Reviewerly/exHarmony huggingface dataset:
Asian Cyber Security Standards

The scientific considerations presented in this article concern the threat of the cyber security quality system resulting from the unclear security standards introduced by China. Over the past few years, the Chinese government has issued nearly 300 new national standards related to cyber security. These standards cover a range of Information and Communications Technology (ICT) services as well as products, including software, routers, switches and firewalls. These standards contribute to the threat to the cyber security quality system, The situation becomes more difficult the more the United States exerts pressure on the Western world towards Chinese companies investing outside of China and for Western companies investing in China. The purpose of the analysis is to identify those threats, which are also difficulties encountered by Western companies trying to develop business in China in order to minimize them. The study was designed as an analysis of Chinese standardization policy documents in the area of cybersecurity and their confrontation with the practice of applying to foreign enterprises, as well as analysis of international standardization and standardization reports and documents in the field of cybersecurity. The theoretical research methods used in this study are: synthesis, analysis, abstraction and generalization.
Analysis of planes of attacks on the Blockchain system

This paper presents a study of attack planessurfaces and possible ways of conducting various attacks on decentralized systems based on Blockchain technology. To accomplish the task, the effectiveness of the attack is studied relative to the plane of its application, namely, relatively: cryptographic designs of Blockchain technology, distributed architecture of systems based on Blockchain technology, Blockchain application context. Several attacks have been identified for each of these planes, including malicious mining strategies, coordinated peer behavior, 51% attacks, domain name attacks (DNS), distributed denial of service attacks, delayed consensus achieving, Blockchain branching, orphaned and obsolete blocks, digital wallet thefts and privacy attacks.An attack by malicious mining allows an attacker to increase rewards by intentionally keeping his blocks closed in order to obtain a longer version of the Blockchain register than the current main version of the register. A 51% attack occurs when a single attacker, a group of nodes, or a mining pool (a combination of miners) in a network reaches most of the total processing power of mining in the system and gets the ability to manipulate the functionality of the Blockchain system. In the plane of DNS attacks, an attacker can potentially isolate peers of the Blockchain system, distribute fake blocks with fraudulent transactions among new nodes, and invalidate transactions. Manifestations of DDoS attacks can vary, depending on the nature of the functionality of the Blockchain application, the features of its network architecture and the behavior of peer nodes. Measures to counter attacks on peer-to-peer peer-to-peer architecture are considered.
Design and application of double closed loop weight control system for cigarette maker

Abstract In order to solve the problem that the precision of cigarette weight control system is not high enough in cigarette machine production, a double closed loop weight control system of cigarette machine is designed according to the characteristics of cigarette machine control system. This system takes IPC as the control core. Firstly, the current cigarette weight is obtained, then the weight deviation is calculated, and then the distance to be moved by the actuator is calculated based on the deviation. Then the current position of the actuator is obtained, and the target position of the actuator is calculated. The results show that the long-term deviation of the weight control system using the double closed-loop control method can be reduced to less than 4.0mg during the production of the target weight of 490mg cigarette, which is 0.8mg lower than that of the single closed-loop control method. This technology can improve the quality of cigarette process and reduce the overall consumption.
Positive semidefinite support vector regression metric learning

Most existing metric learning methods focus on learning a similarity or distance measure relying on similar and dissimilar relations between sample pairs. However, pairs of samples cannot be simply identified as similar or dissimilar in many real-world applications, e.g., multi-label learning, label distribution learning. To this end, relation alignment metric learning (RAML) framework is proposed to handle the metric learning problem in those scenarios. But RAML framework uses SVR solvers for optimization. It can't learn positive semidefinite distance metric which is necessary in metric learning. In this paper, we propose two methds to overcame the weakness. Further, We carry out several experiments on the single-label classification, multi-label classification, label distribution learning to demonstrate the new methods achieves favorable performance against RAML framework.
An Incremental Learning Network Model Based on Random Sample Distribution Fitting

The training of the classification network has tough requirements of data distribution. The more the training data did not consistent with the distribution of the real target function, the higher error rate the network will produce. In the context of incremental learning, the data distribution of the subsequent training tasks may not consistent with the data distribution of the previous tasks. To handle this problem, lots of learning methods were introduced, most of these methods are complicated and heavy computing. In this paper, a novel method which is faster and simpler is proposed to uniform subsequent training data. Artificial training samples are produced from random inputs in current trained network. In subsequent task, these artificial samples were mixed with new real data as training data. The experiments with proper parameters show that new features from new real data can be learned as well as the old features are not forgot catastrophically.
Anchor-free Small-scale Multispectral Pedestrian Detection

Multispectral images consisting of aligned visual-optical (VIS) and thermal infrared (IR) image pairs are well-suited for practical applications like autonomous driving or visual surveillance. Such data can be used to increase the performance of pedestrian detection especially for weakly illuminated, small-scaled, or partially occluded instances. The current state-of-the-art is based on variants of Faster R-CNN and thus passes through two stages: a proposal generator network with handcrafted anchor boxes for object localization and a classification network for verifying the object category. In this paper we propose a method for effective and efficient multispectral fusion of the two modalities in an adapted single-stage anchor-free base architecture. We aim at learning pedestrian representations based on object center and scale rather than direct bounding box predictions. In this way, we can both simplify the network architecture and achieve higher detection performance, especially for pedestrians under occlusion or at low object resolution. In addition, we provide a study on well-suited multispectral data augmentation techniques that improve the commonly used augmentations. The results show our method's effectiveness in detecting small-scaled pedestrians. We achieve 5.68% log-average miss rate in comparison to the best current state-of-the-art of 7.49% (25% improvement) on the challenging KAIST Multispectral Pedestrian Detection Benchmark. Code: https://github.com/HensoldtOptronicsCV/MultispectralPedestrianDetection
Offline Handwritten Recognition of Curved Gujarati Consonants using GHCIR System

Gujarati language has a variety of characters which makes the language diversified.The language has a total thirty-four consonants and eleven vowels that have different shapes.The characters have features like vertical lines, vertical lines with curves, only curve, curve with one loop and curve with two loops that differentiate the characters from one other.In this paper, the researcher has used a set of consonants which only has curves.Total eight (8) consonants "ક" (k), "ટ '(Ta), "દ ' (D), "ર '(Ra), "ળ '(Al), "ફ '(Fa), "ડ '(Da) and "ઝ '(Jha) have only curve as a feature.These consonants have been taken into consideration in this research paper.For training the GHCIR system 1200 samples of each curved consonant has been collected, while the system has been tested with 100 samples of each curved consonant.The average accuracy achieved after processing for all the curved consonant is 84.25%.Further, the researcher has done the performance analysis of the Gujarati Handwritten Consonant Identification and Recognition (GHCIR) System using the Kappa coefficient.The average Kappa Coefficient justify that the system identifies all the Gujarati handwritten curved consonants with a substantial level of agreement.
Visual Features of the Touchscreen Keyboard Guide Attention and Text Entry Behavior: An Eye-Tracking Study

Text entry via the smartphone touchscreen is an increasingly important means of communication. However, there is an offset between the intended landing location and the actual touch location, which reduces the accuracy of text entry. The present study found that at least two visual features of the soft smartphone keyboards in the market may have an effect on touch behavior. Therefore, this study aims to investigate whether symbol shape and key border affect the distribution of attention and user’s touch behavior. Four soft keyboards were designed to record the touch location while simultaneously using the eye tracker to capture the gaze data. The results show that the usability score of bordered keys is better than that of borderless keys, but the touch accuracy of bordered keys is poorer than that of borderless keys. In addition, the center of attention is not consistent with the touch location. The results of this research can be used as a reference for the design of the soft keyboard interface to reduce the error of text entry on the smartphone.
Management of Backup in Enterprise Data Centre

Netvault backup is a prominent method to backup data in cloud.The data is backed up for both data centre and disaster recovery site.But the paper is not only limited to backing up the data but also the scope lies to the restoration of data and the normal issues faced during the data backup.The version used is Quest Netvault 12.4.The data backup is either done on tapes or via phases (phase 1 or phase 2) .Netvault backup is entirely dependent upon the Vmware for taking snapshots of virtual machines and Nutanix for storage virtualization.The aim of the paper is to emphasize on the backup process in cloud and issues faced for the same.
Application of convolutional neural networks in the intelligence security system subsystem

The article proposes the structure of an integrated security system for areal facilities. The main subsystems included in its composition are considered. The tasks of the intelligence subsystem for detecting and recognizing ground-based objects of observation in a complex phono-target environment are defined. The task of detecting an object of observation was solved on the basis of a previously proposed algorithm. The disadvantage of this algorithm was the presence of false positives from a flickering complex phono-target environment. To eliminate this drawback, it is proposed to apply a classifier based on the convolutional neural network, which distributes the selected objects to specific classes. The analysis and experimental studies to evaluate the accuracy of recognition of ground objects by convolutional architectures such as VGG-16, VGG-19, Inception v3, ResNet-50, MobileNet. Training and verification of the recognition quality of architecture data was carried out on an experimentally created data set with a human image on a contrasting background and at different ranges. The results obtained indicate the possibility of using a convolutional neural network in the security system and its ability to work in real time.
Peningkatan Keterampilan Mengonstruksi Debat melalui Model Discovery Learning pada Siswa Kelas X-MIPA-1 SMA Negeri 7 Malang

&lt;p align="center"&gt;This research was motivated by the low learning outcomes of constructing debates of class X students at SMA Negeri 7 Malang. It was seen based on the average score of the skill to construct the debate at 69.38. The purpose of this study was to improve the skills of constructing such a low debate. The research design was classroom action research. Data on constructing students' skills was obtained from the results of practical tests, while data on attitude changes during learning were obtained from interviews, observations, journals, and questionnaires. The subjects of this research were 34 students of class X-MIPA 1, SMA Negeri 7 Malang. The problem of constructing debates in the X-MIPA 1 class, namely (1) the culture of reading students was still low, (2) students were not updated enough about the latest information, and (3) the selection of learning models that were not in accordance with the learning material. The results showed an increase in the debating construction skills as follows, the average pre-cycle score was 69.38, the first cycle of the class average score was 72.85, and the second cycle the class average score was 82.35. The behavior of students in following learning experiences changed in a more positive direction. Based on the results of practical tests and changes in student behavior, it could be concluded that the discovery learning model could improve the skill of constructing debate.&lt;/p&gt;
Coworking As Innovative Educational Content in Modern Higher Education

The definition of “coworking” is just beginning to enter the orbit of Russian and foreign scientific research. Coworking spaces as innovative educational content in higher education are being created in Russian universities. The purpose of the study is the justification, development, and testing of a model of electronic coworking environment in the system of higher pedagogical education. At that, coworking environment is considered as an educational virtual cluster at which a basic platform for educational content is created with all educational products attached to it. The following methods of research were used to solve the tasks: design and modeling; the study of coworking environment products, chat conversations, questionnaires; and mathematical methods of result processing (quantitative and qualitative analysis of research results). The results of the study have revealed the advantages of coworking environment: successful socialization, minimization of time and economic resources, expansion of business partnerships, mutual assistance and a comfortable atmosphere. Analysis of studies on the criterion of coworking productivity revealed an increase in student mobility and an increase in the index satisfaction and communication effectiveness. Testing of the electronic coworking model proves its benefits and prospects of its introduction into the system of higher pedagogical education. The results can be used in social psychology, pedagogy, and practice.
Archaeobotany in the 4th Dimension: Visualising Specialist Data in a 3D GIS

Archaeobotany and GIS are closely linked with archaeology, it is hard to imagine a modern archaeological investigation without them. The two appear to complement each other. GIS links highly complex sets of data with space, and offers a range of analytical tools. Archaeobotanists look for patterns in data over time and space to interpret human behaviour. Yet GIS is underused in archaeobotany. There is a gap between the capabilities of GIS and how it is used by archaeobotanists. With GIS moving into the next dimension, this gap will grow. The problem conceivably stems from the fact that results of archaeobotanical analyses are devoid of spatial data. This thesis develops a methodology in which archaeobotanical data are reunited with location within a 3D GIS. Using material from the 2016 and 2017 excavations at Uppakra, a 3D GIS was built. It incorporates newly created 3D objects which contain archaeobotanical data. A case study was used to revisit an investigation into Iron Age beer brewing at Uppakra. The use of 2D GIS in the original study was critically assessed. The new methodology was then used to visualise archaeobotanical data in 4D. Visualising the data in this way opens new perspectives, widens the scope of investigation and shifts focus from viewing single plant types to the whole assemblage. The thesis concludes with a theoretical discussion about how this methodology could affect future research, considerations to be taken into account and how it fits within a reflexive approach to archaeology. (Less)
Research Topic Recommendation Based on Latent Dirichlet Allocation

Knowledge discovery pushes every discipline, including bibliometrics and innovation management, to reposition itself and stay competitive. With the exponential growth of scientific literature, it has become increasingly difficult for researchers to quickly and effectively identify potential research topics in an interested area to advance their research. This has led to the development of research topic recommendation. In this paper, aiming to explore the potential author-topic relations in depth, we proposed a research topic recommendation methodology based on latent Dirichlet allocation and bipartite network analysis, to predict the inspiring research topics that an author potentially will be interested and working on. A case study on scientific literature in the area of knowledge discovery is then presented to demonstrate the feasibility of the methodology. The result of this research could assist academic researchers in identifying and extending potential research directions.
One Shot 3D Photography.

3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving the viewpoint (as opposed to a stereo pair with a fixed viewpoint). 3D photos are static in time, like traditional photos, but are displayed with interactive parallax on mobile or desktop screens, as well as on Virtual Reality devices, where viewing it also includes stereo. We present an end-to-end system for creating and viewing 3D photos, and the algorithmic and design choices therein. Our 3D photos are captured in a single shot and processed directly on a mobile device. The method starts by estimating depth from the 2D input image using a new monocular depth estimation network that is optimized for mobile devices. It performs competitively to the state-of-the-art, but has lower latency and peak memory consumption and uses an order of magnitude fewer parameters. The resulting depth is lifted to a layered depth image, and new geometry is synthesized in parallax regions. We synthesize color texture and structures in the parallax regions as well, using an inpainting network, also optimized for mobile devices, on the LDI directly. Finally, we convert the result into a mesh-based representation that can be efficiently transmitted and rendered even on low-end devices and over poor network connections. Altogether, the processing takes just a few seconds on a mobile device, and the result can be instantly viewed and shared. We perform extensive quantitative evaluation to validate our system and compare its new components against the current state-of-the-art.
Improved Memories Learning

We propose Improved Memories Learning (IMeL), a novel algorithm that turns reinforcement learning (RL) into a supervised learning (SL) problem and delimits the role of neural networks (NN) to interpolation. IMeL consists of two components. The first is a reservoir of experiences. Each experience is updated based on a non-parametric procedural improvement of the policy, computed as a bounded one-sample Monte Carlo estimate. The second is a NN regressor, which receives as input improved experiences from the reservoir (context points) and computes the policy by interpolation. The NN learns to measure the similarity between states in order to compute long-term forecasts by averaging experiences, rather than by encoding the problem structure in the NN parameters. We present preliminary results and propose IMeL as a baseline method for assessing the merits of more complex models and inductive biases.
Comparative Analysis of the Core Aspects of Library Work with Migrants in Russia and Germany

The paper presents for the first time the analysis of the main aspects of multicultural library work in Russia and the Federal Republic of Germany, based on the data of questionnaire survey conducted by the author in the libraries of two countries. The author considers the terminology used by modern Russian and German libraries in the course of work with migrants. The paper gives definitions and shows the difference in approaches to the use of terms “intercultural library work”, “polycultural library service” and “multicultural library service”. The author reveals that both Russian and German libraries do not mostly maintain statistical records on migrant users. The paper compares the data indicating insufficient knowledge on the interests of readers with migration background. The author revealed institutions of different levels providing statistical data that use the libraries of two countries to analyze the ethnic groups living in the library service area and to clarify the demographic and social characteristics of individual migrant groups. The paper highlights the forms of upgrade qualifications for librarians involved in the development and provision of multicultural services. The survey shows that the important characteristic of German librarians who work with multicultural users is their belonging to a group of migrants. Based on the data obtained, the author concludes that work with migrants in Russia and Germany is mainly funded from the general budget of the library. The author identifies the sources of targeted funding for multicultural work in libraries, as well as the approximate size of the budget allocated for the acquisition of collections for migrants. The paper considers the forms of acquisition and criteria for selecting documents in the languages of migrants. The author presents the comparison of the main forms of mass work with migrants in the libraries of Russia and Germany, as well as identifies the activities that are not held in Russian libraries, but are of interest from the point of view of implementation in the domestic practice.
Delphi Study on Human Rights Education Framework for Families

This study clarifies the definition of and to provides guidelines on educational objectives, core concepts, and content in developing a Human Rights Education Program for families. The Delphi survey method was used to develop a Human Rights Education Program for families. As a result, a Human Rights Education Program for families was defined as education that would ensure all members of the family enjoy universal human rights without discrimination. In addition, that the prejudice and discrimination against socially marginalized would not be created within the family by learning values and attitudes that respects human rights and freedom. The objectives were to learn the merit of respecting individuals, relationships, and community. Core concepts of the program were the rights for myself and others, communicating and responsibilities and a sense of citizenship. Content included human rights, respect of oneself and others, empathetic understanding, acceptance, communication in an intimate relationship, conflict management, sharing the role of caring the family, no discrimination against the socially marginalized, and creating an inclusive community culture. This study can be used as a guideline for family human rights education based on family human rights, which is the core of family democracy.