Reviewerly/exHarmony huggingface dataset:
Dual Modality Instruction &amp; Programming Environments

Dual-modality blocks-text programming environments have shown promise in helping students learn programming and computational thinking. These environments link blocks-based visualizations to text-based representations, which are more typical of production languages. Since prior work shows that some students who learn in dual-modality environments outperform those who learn in text on assessments, we sought to understand specifically how students use dual-modality environments and what support these environments provide to the learning process. We analyzed survey responses and tool logs collected during a study at a large public university in a CS1 course (N=425). We found that students from all prior programming experience backgrounds made use of the ability to visualize code structures by using blocks. Students with prior experience in blocks or no prior experience said they felt the dual-modality instruction helped them understand code structure and meaning. As students progressed through the class, we found that they made more use of the blocks mode's reference palettes than to its drag-and-drop facilities or mode-switching features. By identifying how students interact with dual-modality tools and how they impact student understanding, this work provides guidance for classroom instructors.
Integration of Images into the Patent Retrieval Process

Specialized patent retrieval systems mostly use textual information which is difficult enough because of the specialized characteristics of the text. However, in patents there also are drawings which show the invention. Empirical research has shown that patent experts can use these images to determine relevance very quickly. However, these drawings are binary and sometimes abstract and other times very specific; therefore there has not been an effective way to include the visual information into the information retrieval process. In addition, the number and the quality of drawings differs vastly even inside patent classes. This work focuses on the inclusion of images into the patent retrieval process using a combination of visual and textual information. With this multimodal approach it will hopefully be possible to achieve better results than just by using one modality individually. The goal is to develop a prototypical system using an iterative user-centered process.
Implementación de una aplicación Web y móvil para la gestión de movilización vehicular basado en metodología ágil utilizando servicios de Transferencia de Estado Representacional

Web and mobile application development is an important component within a modern organization, as it enables you to manage your processes efficiently. With this approach, this work details the analysis, design, and implementation of these applications for the management of more flexible and timely information in the control of vehicular mobilization that is managed by the Transport Management Unit of Escuela Superior Politecnica de Chimborazo (ESPOCH). The software was developed under the Scrum methodology and Representational State Transfer Services (REST), which allowed the development team and users to be adequately involved to design the necessary functionalities of the system. To evaluate the efficiency of the processes carried out by end-users, the response times of the old system versus the automated system were measured, significantly improving the management of these processes.
Ideal secret sharing schemes on graph-based $3$-homogeneous access structures

‎The characterization of the ideal access structures is one of the main open problems in secret sharing and is important from both practical and theoretical points of views‎. ‎A graph-based $3-$homogeneous access structure is an access structure in which the participants are the vertices of a connected graph and every subset of the vertices is a minimal qualified subset if it has three vertices and induces a connected graph‎. ‎In this paper‎, ‎we introduce the graph-based $3-$homogeneous access structures and characterize the ideal graph-based $3$-homogeneous access structures‎. ‎We prove that for every non-ideal graph-based $3$-homogeneous access structure over the graph $G$ with the maximum degree $d$ there exists a secret sharing scheme with an information rate $frac{1}{d+1}$‎. ‎Furthermore‎, ‎we mention three forbidden configurations that are useful in characterizing other families of ideal access structures‎.
PERANAN PERUSAHAAN DALAM MENINGKATKAN KEMAMPUAN KERJA PETERNAK DAN KUALITAS HASIL PANEN MADU DI MASA PANDEMI

The Covid-19 pandemic has undeniably crippled the economy of the wider community. Beekeeping and its derivatives business are promising efforts during the current pandemic. Honey, which is one of its derivative products, has become a necessity that is most in demand by the public to maintain stamina and endurance. Currently the market demand for good quality honey is getting bigger, so that this opportunity is widely exploited by honey business actors. The purpose of this study was to analyze the efforts made by Bali Honey in improving the working ability of honey breeders in the midst of the Covid-19 pandemic and to analyze the strategies implemented to improve the quality of the honey harvest to bring benefits to the local community. The data analysis method is descriptive qualitative. Data analysis was carried out by collecting secondary data and primary data. The data and information obtained through field research are then analyzed by doing data reduction, namely summarizing the data from interviews and field observations, then interlinking them with the theoretical basis and literature review to get a final conclusion. The theoretical foundations used in the research are reinforcement theory, expectancy theory, and goal setting theory. The result of the research is that consistent education carried out by Bali Honey plays an important role in improving the working ability of honey farmers so that the quality of the yields produced can compete in the market.&#x0D; Keyword : the role of the company, work ability, product quality
NP-LFA: Non-profiled Leakage Fingerprint Attacks against Improved Rotating S-box Masking Scheme

Abstract DPA Contest is a world-famous side-channel competition aiming at analyzing and evaluating the implementing security of some latest countermeasures. Improved Rotating S-box Masking Scheme (RSM2.0) is one of the most popular countermeasures designed during DPA Contest V4.2, which arms with both Low Entropy Masking Schemes and shuffling strategy to ensure the software security of AES-128, particularly the non-profiled security. Up to now, conducting high efficient non-profiled attacking scheme with low resource costs is still a challenge. In this paper, we first propose general and non-profiled leakage fingerprint attacks (named NP-LFA) for secret cracking and make use of it to crack RSM2.0 random masks with almost 100% accuracy. Further, we analyze the hidden vulnerabilities embedded in RSM2.0 implementation, and utilize them to bypass the shuffling defense and perform the master key recovery. Official evaluation results show that NP-LFA is capable of compromising RSM2.0 within 14 traces, each of which only costs 60 ms processing time. Such result validates the high efficiency and light-weighted characteristics of our attacking scheme, which has ranked the first in the official website till now. In addition, we discuss and put forward some possible strategies to mitigate our NP-LFA threats.
Introduction to Artificial Intelligence and Robotics

Robots, autonomous vehicles, unmanned aerial vehicles, and smart factory, will significantly change human living style in digital society. Artificial Intelligence in Wireless Robotics introduces how wireless communications and networking technology enhances facilitation of artificial intelligence in robotics, which bridges basic multi-disciplinary knowledge among artificial intelligence, wireless communications, computing, and control in robotics. A unique aspect of the book is to introduce applying communication and signal processing techniques to enhance traditional artificial intelligence in robotics and multi-agent systems. The technical contents of this book include fundamental knowledge in robotics, cyber-physical systems, artificial intelligence, statistical decision and Markov decision process, reinforcement learning, state estimation, localization, computer vision and multi-modal data fusion, robot planning, multi-agent systems, networked multi-agent systems, security and robustness of networked robots, and ultra-reliable and low-latency machine-to-machine networking. Examples and exercises are provided for easy and effective comprehension. Engineers wishing to extend knowledge in the robotics, AI, and wireless communications, would be benefited from this book. In the meantime, the book is ready as a textbook for senior undergraduate students or first-year graduate students in electrical engineering, computer engineering, computer science, and general engineering students. The readers of this book shall have basic knowledge in undergraduate probability and linear algebra, and basic programming capability, in order to enjoy deep reading.
Characterizing Smart Systems with Interactive Personalization

The personal adaptation of services, in which a system provides services according to the preferences and needs of individual users, is a key to the realization of the emerging Society 5.0. The personal adaptation of systems has been implemented through personal settings by users. However, it is very difficult for users who are not familiar with ICT to manually define the settings that meet their needs. In this paper, we therefore propose a new notion of smart system: Smart System with Interactive Personalization (SSIP). In SSIP, the system and the user have continuous and interactive conversations during the system operation. In the dialogue, the user tells his or her needs and the system introduces its functions. In this way, the user and the system understand each other and dynamically co-create personal settings. In this paper, in order to define SSIP, we present three functional requirements that the system must meet. We also characterize SSIP from the quality viewpoint by quality in use of the international standard SQuaRE. Finally, as a case study, we take the Mind Monitoring Service being developed by our group, and apply the proposed SSIP framework to individual adaptation of the incentive provision feature.
Human-in-the-loop Approach towards Dual Process AI Decisions

How to develop AI systems that can explain how they made decisions is one of the important and hot topics today. Inspired by the dual-process theory in psychology, this paper proposes a human-in-the-loop approach to develop System-2 AI that makes an inference logically and outputs interpretable explanation. Our proposed method first asks crowd workers to raise understandable features of objects of multiple classes and collect training data from the Internet to generate classifiers for the features. Logical decision rules with the set of generated classifiers can explain why each object is of a particular class. In our preliminary experiment, we applied our method to an image classification of Asian national flags and examined the effectiveness and issues of our method. In our future studies, we plan to combine the System-2 AI with System-1 AI (e.g., neural networks) to efficiently output decisions.
Performing Communicative Language Teaching in Mandarin Mobile Learning

&lt;p class="0abstract"&gt;Students should be able to develop their communication abilities instead of just concentrating on translation methods. As a result, Communicative Teaching Language (CLT) had become the most favored approach to achieving the verbal goal as it was known as the most effective strategy to enhance learners' communicative competence. However, it was not a one-size-fits-all approach, and language instructors were advised to integrate educational technology to develop learning for students. Hence, CLT Mandarin mobile learning via personal action research was conducted to determine the extent of the approach on students' oral learning attainment, attitudes, and learners' recommendations during the learning process. The communicative task used in this study was Chatting to Mandarin Native Speakers programme. Pre- and post-oral assessments had been conducted in response to research inquiries. In verifying the reliability and validity of the study, data were triangulated through students' oral assessments, Students' Diaries, Self-Reflective Journals and Focus Group Interviews. The outcomes showed that students enjoyed the activity and improved their confidence and oral competence. Also, they suggested that there should be more language activities. The findings indicated that, when designing CLT technology-integrated projects, an instructor needed to consider students' learning preferences which make the project a success.&lt;/p&gt;
RANCANG BANGUN APLIKASI BACK END MANAJEMEN SURAT MASUK dan KELUAR SEKRETARIAT DPRD PROVINSI BALI

Archiving is an activity of recording events in various forms and media. Archiving activities are very important in an agency for example in the Bali Provincial Secretariat. At this agency, letter archiving is still done conventionally. So if the letter is received a lot, it will be difficult to find the letter. In addition there is also the risk of losing letters. From these problems the author thinks of a solution that is expected to alleviate the problem of filing letters in the agency. The solution is to implement an incoming and outgoing mail management system at the Bali Provincial DPRD Secretariat agency. This system was developed using the Waterfall method and using the PHP programming language and MySQL database.&#x0D; Keywords: Letter Archive, Waterfall Method, Management Information System.
Adaptation of Students and Teachers in Conditions of Transition to a New Educational Model of Higher Education Using Distance Education Technologies

This article discusses current issues of transition to a new educational model in the higher education system of the Russian Federation. The author notes some problems of using distance educational technologies in the conditions of adaptation of teachers and students, based on their own experience of teaching legal disciplines. Conclusions are made that it is necessary to form innovative approaches to remote interaction between students and teachers, since the electronic form of education is a completely different model of interaction than the traditional one. Methods of analysis, generalization, dialectics, and systematization are used. Scientific and practical significance: the main results of the article can be useful for further work on identifying promising areas for improving and improving the effectiveness of the entire system of higher education and developing the foundations of legal regulation in this area.
Improving Color Space Conversion for Camera-Captured Images via Wide-Gamut Metadata

Color space conversion is the process of converting color values in an image from one color space to another. Color space conversion is challenging because different color spaces have different sized gamuts. For example, when converting an image encoded in a medium-sized color gamut (e.g., AdobeRGB or Display-P3) to a small color gamut (e.g., sRGB), color values may need to be compressed in a many-to-one manner (i.e., multiple colors in the source gamut will map to a single color in the target gamut). If we try to convert this sRGB-encoded image back to a wider gamut color encoding, it can be challenging to recover the original colors due to the color fidelity loss. We propose a method to address this problem by embedding wide-gamut metadata inside saved images captured by a camera. Our key insight is that in the camera hardware, a captured image is converted to an intermediate wide-gamut color space (i.e., ProPhoto) as part of the processing pipeline. This wide-gamut image representation is then saved to a display color space and saved in an image format such as JPEG or HEIC. Our method proposes to include a small sub-sampling of the color values from the ProPhoto image state in the camera to the final saved JPEG/HEIC image. We demonstrate that having this additional wide-gamut metadata available during color space conversion greatly assists in constructing a color mapping function to convert between color spaces. Our experiments show our metadata-assisted color mapping method provides a notable improvement (up to 60% in terms of E) over conventional color space methods using perceptual rendering intent. In addition, we show how to extend our approach to perform adaptive color space conversion based spatially over the image for additional improvements.
On the notion of dialectics in the linguistic bodies theory

This paper addresses the notion of dialectics in the linguistic bodies theory. First, it presents it as a three-aspect concept, namely, the ontological aspect, the methodological aspect, and the dialectical model. Subsequently, it discusses the ontological aspect and the dialectical model and, based on the enactivist linguistic notions of concreteness and abstraction, suggests that it can be conceived as a two-fold concept: methodological and epistemological. This suggestion intends to avoid the paradox we are led to by acknowledging three ontological enactivist claims and a few assumptions of the methodological approach.Keywords: Dialectics, Enactivism, Language, Epistemology, Ontology.
Adaptive Anomaly Detection for Dynamic Clinical Event Sequences

Over the past decade, health information technology (IT) has enabled the amount of digital information stored in electronic health records (EHRs) to expand greatly. However, according to some studies, hazards in health IT can lead to changes in clinical decisions, care processes, and care outcomes, as well as other issues. Thus, the effects of health IT hazards on patient safety have been at the forefront of recent patient safety research. Nonetheless, hazard detection in health IT remains a challenge. In this paper, the authors assume that safety-related issues in health IT would exhibit anomalous characteristics in EHR data. Although all hazards will exhibit some anomalous characteristics, not all anomalies can be regarded as hazards. The authors hypothesize that errors in health IT could lead to interruptions in the sequence of clinical actions. To this end, the problem of detecting anomalous sequences in big EHR data is considered. This paper focuses on dynamic event sequences, which are a series of clinical actions in motion. The authors propose an adaptive anomaly detection approach that uses higher-order network representation to detect anomalous sequences. Furthermore, the authors propose a contiguous subsequence anomaly detection approach that identifies abnormal subsequences in the detected anomalous sequences. The proposed approaches are tested by using synthetic and real-world EHR data. The proposed methods outperform existing state of the art anomaly detection techniques. To reduce the computational complexity associated with the operational implementation of the proposed approaches, the Apache Spark environment was leveraged, and a much shorter run time together with improved performance were achieved, especially for data with more than 60,000 sequences.
Use of Microsoft Teams and Youtube in the Application of E-Learning to Improve Student Learning Outcomes in Three-Dimensional Material

The objectives of this study were (1) to increase the motivation to learn the mathematics of students of XII MIPA-2 with three-dimensional material through the application of E-learning using Microsoft Teams and Youtube, (2) to increase the mathematics learning achievement of students of XII MIPA-2 with three-dimensional material through the application of E-learning using Microsoft Teams and YouTube. The method used is classroom action research. Data collection through tests and non-tests. The test technique is to determine learning achievement using the items while the non-test technique is to determine the development of learning motivation using observation sheets. Data analysis used comparative descriptive for learning achievement data and qualitative descriptive for learning motivation data. The results of this classroom action research showed that the students 'motivation to learn mathematics increased from low to high and the average score of students' mathematics learning achievement increased by 20.85% from 65.05 to 78.61 with an increase in completeness level of 57.88%, namely from 52, 78% to 83.33%, so theoretically and empirically through the application of E-learning using the Microsoft Teams and Youtube application it can improve the results of motivation and achievement in learning mathematics in three-dimensional material for students of class XII MIPA-2 SMA Negeri 1 Jepara in the odd semester of 2020 -2021.&#x0D; Keywords: E-learning, Microsoft Teams, Youtube, three dimensions.
Software Development Life Time Prediction Using Machine Learning Approach and There Comparison

Software Engineering Project Management (SEPM) contributes to being a key factor in determining the success of a software project. One of the major tasks assigned to it is to estimate the time that needs to be put in the process of development of the software. In real life, we use a plethora of different prediction machine learning algorithms in order to calculate the time it takes, but we have to keep in mind the accuracy and performance of this algorithm. To get the comparative study of the different machine learning techniques that is simple linear-regression, multiple-regressions, Artificial neural networks and the Gaussian-algorithm will be put into action in an attempt to correctly calculate the time it takes in software production keeping in mind the parameters. The dataset that we are trending to test is the content of past software development. Eventually the results that we obtained are published.
Batch mode active learning framework and its application on valuing large variable annuity portfolios

In practice, the valuation of a large volume variable annuity contracts relies on Monte Carlo simulation which is quite computationally intensive. To build a more efficient valuation process, statistical models have been used within a data mining framework that consists of two subsequent stages: the data sampling stage to create a set of representative contracts, and the regression modeling stage to make predictions for the remaining contracts in the portfolio. In this article, we work with a new data mining framework based on active learning, in which we iteratively update the regression model efficiently by selecting the most informative representatives. Our metrics take into consideration both the ambiguity and the diversity of the prediction, which allow us to propose two methods that fit well in this active learning framework. Experimental results demonstrate the effectiveness of the proposed active learning approaches over the random sampling as well as the two-stage data mining framework.
Application Use of Augmented Reality in the Educational Process

Educational tools for computer modelling with the implementation of augmented reality elements have an irreplaceable place in the period of the digital revolution of Industry 4.0. The integration of augmented reality into the educational process in the field of computer modelling, in this paper, consists in the creation of technical documentation of the wheel suspension part and the subsequent creation of an application for the visualization of this model in the real environment.