Reviewerly/exHarmony huggingface dataset:
Operational decision-making for cyber operations: In Search of a Model

The decision-making behind cyber operations is complex. Dynamics around issues such as cyber arsenal management, target assessment, and the timing of dropping a destructive payload are still ill-understood. Yet, limited published research has thus far explored formal theoretic constructs for better understanding decisionmaking in cyber operations. Multiple models may offer utility to understand and explain the courses of action through which state cyber missions are executed, including conduct or restraint of cyber effects operations against target systems and networks. This paper evaluates four models - surprise model, duelist model, mating- choice model, and the Black-Scholes model. Each model offers specific advantages, and suffers characteristic drawbacks; and while these models differ in application and complexity each may provide insights into how the unique nature of cyber operations impact the decision dynamics of cyber conflict.
Examination of motivational and value orientation of college students towards professional activity

The subject of this research is the motivational and value orientation of students towards professional activity. Based on the analysis of literary sources, it was established that motivational and value orientation is an integrative dynamic system, incorporating the interconnected professional motives, interests, goals, personal attitudes that ensure the choice of profession. The article analyzes the peculiarities of motivational and value orientation of college students essential for determination of the significant cognitive motives and disaccord between such its components as personal growth, responsibility and presence of a strong desire to pursue the selected profession. In the course of research, the following set of psychodiagnostic instruments was used: original questionnaire, morphological test for life values (V. F. Sopov, L. V. Karpushin), methodology for determination of key motives of choosing profession (E. M. Pavlyutenkov), value orientations (M. Rokeach), methods of mathematical-statistical processing of the results (Spearman&amp;rsquo;s correlation analysis, Mann&amp;ndash;Whitney parametrical method of comparison of two U-criterion samplings). Theoretical importance of this study consists in the analysis of modern conceptual approaches towards the problem of motivational and value orientation of college students towards professional activity that creates foundation for further research in this area, and solution of such problem as rejection of the acquired specialty.
A Study on the Research Trends on the Marine Policy through Network Analysis in recent 11 years

It is time for interest in the marine policy to be made. According to recent news, major maritime issues have been pouring in. Despite the increasing number of issues in marine policy, studies related to marine policy lack interest in any research trends. In this study, we want to network analysis of research trends related to marine policy. For this research, we have analyzed all the articles from 2009 to 2019 that include key terms of
Multi-site Connectivity for Edge Infrastructures : DIMINET:DIstributed Module for Inter-site NETworking

The deployment of a geo-distributed cloud infrastructure, leveraging for instance Point-of-Presences at the edge of the network, could better fit the requirements of Network Function Virtualization services and Internet of Things applications. The envisioned architecture to operate such a widely distributed infrastructure relies on executing one instance of a Virtual Infrastructure Manager (VIM) per location and implement appropriate code to enable collaborations between them when needed. However, delivering the mechanisms that allow the collaborations is complex and error prone task. This is particularly true for the one in charge of establishing connectivity among VIM instances on-demand. Besides the reconfiguration of the network equipment, the main challenge is to design a mechanism that can offer usual network virtualization operations to the users while dealing with scalability and intermittent network properties of geo-distributed infrastructures.In this paper, we present how such a challenge can be tackled in the context of OpenStack. More precisely, we introduce DIMINET, a DIstributed Module for Inter-site NETworking services capable to interconnect independent networking resources in an automatized and transparent manner. DIMINET relies on a decentralized architecture where each agent communicates with others only if needed. Moreover, there is no global view of all networking resources but each agent is in charge of interconnecting resources that have been created locally. This approach enables us to mitigate management traffic and keep each site operational in case of network partitions. A promising approach to make other cloud-services collaborative on-demand.
Autonomous Exploration and Semantic Mapping of a Mobile Robot Using Efficient Frontier Selection

The frontier-based exploration method is a common approach used to navigate unknown region. Although existing frontier-based exploration is computationally simple in the exploration of the frontiers, this algorithm can cause unnecessary motion, thereby increasing the exploration time and decreasing the exploration success rate. To resolve this issue, we propose a method to improve the performance of the existing frontier-based exploration method by using an A-star path planner and a frontier selection algorithm that consider the direction of a mobile robot. In addition, we employed a real-time object detection technique to build a semantic map while exploring an unknown region. To verify our proposed approach, we performed experiments to compare the existing approach with our proposed method in the clutter environment(in real and Gazebo simulation). Through the experimental results showed that our method shortened the exploration path and time.
The Effects of Delayed Interaction Cues in Virtual Reality Training

Interaction cues are commonly used in games and educational systems to direct users to take appropriate actions at particular moments, such as pressing a specific button to start a conversation with a virtual agent. Based on a literature review and a related framework, we identified delayed interaction cues as an underexplored research area. We present a controlled evaluation of the effects of delayed cues in a virtual reality training application. Our results indicate that immediate interaction cues are significantly more efficient than delayed cues. We discuss the implications of our results on the design of interaction cues for future games and educational systems.
[Super-resolution construction of intravascular ultrasound images using generative adversarial networks].

The low-resolution ultrasound images have poor visual effects. Herein we propose a method for generating clearer intravascular ultrasound images based on super-resolution reconstruction combined with generative adversarial networks. We used the generative adversarial networks to generate the images by a generator and to estimate the authenticity of the images by a discriminator. Specifically, the low-resolution image was passed through the sub-pixel convolution layer r2-feature channels to generate r2-feature maps in the same size, followed by realignment of the corresponding pixels in each feature map into r ×r sub-blocks, which corresponded to the sub-block in a high-resolution image; after amplification, an image with a r2-time resolution was generated. The generative adversarial networks can obtain a clearer image through continuous optimization. We compared the method (SRGAN) with other methods including Bicubic, super-resolution convolutional network (SRCNN) and efficient sub-pixel convolutional network (ESPCN), and the proposed method resulted in obvious improvements in the peak signal-to-noise ratio (PSNR) by 2.369 dB and in structural similarity index by 1.79% to enhance the diagnostic visual effects of intravascular ultrasound images.
Higher Education System Management Based on the Development and Implementation of the Personalized Learning Path Approach

Nowadays, there is a need to develop and implement a qualitatively new structural-functional model of higher education system management that would make allowance for labor market requirements, public and societal demands on the one hand and individual adaptive characteristics of students on the other hand. A study of the development and implementation of a higher education system management model based on the personalized learning path approach is relevant due to the societal and labor market demand for specialists capable of continuous self-development and high adaptability to rapidly changing external conditions, which increases the efficiency of management of the country’s social system development. Aim . The study aims to examine the theoretical and methodological aspects of the formation of a higher education system management model based on the personalized learning path approach combined with the socio-occupational integration of students. Tasks . The authors analyze theoretical approaches to the modeling of education system management and develop a structural-functional model of higher education system management based on the personalized learning path approach. Methods . This study uses general scientific methods of cognition and analysis of scientific works of foreign and Russian authors on management, including management of educational and social systems. Results . The model of development and implementation of a personalized learning path is substantiated as the most effective approach to higher education system management. Conclusions . Systematic implementation of a higher education system management model based on the personalized learning path approach has a positive social effect of increasing the quality of education and science along with the active transformation of higher education and application of innovative forms of educational process management through the implementation of the process approach and the Triple Helix concept.
Topic-based automatic summarization algorithm for Chinese short text

&lt;abstract&gt; &lt;p&gt;Most current automatic summarization methods are for English texts. The distinction between words in Chinese text is large, the types of parts of speech are many and complex, and polysemy or ambiguous words appear frequently. Therefore, compared with English text, Chinese text is more difficult to extract useful feature words. Due to the complex syntax of Chinese, there are currently relatively few automatic summarization methods for Chinese text. In the past, only the important sentences in the original text can be selected and simply arranged to obtain a summary with chaotic sentences and insufficient coherence. Meanwhile, because Chinese short text usually contains more redundant information and the sentence structure is not neat, we propose a topic-based automatic summary method for Chinese short text. Firstly, a key sentence selection method is proposed combining topic words and TF-IDF to obtain the score of each text corresponding to the topic in the original text data. Then the sentence with the highest score as the topic sentence of the topic is selected. Considering that the short text of Weibo may contain a lot of irrelevant information and sometimes even lack some important components of topic, three retouching mechanisms are proposed to improve the conciseness, richness and readability of topic sentence extraction results. We validate our approach on natural disaster and social hot event datasets from Sina Weibo. The experimental results show that the polished topic summary not only reflects the exact relationship between topic sentences and natural disasters or social hot events, but also has rich semantic information. More importantly, we can almost grasp the basic elements of natural disaster or social hot event from the topic sentence, so as to help the government guide disaster relief or meet the needs of users for quickly obtaining information of social hot events.&lt;/p&gt; &lt;/abstract&gt;
Gaze+Gesture Interface: Considering Social Acceptability

In public places like cafes, the usage of smart glasses with interfaces including controller, touchpad, voice, or mid-air gesture not only receives a lot of interest from people around him or her but also cannot protect the privacy of individuals. If smart glasses become more advanced and more popular than regular glasses in the future, socially acceptable user interfaces can be required. In this paper, we propose a user interface on HoloLens by using gaze tracking instead of head tracking for navigation, and unobtrusive gesture based on deep learning instead of mid-air gestures for selection/manipulation, that is more socially acceptable than the existing user interfaces on smart glasses. A study was conducted to investigate social acceptability from the users’ perspective, and the results showed the advantages of the proposed method to improve social acceptability.
Evaluating Virtual Reality Experiences Through Participant Choices

When building virtual reality applications teams must choose between different configurations of the hardware and/or software aspects, and other factors, of the experience. In this paper we extend a framework for assessing how these factors contribute to quality of experience in an example evaluation. We consider how four factors related to avatar expressiveness affect quality of experience: Eye Gaze, Eye Blinking, Mouth Animation, and Microexpressions. 55 participants experienced an avatar delivering a presentation in virtual reality. At fixed times participants had the opportunity to spend a virtual budget to modify the factors to incrementally improve their quality of experience. They could stop making transitions when they felt further changes would make no further difference. From these transitions a Markov matrix was built, along with probabilities of a factor being present at a given level on participants’ final configurations. Most participants did not spend the full budget, suggesting that there was a point of equilibrium which did not require maximizing all factor levels. We discuss that point of equilibrium and present this work as an extended contribution to the evaluation of people’s responses to immersive virtual environments.
Minimal Embodiment: Effects of a Portable Version of a Virtual Disembodiment Experience on Fear of Death

Body ownership illusions are the basis of various virtual reality (VR) applications. However, such illusions frequently require elaborate tracking systems, which make deployment in clinical settings challenging. Therefore, we build on Bourdin and colleagues’ former work [3] to trial a virtual out-of-body experience (OBE, individuals view themselves situating outside their physical bodies) with ”minimal embodiment.” We used a consumer system consisting of a 3 degrees of freedom (DOF) headset and its associated 3 DOF hand tracker. In an exploratory study, we compared participants’ fear-of-death (FOD) after undergoing either a control condition (participants remained in control of the avatar body) or a disembodiment condition (participants drifted out of the avatar body and lost visuotactile contact with their avatar). Results revealed an indirect effect of perceived embodiment increasing FOD through a heightened degree of reported OBE in the experimental condition. We discuss limitations and possible extensions of this study, and the future of using simple VR tools in healthcare settings.
VR Piano Learning Platform with Leap Motion and Pressure Sensors

Aiming at helping novices to learn and practice playing piano without a real piano teacher, we propose a virtual reality (VR) piano system which can record the user’s piano fingering data. Our system uses two Leap Motion sensors for wide-range hand tracking, and we developed a method to calibrate and compose the tracking results of two Leap Motion sensors. However, Leap Motion sensors fail to accurately detect whether a finger presses a key because the precision of the estimated depth is not high enough. Hence, we employ multiple pressure sensors attached on the user’s fingertips to more accurately check whether the user is pressing the piano key or not. An HTC Vive headset is used to display the immersive VR environment while the user practices. Moreover, a transparent acrylic board is mounted above the Leap Motion sensors so that the player can directly play on the board, which enhances the immersion and presence by touching a physical object. The experimental results show that our VR piano system provides users a great piano-playing experience and is helpful for piano learning.
Image precise matching with illumination robust in vehicle visual navigation

In vehicle visual navigation, image matching algorithm is highly critical to positioning accuracy and processing efficiency. One single matching algorithm cannot satisfy all types of image features accurate acquisition, so Harris, SUSAN, FAST, SIFT, and SURF are respectively adopted to process various road images under normal lighting condition. During practical application, the appropriate algorithm can be selected based on detection rate and running time of the above algorithms. Aiming at the illumination change interference of the collected images in vehicle visual navigation, many traditional matching algorithms for illumination change are not optimal, so an image precise matching algorithm with illumination change robustness is proposed. Because image edges and detail information have lower sensitivity for illumination change, SURF feature points are optimized by image gradient based on the idea of Canny, and the bidirectional search is used to obtain precise matching points. The experimental results show that feature point detection of the algorithm remains good stability for illumination change in images, and the matching accuracy can reach more than 94%. The algorithm is not only robust to illumination change, but also ensures higher matching speed and meanwhile improves the matching accuracy significantly.
A -SLIC: Acceleration of SLIC Superpixel Segmentation Algorithm in a Co-Design Framework

In this work, we present an optimized pipelined hardware implementation of the accelerated Simple Linear Iterative Clustering algorithm (A-SLIC) for superpixel segmentation. The algorithm is implemented on an FPGA using a hardware-software co-design framework wherein large memory requirements are drawn from off-chip memory. On-Chip resource and time optimization are achieved by employing fixed-point computations and the table look-up for computing color space conversion in place of floating point operations. Also, the color conversion and the distance calculation loops are pipelined for the increased throughput. The design is implemented on the Zynq-7000 system-on-chip (SOC). The component usage, memory requirements, and the segmentation quality using standardized metrics are evaluated and presented for benchmark images. Compared to the sequential software implementation of the SLIC on a CPU, the proposed algorithm executed on the Zynq 7000 device achieves speed up of 10–22.
Detecting a target with quantum entanglement

In the last decade a lot of research activity focused on the use of quantum entanglement as a resource for remote target detection, i.e. on the design of a quantum radar. The literature on this subject uses tools of quantum optics and quantum information theory, and therefore often results obscure to radar scientists. This review has been written with purpose of removing this obscurity. As such, it contains a review of the main advances in the quantum radar literature together accompanied by a thorough introduction of the quantum optics background necessary for its understanding.
Automation of the process of measuring the level of competence development in a competence-oriented learning

Abstract The paper describe methods and tools of monitoring the development of competencies within the framework of a competency-based training model. A formalized model for assessing competencies throughout the educational period is presented. The paper considers the classification of information collected.
A Recipe for Creating Multimodal Aligned Datasets for Sequential Tasks

Many high-level procedural tasks can be decomposed into sequences of instructions that vary in their order and choice of tools. In the cooking domain, the web offers many partially-overlapping text and video recipes (i.e. procedures) that describe how to make the same dish (i.e. high-level task). Aligning instructions for the same dish across different sources can yield descriptive visual explanations that are far richer semantically than conventional textual instructions, providing commonsense insight into how real-world procedures are structured. Learning to align these different instruction sets is challenging because: a) different recipes vary in their order of instructions and use of ingredients; and b) video instructions can be noisy and tend to contain far more information than text instructions. To address these challenges, we first use an unsupervised alignment algorithm that learns pairwise alignments between instructions of different recipes for the same dish. We then use a graph algorithm to derive a joint alignment between multiple text and multiple video recipes for the same dish. We release the Microsoft Research Multimodal Aligned Recipe Corpus containing 150K pairwise alignments between recipes across 4,262 dishes with rich commonsense information.
Advanced Technologies in Blockchain, Machine Learning, and Big Data

Blockchain, machine learning, and big data are among the key components of the future IT track. These technologies are used in various fields; hence their increasing application. This paper discusses the technologies developed in various research fields, such as data representation, Blockchain application, 3D shape recognition and classification, query method, classification method, and search algorithm, to provide insights into the future paradigm. In this paper, we present a summary of 18 high-quality accepted articles following a rigorous review process in the fields of Blockchain, machine learning, and big data.
5G and B5G Technologies to Implement Private Operators Supporting High Quality Video Production in Dense User Environments

5G public networks based on 3GPP Release 15 and 16 will provide great opportunities to implement eMBB, mIoT, and URLLC use cases. Based on market acceptance and needs B5G public networks will provide further updates to radio interface, system architecture, and protocols in 3GPP Release 17 and beyond. In addition to the mainstream PLMN deployments, it is expected that there will be a need for local deployments based on 5G and B5G to support the needs of specific groups of users that are localized in a specific small area and/or operate during a limited period of time. Such local deployments are called “private operators,” “non-public networks,” “micro operators” or “local 5G.” The need for such local deployments is recognized at least on the level of 3GPP standardization and national radio regulatory authorities. This paper describes different technologies in 5G and B5G to support private operator deployments with some focus on high quality video production in dense user environments.