Reviewerly/exHarmony huggingface dataset:
Designing a Credit Bank Model Based on Blockchain Technology

In the implementation of credit bank, the transformation of learning accomplishments cannot be automated, and the workload of credit achievement management is large. Credits cannot interact freely across different credit banking systems. In order to solve the aforementioned problems, this study proposes the use of alliance chain technology to overcome the technical challenges encountered in the establishment of credit bank. In line with the basic framework of the alliance chain, a credit bank model based on blockchain technology is designed. At the moment, only the model design has been completed; the implementation of the model will take place in the later stage.
Commons Economies in Action

We start this chapter by defining two key concepts-the commons and peer-to-peer production-and outlining a vision for a contributive economy based around them.Following the research by Elinor Ostrom, we define "the commons" as a set of shared resources that are maintained, created, or cared for by a situated community or group of stakeholders. 1 While the first part of the definition proposes that commons are something objective, the second adds a subjective element: commons are constituted by human beings, it is a choice a "we" makes as to how they manage a resource (natural or otherwise) and the allocations it can provide.The third stresses self-governance: around the commons, specific rules and norms are created.This clearly distinguishes it from the "dominium" principles of private property, but also from public goods that are managed by an external agent, i.e., the State.Here we should stress that post-anthropocentric discourses question the definition of natural resources in terms of its ontological dualism between nature and culture.The definition of commons can meaningfully be deepened here by borrowing the notion of "web of life" 2 as an extension of the resources, their governance, and the (multi-species) communities involved.A key issue today is to move from the idea of human commons that manage "external" resources, to the idea of commons as an alliance or partnership between human and nonhuman communities and entities as interdependent agents and subjects.Many Indigenous cultures, more conscious of their interdependencies in the web of life, often achieved this through the sacralization of the forces of life and nature, and by declaring certain zones off limits to human exploitation.Today we could reinterpret this as a form of "sacred property."The commons, as a modern form of inalienable property, can be seen as a reiteration of that insight.
Preferences and Effectiveness of Sleep Data Visualizations for Smartwatches and Fitness Bands

We present the findings of four studies related to the visualization of sleep data on wearables with two form factors: smartwatches and fitness bands. Our goal was to understand the interests, preferences, and effectiveness of different sleep visualizations by form factor. In a survey, we showed that wearers were mostly interested in weekly sleep duration, and nightly sleep phase data. Visualizations of this data were generally preferred over purely text-based representations, and the preferred chart type for fitness bands, and smartwatches was often the same. In one in-person pilot study, and two crowdsourced studies, we then tested the effectiveness of the most preferred representations for different tasks, and found that participants performed simple tasks effectively on both form factors but more complex tasks benefited from the larger smartwatch size. Lastly, we reflect on our crowdsourced study methodology for testing the effectiveness of visualizations for wearables. Supplementary material is available at https://osf.io/yz8ar/.
Solving Symmetrical Drop Suspended Equilibrium Equation by Artificial Bee Colony Programming

In this paper we study the aptitude of Artificial Bee Colony Programming (ABCP) to solve a Suspended Symmetric Drop Equilibrium Equation (SSDEE) described by a non linear second order differential equation.Artificial Bee Colony Programming was developed by Boudouaoui and Karaboga in 2020 to extend Artificial Bee Colony for symbolic regression problems as Genetic Programming (GP) where food source represents tree.The Suspended Symmetric Drop Equilibrium Equation is represented by a second order non linear Differential Equation with boundary conditions.The solving process is fully symbolic, and The Artificial Bee Colony Programming aims to find the best solutions according to fitness.We apply it with different parameters adjustment and we also apply the 4th Runge-Kutta method as usual method.The Artificial Bee Colony Programming solution was compared with the Fourth Runge-Kutta(4RK) and we found that Artificial Bee Colony Programming can solve Suspended Symmetric Drop Equilibrium Equation with a bite agreement and with fewer constraints.
GisGCN: A Visual Graph-Based Framework to Match Geographical Areas through Time

Historical visual sources are particularly useful for reconstructing the successive states of the territory in the past and for analysing its evolution. However, finding visual sources covering a given area within a large mass of archives can be very difficult if they are poorly documented. In the case of aerial photographs, most of the time, this task is carried out by solely relying on the visual content of the images. Convolutional Neural Networks are capable to capture the visual cues of the images and match them to each other given a sufficient amount of training data. However, over time and across seasons, the natural and man-made landscapes may evolve, making historical image-based retrieval a challenging task. We want to approach this cross-time aerial indexing and retrieval problem from a different novel point of view: by using geometrical and topological properties of geographic entities of the researched zone encoded as graph representations which are more robust to appearance changes than the pure image-based ones. Geographic entities in the vertical aerial images are thought of as nodes in a graph, linked to each other by edges representing their spatial relationships. To build such graphs, we propose to use instances from topographic vector databases and state-of-the-art spatial analysis methods. We demonstrate how these geospatial graphs can be successfully matched across time by means of the learned graph embedding.
Conversation-Based Hybrid User Interface for Structured Qualitative Survey

Conversational user interfaces (CUIs) have the potential to substantially influence current practice in diverse application fields, one important example being the way in which online surveys are conducted. Currently, CUIs are mainly applied to help improve the user experience with quantitative surveys. We describe the development of a Hybrid User Interface (HUI) prototype that combines a Graphical User interface (GUI) and a CUI to conduct a fully automated but structured qualitative survey according to the Repertory Grid Technique (RGT). This paper describes a pilot study that we conducted to inform the design of the HUI and to converge to a prototype that is sufficiently mature and robust to be used in a more extensive follow-up study. Our experiences with developing this HUI may help others avoid pitfalls and profit from the tools and lessons we have learned as part of our design process.
The Principles of the Implementation of Gaming Technologies in a Blended Learning Environment in a Technical University

We formulated seven general principles for authors for the implementation of educational gaming technologies in an engineering university based on descriptions in the literature. The principles are ordered by their “importance” for the quality of the game model and systemic influence on the student. These principles provide conditions for mastering educational material by resolving problematic game situations. Conclusions are made about the effectiveness of the methodology based on the principles. It was found that the role of the emotional component in the educational process increases, the students’ independent work is stimulated, the quality of teaching increases, and the teacher is freed from routine control operations.
FASTER OPTIMIZATION-BASED META-LEARNING ADAPTATION PHASE

Neural networks require a large amount of annotated data to learn. Meta-learning algorithms propose a way to decrease the number of training samples to only a few. One of the most prominent optimization-based meta-learning algorithms is Model-Agnostic Meta-Learning (MAML). However, the key procedure of adaptation to new tasks in MAML is quite slow. In this work we propose an improvement to MAML meta-learning algorithm. We introduce Lambda patterns by which we restrict which weight are updated in the network during the adaptation phase. This makes it possible to skip certain gradient computations. The fastest pattern is selected given an allowed quality degradation threshold parameter. In certain cases, quality improvement is possible by a careful pattern selection. The experiments conducted have shown that via Lambda adaptation pattern selection, it is possible to significantly improve the MAML method in the following areas: adaptation time has been decreased by a factor of 3 with minimal accuracy loss; accuracy for one-step adaptation has been substantially improved.
Emerging Telepresence Technologies in Hybrid Learning Environments

The last several years have seen a strong growth of telerobotic technologies with promising implications for many areas of learning. HCI has contributed to these discussions, mainly with studies on user experiences and user interfaces of telepresence robots. However, only a few telerobot studies have addressed everyday use in real-world learning environments. In the post-COVID 19 world, sociotechnical uncertainties and unforeseen challenges to learning in hybrid learning environments constitute a unique frontier where robotic and immersive technologies can mediate learning experiences. The aim of this workshop is to set the stage for a new wave of HCI research that accounts for and begins to develop new insights, concepts, and methods for use of immersive and telerobotic technologies in real-world learning environments. Participants are invited to collaboratively define an HCI research agenda focused on robot-mediated learning in the wild, which will require examining end-user engagements and questioning underlying concepts regarding telerobots for learning.
Cloud Deployed PHR Using ABE Scheme

Personal health record (PHR) is a patient’s personal health information where a patient can store and maintain his personal health details in a cloud server which is a third party. Therefore, security and sharing of personal health information is a concern from parties like cloud server and unauthorized users. It is very important for a patient to have full control on their personal PHRs, hence it is important that PHRs have to be encrypted before outsourcing them to cyber service provider. In this paper, analysis of various PHR schemes for encryption is compared and results are analyzed.
Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization

In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages.Given English gold summaries and documents, sentence-level labels for extractive summarization are usually generated using heuristics.However, these monolingual labels created on English datasets may not be optimal on datasets of other languages, for that there is the syntactic or semantic discrepancy between different languages.In this way, it is possible to translate the English dataset to other languages and obtain different sets of labels again using heuristics.To fully leverage the information of these different sets of labels, we propose NLSSum (Neural Label Search for Summarization), which jointly learns hierarchical weights for these different sets of labels together with our summarization model.We conduct multilingual zero-shot summarization experiments on MLSUM and WikiLingua datasets, and we achieve state-of-the-art results using both human and automatic evaluations across these two datasets.
Effectiveness of Digital Games in Students’ Vocabulary

Vocabulary is a crucial element in language learning. It has a vital role in building communication. Learning vocabulary is challenging. However, some strategies would help, like digital games. This study aimed to investigate the effectiveness of Digital vocabulary games in developing vocabulary level and attitude among 30 grade 8 learners of Dagatkidavao Integrated School. The vocabulary level of the respondents was identified using a 50-item test, while learners' attitude towards vocabulary learning was determined through a 20- item Likert scale questionnaire adapted from Gimolatan (2016). Descriptive statistics such as mean and mean percentage was used to determine learners' vocabulary level, attitude towards vocabulary learning, experts' assessment, and learners' perception after using Digital vocabulary games. On the other hand, paired sample t-test was used to determine the significant difference in the vocabulary level and attitude of the learners before and after the intervention. Moreover, an Independent t-test was utilized to identify the significant difference in learners' post-tests when grouped according to their attitude. Results showed that the participants improved their vocabulary level and attitude towards vocabulary learning after the intervention. Moreover, the increase in vocabulary level, attitude, and difference in the post-test scores when grouped according to their attitude was statistically significant. Thus, Digital vocabulary games effectively improved the learners' vocabulary level and enhanced their attitude towards vocabulary learning. Furthermore, the experts and learners find the material ready to be utilized and develop learners' vocabulary level. Hence, educators and school administrators are encouraged to incorporate digital games in the teaching and learning process, explicitly enhancing learners' vocabulary levels. Keywords: digital vocabulary game, attitude, vocabulary level.
Design Web-Based Information System of Tri Dharma Higher Education for Lecturer

Tri dharma of higher education consisting of education &amp; teaching, research, and community service which must upheld by every lecturer at universities in Indonesia. Lecturer who has implemented the tri dharma of higher education need these tri dharma files for promotion and lecturer performance report to get allowance. It is important to have an online system to store those files. In this research we develop a web-based information system for processing lecturer tri dharma activities data using Rapid Application Development (RAD) Method which started from requirement planning, system design, and implementation.
Hyperspectral image compressed processing: Evolutionary multi-objective optimization sparse decomposition

In the compressed processing of hyperspectral images, orthogonal matching pursuit algorithm (OMP) can be used to obtain sparse decomposition results. Aimed at the time-complex and difficulty in applying real-time processing, an evolutionary multi-objective optimization sparse decomposition algorithm for hyperspectral images is proposed. Instead of using OMP for the matching process to search optimal atoms, the proposed algorithm explores the idea of reference point non-dominated sorting genetic algorithm (NSGA) to optimize the matching process of OMP. Take two objective function to establish the multi-objective sparse decomposition optimization model, including the largest inner product of matching atoms and image residuals, and the smallest correlation between atoms. Utilize NSGA-III with advantage of high accuracy to solve the optimization model, and the implementation process of NSGA-III-OMP is presented. The experimental results and analysis carried on four hyperspectral datasets demonstrate that, compared with the state-of-the-art algorithms, the proposed NSGA-III-OMP algorithm has effectively improved the sparse decomposition performance and efficiency, and can effectively solve the sparse decomposition optimization problem of hyperspectral images.
Odia Text Classification Using Naïve Bayes Algorithm : An Empirical Study

Text classification is recognized as one of the key techniques basically used for classifying the text in different classes including positive, negative and neutral. This paper illustrates the Odia text classification process using Naïve Bayes Algorithm, which is a very fast growing discipline in computer science. This classification algorithm is suitable for binary and multiclass classification in machine learning concept and belongs to supervised classification category used to classify future objects by assigning class labels to instances using conditional probability. In this paper, an auxiliary feature method for Odia text is proposed. It determines features by an existing feature selection method of Naïve bayes algorithm, and selects an auxiliary feature which can classify the text at the selected features, and then the chosen conditional probability is used to improve high classification accuracy. Illustrative examples are shown that the proposed method increases the performance of Naïve Bayes classifier. Around one thousand sentences are taken to be considered as both training and tested for empirical diagnosis of the proposed work. Accuracy is depending on mainly training the corpus size which is designed by own and may be increased to some extend depend on the parameters as well as the large size of corpus further. The result shows that Naïve Bayes technique significantly outperform many other technique like HMM (Hidden Markov Model), CRF (Conditional Random Field) and KNN (K Nearest Neighbourhood). Text classification plays an important role in Sentiment Analysis, Information Extraction, Text Summarization, Text Retrieval, and Question Answering.
Design of Sand Blasting Machine

Abstract: When a metal is exposed to atmosphere, it gets corroded by atmospheric air. To overcome this sand blasting process are used. When machining leaves the sharp burrs or edges on an object, sandblasters can smooth it until it is safe to handle. Sand blasting is a method used to clean, polish or strengthen metal with the help of abrasive material. Sand blasting is used in almost every industry that uses metal, including aerospace, automotive, construction, shipbuilding, rail, and many others. Sand blasting machines uses abrasive material like steel grit, glass bead, sand. The blast media is pneumatically accelerated by compressed air and projected by nozzles onto the component to roughen a smooth surface, shape a surface or remove surface contaminants. For the application of sand blasting process on a big component, which may require secondary surface treatment, which is carried out in a confined space, so many times we have to shift jobs to confined room. Due to this material handling cost increases. To avoid this, there is need of design of portable type of sand blasting machine. Keywords: Sand Blasting, Abrasive Material, Surface Treatment Process, Material Handling Cost, Portable
Information Needs and Information Seeking Behaviour of Secondary School Students in Mysore North Block: A Study

School libraries store the energy that enlightens and empowers the creative minds of students. As the COVID-19 outbreak has put up a bar on going outside, school libraries play a unique role in the process of providing students access to knowledge. In the present Internet era, students can visit a library without leaving home. Current research assesses how students utilize and perceive their school library to access knowledge. To examine the questionnaire survey was developed to collect data from 200 secondary school students in Mysore North block and an overall 194 questionnaires were received and the response rate was 97 percent. The findings of the study inferred that the intensification of the internet has helped students to access various educational resources for their academic and individual information improvement. Notable findings from the study offered insights into professional librarians to initiate library orientation programs to make students and teachers aware of the library resources and services in the knowledge society of the 21st century.
A New Code-Based Traceable Ring Signature Scheme

Traceable ring signatures (TRS) can reveal the identity of the signer if he signs two different messages on the same tag in the group of users. They are widely used in e-voting and cryptocurrencies such as Monero. However, there is still no secure code-based TRS scheme in the random oracle model (ROM). In this paper, we propose a code-based TRS scheme whose security is based on the hardness of the syndrome decoding problem and 2-regular null syndrome decoding problem. We show that our scheme is secure in the ROM in terms of tag-linkability, anonymity, and culpability. The signature size of our scheme is logarithmic in terms of the ring size.
IOT Based Solar Dryer and Irrigation System

Abstract: “Sun drying” is the earliest method of drying farm produce ever known to man and it involves simply laying the agricultural products out open in the sun. This has several disadvantages since the farm produce are laid in the open sky and there is greater risk of spoilage due to adverse climatic situations and insects. Solar dryer is a device which are used to dry substances, mostly food products. A solar dryer is of two types – direct and indirect. In this paper the main idea is to construct a hybrid solar dryer by using the excess heat generated around the solar panel. We have learnt from various researches that as the temperature rises, the panels generate less voltage and become less efficient in producing electricity. So, to overcome this problem we have proposed a system such that a solar dryer can be constructed by using the excessive hot air generated near the solar panels. This will also keep the solar panel cool and maintain the efficiency. The electricity generated from the solar panel will be used in drip irrigation. This system will help the farmers to irrigate their farm and dry their food products with the help of solar energy. Keywords: IoT, Hybrid Solar Drying, Irrigation System
The “Kinesthetic HMD”: Inducing Self-Motion Sensations in Immersive Virtual Reality With Head-Based Force Feedback

The sensation of self-motion is essential in many virtual reality applications, from entertainment to training, such as flying and driving simulators. If the common approach used in amusement parks is to actuate the seats with cumbersome systems, multisensory integration can also be leveraged to get rich effects from lightweight solutions. In this paper, we introduce a novel approach called the “Kinesthetic HMD”: actuating a head-mounted display with force feedback in order to provide sensations of self-motion. We discuss its design considerations and demonstrate an augmented flight simulator use case with a proof-of-concept prototype. We conducted a user study assessing our approach’s ability to enhance self-motion sensations. Taken together, our results show that our Kinesthetic HMD provides significantly stronger and more egocentric sensations than a visual-only self-motion experience. Thus, by providing congruent vestibular and proprioceptive cues related to balance and self-motion, the Kinesthetic HMD represents a promising approach for a variety of virtual reality applications in which motion sensations are prominent.