Reviewerly/exHarmony huggingface dataset:
A Study on Improve Operational Safety of HEMS

Korea’s HEMS are mainly operated during the week, but they are pushing for 24-hour operations. This study has made an overall comparison and review of helicopter safety management that should be accompanied to this end. For research purposes, helicopter regulations and helicopter accident statistics were analyzed, with a high accident rate associated with pilot error and night flight. It was proposed that future preparations would require reinforcement of laws and regulations, reinforcement of pilots’ night training, and introduction of training and preflight risk assessments. This study will provide a direction for future helicopter safety. This study will provide for future direction of helicopter safety research.
Exploration of the leached Fe geochemical fractions in Tiga Warna Beach sediment, Indonesia

To elucidate the sources of Fe in Tiga Warna Beach, fine sediment can be monitored through their analysis with the BCR microwave optimized method using AAS. The accuracy and precision of the optimized BCR microwave method were analyzed for exploring of Fe concentrations detailed after XRF analysis. Assessment of contamination factors (CF) and geo-accumulation index values (Igeo) was evaluated in each fraction to establish the anthropogenic or natural sources. The results showed that the optimized microwave BCR method can be used for leaching Fe accurately (89.4%) with precision (RSD <30%). The explored of Fe in sediments tended to accumulate in easily oxidized and residual fractions. Assessment of Fe in sediment can be categorized in Tiga Warna Beach with low levels of Fe contents in blue water (CF: 1.00, Igeo: 0.23), red water (CF: 1.83, Igeo: 1.10), and green water (CF: 2.42, Igeo: 1.51) locations. We suggested the assessed sediment as the uncontaminated or natural Tiga Warna Beach sediment.
Anonymity Preserving Byzantine Vector Consensus

Collecting anonymous opinions has applications from whistleblowing to complex voting where participants rank candidates by order of preferences. Unfortunately, as far as we know there is no efficient distributed solution to this problem. Previous solutions either require trusted third parties, are inefficient or sacrifice anonymity. In this paper, we propose a distributed solution called the Anonymised Vector Consensus Protocol (AVCP) that reduces the problem of agreeing on a set of anonymous votes to the binary Byzantine consensus problem. The key idea to preserve the anonymity of voters—despite some of them acting maliciously—is to detect double votes through traceable ring signatures. AVCP is resilient-optimal as it tolerates up to a third of Byzantine participants. We show that our algorithm is correct and that it preserves anonymity with at most a linear communication overhead and constant message overhead when compared to a recent consensus baseline. Finally, we demonstrate empirically that the protocol is practical by deploying it on 100 machines geo-distributed in three continents: America, Asia and Europe. Anonymous decisions are reached within 10 s with a conservative choice of traceable ring signatures.
The Status Quo and Problem Analysis of Hebei Red Cultural Value Identification by English Majors in Hebei Province

Red culture is Chinese people's precious cultural heritage forged in revolutionary war era, carrying rich revolutionary spirit and profound cultural connotation.It's essential for young generation to know and inherit red culture and spread it to the world.To identify the recognition of Hebei red culture value among English majors and the current involvement of red culture in English teaching as well as students' needs, this paper firstly introduces the significance of Hebei red culture and the three targets the research plans to achieve.Then the research design is introduced and data are analyzed.Based on the problems reflected through the questionnaire data, some suggestions are put forward.Hopefully, this paper may deepen students' recognition of Hebei red culture, further strengthen their cultural confidence and have some enlightment for English teaching with the topic of Hebei red culture.
Influence of Human Visual Perception and Eye Tracking Motion on the Quality of Moving Image in LCD

There is a very important index in the influence of human visual perception, that is, the degree of the motion blur about the moving image on display device. In this paper, a new kind of improved method is proposed to calculate the response time of liquid crystal under the new backlight driving and modulation, which is more accurate than the traditional moving window integration method. This paper also discusses the eye tracking movement of the human visual system, including studying the influence of image content, size, motion speed and motion direction, based on the human vision property study and the analyzes of the simulation model of image motion artifacts perceived by human eyes. Experiments are performed, using the human eye vision perception measurement system. The experiment data shows that the edge blur time can be reduced to 10.5 ms, compared with the 16.5 ms in traditional drive, reduced by 36.4%, and the human perception of motion blur can be markedly reduced. Also, the results show that the simulation results are in good agreement with the actual measurement data by modifying the proportion coefficient of the eye tracking object model to 0.9. At the same time, through the improved human eye tracking model of smooth moving objects, the actual motion blur phenomenon perceived by the human eye can be calculated more accurately, and the results can be used in image processing algorithms to improve the quality of the moving image on the display.
Usability Testing on QR Code Scanner Application for Lecture Presence

Universities are obliged to facilitate lectures. Many students require universities to provide a fair teaching and learning services with a minimum of student cheating. In order to improve the quality of teaching and learning, each university develops a lecture presence system electronically. The QR code scanner application became a solution offered for leak problems that previously existed on the magnetic card system. Before the application applied on a large scale, developers needed to conduct an assessment of the usability of the QR scanner application. The assessment aimed to make lectures go smoothly and to maintain the good reputation of the university. The method used is usability testing. The result of this study is a usability system at the level of 65%. This value consists of an effectiveness value of 70%, an efficiency value of 54.31%, and a satisfaction value of 70.85%. The improvements of user interface recommended in this study include adding of placeholders to inform the correct NIM format, changing the QR scanner icon into a titled icon and choosing a stimulating color, providing a zoom feature on the scanner camera, and applying a more familiar logout icon according to the mental model of the user.
Upgrading the Newsroom: An Automated Image Selection System for News Articles

We propose an automated image selection system to assist photo editors in selecting suitable images for news articles. The system fuses multiple textual sources extracted from news articles and accepts multilingual inputs. It is equipped with char-level word embeddings to help both modeling morphologically rich languages, e.g. German, and transferring knowledge across nearby languages. The text encoder adopts a hierarchical self-attention mechanism to attend more to both keywords within a piece of text and informative components of a news article. We extensively experiment with our system on a large-scale text-image database containing multimodal multilingual news articles collected from Swiss local news media websites. The system is compared with multiple baselines with ablation studies and is shown to beat existing text-image retrieval methods in a weakly-supervised learning setting. Besides, we also offer insights on the advantage of using multiple textual sources and multilingual data.
TRENDS IN THE DEVELOPMENT OF THE MARKET FOR NEW EDUCATIONAL TECHNOLOGIES

Questions related to education and its quality are always relevant. The growing momentum of online education raises many questions for participants in the educational process, in particular, the choice of a platform provider of online services, the development of educational content, the placement and updating of online resources, the promotion of educational content among users, etc. The typology and characteristics of the market of online educational technologies have been presented in the article, trends of its further development have been defined. The classification and brief description of Russian and foreign platform providers implementing online training have been given. The forms of education, where the special place is given to adaptive education and development of self-education possibility have been considered. The tendencies of the Internet development as a necessary element of the online learning system have been revealed.
Differential Evolution Algorithm Based on Ensemble of Constraint Handling Techniques and Multi-Population Framework

Aimed at improving the insufficient search ability of constraint differential evolution with single constraint handling technique when solving complex optimization problem, this paper proposes a constraint differential evolution algorithm based on ensemble of constraint handling techniques and multi-population framework, called ECMPDE.First, handling three improved variants of differential evolution algorithms are dynamically matched with two constraint handling techniques through the constraint allocation mechanism.Each combination includes three variants with corresponding constraint handling technique and these combinations are in the set.Second, the population is divided into three smaller subpopulations and one larger reward subpopulation.Then a combination with three constraint algorithms is randomly selected from the set, and the three constraint algorithms are run in three sub-populations respectively.According to the improvement of fitness value, the optimal constraint algorithm is selected to run on the reward sub-population, which can share information and close cooperation among populations.In order to verify the effectiveness of the proposed algorithm, 12 standard constraint optimization problems and 10 engineering constraint optimization problems are tested.The experimental results show that ECMPDE is an effective algorithm for solving constraint optimization problems.
A Q-Learning-Based Approach for Simple and Multi-Agent Systems

This study proposes different machine learning-based solutions to both single and multi-agent systems, took place on a 2-D simulation platform, namely, Robocode.This dynamic and programmable platform allows agents to interact with the environment and each other by employing a variety of battling strategies.Q-Learning is one of the leading and popular machine learning-based solutions to be applied to such a problem.However, especially for continued spaces, the control problem gets deeper.Essentially, one of the main drawbacks of reinforcement learning (RL) is to design an appropriate reward function that the function can be described by only employing few parameters for simple tasks, whereas estimating the goal of the reward function may be a challenging problem.Recent studies prove that neural network-based approaches can handle these challenges and achieve to learn control strategies from 2-D or 1-D data.Besides those problems of RL algorithms for single robots, once the number of robots increases and the systems need to behave as multi-agent systems, the overall design requirements become more complex.Accordingly, the proposed system is validated by considering different battle scenarios.The performance of the Q-Learning-based system and the supervised learning techniques are compared by employing different scenarios for this problem.Results reveal the superiority of the ANN-based approach over other methods.
New generation cloud computing

We are pleased to present a special issue that focuses on the trends in the next generation of cloud computing. An obvious question that may arise in the mind of the reader is why another issue on clouds when there is plenty of discourse on the topic. Undoubtedly, the cloud computing landscape is rapidly changing to meet the challenges of emerging paradigms, such as Fog/Edge computing and the Internet-of-Things (IoT). These paradigms rely on services offered by the cloud but are demanding—need to scale for billions of heterogeneous devices and sensors while operating efficiently in real-time. In conventional cloud computing, all data is transmitted to data centers where it is processed and stored. The rate of expansion of data centers across the globe raises energy concerns and calls for innovative solutions to make data center computing sustainable. With billions of devices getting connected there is an urgent need for more pragmatic solutions that alleviate network congestion and reduces latencies that maintain and even improve the overall Quality-of-Service and Quality-of-Experience. Some of the new trends seen in cloud computing over the last couple of years include computing at the edge of the network outside centralized data centers, redesigning/reconfiguring data centers for optimized execution of workloads, using heterogeneous processors, such as hardware accelerators in the cloud for faster application execution, and novel applications finding new generation clouds to satisfy their requirements. These articles provide new definitions, architectures and approaches that have evolved from current clouds to accommodate the emerging computing paradigms and workloads. They address challenges across multiple dimensions of scalability, management, reliability, sustainability, heterogeneity and security. We trust that you will find this special issue truly enjoyable and informative.
Psychological and pedagogical conditions for overcoming psychological barriers among university students from rural areas

The object of this research is the psychological barriers of students from rural areas. The subject of this research is the psychological and pedagogical conditions for overcoming psychological barriers among students from rural areas. The goal consists in theoretical substantiation and experimental testing of psychological and pedagogical conditions for overcoming psychological barriers among students from rural areas during studying in university. The author attempts to identify the main types of psychological barriers common to the students from rural areas; determine the factors that impede overcoming the psychological barriers; develop and measure the impact of experimental program of psychological support of such students. The main conclusions lie in highlighting the factors that hinder overcoming psychological barriers by the students from rural areas during studying in university. In order to eliminate negative impact of the factors that inhibit overcoming psychological barriers among students, the author determined the psychological and pedagogical conditions that contribute to overcoming psychological barriers. Based on the data acquired as a result of theoretical research, was formulated and implemented the program of psychological support for the students from rural areas to help them overcome psychological barriers during studying in university. Assessment was conducted of a number of indicators among the students of control and experimental groups, prior and after the introduction of psychological support program.
Tools for enabling teaming during mission planning and rehearsal

The Army anticipates that future battles will be in more complex and dynamic environments, requiring the Army to push modernization priorities. In order for Soldiers to thrive within these challenging operational contexts, they must rapidly adapt to leverage and integrate technology in order to gain and maintain overmatch over near peer adversaries. Teaming will be especially critical for mission success. Soldier teams will need to be adaptive and fluid in their roles to respond to dynamic mission demands. Technology can be leveraged to enable and enhance teaming between human and humanagent teams. Augmented reality (AR) technology may provide an adaptive solution for information sharing across individuals and teams to promote a common operational picture within future operational environments. Here, we present a small teams study where dyads leveraged technological tools that helped facilitate teaming during a simulated mission planning and rehearsal scenario. Partners worked together to plan a path to extract a high value target while avoiding obstacles and hostile forces. Dyads completed missions using two technologies counterbalanced across the study. The first condition was reflective of current methods for mission planning in the Army; dyads used a Table Top to plan, rehearse, and execute the simulated mission. In the second condition, dyads used the Microsoft HoloLens to complete the mission in an augmented reality environment. This paper will present findings of how perceived teaming efficacy and performance relate to mission performance and workload in the two technologies.
Developing an Organization’s Corporate Knowledge Through Action-based Learning Technologies

The paper explores the impact of learning technologies on the development of the corporate knowledge base of modern organizations. The authors consider the action training technologies as an alternative to traditional training, which is based on the active involvement of enterprise employees in the process of generating and practical use of new corporate knowledge. A conceptual model of action training has been developed that is tested in large industrial enterprises participating in the national project “Productivity and Employment Support” in the Perm region. The study uses the methodology of system analysis, analysis methods of statistical information and expert data. There has been concluded the usage of the developed model of training by action in projects to increase productivity in industrial enterprises leads to the formation of positive effects. The practical application of the study results will allow a more reasonable definition of the implementation of training technologies for individual enterprises; will facilitate faster and more effective implementation of national programs and projects of the Russian Federation.
Channel-by-Channel Demosaicking Networks with Embedded Spectral Correlation

Demosaicking is standardly the first step in today's Image Signal Processing (ISP) pipeline of digital cameras. It reconstructs image RGB values from the spatially and spectrally sparse Color Filter Array (CFA) samples, which are the original raw data digitized from electrical signals. High quality and low cost demosaicking is not only necessary for photography, but also fundamental for many machine vision tasks. This paper proposes an accurate and fast demosaicking model based on Convolutional Neural Networks (CNN) for the Bayer CFA, which is the most popular color filter arrangement adopted by digital camera manufacturers. Observing that each channel has different estimation complexity, we reconstruct each channel by an individual sub-network. Moreover, instead of directly estimating the red and blue values, our model infers the green-red and green-blue color difference. This strategy allows recovering the most complex channel by a light weight network. Although the total size of our model is significantly smaller than the state of the art demosaicking networks, it achieves substantially higher performance in both demosaicking quality and computational cost, as validated by extensive experiments. Source code will be released along with paper publication.
Risorse in rete per lo sviluppo della competenza testuale. Riviste e giornali russi online Una proposta per la lingua russa

This work represents the next step on the path that began with previous studies, where we focused on the advantages and disadvantages connected with the use of online resources to learn and teach Russian. In the present essay we consider how websites and online resources can help to develop textual competence. Some new online resources will be analysed and we will examine how they can be used to develop textual competence. The purpose is to increase the inventory of sites and make it available to learners and teachers. In particular, we will dwell upon Tekstoteka CMO MGU and the use of online Russian newspapers and journals for the development of textual competence.
Infrared spectroscopy as the method for evaluating technological properties of minerals and their behavior in technological processes

Infrared spectroscopy (IR) is a highly effective method for the analysis of minerals, rocks and ores, capable of solving a whole range of problems when choosing innovative solutions for the technological processing of various types of mineral raw materials. The article considers the main directions of using the infrared spectroscopy method in assessing the technological properties of minerals and their behavior in technological processes: evaluation of the grade (quality) of mineral raw materials; analysis of the behavior of minerals in the technological process with prediction of their technological properties; analysis of changes in the structure and properties of minerals in technological processes; operational analysis of mineral substances at various stages of technological processing. The article illustrates all aspects of the use of infrared spectroscopy at various stages of studying the material composition of mineral raw materials in its enrichment assessment by specific examples of solving problems arising from the technological redistribution of various types of ore and non-metallic minerals.
Search space reduction of asynchrony immune cellular automata

Abstract We continue the study of asynchrony immunity in cellular automata (CA), which can be considered as a generalization of correlation immunity in the case of vectorial Boolean functions. The property could have applications as a countermeasure for side-channel attacks in CA-based cryptographic primitives, such as S-boxes and pseudorandom number generators. We first give some theoretical results on the properties that a CA rule must satisfy in order to meet asynchrony immunity, like central permutivity. Next, we perform an exhaustive search of all asynchrony immune CA rules of neighborhood size up to 5, leveraging on the discovered theoretical properties to greatly reduce the size of the search space.
Performance of Methods in Identifying Similar Languages Based on String to Word Vector

Indonesia has a large number of local languages that have cognate words, some of which have similarities among each other. Automatic identification within a family of languages faces problems, so it is necessary to learn the best performer of language identification methods in doing the task. This study made an effort to identification Indonesian local languages, which used String to Word Vector approach. A string vector refers to a collection of ordered words. In a string vector, a word is represented as an element or value, while the word becomes an attribute or feature in each numeric vector. Among Naïve Bayes, SMO, J48, and ZeroR classifiers, SMO is found to be the most accurate classifier with a level of accuracy at 95.7% for 10-fold cross-validation and 94.4% for 60%: 40%. The best tokenizer in this classification is Character N-Gram. All classifiers, except ZeroR shows increased accuracy when using Character N-Gram Tokenizer compared to Word Tokenizer. The best features of this system are the TriGram and FourGram Character. The TriGram is preferred because it requires smaller training data. The highest accuracy value in the combination experiment is 0.965 obtained at a combination of IDF = FALSE and WC = TRUE, regardless the conditions of the TF.