Reviewerly/exHarmony huggingface dataset:
Study on Human Detection System Using Deep Neural Network and Alternative Learning for Autonomous Flying Drones

An alternative learning and its application to construct an overviewing human detection system (OHDES-V2) of flying drone for emergency rescue and investigation is presented in this paper. In this system, a deep neural network and alternative learning are used key techniques for object recognition from a free viewpoint. Simple appearance-based characteristics is determined from captured images, and the system uses a deep neural network to automatically classify human body, automobiles and so forth. The proposed system shows that several objects can be recognized from a bird's-eye view. Experimental results show that the system can effectively recognize four types of objects and walking persons with accuraces of 98.5% and 97.12%, respectively.
Information Security Threats in Public and Private Organizations

Along with the incontestable benefits for the modern society, the information and communication technology developments induce new vulnerabilities. Mobile computing devices, cloud computing, and privacy issues are just a few elements that should be taken into account when shaping the modern information security that is essential to our modern way of life. Since information security risks are rapidly evolving and taking new forms, the real benefits of information and communication technologies may be exploited only if trust is built on every layer of responsibility. This study explores of the present main information security threats faced by Romanian organizations, as well as of the attitude of Romanian organizations towards information security, as resulted from a research and detailed survey questionnaire performed by the authors. Following the results of this research, the authors propose a way to improve the security posture of Romanian organizations, as well as knowledge, capabilities, and decision making of business managers.
Sparse Coding of Bottleneck Features-Based i-Vector Representation for Language Recognition

In recent years, the deep neural network (DNN) and the sparse coding paradigms have received a lot of attention in many pattern recognition domains including language recognition (LR). Motivated by their success, we have explored sparse coding of DNN-based i-vectors for LR task in this work. For i-vector representation, DNN-based bottleneck (BN) front-end features are used unlike the conventional mel frequency cepstral coefficient (MFCC) features. Different kinds of KSVD-based dictionary learning approaches have been explored for LR task. The effectiveness of the proposed approaches has been evaluated on AP17-oriental language recognition datasets in closed-set test conditions. On comparing with the baseline method (BN feature-based i-vector with cosine distance scoring), the proposed LR approaches are found to yield competitive performances.
Effect of Observation by Angle Only Navigation to Plan Non-Cooperative Approach for ADR

The objective of this paper is to study the effect of observation by Angle Only Navigation to plan non-cooperative Active Debris Removal approach for debris mitigation, and to have a concept of criteria for safe operation and mission assurance.
The Research of Data Blood Relationship Analysis on Metadata

In the process of continuous expansion of data and continuous expansion of the system, various data relations and data forms form crisscross connections, forming an extremely complex network diagram. If there is an error in the data, how do we quickly lock the cause of the problem? How do we find out which entities are affected by the implications or changes of the problem? These issues create challenges and pressures for large-scale, enterprise-level data platforms. The paper proposes to use data blood analysis to solve the relationship among tens of millions of tables. To get this kind of more underlying blood information, we need to add embedded parts to the execution engine, which will be fed into the blood relationship collection system using push mode when the job is executed. The paper is to implement field level blood relationship analysis in the data warehouse of China Commercial bank on the architecture of Teradata, and separated it from the ETL process and made it into a single part. By parsing multiple ETL jobs, we get a number of mapping relationship of atoms, and atoms and relationships make up the molecules that form the blood relationship network we need. This experimental scheme can be simply embedded into the data platform by eliminating the complexity of the system and achieving a separate component structure. The blood relationship can be conducted any time and temporary scripts and error logic of related data will have no data pollution on the data blood relationship.
Deconstructing 'Decentralization': Exploring the Core Claim of Crypto Systems

In stating that ether is not a security, the SEC has suggested that the 'decentralization' of a blockchain system may have legal consequences. This paper examines the common ways 'decentralization' is used in blockchain discourse, arguing that it is generally used to suggest that the systems are resilient and lack concentrated power centers. The paper critically examines the claims of 'decentralization,' providing examples of actions by core developers and miners within crypto systems that undermine claims of decentralization. Finally, the paper's core contribution is to examine the consequences of uncritically applying the term 'decentralized' to blockchain systems and making legal judgments based on it. The paper argues that in suggesting that blockchain systems lack sites of centralized power, the term decentralized in effect functions as a liability shield for those operating the systems (developers and miners), creating what I call a Veil of Decentralization and giving a core benefit of organizational law to participants in these systems without accompanying obligations. Further, misunderstanding the power dynamics within blockchain systems can lead to faulty risk assessments, in that we may view the tokens of these systems as less malleable than they actually are. This errant risk assessment affects direct uses of the tokens as well as any financial products that use them as infrastructure, and may affect our understanding of them as commodities or money.
The Use of Augmented Reality as a Teaching Tool

Augmented reality (AR) has shown to be a facilitating tool and motivation to work with children, young people, and adults in times of recreation (entertainment) and also in classrooms (formal spaces of education). Augmented reality provides a different way of learning with the support of different technologies such as computers, tablets, and smartphones. It allows easy visualization and manipulation of the study object, reproducing the complex data in the form of objects and three-dimensional texts, increasing the student's ability to perceive, which is stimulated by the possibility of interaction with the interface. This chapter aims to present the different augmented reality technologies used in education and also to discuss methodologies for the use of augmented reality applications to improve the teaching and learning process.
Implementing Active Complaint Management

The goal of implementation is to introduce a system of complaint management in the desired form quickly and without any major difficulties. In order to accomplish this goal, a series of measures must be realized in phases. Moreover, significant barriers to implementation must be overcome, so that a successful introduction is guaranteed. Five phases of the implementation process should be distinguished: (1) The decision phase—preparation of the top management decision to introduce complaint management; (2) The project organization phase—establishment of the project organization; (3) The analysis phase—analysis of the actual state of complaint handling and the internal and external framework conditions; (4) The conception phase—definition of the objectives of complaint management, choice of the basic complaint management strategy, development of a concept for all complaint management tasks and drawing up a budget and schedule; (5) The introduction phase—implementation of the new processes and changes in the company’s organizational structure and execution of internal audits. The introduction of complaint management is generally met with considerable resistance. This must be taken into account during implementation. In this chapter, the main acceptance, management and organizational barriers to the introduction of complaint management are discussed in detail, along with possible countermeasures.
FME Technique for Reduced Method Rejection

In situational method engineering (SME), there are two core intentions that method engineers look for: 1) a set method engineering goal that is the kind of method needed and 2) a method allowing him to satisfy this goal. This chapter can capture method engineering's goal using a generic process model (GPM) that guides the method engineering in the definition of his project method engineering goal and in the selection approach that best allows him to achieve it. The authors wish to move to functional method engineering so as to explore the context of method engineering/situational method engineering more fully based on functional and non-functional method situation. The implications of the approach on CAME tool design are considered and illustrated through a running example.
The Role of Social Robots in Public Space

The purpose of this research is to understand what might be today—on the edge of the social robotics era—the role of robots in public spaces. In Europe, there was a strong tradition of automata exhibition in the ‘600 and 700’ with ostensive purpose. Exposing automata in various fairs was meant to inspire awe towards the advancement of technology and science in the public who attended numerous public events. This study aims to investigate whether in the modern world the robot may have the same or other functions in public space. The study has analyzed the public display of the robot DORO: a technological artifact created by the Sant’Anna School during the European project ROBOT-ERA. Two distinct public moments were examined. The first was the night of researchers in Pisa on 30 September 2016 in Martiri della Libertà’s square, where DORO was exhibited to the public. The second occasion was the inauguration of the 39th academic year of the University of Udine. On this occasion, DORO brought to the rector his inaugural lecture and exchanged—in front of a large auditorium—a brief dialogue with the rector of the University of Udine, prof. Alberto de Toni.
The use of Modern Interactive Technologies in Shaping the Spatial Thinking of Schoolchildren

The main task of education today is to learn how to independently obtain information, set problems, look for ways to solve them, be able to analyze the knowledge gained and apply it to solve problems. The degree of learning at all stages of learning determines the level of development of spatial thinking, which is one of the characteristics of the intellectual development of the individual. The article discusses the characteristics of the formation of spatial thinking of schoolchildren. The analysis of the requirements of the Federal State Educational Standards of primary and secondary (complete) general education to knowledge and skills in mathematics has been carried out. A review of modern interactive technologies has been made, allowing to stimulate the development of spatial thinking of schoolchildren since early school.
Comparison of Isotropic and Anisotropic Models for Solar Radiation on Sloped Surfaces Under Fuzzy Logic

Energy is a vital necessity that ensures the continuity of life. It is also important to ensure the existence and continuity of the energy. Solar is the most important source of energy among renewable energy sources that are being developed as an alternative to fossil fuels that are consuming. This study develops models for the evaluation of solar energy systems and allows calculation of radiation values in the sloped surface for isotropic and anisotropic sky conditions. In literature, the effects of extraterrestrial, atmospheric, and terrestrial uncertainties are usually ignored. In the proposed fuzzy models, these uncertainties inherit in the solar energy production capacity are considered. These newly developed isotropic and anisotropic fuzzy models help to determine the most appropriate solar energy system by providing more realistic calculations.
M. M. PRISHVIN’S CREATIVE HERITAGE STUDY IN CHINA: HISTORY AND CURRENT STATUS

The article shows the most important achievements of M. M. Prishvin studies in China. These are relevant sections of textbooks and scientific publications dedicated to the Russian literature, articles in academic journals, dissertations, a monograph about M. M. Prishvin and his creative work. The focus of the Chinese Prishvin scholars is on spiritual search, philosophy of nature, Prishvin’s ecological ideas, as well as mythological motives and specific images of nature in his works. Prishvin’s creativity is often viewed in the comparative aspect as well. The paper aims to identify the originality of the history and current status of studying Prishvin’s creativity in China. The basic tendencies in the development of the Chinese Prishvin studies are determined. This is the scientific novelty of the article.
Research and development of light field microscope for measuring 3D microstructures

Precision measurement of three-dimensional (3D) microstructures has drawn great interests from researchers and industries. Currently there are a bunch of high precision measurement methods such as contour-graphs, interferometers and optical computed tomography used in industrial applications. Nonetheless, the loss of information, low efficiency and possible surface damaging of traditional ways still exist. This paper presents a new way to measure micro/nano structures based on light field microscope. The light field information of the microstructures is acquired by using a microlens array which is inserted between the camera sensor and the objective lens. Then a series of regular sub-images are recorded by the photosensor, which is used to reconstruct a 3D image by the developed algorithms. The non-contact shooting process is realized through only one exposure which is much more efficient than the traditional ways. Microlens array with aspheric surface is also designed and used in the developed system, to eliminate aberrations and compensate the loss of spatial resolution. A series of simulation and experimental studies have been undertaken to measure microstructures, and the feasibility of the developed system is validated.
School Room of World Art Culture

The article highlights the work on the creation in the school office “World Art Culture.” The description of the content of eight proposed stands, which reveal the richness of the world artistic culture, is given. The article considers the peculiarities of using the materials of the exposition of the cabinet by the primary school teacher in the process of teaching the subject “Basics of the spiritual and moral culture of the peoples of Russia”, which makes it possible to enrich the knowledge of younger schoolchildren, expand their horizons, generate interest in world artistic values and the need to communicate with them.
A Cybersecurity Model for Electronic Governance and Open Society

This paper starts by presenting the research landscape of the vulnerabilities of cyberspace; afterwards, it classifies the cyber vulnerabilities identified in the literature; finally, it proposes a cybersecurity model to tackle the cyberspace vulnerabilities found. The proposed model is grounded in three main pillars: a cybersecurity governance approach, cybersecurity capabilities, and cybersecurity best practices. The research methodology used to conduct this study is based on a quantitative and qualitative analysis of the literature on the field. The paper concludes that the model can be a useful tool for preventing and mitigating cyberattacks in public and private organizations.
A Novel Simulation Based Classifier Using Random Tree and Reinforcement Learning

In this work, we present a new classification model to solve Human Activity Recognition (HAR) problem. The new classifier is a hybrid of Random Tree and Monte-Carlo simulations where Random Tree is used to select random samples for each simulation. The simulation use a generative model to train a value function that predicts a activity depending on sensor values. The classifier trains in an unsupervised learning style and does not require a training example dataset. It builds value function depending on response from environment. The experiments are performed on HAR dataset and compared with the start-of-the-art rival techniques. The performance is measure using precision, recall, f-Score and accuracy rate. The results show the new algorithm performs better than its rival techniques in f-score and accuracy. The classifier is also scalable and can also generalize non-deterministic behaviours.
Static image facial expression recognition based on separability assessment of discrete separable shearlet transform

We present the discrete separable shearlet transform (DSST) separability assessment system for recognizing facial expressions. DSST is an image multiscale geometric analysis method. We use a separability assessment to evaluate the separability of different scales and directions of the coefficients after DSST transformation. First, all test and training images are normalized and equalized. Then, all preprocessed images are DSST-transformed, and all low- and high-frequency coefficients are obtained. Next, the separability of different scales and directions of the coefficients is evaluated, and we use only those that have a large separability index. Then, we combine the low- and high-frequency coefficients for the best separability direction and scale as the extracted features. Finally, we use a support vector machine to classify seven expressions (i.e., happiness, sadness, surprise, disgust, fear, anger, and neutrality) from the Japanese Female Facial Expression, Extended Cohn–Kanade, MMI, and Psychological Image Collection at Stirling datasets. The experimental results show that the recognition rate of the proposed method is better than those of state-of-the-art methods.
Correspondence Between Multiscale Frame Shrinkage and High-Order Nonlinear Diffusion

Wavelet frame and nonlinear diffusion filters are two popular tools for signal denoising. The correspondence between Ron-Shen’s framelet and high-order nonlinear diffusion has been proved at multilevel setting. However, for the general framelet, the correspondence is established only at one level. In this paper we extend the relationship between framelet shrinkage and high-order nonlinear diffusion in Jiang (Appl Numerical Math 51–66, 2012 [19]) from one level framelet shrinkage to the multilevel framelet shrinkage setting. Subsequently, we complete the correspondence between framelet shrinkage and high-order nonlinear diffusion. Furthermore, we propose a framelet-diffused denoising method for processing the dynamic pressure signals which are generated by a transonic axial compressor. Numerical results show that our algorithm has superior noise removal ability than traditional algorithms and presents the ability in analyzing the pressure signals from an axial transonic compressor.
ENDOSCOPIC IMAGES DIGITAL PROCESSING FOR CLINICAL DECISION SUPPORT SYSTEMS

The purpose of this research is to create new automatic methods for endoscopic image digital processing, ensuring their high ergonomics and the possibility of effective use in clinical decision support systems. As the result of investigation, the following methods were proposed: the detection and removal of specular highlights; compensation of radial and tangential geometric distortions; the mosaic panorama creation from the input video stream with low level of detail; brightness and contrast enhancement, providing simultaneous successful correction of both dark and bright areas of the image (uneven contrast) without significant underlining of the noise component typical for the existing nonlinear contrasting methods, especially in low-detail image areas; custom color correction based on linear transformation matrix taking into account endoscopic image characteristics and making it possible to customize color palette according to the physician individual preferences. The methods considered were successfully tested on real endoscopic images at the department of innovative medical devices of the Korean Electrotechnological Research Institute. The test results demonstrate their effectiveness and applicability in clinical decision support systems.
Data Analysis Algorithms for Revenue Assurance

In companies there are dissimilar factors that influence the loss of income, such as errors in planning, in decision-making, inadequate control of projects and poor treatment of inaccuracy and uncertainty in the data. Some of these causes can be mitigated if anomalous data contained in the information systems of the organizations themselves are analyzed. Present research proposes several algorithms to support revenue assurance in project management organizations. As a novelty, this proposal combines outlier mining, proactive risk management and soft computing techniques. A variety of algorithms for detection of anomalous data in revenue assurance is implemented in a library based on free software. These algorithms apply methods based on data spatial analysis, K-means, Mahalanobis and Euclidean distances, partial clustering with automatic estimation of the clusters number, pattern recognition techniques, heuristics, among others. In the research, cross-validation tests, non-parametric tests and evaluation by a group of experts are carried out. For the application of the proposal in a real environment, databases of finished projects are used and the identification of situations generating anomalous data in project-oriented organizations is achieved. In addition, the proposal has been implemented in a computer tool dedicated to project management with which several companies and centers of development of information technologies have benefited, with more than 300 projects and 5000 users.
An Efficient and Enhanced Mechanism for Message Hiding Based on Image Steganography Using ECC-Cryptosystem

With the rapid growth and advancement in computer technology, secure data communication over public networks become a major concern in todays era. Out of the various alternatives, image steganography is one of the key solutions for secure data communication over untrusted network. The main focus of this article is to define an embedded technique to hide the information in a digital image by which any adversary cannot predict the existence of secret information. And, to provide the higher security with smaller key size, ECC-cryptosystem has to be used. In this proposed method, LSB substitution strategies are used for higher imperceptibility. To prove the efficiency and security enhancement, a comparative study with existing schemes is also performed at the end based on the MSE and PSNR values.