Reviewerly/exHarmony huggingface dataset:
The Use of New Technologies in the Organization of the Educational Process

This paper discusses the use of new technologies in education. The analysis of the implementation of various innovative developments in education is given. The authors presented the software product using smart technologies, which allows studying physics using virtual reality. Such approach allowed to make interaction with the application more interesting and memorable, and learning more effective. The Unity 3D cross-platform environment was chosen as the development platform. The main functionality was written in C#. Graphic models were created using Substance Painter.
Delegatable searchable encryption with specified keywords for EHR systems

With the development of big data and cloud computing, more and more data owners store their data with encrypted form in the cloud server. To retrieve some data they are interested in, an important technology called searchable encryption can be adopted. Sometimes, the encrypted data are desired to be shared to some users by the data owners without destroying the user privacy. To address this problem, many works of delegated searchable encryption (DSE) have been studied. However, in the existing DSE schemes, the delegated users can make keyword search over the encrypted data without any restrictions. In some systems such as E-health record system in which the data are sensitive, it is desired that the delegated users can only make search with some specified keywords designated by the data owners. In this work, we present an efficient solution to this problem and give a concrete construction. Then we show that our construction is efficient and practical for real applications by experimental results.
Single-ion qubit with coherence time exceeding 10 minutes

Quantum memory device capable of storing quantum information for a long period of time is one of the fundamental ingredients to realize large-scale quantum computation and quantum communication. Comparing with other quantum computation platforms, one of the advantages of the trapped-ion system is the long intrinsic coherence time. Before our work, the longest single-qubit coherence time in trapped-ion systems has been achieved to be less than 1 minute. It is discovered that the main limitation for the coherence time is the motional mode heating and the environment noise that includes the contributions from the magnetic field fluctuation and the phase noise of the microwaves. In a hybrid trapping system simultaneously trapping &lt;sup&gt;171&lt;/sup&gt;Yb&lt;sup&gt;+&lt;/sup&gt; and &lt;sup&gt;138&lt;/sup&gt;Ba&lt;sup&gt;+&lt;/sup&gt; ions, single-qubit quantum memories with coherence time longer than 10 minutes can be realized by applying sympathetic cooling and dynamical decoupling. This technique may have some value as the building blocks for quantum cryptography protocols and hybrid quantum computation platforms.
phonetic case study on prosodic variability in suicidal emergency calls

Speech prosody has been applied in numerous speech emotion recognition tasks. Yet, especially in forensic speech science, a need for acoustic-phonetic analyses with human evaluation still exists since many current speech emotion models are trained with speech data wherein emotions are considered as constant states and the dynamic effects of the interlocutor have been disregarded; for instance, during an emergency call, the caller’s emotional prosody varies according to the communication with the emergency operator, which causes problems for existing speech emotion models when analysing individual emergency recordings. In this phonetic case study, prosodic variation was investigated in two suicidal emergency calls; eight prosodic features from two adult male callers were analysed before and after hearing the emergency operators’ offer to help. In addition, the existence of a possible linear association between the emergency operator’s and the caller’s prosodic features were evaluated. The results show that caller and operator pitch are negatively correlated (?0.33), and half of callers’ prosodic features vary significantly (p &lt; 0.05) after hearing the offer of help.
Augmented Reality for City Planning

We present an early study designed to analyze how city planning and the health of senior citizens can benefit from the use of augmented reality (AR) with assistance of virtual reality (VR), using Microsoft’s HoloLens and HTC’s Vive headsets. We also explore whether AR and VR can be used to help city planners receive real-time feedback from citizens, such as the elderly, on virtual plans, allowing for informed decisions to be made before any construction begins. In doing so, city planners can more clearly understand what design features would motivate senior citizens to visit or exercise in future parks, for example. The study was conducted on 10 participants 60 years and older who live within 2 miles from the site. They were presented with multiple virtual options for a prospective park, such as different walls for cancelling highway noise, as well as benches, lampposts, bathroom pods, walking and biking lanes, and other street furniture. The headsets allowed the participants to clearly visualize the options and make choices on them. Throughout the study the participants were enthusiastic about using the AR and VR devices, which is noteworthy for a future where city planning is done with these technologies.
Towards the Ethnic Understanding of Taiwanese Indigenous Peoples: A Mashup Based on Semantic Web and Open Data

The purpose of this study is utilizing semantic web technologies to mix diverse datasets of Taiwanese indigenous peoples to facilitate ethnic understanding. Because indigenous peoples have been in a lower social grade for centuries, indigenous culture and corpus are relatively rare in the modern society. Insufficient information not only enlarge the gap of misunderstanding but lead to the emotional alienation between ethnics. To integrate multiple data sources, a data mashup is a way to achieve the integration of data. Furthermore, the result of mashups may offer new insights to discover interesting knowledge. To implement data mashup on the Web, three components are identified: (1) collecting available open data related to indigenous people; (2) performing a data conversion process to convert non-RDF to RDF data; (3) developing SPARQL federated queries to mix data from diverse endpoints. Furthermore, a web-based application based on an interactive map is utilized to facilitate ordinary users to find information from the general information of tribes to cultural artworks. The experimental results show that data mashup design can help users quickly understand essential information of indigenous peoples.
Hand Gesture Recognition for Smartphone-Based Augmented Reality Applications

Hand Gesture Recognition (HGR) is a principal input method in head-mounted Augmented Reality (AR) systems such as HoloLens, but the high cost and limited availability of such systems prevent HGR from becoming more prevalent. Alternatively, smartphones can be used to provide AR experiences, but current smartphones were not designed with HGR in mind, making development of HGR applications more challenging. This study develops a software-based framework that implements HGR as a principal input method for smartphone AR applications. This framework assumes a contemporary smartphone with dual back-facing cameras, which enable stereo imaging and thus allow extraction of limited depth information from the environment. Several image processing techniques, derived and improved from previous work, were used to filter the noisy depth information to segment the user’s hand from the rest of the environment, and then to extract the pose of the hand and fingers in real-time. The framework additionally facilitates the development of cross-platform AR applications for both head-mounted (HoloLens) and smartphone configurations. A user experiment is held to determine whether a smartphone-based AR application developed using our HGR framework is comparable in usability to the same application on the HoloLens. For each device, participants were asked to use the application and fill out a usability questionnaire. They were also asked to compare the two systems at the end. This experiment shows that, despite the current limitations of smartphone-based HGR, the smartphone system’s usability is competitive with that of the HoloLens. This study ends with recommendations for future development.
Method of monitoring and detection of failures in PV system based on machine learning

Machine learning methods have been used to solve complicated practical problems in different areas and are becoming increasingly popular today. The purpose of this article is to evaluate the prediction of the energy production of three different photovoltaic systems and the supervision of measurement sensors, through Machine learning and data mining in response to the behavior of the climatic variables of the place under study. On the other hand, it also includes the implementation of the resulting models in the SCADA system through indicators, which will allow the operator to actively manage the electricity grid. It also offers a strategy in simulation and prediction in real-time of photovoltaic systems and measurement sensors in the concept of smart grids.
New Oracle-Efficient Algorithms for Private Synthetic Data Release

We present three new algorithms for constructing differentially private synthetic data---a sanitized version of a sensitive dataset that approximately preserves the answers to a large collection of statistical queries. All three algorithms are \emph{oracle-efficient} in the sense that they are computationally efficient when given access to an optimization oracle. Such an oracle can be implemented using many existing (non-private) optimization tools such as sophisticated integer program solvers. While the accuracy of the synthetic data is contingent on the oracle's optimization performance, the algorithms satisfy differential privacy even in the worst case. For all three algorithms, we provide theoretical guarantees for both accuracy and privacy. Through empirical evaluation, we demonstrate that our methods scale well with both the dimensionality of the data and the number of queries. Compared to the state-of-the-art method High-Dimensional Matrix Mechanism \cite{McKennaMHM18}, our algorithms provide better accuracy in the large workload and high privacy regime (corresponding to low privacy loss $\varepsilon$).
Evaluasi Program Bantuan Operasional Sekolah (BOS) di Sekolah Dasar

This research aims to gather information and obtain gaps in the implementation of the school operational assistance (BOS) program to improve the quality of education. This study used a gap evaluation model (Discrepancy). The subjects of the research were the principal, the teacher (BOS treasurer), the school supervisor, the school committee, the District coordinator, and the parents of the students. Data were collected from research sites using observation techniques, document studies and interviews. Information obtained was analyzed by using the Miles and Hubermen model which included data reduction, presentation, and conclusion drawing. Based on the result of the study, there were still gaps in several aspects between implementation and standards of BOS program. Design aspect was following BOS 2019 Technical Guidelines. There was a gap at the installation stage; there were sudden and costly activities, while expenses must be adjusted to the liability letter (SPJ). At the implementation stage, there was a delay in the process of disbursing BOS, which was the main source of education funding. Thus, from the implementation stage it can be concluded that there are still gaps between the implementation of BOS with the Technical Guidelines.
SyncMeet: Virtual Work Environment for Collaborative Manga Creation

In recent years several efforts using technologies to improve collaborative work have been made in fields such as education, training, entertainment, and technology; however, there has been limited research for collaborative creative thinking and art. In this study, we explore the opportunities within virtual collaboration in creative activities via a virtual work environment named SyncMeet. This virtual environment aims to support the discussion of artistic ideas and effective collaboration during a brainstorming session for a storyboard of Japanese comic (manga) between two people who have different narrative abilities such as a writer and illustrator, and who work in distant locations. In this approach, we demonstrated that working inside an immersive environment could improve the users' collaboration, creative skills, and communication. We handled three different experiment sessions that allowed us to compare effectiveness in face-to-face environments, Skype, and SyncMeet. The results indicated that SyncMeet supports verbal and non-verbal communication as a fundamental part of collaboration in a creative task, and the users who were able to immerse themselves inside the environment showed active participation when they worked in distant locations.
TEACHING READING THROUGH RECIPROCAL TEACHING METHOD

This paper aims to investigate whether the university students who are taught reading through Reciprocal Teaching Method achieve better in reading ability than those who are taught through Direct Reading Thinking Activities. The design of this study is a quasi-experimental, non-randomized control group, pretest-posttest since it is conducted in a classroom setting that the subjects have been organized into classes. The subject of the study was the fourth term of university students of English education study program consisting 30 university students. The instrument of this research was a test as Pre-test and Post-test in the form of reading comprehension questions. The data analysis used Independent T-Test. Based on the result of the calculation of post-test from experimental and control groups, the alternative hypothesis (Ha) was accepted. The result of the study shows that the use of the Reciprocal Teaching Method can improve the university students’ reading ability. It proves the hypothesis of the study that students who are taught reading through the Reciprocal Teaching method achieve better in reading ability than those who are taught through Direct Reading Thinking Activities. Based on this result, it can be concluded that the Reciprocal Teaching Method can be used as an alternative method to teach reading, so that the students are able to understand the texts comprehensively. It also makes the university students more active in the teaching learning process and can improve their ability as well.
Synthesis of the Method of Operative Image Analysis based on Metadata and Methods of Searching for Embedded Images

The purpose of this work is to develop a mobile application for assessing the credibility of a digital image. To achieve this goal, an analysis of image forensics methods was conducted, as well as a comparative analysis of existing image confidence assessment resources. A method of trusting an image in a mobile app has been developed and implemented.
Study on the Development of Augmented-Reality Navigation System for Transsphenoidal Surgery

In this study, we developed an augmented-reality (AR) navigation system that can assist surgeons during transsphenoidal surgery, including identification of the tumor site. Since transsphenoidal surgery is performed by looking at an endoscopic image, thus requiring situational judgment on the image, transsphenoidal surgery poses greater challenges with regard to grasping the positional relationships between the tumor and the organs compared with normal operations. The proposed system is expected to help surgeons understand the conditions surrounding the operating field, by intraoperatively displaying a real-time overlaid 3D model based on preoperative MRI images of the patient. Markers were used to obtain the data necessary to view the overlaid images, which were attached to the operating table and to the end of the endoscope. The patient’s head was held in a fixed position during the surgery. The relative positions of the maker on the operating table and the feature point on the patient’s head were captured by a camera mounted on top of the operating table. Then, using this information, the positions of the tumor and the organs were estimated, and a 3D model was created using the patient’s MRI scans. Further, by obtaining the relative position of the markers attached to the end and tip of the endoscope, the position of the tip of the endoscope was estimated from the marker at the end even if it could not be seen from outside after inserting it into the patient’s body during surgery. The relative positions of the tip of the endoscope and the tumor site were calculated, and a 3D model was displayed using the MRI images in conjunction with the current endoscopic image. By constantly updating the positional information in accordance with the behavior of the endoscope, the overlaid image of the tumor and the organs could be viewed. In this study, we developed a prototype of the proposed system, and discussed the accuracy of its results.
Research on Intelligent Design Tools to Stimulate Creative Thinking

With the development of artificial intelligence technology, AI has been more and more employed in the process of design, providing unlimited possibilities for future design tools. In order to promote AI technology to better assist design and meet the needs of non-professional designers who want to participate in design, we research on design tools with AI’s participation, based on the ‘double diamond’ design process model, combining reasonable design thinking processes and design tools. Taking the expansion stage of students’ thinking as the starting point, we use the WoZ method to conduct experiments and compare the different effects of AI’s assistants with different functions in different thinking stages. We explore what role AI should play in the design process and how strong it should interfere with the designers and put forward some ideas for future design tools.
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space

Recent advances in the field of artificial intelligence have been made possible by deep neural networks. In applications where data are scarce, transfer learning and data augmentation techniques are commonly used to improve the generalization of deep learning models. However, fine-tuning a transfer model with data augmentation in the raw input space has a high computational cost to run the full network for every augmented input. This is particularly critical when large models are implemented on embedded devices with limited computational and energy resources. In this work, we propose a method that replaces the augmentation in the raw input space with an approximate one that acts purely in the embedding space. Our experimental results show that the proposed method drastically reduces the computation, while the accuracy of models is negligibly compromised.
Metrological Research on the Application Literature of AI Education in China: 2009-2019

Abstract Based on the CSSCI (Chinese Social Sciences Citation Index) full-text database of CNKI, this paper selects 468 journal articles on the application of AI in education from 2009 to the present. Based on the measurement visualization software CiteSpace, the data mining and content analysis are carried out, and the in-depth analysis is carried out from six aspects: the overall trend, core authors, research institutions and fund distribution, research hotspot, evolution trend and research clustering, etc. It also shows the research situation in the field of AI education application in recent ten years by means of tables and visual knowledge maps, which can provide important reference for researchers in this field.
Integration Model of English Teaching Resources based on Artificial Intelligence

Aiming at the problems of low accuracy and high redundancy in the integration of teaching resources, an artificial intelligence-based model of English teaching resources integration is proposed. Web crawler recognition technology is used to obtain web page information of English teaching resources and to establish index database. L-NCD is introduced to eliminate redundant data of English teaching resources. ISPO algorithm and K-means algorithm are combined to complete the integration of English teaching resources and output results. The experimental results show that the resource integration accuracy of the model is higher than 90%, which proves that the resource integration accuracy of the model is higher. The resource repetition rate of this model is less than 1%, which proves that this model has a good effect of de-redundancy.
Research on Integration Method of AI Teaching Resources Based on Learning Behavior Data Analysis

Aiming at the problem of long running time and low precision of traditional artificial intelligence resource integration method, a new artificial intelligence teaching resource integration method based on learning behaviour data analysis is proposed. Analyse online learning behaviour data, extract relevant data of artificial intelligence teaching resources, and realise sample collection of artificial intelligence teaching resources. Random forest algorithm was used to classify them, reward and punishment factors were added, and mountain-climbing method was used to search the solution space, so as to realise the integration of artificial intelligence teaching resources. The experimental results show that this method can improve the efficiency and precision of the whole method, and obtain better integral results.
Designing Virtual Equipment Systems for VR

Skeuomorphism in virtual reality can provide more than just visual cues for quick recognition, it can also provide spatial information. A Virtual Equipment System is a system that takes advantage of the spatial information from a user’s body by equipping them with virtual counterparts of common wearables. It provides ways to quickly adjust a suite of functions that are conceptually related using spatial knowledge of human anatomy corresponding to the equipment. The system can also be used to provide shortcuts for interacting with properties of other objects related to the user’s sensory channels. As a software solution, this Virtual Equipment System can be standardized and implemented across different devices and applied to different extended realities.
Sandbox for Minimal Viable Governance of Blockchain Services and DAOs: CLAUDIA

To address the challenges of on-chain and off-chain governance of a blockchain project, CLAUDIA combines an on-chain services, such as Ethereum based DAO (Decentralized Autonomous Organization), timestamping solution (WUDDER), and decision making support (ARAGON), with off-chain “compliance desk”. The off-chain “compliance desk” enables stakeholders to report security issues and breaches of the codes of conduct and discuss necessary actions. The robust solution makes CLAUDIA user friendly but also adaptable. It can be offered as an app to various publics that do not necessarily care about the underlying solutions, but it can also meet the needs of variety of institutions that operate under different jurisdiction and business models. We discuss the advantages of this hybrid solution that combines the current modes of blockchain application testing in testnets and sandboxes to tackle the challenges of blockchain governance.
n-Refined Neutrosophic Rings

The aim of this paper is to introduce the concept of n-refined neutrosophic ring as a generalization of refined neutrosophic ring. Also, wepresent concept of n-refined polynomial ring. We study some basic concepts related to these rings such as AH-subrings, AH-ideals, AH-factors, and AH-homomorphisms.