Reviewerly/exHarmony huggingface dataset:
Teaching reading through cornell notes strategy

The purposes of the research are to describe the implementation, advantages and disadvantages, and solution from disadvantages of teaching reading by using Cornell Note strategy. The research uses descriptive qualitative research as approach and type of research. The sources of data are social situation, participant, and document. The techniques of collecting data are observation, interview, and documentation. To know the validity of the data, the researcher uses methodology triangulation. The technique of data analysis are data condensation, data display, conclusion and verification.The result of the research shows that the implementation of Cornell Note strategy has three steps included pre-activity, whilst- activity, and post- activity. The pre-activities include greeting, praying, checking students’ attendence and explaining the purpose of the meeting. The whilst- activities, the teacher explains how the procedures to read the text by using Cornell Note strategy. The procedures are prepare the worksheet, takes note in right column, write the question in left column, summarize information in bottom space, recite the note. Lastly, post- activities include reviewing and making resume of the material. The advantages are; first, can help the students to analyze the important information in the text. Second, motivate to read a text. Third, train the students’ concentration. Lastly, make the students enjoy in learning reading. Meanwhile, the disadvantages are; first, the students are difficult to know the meaning of the word in the text and make the question with correct structure into English. Besides, the solutions for the disadvantages of implementation Cornell Note strategy are; first, the teacher gives axamples the students to make a simple question. Second, the students can search a difficult word in the dictionary. In this research, the researcher also gives suggestions for the teacher, students, the school and the onther researchers.
PERCEPTION OF KNOWLEDGE IN THE AREA OF DIGITAL COMPETENCES BY SECONDARY SCHOOL TEACHERS

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 2417-2425ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.0643Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
XSlit cameras for free navigation with depth image-based rendering

In free navigation applications, any viewpoint to a three-dimensional scene can be synthesized through Depth Image-Based Rendering (DIBR). In this paper we show that XSlit cameras achieve up to 3 dB PSNR gain over conventional pinhole camera arrays when synthesizing virtual views to the scene with DIBR for small camera displacements.XSlit cameras are a type of general linear cameras where the light rays pass through two non-intersecting slits instead of a single point (the optical center of conventional cameras), resulting in a different epipolar geometry and projection equations. Instead of synthesizing virtual views with DIBR from a set of conventional pinhole cameras, e.g. a stereo camera pair, a single XSlit camera exploits the distance between its slits and their relative rotation to obtain disparity, out of which DIBR virtual views can be synthesized. We first present a theoretical study to present the parameters of XSlit cameras, different from pinhole cameras, at the same time making sure that the XSlit camera is physically implementable. We then validate the study with DIBR achieved on synthetic content using perfect depth maps obtained from an in-house modified version of Blender’s engine Cycles to simulate XSlit cameras. The virtual view synthesis uses an adapted version of the Reference View Synthesis software used in MPEG, the worldwide standardization committee for media compression. Our experiments show that for the same overall space covered by the studied camera architectures, XSlit cameras often obtain better DIBR view synthesis results, with up to 3 dB PSNR gain.
Teaching Students Mathods of Self-Regulation in Solving Mathematical Tasks

Actual problem of modern theory and methods of teaching mathematics – teaching methods of self-regulation in the process of solving mathematical tasks.
Development of a Reinforcement Learning Inspired Monte Carlo Tree Search Design Optimization Algorithm for Fixed-Wing VTOL UAV Propellers

A novel Monte Carlo Tree Search Optimization Algorithm that is trained using a Reinforcement Learning approach is developed for the application to geometric design tasks. It is capable of evaluating design parameters and demonstrates the successful application of reinforcement learning strategies on a physics informed design optimization task. The algorithm is intended to be used for the parametric design of the optimal geometry of a propeller for Fixed-Wing VTOL UAV but is also applied to an aircraft design problem with ease.
Cooperative Privacy Preservation for Internet of Vehicles with Mobile Edge Computing

The mobile edge computing is an attractive system paradigm to perform the local data processing and interactions at the edge of networks. The mobile edge computing enabled the internet of vehicles (MEC-IoV) is emerging as a convergence of the internet of things and mobile vehicular networks. The virtual vehicle shadow based privacy preservation scheme is proposed to address the cooperative scenarios, in which predictive location and segmented secret are jointly considered for protocol design. Meanwhile, the MinHash based similarity computing and the selective disclosure mechanism are respectively introduced for location and identity privacy preservation. The proposed scheme launches a new perspective of cooperative privacy preservation in the MEC-IoV with enhanced security requirements; it is suitable for the cooperative edge computing applications.
Research on Intention Recognition Method Based on Radial Basis Function Neural Network

A robot should be endowed with certain collaboration experience to recognize human’s behavioral intention. This paper provides a method based on machine learning to recognize the collaborator’s intention. A radial basis function neural network model was built for offline practice of a robot to recognize intention. Some collaboration skills can be obtained by the robot by building a map between the collaborator’s intention and the system state, deducing human’s intention based on the dynamic characteristics of collaborator and robot and taking the collaborator’s intention as the feedforward information for controlling the robot so as to estimate the human’s intention online based on collaborator’s force and robot’s motion characteristics during collaboration. The proposed method can overcome the difficulties in building the human-robot collaboration model by traditional method, especially the complicated human motion model, and difficulties in estimation of impedance parameters of human body. An experiment was conducted on a motion platform with single degree of freedom. The results prove that the collaborator’s force is reduced while synchronization of human-robot collaboration is improved, so that the compliance of collaborated motion is also improved.
Implication via Spacetime

In this paper we intend to study implications in their most general form, generalizing different classes of implications including the HeytingHeyting, A. implication, sub-structural implications and weak strict implicationsStrict implication. Following the topological interpretation of the intuitionistic logicIntuitionistic logic, we will introduce non-commutative spacetimes to provide a more dynamicDynamics and subjective interpretation of an intuitionistic proposition. These combinations of space and time are natural sources for well-behaved implications and we will show that their spatio-temporal implications represent any other reasonable abstract implication. Then to provide a faithful well-behaved syntax for abstract implications, we will develop a logical system for the non-commutative spacetimes for which we will present both topological and KripkeKripke, S. semantics. These logics unify sub-structural and sub-intuitionist logics by embracing them as their special fragments.
Multiple DOF platform with multiple air jets

We have been studying noncontact object manipulation technology in which a single ball-shaped object is floated and controlled for its 3D position with multiple air jets driven by a pan-tilt actuator. In this paper, we try to control position and orientation of an arbitrary shaped object. Here an arbitrary object is connected with a triangle platform which is composed of three spheres linked with thin wires. Each sphere is spatially controlled by an air jet unit which consists of an air jet on a pan-tilt actuator. Kinematics of the air jet platform as a parallel link mechanism is calculated and a control method for the air jet platform is proposed.
Novel Is Not Always Better: On the Relation between Novelty and Dominance Pruning

Novelty pruning is a planning technique that focuses on exploring states that are novel, i.e., those containing facts that have not been seen before. This seemingly simple idea has had a huge impact on the state of the art in planning though its effectiveness is not entirely understood yet.We relate novelty to dominance pruning, which compares states to previously seen states to eliminate those that are provably worse in terms of goal distance. Novelty can be interpreted as an unsafe approximation of dominance, where states containing novel facts are relevant because they enable new paths to the goal and, therefore, they are less likely to be dominated by others. This provides a framework to understand the success of novelty, resulting in new variants that combine both techniques.
A Comprehensive Analysis of Classification Methods for Big Data Stream

Traditional tools for mining the big data have become insufficient due to ever-growing data in the world. For handling big data, real-time and distributed processing is adopted. From so many mining tools options, it can be difficult for a researcher to opt an efficient tool. This paper is intended to aid the researcher who understands WEKA but is inexperienced with big data. The preliminary stage of data mining is classification, which categorizes the data into predefined groups. In this paper, WEKA with MOA package is used to classify big data stream with four different classifiers. Performance of these classifiers is analyzed on the basis of accuracy, i.e., correctly and incorrectly classified instances, time taken to test the model, and time taken to build the model. For this particular scenario, obtained results prove that naive Bayes is the most accurate classifier and decision stump is least effective classifier for big data.
Using Web Pages Dynamicity to Prioritise Web Crawling

Web crawling is a process performed to collect web pages from the web, in order to be indexed and used for displaying the search results according to users' requirements. In addition, web crawlers must continually revisit web pages, to keep the search engine database updated. Moreover, it is fundamental to determine in the crawling process, the most important pages to be recrawled first. This is to avoid the time limitation and network issues that face the web crawling process. Thus, this research attempts to introduce a method that is used to indicate the crawler, specifically, in order to identify in what order it should recrawl web pages that have been crawled before, as to acquire more important and valuable pages earlier than others. In addition, the researchers proposed a web crawling strategy which is based on the topic similarity, accompanied with the dynamicity of web pages, where the crawler was downloading relevant pages and recrawling them recursively. Also, every time a change emerged in one of the pages, its counter increased. Therefore, if the page was relevant and changed frequently it would be considered an important page and was given a high priority in the crawling process. The obtained results indicated that using web pages' dynamicity is an effective way for prioritising web pages in the crawling process, in order to obtain the highest dynamic pages first, as there is a high possibility of being changed in terms of their content, before the least dynamic ones.
Control of Eye-And-Hand type robot arm by visual servoing based on visual space

The complexity of the trajectory of the robot in the feature-based visual servoing is caused by the nature of the deviation used for control and the content of the relationship Jacobian generating the motion of the robot therefrom.Therefore, in this research, we focus on the fact that the visual space coordinate deviation is obtained from the image coordinates in the Eye-And-Hand type robot arm, and propose a visual space based visual servoing with the deviation part as the visual space coordinate deviation of the feature point.Since the control is such that the deviation of the visual space coordinate is minimized, it is considered that occurrence of unexpected movement can be suppressed.
Resource Construction and Distribution Analysis of Internal Structure of Modern Chinese Double-Syllable Verb

In this paper, we analyze the necessity of the construction of internal structure resources of verbs from the perspectives of linguistics and NLP application. We also introduce the method and process of the internal structure annotation of double-syllable verbs in Modern Chinese Dictionary (7th Edition). A total of 9697 double-syllable verbs are annotated. From the results of the annotation, it is found that there are 61.19% of words with a character inside the word as the center of the verb. Among them, the words with verb-object structure is the most (64.5%), followed by the adverbial-head structure (27.77%). This paper can provide basic resources for syntactic and semantic analysis so as to realize the unified analysis of lexicon and syntax.
Unsupervised adaptation of PLDA models for broadcast diarization

Abstract We present a novel model adaptation approach to deal with data variability for speaker diarization in a broadcast environment. Expensive human annotated data can be used to mitigate the domain mismatch by means of supervised model adaptation approaches. By contrast, we propose an unsupervised adaptation method which does not need for in-domain labeled data but only the recording that we are diarizing. We rely on an inner adaptation block which combines Agglomerative Hierarchical Clustering (AHC) and Mean-Shift (MS) clustering techniques with a Fully Bayesian Probabilistic Linear Discriminant Analysis (PLDA) to produce pseudo-speaker labels suitable for model adaptation. We propose multiple adaptation approaches based on this basic block, including unsupervised and semi-supervised. Our proposed solutions, analyzed with the Multi-Genre Broadcast 2015 (MGB) dataset, reported significant improvements (16% relative improvement) with respect to the baseline, also outperforming a supervised adaptation proposal with low resources (9% relative improvement). Furthermore, our proposed unsupervised adaptation is totally compatible with a supervised one. The joint use of both adaptation techniques (supervised and unsupervised) shows a 13% relative improvement with respect to only considering the supervised adaptation.
THE RELATIONSHIP BETWEEN TOTAL QUALITY MANAGEMENT AND SERVICE QUALITY IN HIGHER EDUCATION OF UAE

The impact of Total quality management (TQM) on service quality is significant and could enhance the quality of education service of higher education institutions. TQM represents a set of factors to achieve sustainable success for service organizations such as universities and colleges through implications of certain quality principles such as decision making process, customer focus, leadership, education process approach, continuous improvement, relationships management, and engagement of people. The influences of these factors on service quality of higher education institutions in UAE have been examined in this study using quantitative approach based on Pearson collection coefficients to measure the strength of association of TQM factors with service quality within higher education context. Two institutions are selected to conduct the quantitative survey. The result of this study indicates that TQM factor have moderate and strong association with service quality of UAE universities and colleges. It is recommended to implement all factors of TQM without exemption to deliver high educational service for students in UAE or other countries. Article visualizations:
A Location-Aware Authentication Model to Handle Uncertainty in IoT

The process of authentication for location-aware services is more challenging over the Internet of Things (IoT) than before due to a number of inherent IoT characteristics like dynamism and heterogeneity. Authentication in such an environment is no longer dependent only upon credentials but rather needs more spatio-temporal parameters (i.e. Time, Location) to be considered. Moreover, big data produced by IoT enabling technologies like wireless sensors, RFID tags and mobile phones introduce new challenges in terms of real-time authentication. This work defines one of the neglected challenges in IoT called uncertainty in authentication. Considering this challenge is important because IoT has a number of characteristics that amplify uncertainty in authentication. Moreover, using existing access control models does not result in flexible and resilient solution to handle uncertainty. Therefore, this work introduces an uncertainty-aware authentication model based on Attribute-Based Access Control (ABAC), which uses spatio-temporal parameters as attributes. Our model can achieve authentication performance with 86.92% accuracy with lower overhead using Neural Networks.
Sensor-Based Weightlifting Workout Assisting System Design and Its Practical Implementation

The paper is devoted to the problem of counting repetitions and automatic weight stack detection in a weightlifting machine used for weight training. Some weightlifting machines include a weight stack that can be adjusted by a user. For example, the user can choose to increase or reduce the weight load using the weight stack, thus changing the difficulty level of a particular exercise. Users may want to perform a desired number of repetitions of an exercise or to perform an exercise with a desired range of motion when using such weightlifting machines. From a medical point of view, it is often required that an exact number of repetitions of a given load are performed in order to aid in a prompt recovery. This paper describes a complete design of the system and the algorithm that allows one to collect data from such a machine. Data can then be used for various purposes: in overviews and statistical analysis of a number of workouts. The approach presented in this paper is part of an application for European patent number 18461537.5-1126.
A Feature Selection Method Based on Adaptive Differential Evolution

This paper proposes a feature selection method based on adaptive differential evolution-ISHADEFS. By using mutual information and Pearson correlation coefficient to construct a new fitness function, the enhancement effect of correlation and similarity is used to improve the efficiency and accuracy of filtering. A triangular mutation operator is improved, and the operator diversity is enhanced by the operator adaptive structure to improve the performance of the algorithm. The experimental results show that compared to conventional filtering methods and original evolution methods, ISHADEFS can achieve better classification performance.
Development of lock mechanisms using Jizaikagi mechanisms for forceps force limiter

In previous study, I developed a forceps force limiter which uses leaf spring buckling. However, the maximum stress of the buckled leaf spring might exceed the allowable stress because this mechanism does not limit the displacement of the leaf spring. This paper proposes a lock mechanism of the force limiter which applies the friction mechanisms of ”Jizaikagi”. The shape of ”Jizaikagi” is slender, which enables to install it in forceps. If the displacement of the buckled leaf spring exceeds the threshold value, then this mechanism locks the handles of the proximal side. The developed lock mechanism has 12 mm in thickness, and I confirmed that the proposed mechanism locked the handles when grasping force was 13 N.
Learning Non-verbal Behavior for a Social Robot from YouTube Videos

Non-verbal behavior is crucial for positive perception of humanoid robots. If modeled well it can improve the interaction and leave the user with a positive experience, on the other hand, if it is ...
A Development of Fuel-Debris Retrieval Robot for the Decommissioning Robot Contest

In this paper, we describe a fuel debris picking-up mobile robot for the Creative Robot Contest for Decommissioning. Our robot has an extendable telescopic arm with gripper utilizing the convex rule, and has 2 crawlers. In addition, it has an omnidirectional camera equipped on robot ’s body and a micro USB camera. The former is for surrounding view, and the latter is for forward view. Our robot is remote-controlled through wired Ethernet by utilizing ROS system. In the contest, our robot could not achieve all competition task. However, it had shown the ability to extend its arm to the bottom of the pedestal to confirm the existence of simulated debris, and return to base safely within the time limit.
A Computational Approach to Source Adaptation in Thomas Malory’s &lt;i&gt;Morte Darthur&lt;/i&gt;

The many source texts that late medieval adaptors like Thomas Malory worked with constitute a potential wealth of information concerning the genesis of the linguistic and stylistic features shaping their works. As a result, their texts provide a useful framework for further developing and testing methods of stylometric analysis in the context of adaptation as a collaborative form of authorship. Our interdisciplinary team has undertaken a stylometric analysis of the eight different sections of Thomas Malory’s <em>Morte Darthur</em>, in order to identify differences between these sections and how they correspond to the language of the Old French and Middle English sources that Malory is known to have worked with in the different sections of his work. Our findings provide a basis for addressing unresolved scholarly questions concerning Malory’s Morte, such as the nature of the source used for his “Tale of Sir Gareth” and whether Malory himself was responsible for the differences between the two surviving versions of his “Roman War” episode in Book II of the <em>Morte</em>. They further shed light on ongoing controversies concerning the overall textual unity of the <em>Morte</em> and the process by which Malory created the different sections of his work—an issue that lies at the heart of broader debates concerning where Malory and other late medieval adaptors are to be situated on the continuum between “faithful translator” and “original author.”