Reviewerly/exHarmony huggingface dataset:
Solutions of Nonlinear Bending Problems of Plates with Complex Shapes

A high-order wavelet method is developed for general nonlinear boundary value problems with complex boundaries in mechanics. This method is established based on wavelet approximation of multiple integrals of interval bounded functions combined with an accurate and adjustable boundary extension technique. The convergence order of this approximation has been proven to be N as long as a typical family of wavelets named Coiflets with N-1 vanishing moment are adopted, which can be any positive even integers. Error analysis has proven that the proposed method is in accuracy of order N, and condition numbers of relevant matrices are almost independent of the number of collocation points. Examples of a wide range of strong nonlinear problems in engineering, especially in mechanics, including the extremely large deflection bending of plates with complex shapes, demonstrate that accuracy of the proposed method is even greater than the theoretical estimated order of N, and most interestingly, such accuracy is independent of the order of the differential equation of a problem to be solved. Comparison to existing numerical methods further justifies the accuracy and efficiency of the proposed method.
THE RELATIONSHIP BETWEEN PERSONALITY AND INTERNET ADDICTION AMONG PRE-SERVICE TEACHERS

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1000-1006ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0324Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
A long-term secure data transmission and storage network based on quantum key distribution

Integration of secret sharing and Quantum key distribution is proposed to provide network functions of transmission, storage, and processing, which guarantees long term security to be a infrastructures supporting high-quality, efficient and safe society.
Analisis Cluster Pada Pengelompokan Siswa Diktuk Bintara Polri TA. 2018/2019, SPN Singaraja - Polda Bali Menggunakan K-Means dan K-Harmonic Means

Education is basically one step to improve and develop all aspects of human beings. Education is not only in the form of science, but also in the form of values, skills and attitudes, so that in education it is expected to be able to make a person intelligent, skilled and be able to behave according to the prevailing norms. Mathematics is one of the subjects taught since elementary school education. Geometry and measurement are aspects of basic competencies found in elementary school mathematics learning ranging from class I to class VI. To make a child have good geometry measurement skills, the teacher (parent, teacher or family) must have a means or media that can train children's geometry measurement skills in an interesting and fun way. The purpose of this study was to create a media to train geometry measurement capabilities, especially for class V through an Android-based application, the application created was packaged in the form of an educational game. The game was developed using SDLC with V-models and the game was tested through blackbox, installation tests and questionnaires.
Approaches for immersive media curriculum implementation

The rapid expansion of availability, affordability and implementation of immersive media technologies in the market place has spawned an increasing interest in integration of design and production methodologies into higher education curriculum, while simultaneously posing a host of challenges to educators when with regards to resources, pedagogy and identifying industry needs. This panel brings together the directors of programs from Texas A&M University, The Ringling College of Art + Design, and Drexel University who have integrated immersive media into existing programs in visualization, as well as launched entire degree programs focused on the teaching design and production methodologies, to share and discuss their experiences with fellow
Depression Represented In Ned Vizzini’s Novel It’s Kind Of A Funny Story: A Psychoanalysis Study

This study examines depression in the main character in It’s Kind of A Funny Story written by Ned Vizzini. In order to carry out the process of analyzing, the study uses a depression theory by Aaron Beck (1967) and to analyze the data uses qualitative method research. This study focuses on depression represented in a 15 years old boy named Craig Gilner and it shows Craig survives from depression that affects many aspects of his life. Craig Gilner is a person who can get stress and pressure easily but his depression becomes worse when he is in High School. Finally, the findings found are the causes of Craig's depression, the Negative Cognitive Triad include negative overviews of self, future, and world. The study also found the secondary symptom experienced by Craig and how Craig deals with his suicide desire and recuperation process.Keywords: Psychology, Depression, Novel, Negative Cognitive Triad, Causes of Depression, Suicide, Sadness.
A NOVEL ENTER WORD SEARCH WITH NOMINATED TESTER AND TIMING FACILITATE EXCHANGE RE CIPHER TEXT ROLE FOR ONLINE PHYSICAL CLOUDS

The Search File Encryption (SE) plan is indeed a technology that includes security and favorable functionality that can play a very important role in the e-health registration system. The Digital Health Information Product is a unique application that offers great comfort in healthcare. In this document, we present a unique encryption primitive, called a common search engine for the searcher, and a timing-enabled proxy transfer encryption, which is a time-dependent SE plan. We designed a unique search file encryption plan that supports secure search for affiliate keywords and approved broadcast functionality. Unlike in existing systems, work can synchronize the re-encryption of the proxy file allowed by effective cancellation of the delegation. The security and privacy of sensitive private data are major user concerns that may hinder the development and widespread deployment of systems. We create a method model together with a security model so that the proposed Re-dtPECK plan shows that it is a skilled plan that has proven to be safe in a standard model. Comparison and large-scale simulations show that it represents low computation and storage. It could allow patients to transfer the legal rights of others to a partial use to perform search operations on their records within a short period of time. The time period during which the Trustee can view and decrypt the Trusted Encrypted Document can be managed.
Enhancing Quality of Movies Recommendation Through Contextual Ontological User Profiling

Nowadays, the Internet and Cloud Computing technologies have enabled movies watching to be enjoyed anytime and anywhere in richer varieties and choices. As a result, one will be overwhelmed and tend to make poor choices. The increasing on-demand movies services motivates more choices of the programs to be offered and users need recommendation system to provide them with contextual and personalized suggestions. This paper proposes to use contextual ontological user profiling for movies recommendation which considers personalization in enhancing the effectiveness of the recommendations. We evaluated the performance of our proposed solution with few scenarios representing problems aroused from traditional collaborative and content-based recommendations. These problems are the cold start, data sparsity, over specialization, gray sheep and inefficiency issue. Evaluation results and analysis show that proposed work not only is capable of resolving these problems but is also competent in mitigating the scalability and inefficiency issue.
INITIAL DIAGNOSIS ON THE PERCEPTION AND THE LEVEL OF APPROPRIATION IN THE USE OF M-LEARNING ENVIRONMENTS OF STUDENTS OF THE AUTONOMOUS UNIVERSITY OF BAJA CALIFORNIA SUR, MEXICO

INITIAL DIAGNOSIS ON THE PERCEPTION AND THE LEVEL OF APPROPRIATION IN THE USE OF M-LEARNING ENVIRONMENTS OF STUDENTS OF THE AUTONOMOUS UNIVERSITY OF BAJA CALIFORNIA SUR, MEXICO
SGM-Based Disparity Estimation Under Radiometric Variations

The semi-global matching (SGM) performances excellent in stereo correspondence field, it reaches a good trade-off between correspondence accuracy and computational complexity. However, the performance of SGM is limited under radiometric variations, such as varying lighting and exposure conditions. In this paper, an improved SGM method is presented to remedy this problem. To eliminate the discrepancy of illumination between the stereo images, both histogram equalization and binary singleton expansion are adopted in pre-processing stage. The weighted median filter is adopted after conventional LRC in the disparity refinement stage to remove the outlier errors and preserve edges. The stereo images from the Middlebury benchmark are used in the experiment. The experimental result show that the average RMSE of the improved SGM method is 12.64% lower than the raw SGM. The proposed method can effectively improve the accuracy of disparity map compared to the SGM algorithm.
Topsoe to test biogas route to methanol

The Danish catalysis company Haldor Topsoe will build a 10 kg/h plant to demonstrate technology for producing methanol from biogas using its electrified reactor. Topsoe’s technique for producing synthesis gas from methane with electricity was recently published in Science. The demonstration facility, to open in 2022 in Foulum, Denmark, will convert methane from organic waste decomposition into synthesis gas and then into methanol.
Conceptual Review on Employee Engagement and its Drivers

Employee engagement can be defined as the extent or the level to which employees in the organization value, enjoy and believe in their job profiles, it is also the extent an employee is commited, enthusiastic and involve his/herself towards the achievement of organizational goals and its values. Employee engagement involves interventions that enhance commitment towards job, motivation or productivity. It reflects the measureable level of an employee’s emotional attachment to his/her organization, it can be either positive or negative towards his colleagues, job and the organization. The present research work was planned to study the relationship of employee engagement with employee performance, employee satisfaction, and employee turnover and employee absenteeism. The goal for the research was to investigate the factors that engage employees to perform to their best and the impact of the employee engagement on the performance of employees. This is a conceptual paper, literature has been explored from research papers, journal. Articles, textbooks, dissertations, published online resources. Databases like EMERALD, EBSCO, WILEY, ABI Inform, Business Source Premier etc were also explored. Reflective stance on the topic has been developed by evaluating the available literature. The literature analyzed is indicating that there might be a strong association among employee engagement, performance, and satisfaction and employee turnover. Employee engagement contributes to competitive advantage in an organization. Important drivers/antecedents of engagement discussed as communication, recognition, workers Participation in Management, support health and safety, hygienic and clean work place, safe and clean drinking water, human factor and ergonomic workplace, results-based incentives.The drivers of engagement greatly get influenced by industry type, sector and other specifications. There cannot be one best customized approach for all.So organizations are required to customize their engagement strategies for organizational excellence.
Long-Tailed Contrastive Loss for Video-Based Person Re-identification

Contrastive loss based deep metric learning has been generally used in video-based person re-identification, which learns a metric by preserving the distance between positive sample pairs close and negative sample pairs far on the embedding space. Yet contrastive loss still suffers not only from “hard” negative examples loosely defined by a hard margin, but also from severe sampling imbalance caused by equal sampling technique. To address these defeats, this paper presents a novel loss called Long-Tailed Contrastive Loss (LTCL). A Gaussian kernel function is used as the negative loss term, which takes into account the effect of long-range negative sample pairs. Meanwhile, a focusing factor is introduced for adaptive hard negative data mining and a rebalancing factor is used to compensate the sampling imbalance. Experiments conducted on two classic datasets demonstrate the effectiveness of the proposed method.
Sharing books… Monkey Puzzle

Nursery WorldVol. 2019, No. 15 EYFS ActivitiesSharing books… Monkey PuzzleJulia Donaldson, Axel ShefflerJulia Donaldson(Macmillan Children's Books, 2000)Search for more papers by this author, Axel Sheffler(Macmillan Children's Books, 2000)Search for more papers by this authorJulia Donaldson; Axel ShefflerPublished Online:25 Jul 2019https://doi.org/10.12968/nuwa.2019.15.18AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article FiguresReferencesRelatedDetails 22 July 2019Volume 2019Issue 15ISSN (print): 0029-6422ISSN (online): 2059-9358 Metrics History Published online 25 July 2019 Published in print 22 July 2019 Information© MA Education LimitedPDF download
A blowfish-RC6 (BRC6) with sending identification bit (SIB) mechanism for data security in XSS

16] suggested an offline and online based model for the malicious XSS attack detection on in online social network.They have tested their approach on five online social network for the XSS attack.Their result shows the little false Review
Spectral Pooling Based CNN Model Compression for Light Field Depth-Estimation

In the design of the traditional CNN model, there is always a balance between the spatial dimension and the number of channels. The high-dimensional spatial resolution is to preserve more detailed local information, while the large number of channels ensures more complex feature representation. For the current Light-field depth estimation algorithm, the designers usually choose to maintain a high spatial dimension in the network to improve the accuracy of the depth estimation, which results in a situation where the model has a large size and will take up huge amount of computing resources in the depth estimation process. In this paper, we introduce an effective pooling method: spectral pooling, to improve the problems of the original Light-field depth estimation network mentioned above. We transfer the light field feature map to the frequency domain through Fourier transform and reasonably reduce the size of the feature map in the frequency domain to an arbitrary size. The method can be used to reduce the complexity of the network and speed up training with similar performance to the original algorithm. More importantly, the new model with less memory demand can be better applied to light mobile device.
Micro- to macroscale controls on REE distribution in the Ambohimirahavavy ion adsorption deposit, Madagascar

"Micro- to macroscale controls on REE distribution in the Ambohimirahavavy ion adsorption deposit, Madagascar." Applied Earth Science, 128(2), pp. 59–60
The role of smartphone in recommender systems: opportunities and challenges

The popularity of smartphones in people&apos;s daily life brings new opportunities as well as challenges in recommender system. New opportunities include new available context data, e.g., user interaction time (usually from native mobile app) and geo-location data (from equipped GPS sensors). These metainformation provides different ways of inferring user preference, which ultimately improves the recommendation performance. For instance, with record of tap-in and tap-out timestamp, the dwell time can be estimated. It thus provides an opportunity to address the “silent viewing” issue by inferring people&apos;s implicit rating, which will benefit conventional recommender systems that suffer from rating-sparsity. At the meantime, new challenges are mainly in two-fold. First, such side information is not included in conventional recommendation model, and thus it is not easy for integration. Also, recommendation services via smartphones is itself a scenario different from traditional PC-based one, which leads to “pitfalls” where existing techniques may fail. Particularly, we focus on two representative recommendation scenarios in smartphones, i.e., app and point-of-interest (POI) recommendation. For the former one, conventional model may recommend apps that users would never download due to the ignorance of potential conflict between candidate apps and installed ones. To recommend POI, failure of modeling physical location may lead to candidates that are too far away. In this chapter, we reveal these issues and describe corresponding solutions.
Improving Robot Tutoring Interactions Through Help-Seeking Behaviors

Robot tutors have great potential for supporting personalized learning, in both home and classroom settings. To be effective, robot tutors must encourage users to seek help as needed during the learning process. We conducted a between-subjects study with N=45 participants to compare different types of learner help-seeking behaviors–pressing an on-screen button, pressing a physical button, and raising a hand– and assess how help-seeking behavior preferences relate to perceptions of the robot tutor. The results indicate that hand raising was seen as the hardest method for a user to perform but the most useful and beneficial, with positive trends in students’ intention to use a robot.
MATHEMATICAL LITERACY FROM THE POINT OF VIEW OF PRE-PRIMARY SCHOOL TEACHERS

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 5240-5246ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.1289Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Groovy assignment: the VR ride

In this Groovy Assignment submission, we present a VR Ride assignment that challenges students to create a fully interactive VR computer graphics experience integrated with a themed ride. For this assignment, a ride is an apparatus that fully supports the users weight, utilizes the user's body motions as a primary input for computer interactivity, and provides haptic feedback relevant to the VR experience.
Performance metrics for traditional and context-aware big data recommender systems

Recommender System (RS) concept was coined in the mid-1990s, when researchers took interest in recommendation problems that primarily used the concept of ratings to obtain the user preferences for different items. A lot of work has been exercised and investigated in this area for recommending the most relevant information and contents to users without taking the contextual information, such as date, time, location and event. In the last few years, context-aware recommender systems (CARS) have made tremendous contributions in all domains of life and improved the recommendation process based on the contextual information along with the traditional approaches. The effectiveness of an algorithm can be measured in the sense that how efficiently it returns the recommendation to users/customers with respect to context or occasion. To assess the effectiveness and performance of any recommender algorithms completely, some common metrics are defined to assess the performance of the recommender algorithm beforehand.
LO represents motion and semantic categories in addition to object boundaries

Segmenting objects from backgrounds is a critical function of the human visual system. Studies have shown that intermediate-level visual areas including Lateral Occipital cortex (LO) represent information about object boundaries, but also represent other other features such as motion and visual semantic categories. However, because most studies use tightly controlled stimuli (e.g. stimuli with contours and no motion or vice versa), it is unknown how important object boundary contours are relative to other features. To address this issue, we measured fMRI responses while humans subjects viewed natural movies. We modeled responses to these movies as a function of motion energy, object boundary contours, and visual semantic categories. We used a customized version of a recent convolutional neural network (Deeplab v2) to label contours. We used the encoding models for each type of feature to predict withheld fMRI data, and used variance partitioning to determine whether the models explained shared or unique variance. We found that the boundary contour model explained some variance that was not explained by the motion energy model in LO. The same was true in areas selective for faces and bodies. However, this variance was shared with the semantic category model, and the motion energy model explained more unique variance than the boundary contour model. Thus, LO and other areas may represent boundary contours (perhaps specifically boundaries of animate entities), but that representation is mixed with representation of motion and semantic categories. Other features appear to affect responses in LO as much as object boundaries do.
Compiler Design for Legal Document TranslationIn Digital Government

One of the main purposes of a computer is automation. In fact, automation is the technology by which a manual task is performed with minimum or zero human assistance. Over the years, automation has proved to reduce operation cost and maintenance time in addition to increase system productivity, reliability, and performance. Today, most computerized automation are done by a computer program which is a set of instructions executed from within the computer memory by the computer central processing unit to control the computers various operations. This paper proposes a compiler program that automates the validation and translation of input documents written in the Arabic language into XML output files that can be read by a computer. The input document is by nature unstructured and in plain-text as it is written by people manually; while, the generated output is a structured machine-readable XML file. The proposed compiler program is actually a part of a bigger project related to digital government and is meant to automate the processing and archiving of juridical data and documents. In essence, the proposed compiler program is composed of a scanner, a parser, and a code generator. Experiments showed that such automation practices could prove to be a starting point for a future digital government platform for the Lebanese government. As further research, other types of juridical documents are to be investigated, mainly those that require error detection and correction.
RDF/JSON serialization of knowledge patterns

This paper presents the way of serialization RDF representation of Knowledge patterns by RDF/JSON syntax. Knowledge patterns are general patterns of knowledge which can be used many times. The use of pattern is realized by morphism, the process when symbols from a pattern are renamed by concrete symbols. RDF/JSON is a concrete syntax for RDF which is defined in the RDF Concepts and Abstract Syntax W3C Recommendation and uses JavaScript Object Notation (JSON).