supply Chain (SC) where sophisticated flowsof materials, information and capital take place in adynamic environment. In this context, building trustamong partners is a necessary requirement to deliver asuccessful project on time and on budget. This paperinvestigates the main factors that build inter-firm trustin large construction projects and explores thedisruptive effect that the Internet of Things (IoT) andBlockchain (BC) could have in this process. Thefindings are based on an in-depth analysis of theliterature and ten one-to-one telephone and face-toface interviews. The findings contribute to theliterature by suggesting that a Blockchain-enabled IoTecosystem has the potential to generate inter-firm trustat the front-end, during contract development, andthroughout the construction phase. Moreover, the datadenotes the need for further technological adoption inthe construction industry as a means of smoothing thetransition from relational trust to technological trust.
LibGuides: Getting Started at University: Online study guide

If you're new to university or returning to study after a break, this guide includes our top tips and guidance on finding your feet and information on how to develop your core academic skills.
RDA in Norway

Poster presented at the RDA 14th Plenary conference, arranged by Reseach Data Alliance, Helsingfors, 23.10.19 - 25.10.19. https://www.rd-alliance.org/plenaries/rdas-14th-plenary-helsinki-finland.
Optimizing for Robot Transparency

Author(s): Huang, Sandy Han | Advisor(s): Dragan, Anca D; Abbeel, Pieter | Abstract: As robots become more capable and commonplace, it becomes increasingly important that they are transparent to humans. People need to have accurate mental models of a robot, so that they can anticipate what it will do, know when and where not to rely it, and understand why it failed. This helps engineers ensure safety and robustness of the robot systems they develop, and enables human end-users to interact more safely and seamlessly with robots.This thesis introduces a framework for producing robot behavior that increases transparency. Our key insight is that a robot's actions do not just influence the physical world; they also inevitably influence a human observer's mental model of the robot. We attempt to model the latter---how humans might make inferences about a robot's objectives, policy, and capabilities from observations of its behavior---so that we can then present examples of robot behavior that optimally bring the human's understanding closer to the true robot model. In this way, our framework casts transparency as an optimization problem.Part I introduces our framework of optimizing for robot transparency, and applies it in three ways: communicating a robot's objectives, which situations it can handle, and why it is incapable of performing a task. Part II investigates how transparency is useful not just for safe and seamless interaction, but also for learning. When humans teach a robot, giving human teachers transparency regarding what the robot has learned so far makes it easier for them to select informative teaching examples.
PENINGKATAN HASIL BELAJAR MELALUI MODEL DISCOVERY LEARNING DENGAN PENDEKATAN SAINTIFIK

This reseach was conducted with Classroom Action Reseach in  two cycles. the aim of this reseach was to improve the learning process and the learning result on  through descovery learning model. The research sample was fourth grade consisted of 28 students, both are 12 boys and 16 girls. The research was conducted in odd semester of academic year 2018/2019. the result of the research shows that the learning implementation in first cycle got 67,5 in average and the second cycle got 86,25 in average. so does the result of the studen't behavior which shows the improvement. the average in firat cycle was 77,11 and second cycle was 82,14. the result of student's skill also shows the improvement. in the first cycle, it got 76,04 in average and the second cycle got 89,8 in average. the passing grade of the first cycle got 75% with the average score was 65. and the second cycle got 89% with the average score was 78.
Synthesis of the Two-Level Intelligent Hierarchical Control System of the Mobile Robot

The actual problems related to the operation of high-quality intelligent control systems under the conditions of autonomy of two-wheeled mobile robots have been investigated in the paper. The synthesis method of the two-level intelligent control system of two-wheeled mobile robot for a dynamic object written by a multiply connected nonlinear model is proposed. According to the proposed method, an algorithmic support of the synthesis problem of a two-level intelligent control system is developed on the bases of fuzzy logic and finite automata. One of the advantages of the proposed in the paper method is to provide the activity of a two-wheel mobile robot, quickly, with high dynamic accuracy and without collision with barriers in the environment of several obstacles.
Synthesizing 360-Degree Live Streaming for an Erased Background to Study Renovation using Mixed Reality

In a modern society, people spend more time indoors. Indoor Environmental Quality (IEQ) and its effect on occupants' health and comfort has become an important area of study. Many existing building stocks still have huge social, economic, and environmental value. There is a high demand for stock renovation, which gives existing buildings new lives, rather than building new ones. In the early stage of the renovation design, it is essential to achieve a timely feedback process as bring together stakeholders. Introducing Mixed Reality (MR) with Diminished Reality (DR) provides users with an indirect view of the world where some objects have been made invisible which makes it easier to display indoor renovation plans. This paper describes the development of an MR system for architectural designers that integrates DR results into the MR system. Aiming to provide a stable, realistic and real-time DR results for enhancing feedback efficiency during renovation design which can help stakeholders better understand or evaluate the renovation plan.
Evidências sobre o isolamento social em pacientes com exsudato em feridas neoplásicas: revisão integrativa

Objetiva-se identificar as evidências científicas sobre o isolamento social em pacientes com feridas neoplásicasexsudativas. Revisão integrativa realizada nas bases de dados da Biblioteca Virtual de Saúde (BVS) e PubMed: LiteraturaLatino Americana e do Caribe em Ciências da Saúde (LILACS), Medical Literature Analysis and Retrieval Sistem on-line(MEDLINE) e Cochrane Database of Systematic Reviews (COCHRANE) com a questão norteadora: quais são as evidênciascientíficas sobre o isolamento social em pacientes com feridas neoplásicas exsudativas? Utilizou-se estratégia PICOcom recorte temporal de 2002 a 2014, nos idiomas português, inglês e espanhol. As informações foram tabuladas emprograma Microsoft Excel® e processadas a partir da média aritmética descritiva simples, frequência absoluta e relativa.Identificaram-se 288 artigos em sua totalidade. Após aplicação dos critérios de elegibilidade, foram selecionadas 23evidências científicas avaliadas a partir da categoria: os principais aspectos psicossociais prejudicados pelo exsudatoem pacientes com feridas neoplásicas. Concluí-se que o exsudato é um dos sintomas que interfere negativamente nosaspectos psicossociais do paciente com feridas neoplásicas, causando alteração da imagem corporal, perda dos limitesfísicos, ansiedade e depressão, fatores que favorecem diretamente o isolamento social.Palavras-chave: Cuidados Paliativos; Enfermagem Oncológica; Ferimentos e Lesões; Exsudatos e Transudatos;Isolamento Social.&#x0D; ABSTRACTThe aim is to identify the scientific evidence on social isolation in patients with exudative neoplastic wounds.An integrative literature review conducted in the Virtual Health Library databases (VHS) and PubMed: LiteratureLatin American and Caribbean Health Sciences (LILACS), Medical Literature Analysis and Retrieval System online(MEDLINE) and Cochrane Database of Systematic Reviews (COCHRANE), with the guiding question: what are thescientific evidences about the social isolation in patients with exudative neoplastic wounds? We used a PICOstrategy with a temporal cut from 2002 to 2014, in Portuguese, English and Spanish languages. The informationwas tabulated in Microsoft Excel® program and processed from simple descriptive arithmetic mean, absoluteand relative frequency. It was identified 288 articles in their entirety. After applying the eligibility criteria, wasselected 23 scientific evidence evaluated from the category: the main psychosocial aspects impaired by exudatein patients with neoplastic wounds. It concludes that exudate is one of the symptoms that negatively interferesthe psychosocial aspects of the patient with neoplastic wounds, causing alterations in body image, loss of physicallimits, anxiety and depression, factors that directly favor social isolation.Keywords: Palliative Care; Oncology Nursing; Wounds and Injuries; Exudates and Transudates; Social Isolation.
HTMRL: Biologically Plausible Reinforcement Learning with Hierarchical Temporal Memory.

Building Reinforcement Learning (RL) algorithms which are able to adapt to continuously evolving tasks is an open research challenge. One technology that is known to inherently handle such non-stationary input patterns well is Hierarchical Temporal Memory (HTM), a general and biologically plausible computational model for the human neocortex. As the RL paradigm is inspired by human learning, HTM is a natural framework for an RL algorithm supporting non-stationary environments. In this paper, we present HTMRL, the first strictly HTM-based RL algorithm. We empirically and statistically show that HTMRL scales to many states and actions, and demonstrate that HTM's ability for adapting to changing patterns extends to RL. Specifically, HTMRL performs well on a 10-armed bandit after 750 steps, but only needs a third of that to adapt to the bandit suddenly shuffling its arms. HTMRL is the first iteration of a novel RL approach, with the potential of extending to a capable algorithm for Meta-RL.
Switching Strategy of Recommendation Algorithms in Online Dating Platform

With the popularity of online dating platform, more and more platforms want to recommend suitable candidates to users. However, the recommendation algorithms they used do not meet accuracy, coverage, and other requirements at the same time. Therefore, using many recommendation algorithms with a certain weight to mix together which often increases the difficulty of project architecture and causes some unnecessary losses in the recommendation process. This paper proposes a set of strategies for switching recommendation algorithms in different situations with a certain rule, which is compatible with the advantages of various recommendation algorithms, reduces the overhead caused by mixed recommendation results in a single recommendation, and facilitates the personalized diversity of the algorithm. This paper compares the recommendation system under multiple switching strategies with the individual recommendation algorithm, analyze its advantages and disadvantages, and draw a conclusion that several switching algorithms are generally higher in accuracy and coverage.
Geometric Trajectory Planning for Robot Motion Over a 3D Surface

Abstract Mapping a desired 2D pattern onto a curved surface has many applications. This includes motion planning for mobile robots to perform coverage path planing, robot end effector trajectory design for tasks such as printing, depositing, wielding on a 3D surface. This problem becomes more difficult if we want the mapped pattern to keep the properties of the original pattern (i.e, least possible mapping distortion), and pass over some desired points and/or remain bounded in a specific region on the surface. In this paper, we apply surface parameterization and mapping distortion analysis, which is rarely used in robot motion planning works, to map a pattern onto 3D surface. To meet additional goals such as passing over certain points, a planar mapping determined by constrained optimization is employed on the original pattern. Our focus is on printing/depositing materials on curved surfaces, and simulations and experiments are provided to confirm the performance of the approach.
LEARNING SCENE SPECIFIC RECONSTRUCTION OF MONTE CARLO PATH TRACED IMAGE SEQUENCES WITHOUT ADDITIONAL CLEAN DATA

When using deep learning models for reconstruction of one path per pixel Monte Carlo path traced image sequences, reconstruction of unseen features can be a concern. This can be solved by training ...
Upaya Meningkatkan Hasil Belajar IPA Siswa dengan Menggunakan Metode Demonstrasi pada Kelas VI SD Negeri 01 Durian Tinggi Kecamatan Kapur IX Kabupaten Lima Puluh Kota

This study aims to improve student learning outcomes in class VI State Elementary School 01 Durian Tinggi, because so far classical learning models have not been able to improve student learning outcomes. Data collection is carried out by observation, tests, and observation sheets. The results of the observations are then analyzed and made as an action planning material in the next cycle and then processed in order to draw conclusions. Based on preliminary observations, the initial data obtained about student learning outcomes is that 4 people get very good grades, 7 people get good grades, 20 people get pretty good grades and 1 person gets bad grades. Then the average grade obtained is 73.125. After being implemented in the first cycle, 10 people got very good grades, 15 people got good grades, 6 people got good grades and 1 person got bad grades. The average score of students in cycle I was 78.75. And after implementing the second cycle, 12 people get very good grades, 21 people get good grades, and no one gets good enough grades and less grades. The average score of students in cycle II is 83.98. Based on the results above we can conclude that student learning outcomes have experienced a very good improvement.Implications of the results of Classroom Action Research (CAR) by using the Demonstration method can improve the students’ learning outcomes and also have a positive effect on the activities of class VI students of SDN 01 Durian Tinggi.
Exploration Method of Stone Statue Based on Nondestructive Testing Technology-Taking Xinchang Maitreya Statue as an Example

Non-destructive detection of cultural relics has always been a difficult issue.To effectively detect the degree of weathering in the superficial layer of the Maitreya statue in Xinchang grotto, the microwave humidity nondestructive testing technology was used to detect the humidity of 328 points of the Maitreya statue.For the internal materials of the irregular Maitreya statue, taking moisture detection as the object, the infrared thermography and the microwave humidity method were used to detect the calf parts of the statue respectively, and the weathering degree obtained was basically the same.Results show that the infrared thermography method and the microwave humidity method are suitable for the internal looseness detection of the irregular Maitreya statue and the result has a certain reliability.The conclusions obtained in the study are of the reference value to the similar engineering.
“Reporting or Interpreting?”—A Discoursal Study of Broadcasts on NBA Games in China

From the perspective of empirical discourse analysis, this paper identifies the site broadcasters’ roles and cognitive blending process in NBA (National Basketball Association) broadcasts in China. The authors find that NBA broadcasters chiefly interpret the information they have obtained from sports sites and interviews with the coaches and players, employing various interpreting strategies, such as commentary, amplification, supplementation and restructure. Cognitively, the language that NBA broadcasters applied reveals their cognitive blending process of interpreting techniques, strategies, sports knowledge and attitudes towards the games, of who take up different roles to fulfill different communicating purposes, all of which project various cognitions on NBA games. Despite the fact that one role might make certain linguistic behaviors prevail over the others, especially their interpreting role, NBA site broadcasters coordinate it with other roles properly through which they present different levels of translational and constructional schematicity, thus yielding a coherent and constructional working mode of NBA broadcasting practice in China.