Reviewerly/exHarmony huggingface dataset:
Research on Decision-Making Model of Shared Tower for Power and Communication under Incomplete Information

The shared tower for power and communication is strategic cooperation implemented by and between State Grid Corporation of China and China Tower in recent years. An important factor to promote the shared tower is mounting the communication base station onto the power transformation tower with the view of realizing wider signal covering, while the tower resources which can be shared are limited, so how to make a decision among different shared projects is a difficult problem. In this text, through analyzing the influence of shared tower on both parties, 6 key factors which influence the decision making of shared tower are summarized; after the key factors are used as evaluation indexes and the grey interval number model is combined, the shared tower decision making model is established, and the example measurement and calculation are conducted.
A proposal for a nonlinear Kalman filter using state dependent linear representation system and its performance analysis by numerical simulations

This paper considered a new nonlinear state estimation method based on the Kalman filter. In this method, we employed a state-dependent linear representation which is rewritten the system nonlinear equation into pseudo linear equation without any approximation, then applied a linear kalman filter to estimate the system state using the observed output. The method is inspired by a method based on the state-dependent Riccati equation (SDRE), which is a method for designing controllers or observers for nonlinear systems. Our filter approach is very simple and can be implemented more easily than the conventional methods of similar nonlinear state estimation methods such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). The effectiveness of the proposed method was verified by numerical simulations. As a result, we confirmed that the proposed method is faster in computation time and easier in design than the SDRE-based observer. In addition, from the comparison between the estimation results by the proposed method and the estimation results of EKF and UKF, it was confirmed that the proposed method can be applied to the same state estimation problems as EKF and UKF.
INFORMATION ETHICS AS A NECESSARY ELEMENT OF THE REGULATION OF THE MODERN INFORMATION SOCIETY

The article is devoted to the analysis of the importance of information ethics in the active development of information and communication technologies. Active research on the issues of cyberspace has been conducted since the second half of the ХХth century. These studies are becoming more intensive every year. Many scientists are interested in analysis of these issues because communication plays the fundamental role in our dynamic modern world. Modern telecommunication technologies and, first of all, the global Internet, are one of the most important factors in the development of the world community, which has a decisive influence on the social, political, economic and socio-cultural spheres. And the global pandemic Covid-19 since 2020 has brought these issues to the forefront of socio-humanitarian research. The information space of the Internet, which has already become the main infrastructure of social communication at the local and global levels, is a relatively new cultural phenomenon. It is obvious that a clear and effective system of moral regulation in this area has not yet developed. This space provides a person with unprecedented opportunities in terms of personal freedom, challenging traditional moral attitudes. Of course, this raises many ethical issues, both general and applied, related to the spread of coercive and aggressive Internet advertising, pornography, violence, intrusion, privacy, and many other aspects. Computer technologies are not neutral. They are filled with human, cultural and social values. These values can be predicted and taken into account, they can appear and evolve after many trials and errors. In our multicultural world conflicting value system can often arise. Future research needs to do as much as possible to create a broader and more promising concept of what it means to be human in the stream of transformations that exist today. The solution of certain problems in information ethics is different depending on who solves these problems. All dilemmas and problems within the framework of the considered direction of applied ethics are open, and no one can give an exact answer to the questions yet. Thus, since in the modern information society there is a direct relationship between the intensity of technological development and the growth of crises in the field of moral values and spiritual culture, information ethics already makes a serious claim to the moral regulation of human behaviour.
An Intermediate Secret-Guessing Attack on Hash-Based Signatures

Digital signature schemes form the basis of trust in Internet communication. Shor (FOCS 1994) proposed quantum algorithms that can be used by a quantum computer to break the security of today’s widely used digital signature schemes, and this has fuelled intensive research on the design and implementation of post-quantum digital signatures. Hash-based digital signatures base their security on one-way functions that in practice are instantiated by hash functions. Hash-based signatures are widely studied and are part of NIST’s post-quantum standardization effort.In this paper we present a multi-target attack that we call Intermediate Secret-Guessing attack on two hash-based signatures: XMSSMT (Draft SP 800-208 that was considered by NIST for standardization), and K2SN-MSS (AsiaCCS 2019). The attack allows an adversary to forge a signature on an arbitrary message. We describe the intuition behind the attack and give details of its application on the attacked schemes together with corresponding theoretical analysis. The attack implies that the effective security levels of XMSS (a special case of XMSSMT), XMSSMT, and K2SN-MSS are 10, 39 and 12 bits lower than their designed security levels given access to \(2^{20}\), \(2^{60}\), and \(2^{20}\) signatures, respectively.We implement the attack for each scheme, and give our results for reduced security parameters that validate our theoretical analysis. We also show that the attack can be avoided by modifying the application of a pseudorandom function for key generation. Our work shows the subtleties of replacing randomness with pseudo-randomness in the key generation of hash-based signatures, and the need for careful analysis of such designs.
Adaptive Neural Networks Based Robust Output Feedback Control for Nonlinear System

The performance of the control system is reduced by uncertain nonlinearities behaviors, which can be enhanced by implementing an adaptive approach represented by the robust output-feedback control and artificial neural network, which is proposed in this paper and utilized for identification and control of a nonlinear system. The Cart Pole System (CPS) is treated as a multi-body dynamical system, and the nonlinear swing-up problem is handled by designing an adaptive neural network which trained using a modified conventional controller called Linear Quadratic Optimal State Estimator with Integral Control (LQOSEIC). In this paper, the nonlinear system CPS stabilized utilizing robust output feedback control called LQOSEIC, this controller allows a linearized system to act as a model reference for the original nonlinear system, but they are only valid for a limited range of operations and will fail if the plant characteristics are unknown or uncertainty. An adaptable neural network is used to overcome this challenge., in which the adaptive neuro controller is trained offline using LQOSEIC to get the initial weights of neurons for layers network, after finished the training the LQOSEIC will be replaced by adaptive neural control. The real advantage of a neuro-controller is its ability to update online depending on the error signal. The neuro-controller demonstrates that when any disturbance or uncertainty arises in a non-linear system, neural networks characterized by online learning compensate for the effect of unpredictable conditions. The suggested adaptive neural network improves control performance and ensures the closed-loop control system's robust stability. Finally, numerical simulations are used to demonstrate the efficacy of the proposed controllers.
Interface Design for Offline Learning

This paper focuses on the design and evaluation of an educational solution centered on environments that do not have internet access. Two different prototypes were evaluated, one focused on creating the class content aimed at teachers, and the other focused on displaying and using the class content aimed at students. For this, twenty teachers and ten students were reached from African and Asian countries where the network conditions are not proper for remote educational environments. Preliminary results state that the participants were favorable to these solutions.
영어 무성 마찰음의 음향 및 스펙트럼 특성에 관한 연구

This study examines the spectral characteristics of English voiceless fricatives depending on the manner and place of articulation, gender, age, the post-fricative vowel height, and the location in a word based on the Buckeye Corpus of Spontaneous American English Speech. The acoustic analysis results indicate that fricative duration, the center of gravity (COG), variance and skewness play a role in distinguishing all English voiceless fricative articulation places, despite variation in gender, age, the location in a word and the post-fricative vowel height. These acoustic parameters distinguished the sibilant /s, ∫/ from the non-sibilant fricatives /f, Ɵ/, and alveolar /s/ from palate-alveolar /∫/, labiodental /f/ from interdental /Ɵ/: fricative duration, COG, and variance of the sibilant fricatives were significantly longer/higher than those of the non-sibilant fricatives. Skewness was high for the non-sibilant fricatives and low for the sibilants. (Korea Polytechnic College)
Traditions in vocational education of future teachers at the university

The modern sociocultural situation actualizes the issue of the role and place of tradition as a criterion for the preservation and transmission of historical experience and the basis of the civic identity of society and the ethnic identity of an individual in vocational education in Russia. Russia’s entry into the world educational space, modernization of Russian education based on the competence-based approach, developed with due account for the general trends in the education development in European countries, involves not only updating the content and technologies of education. The subprogram “Vocational Education Development” of the State Program of the Russian Federation “Education Development” for the period of 2013-2020 has the purpose of increasing the contribution of vocational education to the socio-economic and cultural modernization of Russia, to increasing its global competitiveness, ensuring the demand for each student in the economy and society. Therefore, among the priority tasks of higher education is to improve the quality of training future teachers for the Russian education system at different levels, to form their readiness for pedagogical activity in modern conditions. The purpose of this article is to determine the significance of the historical and sociocultural tradition for vocational education at Russian universities by using the comparative analysis of historical-pedagogical, regulatory-legal and methodological sources. The author traces the possibilities of the impact of the university stage of education on the process of ethnocultural development and ethnic identification of a modern student in university vocational pedagogical education. The fundamental novelty of formulation and ways of solving the issue in this article is determined by taking into account the specifics of the digitalization stage in modern education and the features of university education technologies and techniques during the period of overcoming the consequences of the coronavirus epidemic.
One-shot Line Extraction from Color Illustrations

Sketch colorization has been explored extensively using deep learning-based approaches. However, there are few works on the inverse problem of extracting lines from color illustrations, which is challenging due to the abstract illustration in cartoon rendering and the diversity of colorization style. In this paper, we propose a learning-based framework to explore one-shot line extraction from color illustrations. To avoid over-fitting, we simplified the proposed model and proposed a method for data augmentation when training using a single “color illustration-line drawing” pair. Then, we verified the model's effectiveness and efficiency in a group of color illustrations with similar colorization style. The experiments showed that the proposed, our method can outperform the conventional CNN (convolution neural network)-based sketch extraction methods.
Research on interactive technology of Webpage block localization based on JavaScript

With the development of web applications, the main way for people to obtain information is gradually transferred to the network. XPath can be used to uniquely represent a certain position in a web page for those who are familiar with web applications. However, it is difficult to interact with a computer to locate the content of a web page for most ordinary people who benefit from the web. Thus, we propose a webpage block localization technology based on JS scripts which is convenient for human-computer interaction. The experiments prove that it shows advanced performance both in interaction mode and block mode. Also, our scheme can be integrated with crawler technology to monitor a webpage block through the interaction of webpage block localization, and it can be applied to the problem feedback module of webpage to facilitate users' feedback and suggestions.
Development of Health Monitoring Vest using Velostat

Robotics, rehabilitation, biomechanics, and medicine all benefit from wearable sensors. The wearable vest for health monitoring equipped with flexible velostat. The major goal is to offer elders with health-monitoring services. A wearable vest with flexible material based on non-invasive sensors is also being developed. The technology is designed to provide elderly people with accurate vital sign monitoring as well as therapeutic situations. With the help of this system, it offers reliable vital signs monitoring by supporting the health status of aged persons by using wearable sensors integrated with raspberry pi. The demonstration shows good results of different gyroscopic and accelerometer readings using the cloud platform.
Abnormality Detection in Crowd

Fast increase in population of cities, cause people getting panic because of terrorist movement. Now it has become more dangerous and serious intimidation. Therefore, the crowd analysis in surveillance videos is a new research area, however, public area is having large number of crowded scenes and it contains moving crowd and also involves object movement. The object size is very small because of that the objects appear entirely smaller and in crowd people walk randomly and close up one another. All the factors make the survey difficult. A feature is used to analyze movement of the people. These properties use of space and terrestrial movement information of points of interest. Then a method used group the feature points primarily and then collectiveness is calculated. Collectiveness makes group computation more efficient effectual. People status is obtained by crowd descriptors.
Online Searching for 3-Dimensional Data in Sublinear Time

We give a dynamic data structure that provides a sublinear time for online searching, and online maintaining it upon insertion and deletion. Each element in the data structure is a three-dimensional data item. The searching operation is to find a target element (x,y,z) that satisfies the constraints x < X, y < Y, and z < Z, for some input of positive real numbers X, Y, and Z.
Critical Success Factors for Project Tracking Software Implementation: A Case Study at a Banking Company in Indonesia

In today’s business environment, location is not an obstacle anymore. Teams can work virtually and collaboratively with ease using web-based project tracking software. As a result of computer technology and information flow advances, companies are moving to new project management tools, improved project governance, and increased stakeholder engagement. To keep its competitiveness and ability to deliver products on schedule, one of the Bank in Indonesia adopted Jira Atlassian as project tracking software to replace the previous in-house system which is called e-SDLC (electronic Software Development Life Cycle) that can monitor and track project status. But it did not go well and faced obstacles at the beginning of implementation. This study aims to find and evaluate the Critical Success Factors (CSF) for project tracking software implementation in one of Indonesia banking company. From previous research, there are identified challenges and obstacles when applying project management tools which are governance, adoption process, technology & knowledge, and stakeholders. From this research, we identified 4 keys criteria, namely people, process, organization, and technical as CSF (ordered from the most important criteria using analytical hierarchy process-AHP). The findings of this study could help company increasing the success probability in implementing project tracking software.
Application of 3D Digital Image Correlation to Capture the Impact Beahviour of UHPFRC Plate

In this study, a repeated drop-weight test on a 50 mm thick four-side fixed UHPFRC plate was carried out. A high-speed 3D Digital Image Correlation technique (3D DIC) was employed to capture the full-field response of the plate during impact loading. The DIC results were validated against the measurements of physical accelerometer and strain sensors attached on the top surface of the plate. The DIC results in combination with a polynomial surface fitting method was used to obtain the mid-point deflection. Replicability of the plate’s dynamic response indicated that only negligible damages occurred in the plate due to repeated drops from 0.5 m. During the subsequent impact from 2.0 m, the overall performance was governed by flexure. Lastly, the plate failed with local failure and flexure after impacted from 3.0 m.
Construction Strategy of University Intelligent Art Education Ecosystem based on Big Data

In order to overcome the problems existing in the development of smart art education in colleges and universities, and to improve the informatization level of art education in colleges and universities, this paper puts forward a construction strategy of the ecosystem of smart art education in colleges and universities based on big data. Based on this, the system realizes the combination of art education and wisdom education from multiple dimensions, which are teaching activities, teaching concepts and teaching subjects. In addition, the system can also give full play to the interaction and immersion of big data technology and artificial intelligence technology, comprehensively improve the quality of art education, and build a perfect education ecological environment. The results show that the construction strategy can strengthen the deep integration of art education and information science and technology, and improve the information level of art education in colleges and universities.
Research on Immersive Specialty Stores Design from the Perspective of Flow Experience

This paper takes the needs of customers as the starting point, looking for problems in traditional specialty stores. It studies these problems based on Maslow’s hierarchy of needs theory, consumer behavior psychology theory, and the psychology of optimal experience theory to establish immersive specialty stores experience design framework and explore new design principles and design applications. Combining technology and art, it puts forward immersive space experience principles and starts design research.
Regularized Loss Minimizers with Local Data Perturbation: Consistency and Data Irrecoverability

We introduce a new concept, data irrecoverability, and show that the well-studied concept of data privacy is sufficient but not necessary for data irrecoverability. We show that there are several regularized loss minimization problems that can use perturbed data with theoretical guarantees of generalization, i.e., loss consistency. Our results quantitatively connect the convergence rates of the learning problems to the impossibility for any adversary for recovering the original data from perturbed observations. In addition, we show several examples where the convergence rates with perturbed data only increase the convergence rates with original data within a constant factor related to the amount of perturbation, i.e., noise. A full version of this paper is accessible at: http://arxiv.org/pdf/1805.07645.pdf
Improved Two-stream Network for Action Recognition in Complex Scenes

Compared with the great success of deep convolution network in still image visual recognition, the performance improvement of action recognition is limited by complex scenes such as complex background and fast motion of the object in the video. In this paper, we propose an improved two-stream network to solve the above problems. In the spatial stream network, we design a detection-before-recognition (DBR) strategy to maximize the proportion of effective information in the input image (video frame) and reduce the interference of complex background. In the temporal stream network, an attention mechanism is introduced, which could make the network focus on the object to be recognized and then to optimize the feature blur problem caused by the fast motion of the object. Finally, through the weighted linear combination of their prediction scores, the complex scene problem can be solved and the final recognition results can be improved. Experiments show that our method can get competitive performance on the UCF101 dataset.
Colabo.Space - Participatory Platform for Evolving Research and Publishing Workflows

We explore and evaluate the Colabo.Space ecosystem as a basis for conducting literary (and, by extension, other) research. The key principle of the ecosystem is to support participatory design at each stage to enable visual, declarative and co-creative design and evolution of the ecosystem, its infrastructure, data types and contained (research) knowledge.Accompanied with specialized platforms, it supports describing research workflows; collecting data; distant reading research; publishing and visualizing the findings.We argue for supporting the continuous evolution of the ecosystem, the findings and publishing content, with reference to the ecosystem and its publishing process (both the content and meta-data).We evaluate the constituting components of the Colabo.Space ecosystem within three collaborative research projects.