Reviewerly/exHarmony huggingface dataset:
Multi-level Authentication Protocols Using Scientific Expertise Approach

This paper will describe new approaches for creation of multi-level user authentication protocols, using hybrid verification CAPTCHA codes. Proposed codes will define a new subclass of cognitive CAPTCHA, which require special skills and knowledge for proper user authentication. Such authentication procedure can be oriented especially to provide access for trusted group of experts, who represent particular expertise areas, and based of theirs perception abilities and knowledge. For presented authentication protocols possible examples of applications will be presented and security features will be described.
Camera Zoom Motion Detection in the Compressed Domain

In this paper we investigate the application of local tetra patterns to the compressed domain camera zoom recognition problem. The primary aim is to separate the zooming frames from the non-zooming (panning, tilting) frames for which the block motion vector orientation information is modeled utilizing a 3× 3 neighborhood and local tetra patterns. These patterns are binarized followed by feature reduction using the concept of uniform patterns and finally fed to the C-SVM classifier for recognition purposes. Comparative analysis with state-of-the-art methods using ESME and H.264 obtained block motion vectors extracted from standard video sequences show superior performance for the proposed method.
Design-for-error for a Stand-alone Child Attachment Assessment Tool

Designing technology for problem-free operation is vital, but equally important is considering how a user may understand or act upon errors and various other 'stuck' situations if and when they occur. Little is currently known about what children think and want for overcoming errors. In this paper we report on design-for-error workshops with children (age 5-10) in which we staged 3 simulated errors with a health assessment technology. In our developmentally-sensitive study, children witnessed the errors via a puppet show and created low-fidelity models of recovery mechanisms using familiar 'play-things'. We found the children were able to grasp the representational nature of the task. Their ideas were playful and inspired by magical thinking. Their work forced us to reflect on and revisit our own design assumptions. The tasks have had a direct impact on the design of the assessment.
Development of Student Worksheet Based on Problem Based Learning in Office Management Subject

This study aims to analyze the feasibility and response of students to the Problem Based Learning&#x0D; Student Worksheet in the Office Management subject that has been developed. This type of research&#x0D; is Research and Development research using a 4-D model namely Define, Design, Develop, and&#x0D; Disseminate. The subjects in this study were students of the 2016 Class Office Administration&#x0D; Education Department, Faculty of Economics, Universitas Negeri Surabaya, as many as 20 students.&#x0D; Data collection techniques in this study include student worksheet validation sheets based on&#x0D; Problem Based Learning and student response questionnaires. While the data analysis techniques&#x0D; include validation analysis of material experts and linguists, student response questionnaire&#x0D; analysis. The results showed that the results of the material expert validation sheet analysis on&#x0D; Problem Based Learning student worksheets in Office Management subject showed that the&#x0D; percentage of feasibility was 74,29% seen from the feasibility of content and presentation&#x0D; components and 84% seen from linguistic componens. While the result response questionnaire&#x0D; analysis showed that the percentage of eligibility was 72%.&amp;nbsp;
Compensation for rigid body displacements in study of local deformations using electronic speckle pattern interferometry

The paper addresses techniques of optical compensation for rigid body displacements of objects undergoing deformation in measurement of in-plane displacements using electronic digital speckle pattern interferometry. Results of demonstration tests are presented. The proposed approaches may be useful, in particular, in study of mechanical properties of materials involving samples with stress concentrators.
An Intelligent Speech Interaction Model for Mobile Teaching

Intelligent answer system is a novel information service system which integrates and applies information retrieval, natural language processing, artificial intelligence and semantic analysis to respond users' questions in intelligence and accuracy. This paper focuses on Chinese questions answering matching task and puts forward intensive learning-based questions-answering matching method. First, we study words vector and the model from sequence to sequence, to design and generate questions answering-typed model. Then, we introduces neural network-based sequence mapping model, uses lots of questions answering-paired corpus training model and learns mapping relationship between questions sequence and answer sequence. After the model training is over, the model can generate corresponding answers of questions according to users' inputting questions. Finally, the influence of different comparison experiment tests on system performance and experiment data designs by us show that the model is feasible in practical application.
Consistent video projection on curved displays

The production of curved displays has substantially increased in the past years. This new type of displays can enhance the feeling of immersion by surrounding the viewers with content. In this paper, we propose a content-aware and depth-aware video deformation method for projection of rectangular content on curved displays. Novel deformation and grid-based mapping methods are proposed to prevent over-preservation of foreground content for static and dynamic content and to enforce temporal coherence. The objective evaluation of the results shows that our approach efficiently and consistently preserves both static and dynamic content. A thorough subjective evaluation is also performed using a real-world curved screen as well as a virtual reality setup, showcasing our method against existing methods. Experimental results indicate that our method systematically outperforms the existing state-of-the-art, providing minimal content distortion and high temporal coherence between consecutive frames.
A Toolbox For Calibrating Fundus Camera

Camera calibration has many applications in various fields of computer vision, such as 3d reconstruction, object recognition and pose estimation. It consists in finding the intrinsic parameters and, possibly, the extrinsic parameters of a camera. The intrinsic parameters of a camera include parameters related to the camera itself such as focal length and distortion. The extrinsic parameters indicate the position of the camera in relation to a global coordinate system. In this article, we focus on the calibration of a fundus camera from the background images of the eye, for this we propose a popular calibration technique developed by Jean-Yves Bouguet. The modification attempted in this research aims to exploit our knowledge of the human eye in the manual selection of the extreme corners of the calibration chart. Our method is simple and gives good results.
Attention retargeting using saliency map and projector–camera system in real space

Many attention‐retargeting methods based on the visual saliency model of bottom‐up attention for guiding human attention to target regions have recently been proposed. However, existing attention‐retargeting methods focus on only modulating an image or a video presented to a display. It is difficult for the existing methods to guide humans' attention to objects in the real space. In this paper, we propose an appearance control method using a projector–camera system to realize attention retargeting in real space. The ideal appearance for attention retargeting is estimated on the basis of reverse engineering of the visual saliency map theory. Our system then projects an optimum light pattern calculated from the difference between the ideal appearance and current appearance in real space. Attention retargeting to the plane of real space is addressed as an initial step of our research. As a result, our attention‐retargeting method can effectively control an appearance in real space for attention retargeting compared with spot light projection. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley &amp; Sons, Inc.
Design and implementation of Surakarta game based on iOS

Aiming at the present situation that Surakarta game has a narrow audience and poor user interface and user experience, this paper designs and implements a Surakarta game system based on iOS platform. A chessboard data structure based on iOS platform is designed, which is suitable for different screen sizes of mobile phones. The animation representation of game process, especially the eating process, is realized. This paper studies and attempts to use GCD-based multi-threaded search to solve the problem of limited mobile phone resource performance. Experiments show that the Surakarta game system based on iOS platform can play man-machine game on portable devices and has good performance.
KSI based Sensitive Data Integrity Validation Method for Precision Medicine System

Interest in precision medicine in the medical field is increasing through the United States `Precision Medicine Initiative' announced in 2015. Accordingly, a method for secure and efficient provide of precision medicine services has been continuously studied. Recently, a survey by consulting company shows the importance of verification the integrity of data in decision making is increasing in the analysis of sensitive data of big data size that a key component of precision medicine. Therefore, in this paper, we study integrity validation method of sensitive data by applying signature technology called KSI in precision medicine system.
Scaffolding e-voting in developing countries

Research question: This paper discusses e-voting as an integral part of e-government in developing countries. E-voting enables automation of casting and counting votes. Motivation: The main goal was to investigate the readiness of both the public sector and citizens for switching from common “paper” voting method to electronic system-based voting. In order to improve democracy and trust in the election process (IDEA, 2011), the e-voting system should be reliable, accurate and secure (Mauw, Verschuren, &amp; de Vink, 2007). The example that should be followed is the Estonian e-voting system (Drechsler, 2004). Idea: We proposed a comprehensive e-voting model that includes five components: e-voting services, IT infrastructure, participants’ registration, components integration and a system for counting and reporting. Security is the most important issue that should be overcome by using the cryptographic protocols. Reliability and availability of the e-voting system should not be neglected, and it should be able to save all verified casted votes. Data: In order to examine the readiness and awareness of e-voting potentials in a developing country, we conducted a survey that included 152 persons from three different groups: individuals, legal entities and e-government employees. Tools: In order to establish relationships among opinions of the three groups of respondents to the survey that was conducted, a comparative analysis was performed. For this purpose the questions were divided into four categories. Findings: As it was expected, the study results have showed that survey participants find security, lack of qualified staff and mistrust of the older generations towards new technologies as the crucial issues in developing and implementing the e-voting model. Based on the responses the cost reduction, ease of use and efficiency improvement are recognized as categories that could be realized by implementation of the e-voting system. Contribution: The results show the respondents’ opinion regarding the e-voting system introduction as a legitimate voting tool. It can reduce abuse, voting costs and manual errors.
Russian Music Publishing Business: From Commerce to Philanthropy

In the history of Russian music publi­shing business, there are some areas that require a further study of extensive factual material in terms of succession of times and generations, traditions and experience, individual and common. The process of Russian music publishing formation resul­ted in a unique thought-creating space, which united in a single whole the spiritual and the material, commerce and philanthropy. The economic side of the issue in this case is the most indicative, demonstrating the various analytical perspectives, which create an idea of the mechanisms of entrepreneurial activity in the market of production and marketing of non-printed products, the problems of innovative approach in the field of improving production capacity, the emergence of a whole galaxy of merchants-patrons-educators. Hence, “homo musicus” and “homo financicus” are outstanding representatives of the Russian music publishing business, which opens the prospect of studying personal profiles in the history of philanthropy and charity and creates prerequisites for understanding the unity of financial, economic and artistic spheres. The article aims to study the professional features that allow to determine the genesis of commercial and creative in the most successful music publi­shing business projects implemented in the second half of the 19th century. Of particular interest are the famous names, specifically, M.P. Belyaev, who was a symbol of high service to the musical art. Promoting the works of young Russian composers, providing them with all-round assistance and support, M.P. Belyaev became the first “musical missionary” and educator. His financial activity was deeply patriotic and connected with high spiritual ideals of service to society. These grounds can be used for further study of Russian music publishing business, philanthropy and charity in their inseparable interconnection.
Investigation of Context-aware System Using Activity Recognition

The physical activity is important context information to define and understand the user's situation in real time and in detail. Therefore, we developed a context-aware function using the activity recognition and showed that it is possible to provide more appropriate support according to the user's situation. In this study, we first constructed a model by applying machine learning to data sensed by a smartphone in order to predict the physical activity of the user. In the experiment, high accuracy of 97.6% was obtained by using the model. Next, we developed three functions using the activity recognition. These functions predict the physical activity of user in real time. In addition, user support is performed according to the predicted physical activity. In the experiment using developed functions, it is confirmed that these functions worked correctly in real-world conditions.
A Training Method of Convolution Neural Network for Illumination Robust Pedestrian Detection

In this article, the authors propose a new training method of convolution neural networks for pedestrian detection under the illumination of robust environments of ADAS (Advanced Driver Assistance System). This training method was aimed at proposing a method to increase the recognition rate in a system that classifies objects by receiving distorted images in real time as the ADAS, by using the Convolution Neural Network (CNN). The proposed method used images with an increased distortion level by setting gamma to 0.7, and the conventional method was experimented with images with a gamma set to 1. In this article, the authors experiment with the comparison of the conventional training method using the preprocessing accelerator and the proposed training method using the gamma variation. In this study, pedestrian images with a distorted illumination intensity were used in training and then the accuracy of pedestrian classification was tested with normal images and distorted images as test images. The proposed method shows an error rate of 9.8%, which was improved by 1.2% in accuracy.
Design and Deploying Tools to ‘Actively Engaging Nature’

'Shifting Baseline Syndrome' is highly apparent in the context of generational shifts in work and life patterns that reduce interaction with and knowledge of the natural world, and therefore expectations of it. This is exacerbated by changes in the natural world itself due to climate change, biodiversity decline and a range of anthropogenic factors. Distributed and accessible technologies, and grass roots approaches provide fresh opportunities for interactions, which enable active engagement in ecological scenarios. The My NatureWatch project uses digital devices to collect visual content about UK wildlife, promoting 'active engagements with nature'. The project embodies Inclusive Design in the Digital Age, as the activity; engages a wide demographic community, can be used by all, provided user led agency and produced methodological design lessons. The article frames My Naturewatch as an agent for active designed engagements with nature. The research objective is to comprehend 'how to design tools for positive nature engagement' holding value for; (1) academic communities as validated methodologies (2) the public through access to enabling technologies, content and knowledge (3) industry in the form of new; experiences, engagements and commerce. The approach is specifically designed to yield insights from a multitude of engagements, through the deployment of accessible, low-cost products. Project reporting documents the benefits, pitfalls and opportunities in the aforementioned engagement uncovered through design-led approaches. Insights are gathered from public/community facing workshops, wildlife experts, ecologists, economists, educators and wildlife NGO's. The engagement methodologies are compared highlighting which initiative yielded 'Active Engagement with Nature'.
Classifying and Grouping Narratives with Convolutional Neural Networks, PCA and t-SNE

Each week, the Consumer Financial Protection Bureau (CFPB) receives thousands of consumer complaints about financial products and services. These complaints must be forwarded to the responsible company and posted on the site after 15 days or when the company responds to the complaint, whichever comes first. Published complaints and solutions help consumers solve their problems and also serve as a repository of help for other consumers to avoid or solve problems on their own. Every complaint provides information about the problems people are having, helping them to identify inappropriate practices and allowing them to stop before they become major problems. Culminating in better results for consumers and a better financial market for everyone. Each of the complaints contains information on submission date, company to send the complaint, complaint narrative, among others. However, complaints do not have information on the department to which it should be forwarded. Therefore, in this work, the three approaches to analyze each complaint are: (i) convolutional neural network (CNN) to classify the narratives; (ii) principal components analysis (PCA); and (iii) t-distributed stochastic neighbor embedding (t-SNE) to create a three-dimensional embedding for clustering. Embedding from scratch, Pre-trained Word Vectors (word2Vec) and Global Vectors (GloVe) vectors are used and compared in six different CNNs modeling. The results increase the evidence that pre-trained word vectors is important and that convolutional neural networks and t-SNE can perform remarkably well on real text classification data.
On the Essence of Technology (the Case of Collaboration between Chinese and Russian Enterprises)

The subjects of technology and communication have been studied widely during the last decades. After Martin Heidegger many researchers have noted connection between these notions. Heidegger himself argued the essence of technology is connected to intentionality. This perspective did not find a due resonance in the later studies on the nature of technology. In search of efficient ways of business communication our research focuses on the phenomena of intentionality, communication and technology. The aim of the study is to discover how the three mentioned components are reflected in interactions for business purposes. With this aim a questionnaire for enterprise senior employees was developed. Answers to the questionnaire revealed communication features, means and barriers of communication between representatives of Chinese and Russian enterprises. Taking into account that most of the collaboration took place via technological means of communication, we had to consider the influence of ICT on the communicative process. Results of the analysis showed that such communication is dependent upon disposition and intentions of the participants.
White-Box Cryptography: A Time-Security Trade-Off for the SPNbox Family

White-box cryptography aims to ensure the security of cryptographic algorithms in an untrusted environment where the adversary has full access to their implementations. Typical applications are DRM, Pay Tv boxes, and smartphones. A number of white-box implementations for standard cryptographic algorithms—e.g., AES and DES—have been published in the literature. Unfortunately, such implementations are subjected to algebraic attacks, side channel attacks, etc. and thus researchers developed new ciphers—e.g., SPACE and the SPNbox family—with a dedicated design approach for white-box implementations. In this chapter, we focus on the SPNbox family. Our aim is to modify the small internal block cipher used in SPNbox in order to increase the number of bits of the key used in each round. This approach provides us the possibility to reduce the number of rounds of about 25%, making the algorithm faster than the previous one.
Enhancement of Navigation Systems of Mobile Robots in Gas Leakage Searching

Gas leakage commonly happens in daily life. The leakage can cause many losses and even cause the death. Implementing human and animals in monitoring, checking, and finding the source of leakage can harm their life. The usage of the robot can give many advantages, i.e., it can be programmed easily, it does not feel tired, it does not need much time to be trained, etc. However, to control the robot in navigating to the leakage source is not so Haeasy. In this research, an enhancement of navigation system using two parameters inputs, i.e., distance and concentration of the gas is proposed. A distance fuzzy algorithm and gas fuzzy algorithm is implemented to the robot. The robot can use each parameter depends on the environment and situation that it meets. Both of the algorithms were successful in guiding the robot to move in the correct path. The robot could avoid the obstacles and find the location of the gas leakage.