Reviewerly/exHarmony huggingface dataset:
Sensor selection for hyper‐parameterized linear Bayesian inverse problems

Abstract Models of physical processes often depend on parameters, such as material properties or source terms, that are only known with some uncertainty. Measurement data can be used to estimate these parameters and thereby improve the model's credibility. When measurements become expensive, it is important to choose the most informative data. This task becomes even more challenging when the model configurations vary and the data noise is correlated. In this poster we summarize our results in [1] and present an observability coefficient that describes the influence of the sensors on the inverse solution. It can guide optimal sensor selection towards a uniformly good parameter estimate over all admissible model configurations. We propose a sensor selection algorithm that iteratively improves the observability coefficient, and present numerical results for a steady‐state heat conduction problem with correlated noise.
MIDAS: Model Inversion Defenses Using an Approximate Memory System

Private data constitute a significant share of the training information for machine learning (ML) algorithms. Recent works on model inversion attacks (MIA) have demonstrated that an ML model can leak information about the training dataset. We have examined the existing inversion attacks in this work and proposed a hardware-oriented security solution to defend an AI system from MIA. First, we demonstrate that an ML algorithm's execution flow in physical hardware can be leveraged to secure a trained model. Then, we find that approximate main memory, such as undervolted DRAMs, are useful in adding noise in a loaded model. Next, we design a secure algorithm MIDAS that ensures the safe execution of an ML algorithm under the presence of an adversary. After that, we evaluate MIDAS in terms of model accuracy degradation and similarity metrics. Finally, we examine MIDAS's security and privacy implication and its effectiveness in thwarting model inversion attacks. From our evaluations, we find that a hardware-dependent solution for MIA can ensure the training data privacy, even in an untrusted hardware and software stack.
Exploiting a genre-specific corpus in ESP writing

The purpose of this study is to gain greater understanding of effective approaches to data-driven learning (DDL) in ESP writing courses. To achieve this, it investigates student corpus users’ preferences for learning genre-appropriate phraseology and the corpus-informed strategies they adopt to exploit this phraseology in their writing. The study compares the phraseology in two learner corpora consisting of texts written by 118 university students. The texts in the first learner corpus were written before DDL intervention, while those in the second corpus were produced in an end-of-course exam following use of DDL tasks informed by a genre-specific corpus. An initial analysis considers whether the phraseology encountered in paper-based or computer-based DDL activities was more productive in the students’ writing. Questionnaire responses are then analysed to reveal the types of DDL tasks that students preferred and the corpus-informed strategies that they used while writing their exam texts. These include memorizing phrases encountered in DDL tasks, consulting the ESP corpus during the exam to check previously encountered phraseology, and looking up new phrases in the corpus during the exam. The implications of the results of this study for DDL strategy training and materials development to enhance students’ writing skills are discussed.
What’s Chat and Where to Find It

Chat or ‘non-goal directed’ dialogue has becomse a popular domain for spoken dialog system research, while the exponential increase in the use of commercial chatbots is creating interest in how to add friendly talk to make task-oriented systems more personable, or indeed to create systems which can create and maintain friendly relations with a user through the use of social talk. However, such talk is not very well defined, relevant data sources are few, and how to create artificial social talk is still an inexact science. This non-technical position paper briefly overviews these areas, exploring data used in chat systems and the limitations and challenges involved, and how these impact on the implementation of realistic social talk in spoken dialog systems.
Impact of Situational Impairment on Interaction with Wearable Displays

The number of wearable devices that we carry increases, with smaller companion devices like smartwatches providing quick access for simple tasks. These devices are, however, not necessarily in direct sight of the user and during everyday activities, it is unlikely, even undesirable, that the user constantly focuses on or interacts with these screens. Furthermore, interaction is often limited because our hands are occupied carrying or holding items such as bags, papers, boxes, or tools. In this paper, we evaluate how encumbrance affects, among others, the time it takes to perceive and react to a notification depending on the placement of the companion device. Our experimental results can assist designers in choosing the right device for the task.
Personalizing learning with mobile technology in a secondary school in the Netherlands: Effects on students’ autonomy support, learning motivation and achievement

Personalizing learning with technology in secondary schools is a way to empower students to take control of their learning. The more learners can direct their own learning experiences, including path, pace and instructional approach, the more they may learn what they want and need to learn. In a quasi-experimental design, data about the implementation and evaluation of three interventions in one secondary school in the Netherlands have been gathered with student questionnaires and regular exams. In these three interventions, each lasting one entire school year, teachers attempted to support their students’ autonomy in decisions during their learning process. Effects on students’ perceived autonomy support, learning motivation and their achievement have been examined. One intervention – the one with the highest scores on perceived autonomy support – shows small positive effects on students’ learning motivation and their achievement. Learner control over structural aspects of the curriculum, such as students’ autonomy to choose their tasks for practicing and reviewing and the way to complete them, is a possible effective way of designing personalizing learning in secondary education. In future research, more attention should be addressed to which combination of autonomy supportive activities might be effective. These effects might also be different for different student groups, based on, for example, their learning preferences and abilities.
Modelling user experience of adaptive streaming video over fixed capacity links

Streaming video continues to experience unprecedented growth. This underscores the need to identify user-centric performance measures and models that will allow operators to satisfy requirements for cost-effective network dimensioning delivered with an acceptable level of user experience. This paper presents an analysis of two novel metrics in the context of fixed capacity links: (i) the average proportion of a video’s playing time during which the quality is reduced and (ii) the average proportion of videos which experience reduced quality at least once during their playing time, based on an M/M/∞ system. Our analysis is shown to hold for the more general M/G/∞ system for metric (i), but not for (ii) and simulation studies show an unexpected form of sensitivity of metric (ii) to the flow duration distribution, contrary to the norm of increasing variance causing worse performance. At typical operational loads these new metrics provide a more sensitive and information rich guide for understanding how user experience degrades, than the widely used average throughput metric does. We further show that only the combined use of this existing and our new metrics can provide a holistic perspective on overall user performance.
Quantum Pulse Position Modulation with Photon-Added Squeezed States

This paper introduces the use of photon-added squeezed states (PASSs) for quantum pulse position modulation (QPPM). It is shown that the use of PASSs in QPPM communication systems can reduce the symbol error probability (SEP) with respect to the use of different classes of quantum states with the same energy, including squeezed states and photon-added coherent states. The impact of thermal noise and phase diffusion on the SEP is also evaluated. The findings of this paper show the utility of PASSs in quantum communication systems.
Correlation between the distribution of solar energy resources and the cloud cover in Xinjiang

Abstract In order to study the influence of cloud cover on solar energy resources, it provides scientific basis for the development and utilization of solar radiation resources. Based on the Cloud and the Earth’s Radiant Energy System (CERES) and European Centre for Medium-Range Weather Forecasts (ECWMF) data from 2014-2018, the correlation between the temporal and spatial distribution of solar energy resources and the cloud cover in Xinjiang was studied and analyzed. The results show that solar energy resources have generally shown an upward trend in the past five years, with an average annual radiation of 7206.5 MJ/m 2 and very stable. The overall distribution of solar radiation is mainly dominated by latitude, decreasing from south to north, and the change is relatively uniform. The maximum value of annual total radiation in the southern area of Xinjiang is about 9000 MJ/m 2 , which is 1.5 times of that in the northern area. The maximum daily total radiation is 28.88 MJ/m 2 in July, which is 3.3 times of that in December. The total radiation in summer can reach up to 2200 MJ/m 2 , which is 2.2 times of that in winter. Summer radiation is high but fluctuating, and winter radiation is small but relatively stable. The autumn is the period with the least amount of total cloud during the year, the cloud cover in the northern area is about 40%, and the winter in the northern area is the highest along the foothills of the Tianshan Mountain, up to 70%. The fitting effect of radiation attenuation and cloud cover in the northern area is higher than that in the southern area, and the maximum correlation coefficient is 0.98 in summer and the minimum is 0.571 in winter. The fitting effect of radiation attenuation and cloud cover in the northern area is higher than that in the southern area, and the maximum correlation coefficient is 0.98 in summer and the minimum is 0.571 in winter. The solar radiation is mainly affected by clouds in summer, while in winter, there are other factors such as aerosols.
Sustainable Approach for University Ranking System

In this paper we observe various university ranking system to find the most desirable university worldwide.The primary objective of this article is to present a framework of proposed ranking system which contains the most valuable features of the top five world university ranking systems which helps students and scholars to sharpen the result for their idealised university.A better ranking system approach is shownwhich comprises all the best features of the existing top university ranking system.
A Trusted NUMFabric Algorithm for Congestion Price Calculation at the Internet-of-Things Datacenter

The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information. However, it is difficult to predict the congestion state of the link-end accurately at the source. In this paper, we presented an improved NUMFabric algorithm for calculating the overall congestion price. In the proposed scheme, the whole network structure had been obtained by the central control server in the Software Defined Network, and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated. In this scheme, the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information. Based on the historical data, the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm. The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm. We evaluate this evolved NUMFabric algorithm in NS3, which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.
Generation of Random Key Stream using Word Grid Puzzle for the Applications of Cryptography

The amount of digital data created and shared via internet has been increasing every day. The number of security attacks and threats has been increased due to poor selection of secret keywords and passwords.Cryptographic algorithms and security protocols are primarily rely on random keys to provide security services.Random numbers and key stream are playing major role in applying the security mechanisms in real time. In this paper, a novel method to generate random key stream using word grid puzzle is proposed.The proposed method is experimented and a minor analysis has been performed in the obtained result.
Outcome of mammography examination in asymptomatic women

Background: Early detection of breast cancer is important in reducing mortality, morbidity, and high socioeconomic burden associated with it. Mammography is currently the primary imaging modality used as a screening tool to detect early breast cancer in women experiencing no symptoms as they are most curable in the early stage with availability of breast conservative therapies. Objective: This study aimed at determining the mammographic breast density patterns and outcome in asymptomatic women who presented for mammographic examination in Abuja. Materials and Methods: This descriptive cross-sectional study comprises of 113 asymptomatic women who presented for mammographic examination at the Radiology Department of University of Abuja Teaching Hospital, Gwagwalada from March 2015 to December 2018. Two basic views (craniocaudal and mediolateral views) of the breast were obtained using EXR-650 mammographic machine. Results: The mean age of study population was 40.72 ± 10.45 years with age range of 35 and 65 years. Base on mammographic breast density, breast imaging, reporting, and data system 1 and 2 were the most prevalent. There was a positive correlation between mammographic breast density and age of respondents. This relationship was statistically significant (Pearson correlation = 0.56, P = 0.000). The mammographic outcome among asymptomatic women who had mammographic examination was negative in 69 (61.1%) women and positive in 44 (38.9%). The positive outcome noted in mammograms of women examined was: benign mass in 18 (15.9%) women; 9 (8.0%) had benign calcification; 7 (6.2%) showed architectural distortion; 5 (4.4%) was inconclusive; focal asymmetry in 3 (2.6%); and suspicious mass in 2 (1.8%). Conclusion: In this study, screening of women reveals various benign and malignant breast pathologies which necessitate early interventions.
DESIGNING QUALITY ASSURANCE SYSTEM FOR INTERNATIONAL JOINT STUDY PROGRAMS

The article is concentrating on the new approach to quality assurance system within joint international study programs (joint programs). This problem is quite relevant for the implementation of Federal projects "Young professionals (Improving the competitiveness of vocational education)" and "Export of education" within the national project "Education". The authors argue that new approach to Quality Assurance is based on multilevel model. General structure of the quality assurance system of the joint program is presented. It takes into account internal and external quality assurance in accordance with the logic and concept of ESG-standards, the European approach. A comparative analysis of these fundamental documents is also provided and impact of the European approach on the national legislation, is considered. We prove that the proper multilevel quality assurance system in international joint programs is an important mechanism providing increase of Russian education export.
rgugik: Search and Retrieve Spatial Data from the Polish Head Office of Geodesy and Cartography in R

Dyba et al., (2021). rgugik: Search and Retrieve Spatial Data from the Polish Head Office of Geodesy and Cartography in R. Journal of Open Source Software, 6(59), 2948, https://doi.org/10.21105/joss.02948
Integrating motion capture in a virtual reality intervention planning platform to study radiation protection measures for the ATLAS inner detector decommissioning

Abstract An intervention planning and evaluation platform has been developed to enable dose estimation and personnel training for the ATLAS inner detector decommissioning. The present paper describes the integration of motion capture into the system, including the dose estimation results for the recorded decommissioning steps.
Learning-based Buffer Starvation Modeling for Packets Prefetching Strategies of Video Streaming Services

Abstract Improving the quality of experience (QoE) of video streaming is a significant task in the wireless network scenario. Buffer starvation in the transmission process will cause playback freeze, and a certain number of packets must be prefetched before the service restarts. Taking into account the shortcomings of buffer in video streaming services, this paper proposes a deep learning-based starvation probability calculation model and a reinforcement learning-based packet prefetching model. The deep learning approach extracts the correlation between different timing inputs through the recurrent neural network module to return an explicit result and the precise distribution of the number of buffer starvation. The reinforcement learning approach leverages a better trade-off between start-up/rebuffering delay and buffer starvation by adjusting the packet prefetching strategy, so that the long-term objective quality of experience (QoE) of the video stream is optimized. Our framework can be applied to actual scenarios including finite video streaming and long video streaming transmission.
The Characteristics of Japan’s Preschool Education and Its Enlightenment to China’s Preschool Education

In the field of world education, Japan’s preschool education level has always been in the leading position, which has a great inspiration for China’s preschool education. On the one hand, preschool education is closely related to economic strength, on the other hand, it is related to the development of education. Based on this, this paper analyzes the characteristics of Japan’s preschool education and Its Enlightenment to China’s preschool education, so as to provide theoretical reference for the future work.
A Short Survey on Real-Time Object Detection and Its Challenges

Object detection is an attractive research interest in recent years. It plays a significant role to understand the image in video analysis. Object detection technique has improved in computer vision when deep learning method came to the picture. From the last two decades, several algorithms have been developed and improved to detect the object in different conditions, and still, it has a number of challenges. The objective of this paper is to provide a short survey on object detection and its challenges not only in computer vision but also in the wireless sensor network.
Quantum Approximate Counting with Nonadaptive Grover Iterations

Approximate Counting refers to the problem where we are given query access to a function f : [N] → {0,1}, and we wish to estimate K = #{x : f(x) = 1} to within a factor of 1+e (with high probability), while minimizing the number of queries. In the quantum setting, Approximate Counting can be done with O(min (√{N/e}, √{N/K} / e) queries. It has recently been shown that this can be achieved by a simple algorithm that only uses iterations; however the algorithm performs these iterations adaptively. Motivated by concerns of computational simplicity, we consider algorithms that use Grover iterations with limited adaptivity. We show that algorithms using only nonadaptive Grover iterations can achieve O(√{N/e}) query complexity, which is tight.
Speech etiquette of professional online communities

Networking within online communities is recognized as a new way of social interaction. The authors study Russian Internet communities that unite members of the same profession – professional social networks. In such communities, speech etiquette is formed under the influence of communicative values that are, in turn, formed under the influence of values that are determined by a particular profession. We search for a correlation between professional social networks’ speech etiquette features and the profession of their members, and raise the questions: What communication goals are pursued by the users of the communities studied? What communicative situations form the professional social networks’ speech etiquette? What are the communicative values of an online group for professionals? What kinds of professionals’ speech activity may influence the formation of speech etiquette in professional social networks? Speech activity of professional social networks was analysed in ‘Dentistry’, ‘Overheard in the police’, and ‘Law dot ru’.
Algorithms and conditional lower bounds for planning problems

We consider planning problems for graphs, Markov Decision Processes (MDPs), and games on graphs in an explicit state space. While graphs represent the most basic planning model, MDPs represent interaction with nature and games on graphs represent interaction with an adversarial environment. We consider two planning problems with k different target sets: (a) the coverage problem asks whether there is a plan for each individual target set; and (b) the sequential target reachability problem asks whether the targets can be reached in a given sequence. For the coverage problem, we present a linear-time algorithm for graphs, and quadratic conditional lower bound for MDPs and games on graphs. For the sequential target problem, we present a linear-time algorithm for graphs, a sub-quadratic algorithm for MDPs, and a quadratic conditional lower bound for games on graphs. Our results with conditional lower bounds, based on the boolean matrix multiplication (BMM) conjecture and strong exponential time hypothesis (SETH), establish (i) model-separation results showing that for the coverage problem MDPs and games on graphs are harder than graphs, and for the sequential reachability problem games on graphs are harder than MDPs and graphs; and (ii) problem-separation results showing that for MDPs the coverage problem is harder than the sequential target problem.