Reviewerly/exHarmony huggingface dataset:
Development and Application of Middle School Remote Inquiry-based Science Instructions

The purpose of this study is to develop and apply remote inquiry-based science instructions of middle school science subjects that emphasize teacher-student, student-student interactions, and can be experimented at home. and then find out the effectiveness of the classes and students’ perceptions. To this end, seven remote inquiry-based classes were conducted for 18 first graders of middle school. Classes were conducted in real time using the ‘Online Class Video Class’ platform, and interaction tools such as Tinkerbell Board and Google Survey were used. In order to analyze the effectiveness of remote inquiry classes, science core competency tests, and science process skill tests were conducted, and students’ perceptions of remote inquiry classes were investigated. As a result of the survey analysis, the application of remote inquiry classes significantly improved students’ science core competencies, and science process skills. The biggest advantage was that individuals could perform all experiments directly through the use of individual experimental kits. In addition, it was found that communication between teacher-student and student-student was actively conducted during class, and they thought it was helpful in class. Based on the results, effective inquiry-based classes in non-face-to-face remote class situations were discussed.
Text Recycling in Scientific Writing: What Editors Need to Know

MODERATOR: Kelly Hadsell Federation of State Medical Boards SPEAKERS: Cary Moskovitz Duke University David Hansen Authors Alliance @DigLibCopyright REPORTER: Ruth Isaacson Genetics Society of America Text recycling has long been a source of confusion for researchers, editors, and publishers and is inappropriately regarded as a form of self-plagiarism. To provide clarity regarding text recycling and consensus about what is ethically and legally acceptable, the Text Recycling Research Project1 (TRRP), a multi-institution, NSF-funded initiative, investigates text recycling in STEM research. TRRP members Cary Moskovitz and David Hansen shared some of the TRRP findings and recommendations. TRRP’s definition of text recycling is as follows: Text Recycling is the reuse of textual material (prose, visuals, or equations) in a new document where (1) the material in the new document is identical to that of the source (or substantively equivalent in both form and content), (2) the material is not presented in the new document as a quotation (via quotation marks or block indentation), and (3) at least one author of the new document is also an author of the prior document.2 Moskovitz explained that in publishing, editors often ask authors to rework their materials in 1 of 3 ways to avoid ethical and legal concerns. While on the surface these appear to be reasonable approaches, Moskovitz detailed why text recycling is often more appropriate. Summarize and Cite Editors may ask authors to paraphrase and cite text when it is recycled from a large block of text. However, when documents are behind paywalls, […]
Singed Silhouettes and Feed Forward Flames: Volumetric Neural Style Transfer for Expressive Fire Simulation

While controlling simulated gaseous volumes remains an ongoing battle when seeking realism in computer graphics, creating appealing characters entirely out of these simulations brought this challenge to an entirely new level in Pixar’s film Elemental. For fire characters, like the protagonist “Ember”, their faces and bodies needed to look and move like real fire, but not be so frenetic as to distract from the acting and emotion of their performances. Neural Style Transfer emerged as a key technique to achieving a look that met these criteria. By using more gaseous and languid pyro simulations as input, higher frequency “cusp and curve” shapes could be coherently transferred to the volumes via a GPU based optimization process applying recent advances in neural style transfer (NST) to the voxels themselves. These transferred shapes were controlled by hand painted styles and parameters that could be animated as a way to enhance the character performance. A key benefit of this process was the final shape of the fire was decoupled from the underlying simulation. This allowed the simulation to focus on lower frequency motions and stability, while NST could provide the final touches of shaping, particularly around the silhouette. Users could modify the perceived speed of the NST patterns by modulating the velocity input, and control where the effect was strongest by masking the resulting vector field. For large reusable simulations intended to be seen from many views, NST proved impractical as the multiple stylization viewpoints added excessive computational cost. To solve this, we trained a convolutional neural network to approximate the optimization process for stylization on representative volumes using multiple viewpoints. Then the much cheaper feed-forward neural network could be used, allowing us to bring NST to bear on larger scale environment simulations as well as characters.
Digital Twin Oriented Virtual View Rendering Algorithm Based on K-means

The Depth Image Based Rendering (DIBR) is an important visual simulation method in digital twin, which can be used to generate virtual viewpoints of physical objects, enabling visualization and manipulation of physical objects. DIBR technique can quickly and effectively synthesize virtual viewpoint images. However, the problem of overlapping in the synthesized images seriously affects the quality of the views. To address the overlapping problem in virtual viewpoint images based on binocular fusion, a K-means based layered image virtual viewpoint rendering algorithm is proposed. Most of the existing layered algorithms use the Canny operator to distinguish between foreground and background, which requires manually setting the segmentation threshold. In this paper, a layered mapping drawing method based on K-means is designed to automatically and accurately distinguish between foreground and background. The layered mapping is used to avoid mutual interference between foreground and background pixels. Experimental results show that the proposed algorithm can effectively solve the problem of overlapping in virtual viewpoint rendering, and has better performance in PSNR and SSIM compared to other algorithms.
Best Paper Section IEEE International Conference on Automatic Face and Gesture Recognition 2021

The IEEE International Conference on Automatic Face and Gesture Recognition (FG) is the premier international conference on vision-based automatic face and body behavior analysis and applications. Since the first meeting in Zurich in 1994, the FG conference has grown from a biennial conference to an annual meeting, presenting the advancements and latest research developments related to face and gesture analysis. FG2021 was planned to be an in-person meeting hosted in the historic city of Jodhpur, India. However, due to the COVID-19 pandemic situation, the organizing committee decided to hold FG2021 as an online conference from December 15 to 18, 2021. Over 142 papers were presented at FG2021 and based on the reviewers and area chair recommendations, PC Chairs invited a set of top reviewed papers as part of a special issue on “Best of Face & Gesture 2021” in the IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM). The meticulous review process of T-BIOM ensured that significantly extended research papers that were initially presented at FG2021 are included in this special issue. The nine accepted papers can be classified into three sets: (i) algorithms with 3D information based face/motion processing, (ii) algorithms towards head pose estimation, emotion recognition, differentiable rendering, dictionary attacks, and group detection, and (iii) the student engagement dataset for affect transfer learning for behavior prediction.
Improving Hardware Efficiency of a Sparse Training Accelerator by Restructuring a Reduction Network

Deep learning is used in various applications including recommendation system, natural language processing, and image processing. When training deep learning models, there is inherent sparsity in input or weight matrices. Therefore, efficiently processing sparse general matrix multiplication (spGEMM) is the key to improve training efficiency. In this paper, we present an improved spGEMM accelerator by restructuring a reduction network and using a proper matrix tiling strategy. The overall hardware area is reduced by 21.8% and the power consumption is reduced by 37.5% with the proposed reduction network. When the stationary matrix’s sparsity is 80% and the streaming matrix’s sparsity is 99%, the required clock cycles reduce by 80% using the proposed matrix tiling method.
European framework and proofs-of-concept for the intelliGent aUtomAtion of cybeR Defence Incident mAnagemeNt

Artificial Intelligence and Automation are revolutionizing cyber defence and incident response by addressing traditional inefficiencies and enabling faster and easier incident resolutions. However, challenges arise in cyber response. The European framework and proofs-of-concept for the EUGUARDIAN project aims to develop a reliable AI-based solution focusing on semi-automatic or automatic detection, mitigation, and response to security challenges, supporting analysts and decision-makers, enhancing cyber situational awareness and military infrastructure resilience.
An Appraisal Method for Web Interfaces Based on Aesthetic Measurement

In order to better guide the design of web interfaces, this study improved existing calculation formulas based on the research findings of aesthetic measures and proposed a set of interface aesthetic measures that can be used for web interfaces, including measures of balance, proportion, element overlap, and density. MATLAB 2020a was used to measure the aesthetic measures of 16 web interfaces, and a questionnaire was used to obtain participants’ subjective aesthetic perception of the web interfaces. The experimental results showed that measure of grayscale balance and measure of horizontal color balance were positively significantly correlated with subjective balance. Measure of proportion of layer objects to interface frame was significantly positively correlated with subjective proportionality, while measure of proportion of layer objects to interface layout was negatively correlated. There was a significant positive correlation between measure of grayscale balance, measure of horizontal color balance, measure of density and subjective overall aesthetics. Additionally, measure of element overlap was significantly negatively correlated with subjective harmony.
An Exploratory Study on the Impact of Hosting Blockchain Applications in Cloud Infrastructures

Blockchain presents many new examples of delivering a robust audit trail using the distributed ledger. However, some potential issues, especially scalability and privacy, are still ongoing in the blockchain. Fortunately, these issues can be settled by using cloud computing. Cloud computing is an on-demand service that enables consumers to purchase and use IT resources. It saves the consumer's cost as consumers don't have to spend extra on building their on-premises server and providing extra security to the application. Enterprises interested in joining the blockchain flow can run their blockchain in the cloud. Cloud Service Providers (CSPs) provide multiple services such as IaaS, PaaS, SaaS and BaaS that can help a business start its blockchain application. But there are still risks that should be carefully noted. Data leaks and breaching are still possible despite the safety and privacy guarantees. The failure to achieve proper security will have to face massive potential fines. In this research, the authors addressed the impact of utilising the cloud in the blockchain and provided an in-depth understanding of the relationship between blockchain technology and cloud computing.
Algebraic signature algorithms with a hidden group group, based on hardness of solving systems of quadratic equations

A new-type algebraic digital signature schemes on non-commutative associative algebras are developed using technique of performing exponentiation operations in a hidden group. The signature contains two elements: a randomization integer e and a vector S. The used verification equations are characterized in multiple entries of the signature element S. The post-quantum security of the introduced signature algorithms is provided by the computational difficulty of solving a system of many quadratic equations in many variables, like in the public-key multivariate cryptosystems. However in the former case the quadratic equations are set over the finite fields having the order of significantly larger size.
Elevated temperature on leaching of arsenic and boron from excavated rocks

This work evaluated the leaching behaviors of geogenic arsenic and boron of two excavated rocks under different temperatures.Excavated rocks with geogenic contamination are expected to be used in embankments with proper countermeasures.Their leaching behaviors might change because of seasonal and daily changes in ground temperature.However, the effect of temperature on leaching behaviors has not been well examined.Column tests at temperatures of 20 and 40°C were performed using rock samples.Elevated temperatures led to the release of greater amounts of arsenic and boron.The largest arsenic concentrations obtained from the column tests were 0.53 mg/L at 40°C, while at 20°C was 0.15 mg/L for one rock sample.The largest concentrations of arsenic and boron obtained at 40°C were at most 3.5 times larger than at 20°C.Boron concentrations decreased as electric conductivity decreased.Electric conductivity can be one index to predict the leaching behavior of boron.
Self-Supervised Dynamic Graph Representation Learning via Temporal Subgraph Contrast

Self-supervised learning on graphs has recently drawn a lot of attention due to its independence from labels and its robustness in representation. Current studies on this topic mainly use static information such as graph structures but cannot well capture dynamic information such as timestamps of edges. Realistic graphs are often dynamic, which means the interaction between nodes occurs at a specific time. This article proposes a self-supervised dynamic graph representation learning framework DySubC, which defines a temporal subgraph contrastive learning task to simultaneously learn the structural and evolutional features of a dynamic graph. Specifically, a novel temporal subgraph sampling strategy is firstly proposed, which takes each node of the dynamic graph as the central node and uses both neighborhood structures and edge timestamps to sample the corresponding temporal subgraph. The subgraph representation function is then designed according to the influence of neighborhood nodes on the central node after encoding the nodes in each subgraph. Finally, the structural and temporal contrastive loss are defined to maximize the mutual information between node representation and temporal subgraph representation. Experiments on five real-world datasets demonstrate that (1) DySubC performs better than the related baselines including two graph contrastive learning models and five dynamic graph representation learning models, especially in the link prediction task, and (2) the use of temporal information cannot only sample more effective subgraphs, but also learn better representation by temporal contrastive loss.
trie-nlg: trie context augmentation to improve personalized query auto-completion for short and unseen prefixes

Query auto-completion (QAC) aims at suggesting plausible completions for a given query prefix. Traditionally, QAC systems have leveraged tries curated from historical query logs to suggest most popular completions. In this context, there are two specific scenarios that are difficult to handle for any QAC system: short prefixes (which are inherently ambiguous) and unseen prefixes. Recently, personalized Natural Language Generation (NLG) models have been proposed to leverage previous session queries as context for addressing these two challenges. However, such NLG models suffer from two drawbacks: (1) some of the previous session queries could be noisy and irrelevant to the user intent for the current prefix, and (2) NLG models cannot directly incorporate historical query popularity. This motivates us to propose a novel NLG model for QAC, Trie-NLG, which jointly leverages popularity signals from trie and personalization signals from previous session queries. We train the Trie-NLG model by augmenting the prefix with rich context comprising of recent session queries and top trie completions. This simple modeling approach overcomes the limitations of trie-based and NLG-based approaches, and leads to state-of-the-art performance. We evaluate the Trie-NLG model using two large QAC datasets. On average, our model achieves huge $$\sim$$ 57% and $$\sim$$ 14% boost in MRR over the popular trie-based lookup and the strong BART-based baseline methods, respectively. We make our code publicly available at https://github.com/kaushal0494/Trie-NLG .
DEVELOPING CROSS-CULTURAL UNDERSTANDING (CCU) MATERIALS IN TOURISM GUIDING FOR VOCATIONAL STUDENTS

Learning English for Specific Purpose (ESP) for vocational students, is very important so that certain ways are needed to encourage students' needs. Students must receive sufficient material in certain ways based on their interests and majors. This study aims to analyze learning needs of tourism guide materials. The method used in this study is qualitative and quantitative research design where the data is collected with numerical form then described in the form of a description. The research instruments used in this study are questionnaires and open-ended interviews. This study conducts a needs analysis to measure student needs and to develop ESP materials. The participants of this research are 3rd and 4th semester students majoring in D3 Vocational Department UNMER Malang. The results of the study indicate the needs of students to improve their English-speaking skills and develop Cross Cultural Understanding (CCU) as tourism guiding materials. Furthermore, students' English skills also show low results which lead to low self-confidence because the learning methods used by lecturers have not developed due to the application of teacher-centered classes which lead to a lack of practice from students. Therefore, learning methods that are able to stimulate students’ speaking proficiency and CCU material development are needed.
Sistem Pencocokan Aksara Bali Menggunakan Template Matching Dan Komputasi Paralel

Balinese script is a traditional script used to write Balinese language and literature. Balinese script is also one of the richness of Balinese culture. However, Balinese script has a unique shape that is almost the same as each other, and some writings are only distinguished by one line stroke. This can complicate learning as well as in developing applications in this modern era. So because I did research in making Balinese script matching systems using template matching and parallel computation in order to find out what the value of the average dissimilarity of each Balinese script letter can be used as a reference in developing applications related to Balinese script.&#x0D; In this study I used the template matching method to find out the average error value of each Balinese accented letter contained in the bali simbar font. From the method, each pixel value of the Balinese script that has been processed in the binary process will match each pixel value to obtain an error value. The error value will be looked for the average and will be made a table to make it easier to find the largest MSE value or Balinese script that has a small similarity value. In the template matching process, parallel computation is also inserted as well as making comparisons between applications that use parallel computing and do not use parallel computing in order to know whether there is a difference in processing time or not.&#x0D; Based on the research conducted, the results obtained that the largest MSE value of 0.071354167 has a similarity of 93%. Where this shows that the similarity of the Balinese script to the others has similarities above 90% and the results of the data processing time for systems that use parallel computing are 4977 and systems that do not use parallel computing are 4789.&#x0D; &#x0D; Keywords: Template matching, parallel computing, Balinese script matching&#x0D;
Perancangan dan Implementasi Sistem Informasi Geografis Wisata Kota Purwodadi Berbasis Mobile

An abstranct is a brief summary of a In the search for a location, requires a position in the delivery of geographic information from a tourist attraction. Currently the most widely known online map is Google Maps which can be accessed easily via Android Mobile with the help of internet technology. Therefore, by utilizing these technologies, it is expected to produce a mobile application that can make it easier for tourists to find the desired tourist attractions, especially in Purwodadi City. However, there are obstacles in finding tourist attractions, especially for tourists from outside Purwodadi City. Information about tourism in Purwodadi still uses a lot of print media, while the delivery of information in print media can be said to be less effective because it requires a lot of resources, for example, the use of excessive paper. And people who are interested usually first look for information from the internet. The information sought is usually about Purwodadi attractions, Purwodadi City News, Purwodadi city history, gift shops and hotels in Purwodadi city. Along with the development of increasingly advanced technology, the use of the internet can be done anywhere, either through a computer or a mobile device so that the information needed can be accessed quickly. Moreover, by using a mobile device we can access information anywhere because it is easy to carry anywhereally as an overview of what appears in the paper.
Structure of a finite non-commutative algebra set by a sparse multiplication table

Four-dimensional finite non-commutative associative algebras represent practical interest as algebraic support of post-quantum digital signature algorithms, especially algebras with two sided global unit, set by sparse basis vectors multiplication tables. A new algebra of the latter type, set over the field GF(p), is proposed and its structure is investigated. The studied algebra is described as a set of p2 + p + 1 commutative subalgebras of three different types. All subalgebras intersect strictly in the subset of scalar vectors. Formulas are derived for the number of subalgebras of each type.