Reviewerly/exHarmony huggingface dataset:
The wearable augmented reality (AR) approach to support mammographic training: hololens for screener training

Screening training efficiency highly relies on appropriate interaction and feedbacks provided during training.<sup>1,2</sup> A dedicated screening workstation and dedicated viewing software are de rigour for UK breast cancer screener training. These workstation and software are mainly manufactured by leading international vendors without critical technical aspects divulged to allow integrating 3rd party screener training solutions. A non-wearable AR approach has been developed and its accuracy has been quantitatively identified. As a follow-up, this study has refactored previous approaches on the wearable platform, Hololens. Wearable AR solutions are considerably user-friendly in degrees of freedom movements whilst they are seamlessly integrated and less customisable. It has not been aware that screening-suitable room-scale AR approaches have been developed and adopted. However, wearable AR techniques have relatively sophisticated apparatus developed for personal usage. In this study, Hololens is adopted and the difficulties of employing wearable AR techniques on screening training are systematically addressed. It is found infrared sensors of wearable AR solutions cannot retrieve spacious data correctly in the real world while the detected object is a monitor screen or other infrared-relative objects. Moreover, Hololens has the difficulty of detecting large objects and its interaction range and visible ranges are both quite limited. Whereas an alternative method is developed for Hololens and it is fully functional for screening training.
A Study on Visual Perturbations Effect on Balance in a VR Environment

Users sometimes lost their balance or even fell down when they played virtual reality (VR) games or projects. This may be attributed to degree of content, high-rate of latency, coordination of various sensory inputs, and others. The authors investigated the effect of sudden visual perturbations on human balance in VR environment. This research used the latest VR head mounted display to present visual perturbations to disturb balance. To quantify balance, measured by double-support and single-support stance, the authors measured the subject's center of pressure (COP) using a force plate. The results indicated that visual perturbations presented in virtual reality disrupted balance control in the single support condition but not in the double support condition. Results from this study can be applied to clinical research on balance and VR environment design.
Construction of Linked Data Platform Implementing Feedback Data Model of Usage Records

Linked Open Data (LOD) is one of the methods that enables publishing and sharing of data on the Web, and makes data available for many applications. Maintaining the volume and quality of data in LOD requires to keep on engaging people in inputting data. One of the solutions is motivating data producers to input data by giving incentives. However, LOD does not track how data has been used by which applications. In order to track records, data of LOD need to be instantiated to represent who produced it and which applications used it. This paper proposes resource representation by hash value in order to realize instantiation of triple data efficiently according to the concept of RDF which uniquely express instance by URI. This paper also proposes data processing by utilizing the standard SPARQL query to instantiate triple data and feed back usage records to data producers. This paper contributes to showing feasibility of feedback model by building data platform and developing an application enabling people to entry information about spots in town, and by conducting a workshop with people living in Nagasaki city.
Do Metrics Matter?

Scientific search engines enrich result lists with indicators of scientific quality, such as citation counts, in order to enhance user experience and improve performance. This dissertation project aims to study the effect of such integration of impact indicators in search result pages on relevance evaluation, considering both traditional citation-based and altmetric measures. The user behavior is analyzed with a combination of eye-tracking and think-aloud as well as a questionnaire. This paper describes the methodology of an experimental study designed to answer the question if the visibility of metrics alters the behavior during scientific literature search and if behavior varies depending on the kind of metric, specifically citation rate and altmetric score.
Up-Chirplet and Down-Chirplet Transforms of Non-Stationary Signals

Non-stationary signals are results of experiments in many research fields. The analysis of non-stationary signals is a task that demands specific approach. Advanced methods of signals analysis combine Fourier and wavelet transforms. However, some non-stationary signals may require even more sophisticated processing to reveal previously unseen features or enhance observed signals characteristics. One of the promising ways to solve such task is to apply chirplet transform. The present work is aimed at presentation of time-frequency analysis possibilities when non-stationary signals need to be studied.
Adaptive Estimation Algorithms and their Applications to Measurement Data Processing

The paper presents a review of methods for adaptive estimation of signals with unknown structures and parameters of models that determine the properties of both the signal itself and the errors of its measurement. The main approaches to solution of adaptive estimation problems are considered. One of them is aimed at designing algorithms with a learning sample, and the other one relies on the Bayesian approach and aims at solving the joint problem of signal estimation and identification of models used to describe the signal and measurement errors in real time. An adaptive estimation algorithm based on the Bayesian approach is described in detail. The problems in which the proposed algorithm is used are discussed. Its effectiveness is illustrated by the example of gravity anomaly estimation on a moving vehicle under model uncertainty of the signal and measurement errors.
An improved method for Person Re-Identification

In this paper, an effective feature representation named color pairs is proposed, which is robust to illumination and viewpoint changes. It was combined with Scale-invariant local ternary pattern (SILTP) texture features used for person re-identification. And we improved the method of Cross-view Quadratic Discriminant Analysis (XQDA) by adding a close function. It improves the performance of discriminant matric. This method were compared with other hand-crafted methods of feature extraction and measurement matching, then was proved to be advanced.
Improving Higher Education Quality in Jordan Using Mobile Technologies for Better Socio-economic Diversity Integration of Disadvantaged Groups Using a Mobile Multimedia/Augmented Reality Workflow

The mEQUITY (Project Website, http://mequity.dipseil.net/ ) project is the European Union funded initiative to create mobile applications that use augmented reality and multimedia assets adapted for educational purposes amongst disadvantaged groups in Jordan including those having difficulty with housing or employment and typically having refugee status related to neighbouring conflict zones of Gaza and Syria. Within these groups, there is also additional focus in helping those with learning difficulties or having disabilities such as deafness, blindness or physical immobility. Development and adaptation of educational digital resources for mobile devices have been initiated within higher education institutions, such as Jordanian Universities, with the aim of improving engagement and retention of learners.
Generation of Correct Word Sequences from Multiple Outputs of a Conventional Automatic Speech Recognizer for Voice-Activated Information Appliances

In information appliances based on speech recognition, users' spoken queries are converted into text queries using automatic speech recognition (ASR) engines. If the top-1 results of the ASR engines are incorrect, these errors are propagated to the following natural language processing steps. To alleviate this error propagation problem, we propose a post-processing model for revising ASR errors. Based on a sequence-to-sequence neural network, the proposed model generates a correct sentence from multiple candidate sentences returned by an ASR engine. The proposed model does not require any external resources or feature engineering effort, because it uses only syllables as input features. In our experiments with a Korean spoken chatting and FAQ corpus, the proposed model outperformed the previous models.
A Nobel Cryptosystem for Group Data Sharing in Cloud Storage

The biggest challenge of sharing data stored in cloud-storage is privacy-preservation. In this paper, we propose a simple yet effective solution for enforcing the security of private data stored in some cloud storage for sharing. We consider an environment where even if the cloud service provider is not-reliable or is compromised, our data still remain secure. The data Owner encrypts the private files using a secret key, file identifier and hash function and then uploads the cipher text files to the cloud. When a Data user requests access to a file, the owner establishes a key with the user and creates a new key, which is sent to the user. The user can then extract the original key by using the mutually established secret key and use it to decrypt the encrypted file. Thus we propose a system which is computationally simple yet provides a secure mechanism for sharing private data even over an untrusted cloud service provider.
Code Generation for Higher Inductive Types

Higher inductive types are inductive types that include nontrivial higher-dimensional structure, represented as identifications that are not reflexivity. While work proceeds on type theories with a computational interpretation of univalence and higher inductive types, it is convenient to encode these structures in more traditional type theories with mature implementations. However, these encodings involve a great deal of error-prone additional syntax. We present a library that uses Agda’s metaprogramming facilities to automate this process, allowing higher inductive types to be specified with minimal additional syntax.
Murmansk Arctic State University – Scientific and Educational Center of the Murmansk Region

The paper addresses the role of universities in the generation, use and dissemination of knowledge, analyzes principles and ways to develop science and education at universities. It is emphasized that the University is becoming an active player not only in training, but also in the production of a new knowledge, in its dissemination and implementation through innovation. At the same time, it is necessary to note that the conditions of the Far North impose a unique specificity on the work of the University and its scientific and innovative activities. For Murmansk Arctic State University (MASU), scientific and research work is one of the most dynamically developing components that create development potential. The paper presents the range of MASU’s scientific activities which includes 3 main spheres: natural science, technical science, social science, and Humanities. The authors dwell on the students’ and postgraduates’ scientific activities, consider the youth scientific organizational structure. As a flagship University, MASU is implementing a strategic development project “MASU is Scientific and Technological Hub of the Region” formed with the direct support of the Government of the Murmansk region. Within the framework of the project, an information and analytical platform was created in MASU under the partnership with Kola Science Center RAS (IAP MASU-KSC). This platform is an integrating consulting mechanism including a set of technological, commercial and marketing solutions for the development and implementation of innovative products and technologies in organizations operating in the field of ensuring a comfortable human presence in the Far North. As one of the priority goals of the strategic development of the University, the trajectory of the Arctic scientific and educational center (SEC) creation on the basis of MASU is highlighted. The key areas and ways to improve the efficiency of scientific and educational activities of MASU, as well as the expected results of the SEC are considered.
CSF Dream Academy: Using Fiction, Cardboard and Simple Electrical Circuits as Educational Tools to Lift Disadvantaged Children Out of the Poverty Trap

In this paper we propose a strategy for educational inclusion aimed at supporting marginalized children, using a model proposed by the Creative Science Foundation, based on the development of a science fiction micro stories and low cost physical paper/cardboard prototypes. This strategy has been successfully tested with Mexican children aged between 8 and 15, motivating them to develop their STEAM (Science, Technology, Engineering, Arts, Mathematics) skills. Additionally, it allows the development of social skills, such as teamwork, tolerance and respect. This paper describes the model used and reports on its first deployment in a community centre in the outskirts of Leon Guanajuato México, demonstrating that it has the power to attract and motivate such children to engage with STEAM studies which is an essential step on their road to a brighter future for them and their families. In support of the work the paper includes numerous examples of the children’s work.
FACTORS INFLUENCING THE FORMATION OF THE MOTIVATIONAL ENVIRONMENT IN THE IMPLEMENTATION OF THE EDUCATIONAL ROLE MODEL IN ADULT EDUCATION

Solving the problem of adaptation of adults to the new conditions of their life, information support of adult education is designed to solve two important and related problems: the formation of the educational role model of the student and the implementation of the strategy of adaptive-role resonance. Under the educational role model, we understand the anticipation of the role of an adult in the new conditions of life, formed in the process of information support of adult education. The model meets the role needs of an adult, his needs, goals, interests, society; corrects the advanced development of the individual, overcomes the symptoms of confusion of roles at certain stages of human life. In our opinion, the strategy of adaptive-role resonance is the reaction of the student to the educational-role model formed by the information support. And the more professional, purposeful, active, substantive information support of adult education will draw an educational role model, the more effective the strategy of adaptation and role resonance will be implemented. The author raises the problem of formation of motivational environment for more effective functioning of the educational role model of an adult learner. He emphasizes that one of the main features of an adult learner is his willingness to learn (motivation), which is determined by his desire to solve his vital problems and achieve concrete results through learning activities. The author comes to the conclusion that the formation of the motivational environment determines the forms and methods of the educational process, the success of the adaptive-role resonance, the subjective probability of success of an adult learner.
Application Development of Moving Target Route Playback Technology in Intelligent Transportation System

"The 13th Five-Year Plan" emphasizes the concept of intelligent transport in its major project columns. For scene conflicts and ground accidents, it is extremely important to apply intelligent technologies to post-processing. In order to facilitate post-processing evidence collection, and provide reference for similar conflicts planning or accident prevention. The track playback system of vehicle is constructed by the design of three modules: software based on C# and SQL Server for receiving original positioning data in a positioning receiver of vehicle; time and coordinate conversion in the computer server; Baidu map API combines JavaScript to create track playback web page. The built system can realize the historical record query function of the vehicle, and provide information of time, latitude and longitude for each point in the path.
Designing High-Performance In-Memory Key-Value Operations with Persistent GPU Kernels and OpenSHMEM

Graphics Processing Units (GPUs) are popular for their massive parallelism and high bandwidth memory and are being increasingly used in data-intensive applications. In this context, GPU-based In-Memory Key-Value (G-IMKV) Stores have been proposed to take advantage of GPUs’ capability to achieve high-throughput indexing operations. The state-of-the-art implementations batch requests on the CPU at the server before launching a compute kernel to process operations on the GPU. They also require explicit data movement operations between the CPU and GPU. However, the startup overhead of compute kernel launches and memory copies limit the throughput of these frameworks unless operations are batched into large groups. In this paper, we propose the use of persistent GPU compute kernels and of OpenSHMEM to maximize GPU and network utilization with smaller batch sizes. This also helps improve the response time observed by clients while still achieving high throughput at the server. Specifically, clients and servers use OpenSHMEM primitives to move data between CPU and GPU by avoiding copies, and the server interacts with a persistently running compute kernel on the GPU to delegate various key-value store operations efficiently to streaming multi-processors. The experimental results show up to 4.8x speedup compared to the existing G-IMKV framework for a small batch of 1000 keys.
Appropriating the English language as a qualitative attribute for educational perspective

One cannot deny the crucial role and indispensable state of importance to the globally recognised English language not only in developing countries but also in developed countries. Since, the times of post-independence with regard to certain orthodox followers of their native languages, this is appropriate to say that do not throw the baby out with bathwater”. That means English language has become very crucial for the intellectual flights of India intelligentsia in particular and for the whole world in general. This language has been the medium of instruction and means of communication since long times. The intellectual tempo with which our youth is made efficient can be highly inspired by the deep reservoirs of knowledge contained in English language. In this context, the need is to execute the class room learning so elastic in terms of pedagogy that English language skills would be acquired very easily. That is why Robert Frost warns against narrow mindedness as, Education is the ability to listen to almost anything without losing your temper or your self-confidence. This statement is fully giving us the boost of learning English language that becomes a source for encyclopaedic learning across numerous fields of knowledge and various walks of life.
Using Fractal Dimension to Check Similarity Between Mandelbrot and Julia Sets in Misiurewicz Points

Checking the similarity of some Julia sets and Mandelbrot sub areas in Misiurewicz points by calculating their fractal dimension is the main purpose of this paper. MATLAB programs are used to generate the Julia sets images that match the Misiurewicz points; these images are the entry to the FracLac software. Using this software we were able to find different measurements that characterize those fractals in textures and other features. We are actually focusing on fractal dimension and the error calculated by the software. When performing the given equation of regression or the logarithmic slope of an image, a Box Counting method is applied to the entire image, and the chosen features (grid design, scaling method, number of grid positions…) are available in a FracLac Program, then we attempt to prepare the appropriate settings to get the best performance of the software. Finally, a comparison is done for each image corresponding to the area (boundary) where the Misiurewicz point is located.
Cross-media Age Regression with Textual Adaptation

In realistic scenarios, an age regression model learned from one social media (named the source media) generally performs rather poorly when it is tested on another social media (named the target media). In this paper, a textual adaptation approach is proposed to cross-media age regression which aims to improve the age regression performance by exploiting textual features in the labeled data from the source media and unlabeled data from the target media. The basic idea to achieve this lies in the fact that many textual features are shared by the data from both social media. Specifically, two views generated by random subspace generation (RSG) are leveraged to train two separate regressors in a co-training algorithm for adding automatically-labeled samples in the target media. Moreover, we tackle the confidence evaluation challenge in co-training by the query by committee (QBC) approach. Empirical studies demonstrate the effectiveness of the proposed approach to cross-media age regression.
Value Evaluation on Data Assets of P2P Net Loan Platform

P2P net loan platform is the emerging force of economic development. The value evaluation on data assets of P2P net loan platform plays an important role in distinguishing the value of the data assets, providing a reference to improve the value of the data assets, and promoting the future development of the P2P platform. By analyzing the characteristics of the data assets of the P2P net loan platform, this paper proposes to evaluate the value of the data assets by using the B-S model. In the process of evaluation, the analytic hierarchy process is used to confirm the value of the underlying data assets and improve the B-S model. Finally, we conduct an empirical study on five P2P net loan platforms by using the improved model, and make suggestions on how to improve the value of data assets of P2P net loan platform.
ϕ-Divergence Loss-Based Artificial Neural Network

Artificial Neural Networks (ANNs) can fit non-linear functions and recognize patterns better than several standard techniques. Performance of ANNs is measured by using loss functions. Phi-divergence estimator is generalization of maximum likelihood estimator and it possesses all its properties. A neural network is proposed which is trained using phi-divergence loss.
Review on Human face and Expression Recognition

There are the different popular algorithms and techniques available which are used for implementation of face and expression recognition all having respective advantages and disadvantages. Some of the algorithms improve the efficiency of face and expression recognition, under the different varying illumination and expression conditions for input source. The main steps for face recognition are Feature representation and classification. The different authors have described different novel approaches for face and emotion recognition. Present review paper discrebie the different methods and techniques used to identified the person with the facial expression and person emotion with the voice of the person.