Reviewerly/exHarmony huggingface dataset:
A Method for Measuring the Perceived Location of Virtual Content in Optical See Through Augmented Reality

For optical, see-through augmented reality (AR), a new method for measuring the perceived three-dimensional location of a small virtual object is presented, where participants verbally report the virtual object's location relative to both a horizontal and vertical grid. The method is tested with a Microsoft HoloLens AR display, and examines two different virtual object designs, whether turning in a circle between reported object locations disrupts HoloLens tracking, and whether accuracy errors found with a HoloLens display might be due to systematic errors that are restricted to that particular display. Turning in a circle did not disrupt HoloLens tracking, and a second HoloLens did not suggest systematic errors restricted to a specific display. The proposed method could measure the perceived location of a virtual object to a precision of ~1 mm.
Digital museum: features and prospects of development. (Review)

The review describes the main characteristics of digital museum. Shows the role of digital museum in the modern educational space. Presents risks and prospects of digitalization of modern museum activities.
Energy Storage Scheduling: A QUBO Formulation for Quantum Computing

Energy storage systems and home energy management and control systems will play an important role in reaching the Paris Agreement on climate change. Underlying scheduling mechanisms will lead to a computational burden when the size of the systems and the size of the control space increase. One, upcoming alternative to overcome this computational burden is quantum computing. Here a quantum computer is used to solve the scheduling problems. In this paper an approach of using the D-Wave quantum annealing to solve an energy storage scheduling problem is proposed and used to solve a small example. The example shows the potential that quantum computing can have in this area in the future.
Every finite abelian group is the group of rational points of an ordinary abelian variety over $\mathbb{F}_2$

We show that every finite abelian group $G$ occurs as the group of rational points of an ordinary abelian variety over $\mathbb{F}_2$. We produce partial results for abelian varieties over a general finite field $\mathbb{F}_q$. In particular, we show that certain abelian groups cannot occur as groups of rational points of abelian varieties over $\mathbb{F}_q$ when $q$ is large.
An unsupervised person re‐identification approach based on cross‐view distribution alignment

Unsupervised clustering is a kind of popular solution for unsupervised person re-identification (re-ID). However, due to the influence of cross-view differences, the results of clustering labels are not accurate. To solve this problem, an unsupervised re ID method based on cross-view distributed alignment (CV-DA) to reduce the influence of unsupervised cross-view is proposed. Specifically, based on a popular unsupervised clustering method, density clustering DBSCAN is used to obtain pseudo labels. By calculating the similarity scores of images in the target domain and the source domain, the similarity distribution of different camera views is obtained and is aligned with the distribution with the consistency constraint of pseudo labels. The cross-view distribution alignment constraint is used to guide the clustering process to obtain a more reliable pseudo label. The comprehensive comparative experiments are done in two public datasets, i.e. Market-1501 and DukeMTMC-reID. The comparative results show that the proposed method outperforms several state-of-the-art approaches with mAP reaching 52.6% and rank1 71.1%. In order to prove the effectiveness of the proposed CV-DA, the proposed constraint is added into two advanced re-ID methods. The experimental results demonstrate that the mAP and rank increase by ∽0.5–2% after using the cross-view distribution alignment constraint comparing with that of the associated original methods without using CV-DA.
On using Stack Overflow comment-edit pairs to recommend code maintenance changes

Code maintenance data sets typically consist of a before version of the code and an after version that contains the improvement or fix. Such data sets are important for various software engineering support tools related to code maintenance, such as program repair, code recommender systems, or Application Programming Interface (API) misuse detection. Most of the current data sets are typically constructed from mining commit history in version-control systems or issues in issue-tracking systems. In this paper, we investigate whether Stack Overflow can be used as an additional source for building code maintenance data sets. Comments on Stack Overflow provide an effective way for developers to point out problems with existing answers, alternative solutions, or pitfalls. Given its crowd-sourced nature, answers are then updated to incorporate these suggestions. In this paper, we mine comment-edit pairs from Stack Overflow and investigate their potential usefulness for constructing the above data sets. These comment-edit pairs have the added benefit of having concrete descriptions/explanations of why the change is needed as well as potentially having less tangled changes to deal with. We first design a technique to extract related comment-edit pairs and then qualitatively and quantitatively investigate the nature of these pairs. We find that the majority of comment-edit pairs are not tangled, but find that only 27% of the studied pairs are potentially useful for the above applications. We categorize the types of mined pairs and find that the highest ratio of useful pairs come from those categorized as Correction, Obsolete, Flaw, and Extension. These categories can provide data for both corrective and preventative maintenance activities. To demonstrate the effectiveness of our extracted pairs, we submitted 15 pull requests to popular GitHub repositories, 10 of which have been accepted to widely used repositories such as Apache Beam ( https://beam.apache.org/ ) and NLTK ( https://www.nltk.org/ ). Our work is the first to investigate Stack Overflow comment-edit pairs and opens the door for future work in this direction. Based on our findings and observations, we provide concrete suggestions on how to potentially identify a larger set of useful comment-edit pairs, which can also be facilitated by our shared data.
Revisiting PULSE 2 Textbook after Three Years: Have Teachers Changed Their Mind?

The present study aims to further explore Malaysian secondary English teachers’ perspective on the use of PULSE 2 in their language classrooms, after three years of its introduction in Malaysian secondary schools. The study is qualitative in nature, employing semi-structured interview as the approach for data collection the data. However, due to the Movement Control Order (MCO) the study was conducted through a Mobile Instant Messaging (MIM) application, WhatsApp. ATLAS ti. was employed to perform the content analysis to the collected data. The findings revealed that the respondents preferred to use imported English textbooks with local modifications in their language classroom. Most of them also felt that the level of the language content and skills offered by PULSE2 did not match with their students’ abilities. They also reported grouses about the difficult foreign content of PULSE 2, which indicated that they have yet to change their mind about it even after using it for three years. It is suggested that relevant stakeholders such as the Ministry of Education Malaysia (MOE) to review the use of imported textbooks such as PULSE 2 in Malaysia, as this will bear an impact on the creation of the country’s version of the Common European Framework of Reference for Languages (CEFR) called ‘CEFR-M’ as projected in the on-going English Language Education Reform in Malaysia by 2025. Not only that, selecting a textbook that is relatable, localized, and matches the students’ level is crucial in this COVID-19 era, where the new normal in education forces learning to be done remotely. Inevitably, there will be students who are less privileged, and their only hope to gain access to continuous education is through a textbook that can easily be used for self-study and is readily available, without having the needs to have access to advanced technological devices.
Research of Intelligent Campus Design Based on Immersive BIM + VR Technology

Abstract With the maturity of virtual reality technology, more and more domestic colleges and universities have introduced virtual reality technology into the construction of the intelligent campus, establishing vivid and real three-dimensional virtual campuses, and achieving the goal of campus information, intelligence and visualization. This topic mainly studies the construction process of the smart campus based on BIM + VR technology. Taking the university buildings as the research area, the whole process from basic modeling to content innovation is discussed in detail. The VR smart campus is successfully established, and the innovative application of VR smart campus and campus sightseeing and VR fire simulation escape is realized.
Engineering Model-Based Software Testing of WIMP Interactive Applications

The goal of software testing is to detect defects with the objective of removing them at a later stage in the development process. Interactive software development follows the User Centered Design approach that promotes continuous involvement of users both at design and evaluation phases. This process is meant to produce usable interactive software by gathering functional and non-functional requirements related to both user needs and context of use. However, taking into account these potentially very-complex-to-implement requirements increases the complexity of the software that is likely, without appropriate methods and tools, to encompass a large number of defects. One of the limitations of UCD approaches is that it provides no guidance on the engineering of the interactive application, which thus usually embeds numerous defects resulting in failures at the origin of user frustrations and performance drops. Even though a classification of interactive application defects has been proposed, interactive application testers remain only superficially supported in detecting them. This paper defines a model-based approach to engineer the testing activity for interactive applications. It proposes a process that bridges the gap between UCD artefacts and interactive software implementation by the production of a dedicated formal model exploited for testing purposes only. The application of the process is demonstrated on an interactive cockpit WIMP application. Finally, threats to validity (capability of the approach to detect defects and to ensure an acceptable coverage testing of the interactive application) are addressed by a longitudinal study on 61 variants of a simple application developed by 61 different developers. ?
An Analysis of Text-to-Image Synthesis

The technique of generating an image from the given text description is called Text-to-image synthesis. Human beings can visualize and conceptualize images described by natural language elucidations. Which appears to be a simple task for the human brain is one of the foremost challenging problems in Natural Language Processing and Computer Vision. The digital world is overflooded with various types of images. But still getting an image of the required resolution, scale or mode is a distant dream. Capturing advanced medical images or satellite images with needed quality is very challenging due to the complexity involved. Text-to-image synthesis is a blessing for such fields. Some other fields like fashion designing, interior designing, etc. are the application areas of text-to-image synthesis. It is considered a hard problem compared to the reverse problem of captioning of images due to its multimodal nature and complexity involved in problem-solving. With the introduction of Generative Adversarial Networks (GANs), text-to-image synthesis has gained new heights of success and received much attention. Many image synthesis models have been proposed in the literature, where GANs play a pivotal role. This paper aims to give a glimpse of the revolutionary models in the field of text to image synthesis. We also discuss the evaluation metrics and datasets used and the various issues and the likely directions of future research.
A Joint Summarization and Pre-Trained Model for Review-Based Recommendation

Currently, reviews on the Internet contain abundant information about users and products, and this information is of great value to recommendation systems. As a result, review-based recommendations have begun to show their effectiveness and research value. Due to the accumulation of a large number of reviews, it has become very important to extract useful information from reviews. Automatic summarization can capture important information from a set of documents and present it in the form of a brief summary. Therefore, integrating automatic summarization into recommendation systems is a potential approach for solving this problem. Based on this idea, we propose a joint summarization and pre-trained recommendation model for review-based rate prediction. Through automatic summarization and a pre-trained language model, the overall recommendation model learns a fine-grained summary representation of the key content as well as the relationships between words and sentences in each review. The review summary representations of users and items are finally incorporated into a neural collaborative filtering (CF) framework with interactive attention mechanisms to predict the rating scores. We perform experiments on the Amazon dataset and compare our method with several competitive baselines. Experimental results show that the performance of the proposed model is obviously better than that of the baselines. Relative to the current best results, the average improvements obtained on four sub-datasets randomly selected from the Amazon dataset are approximately 3.29%.
Efficient Hardware Accelerator for Compressed Sparse Deep Neural Network

This work presents a DNN accelerator architecture specifically designed for performing efficient inference on compressed and sparse DNN models. Leveraging the data sparsity, a runtime processing scheme is proposed to deal with the encoded weights and activations directly in the compressed domain without decompressing. Furthermore, a new data flow is proposed to facilitate the reusage of input activations across the fully-connected (FC) layers. The proposed design is implemented and verified using the Xilinx Virtex-7 FPGA. Experimental results show it achieves 1.99×, 1.95× faster and 20.38×, 3.04× more energy efficient than CPU and mGPU platforms, respectively, running AlexNet.
Hyperradiance by a stream of phase-correlated atomic dipole pairs traversing a high-Q cavity

Abstract Hyperradiance in which radiation rate exceeds that of superradiance has been theoretically investigated in various coherently-coupled emitter-field systems. In most cases, either proposed setups were experimentally challenging or the mean photon number in a cavity was limited. In this paper, with numerical simulations and analytic calculations, we demonstrate that significant hyperradiance with a large mean photon number can occur in a microlaser system, where pairs of two-level atoms prepared in quantum superposition states traverse a high- Q cavity in the presence of a pump field intersecting the cavity mode. Hyperradiance is induced when the intracavity-pump Rabi frequency is out of phase with respect to the atom-cavity coupling so that the reduction of atomic polarization by the atom-cavity coupling is compensated by the pump Rabi frequency in the steady state to maximize atomic photoemission.
Global path planning of unmanned boat based on improved ant colony algorithm

When the ant colony algorithm is used to solve the global path planning of the unmanned boat, it is prone to problems such as local optimization and too slow convergence speed. This paper combines the problems encountered in the actual application of the unmanned boat and proposes an improved ant colony algorithm. Based on the traditional ant colony algorithm, the state transition rules are optimized and the pheromone volatilization coefficient is dynamically adjusted. The simulation results show that the improved ant colony algorithm compared with the traditional ant colony algorithm, the shortest path and path finding time of the USV to the destination are optimized, and the smoothness of the USV's search path is also improved.
Modeling in the environment of three-dimensional graphics as a method of forming students' critical thinking

The problem and the aim of the study. The formation of critical thinking is one of the most important tasks that teachers face in the vocational education system. The complexity, versatility of the studied objects, phenomena and processes of reality make it necessary for the mentors of the digital school to look for universal methods of cognition. The authors propose to use the modeling method in 3D graphics environments to form critical thinking as an important skill that meets the challenges of globalization and transformation. Research methods. The main method is modeling, as a general scientific method for studying the phenomena of reality using the analogy between the model and the original. The research was carried out on the basis of Vyatka State University for students of the training programme 44.04.01 Pedagogical education, profile Informatization of Education (master degree level). A software tool for organizing modeling as a method of teaching and scientific cognition is SketchUp. The Pearson’s χ2 (chi-square) criterion was used as a method for statistical processing of the experimental data. Results. The students of the experimental group used modeling in the environment of three-dimensional graphics at the following stages: acquiring theoretical information about the original object, creating a substitute model, developing a system of research problems, reflection, checking and adjusting the results in the conditions of the original object, the statement of a qualitatively new knowledge. The assessment of the levels of formation of critical thinking was carried out and statistically significant differences in the qualitative changes that occurred in the pedagogical system were revealed, χ2emp.2 &gt; χ2crit0.05 (6.42 &gt; 5.99). In conclusion, the conditions under which three-dimensional modeling contributes to the development of basic properties that ensure the formation of critical thinking are generalized: application together with other methods of scientific knowledge; modeling not only in a software environment for creating a 3D project, but also developing an Instruction as a model for its practical application; obtaining qualitatively new knowledge, etc.
The Effect of Blackboard Learning on the Development of English Writing Skills among University Students

This study investigated the effect of Blackboard platform on the development of students' writing skills in English.It employed a quasi-experimental design followed by qualitative interviews.The sample consisted of seventy students enrolled in the second semester of the academic year 2019/2020.They were divided equally into two groups (experimental and control).The experimental group was taught through Blackboard platform whereas the control group learned through conventional lectures.The researcher prepared a writing achievement test depending on the basic information needed to deal with English writing course ( ENGL 104) taught at Taibah University.The two groups were pre-post tested using a writing achievement test.The researcher analyzed data through Statistical Package for Social Sciences(SPSS).Twenty students in the experimental group were interviewed to identify their perceptions about Blackboard learning.Results revealed that Blackboard learning was effective in developing and improving the writing skills of the experimental group.The results also revealed a positive attitude towards Blackboard learning.The researcher recommended other researchers to conduct similar studies by using different sample in other areas and other language skills to determine the effect of Blackboard learning on English language learning.
PEMODELAN GEOGRAPHICALLY WEIGHTED GENERALIZED POISSON REGRESSION (GWGPR) PADA KASUS KEMATIAN IBU NIFAS DI JAWA TENGAH

Maternal mortality is one indicator to describing prosperity in a country and indicator of women's health. Most of the maternal mortality caused by postpartum maternal mortality. The number of postpastum maternal mortality is events that the probability of the incident is small, where the incident depending on a certain time or in a certain regions with the results of the observation are variable diskrit and between variable independent each other that follows the Poisson distribution, so that the proper statistical method is Poisson regression. However, in Poisson regression model analysis sometimes assumptions can occur violations, where the value of variance is greater than the mean value called overdispersion. Generalized Poisson Regression (GPR) is one model that can be used to handle overdispersion problems. This modeling produces global parameters for all locations (regions), so to overcome this we need a method of statistical modeling with due regard to spatial factors. The analytical method used to determine the factors that influence the number of postpartum maternal mortality in Central Java that have overdispersion and there are spatial factors, is Geographically Weighted Generalized Poisson Regression (GWGPR) using the Maximum Likelihood Estimation method and Adaptive Bisquare weighting. Poisson regression and GPR modeling produces a variable percentage of pregnant women doing K1 which has a significant effect on the number of postpartum maternal mortality, while for GWGPR modeling is divided into four cluster in all regency/city in Central Java based on the same significant variable. From the comparison of AIC values, it was found that the GWGPR model is better for analyzing postpartum maternal mortality in Central Java because it has the smallest AIC value.Keywords: The Number of Postpartum Maternal Mortality, Overdispersion, Generalized Poisson Regression, Spatial, Geograpically Weighted Generalized Poisson Regression, AIC
Exclusive use and evaluation of inheritance metrics viability in software fault prediction—an experimental study

Software Fault Prediction (SFP) assists in the identification of faulty classes, and software metrics provide us with a mechanism for this purpose. Besides others, metrics addressing inheritance in Object-Oriented (OO) are important as these measure depth, hierarchy, width, and overriding complexity of the software. In this paper, we evaluated the exclusive use, and viability of inheritance metrics in SFP through experiments. We perform a survey of inheritance metrics whose data sets are publicly available, and collected about 40 data sets having inheritance metrics. We cleaned, and filtered them, and captured nine inheritance metrics. After preprocessing, we divided selected data sets into all possible combinations of inheritance metrics, and then we merged similar metrics. We then formed 67 data sets containing only inheritance metrics that have nominal binary class labels. We performed a model building, and validation for Support Vector Machine(SVM). Results of Cross-Entropy, Accuracy, F-Measure, and AUC advocate viability of inheritance metrics in software fault prediction. Furthermore, ic, noc, and dit metrics are helpful in reduction of error entropy rate over the rest of the 67 feature sets.