Reviewerly/exHarmony huggingface dataset:
Interactive Perception-Based Multiple Object Tracking via CVIS and AV

Cooperative Vehicle and Infrastructure System (CVIS) and Autonomous Vehicle (AV) are two mainstream technologies to improve urban traffic efficiency and vehicle safety in the Intelligent Transportation System (ITS). However, there remain significant obstacles that must be overcome before fully unmanned applications are ready for widespread adoption in a transportation system. To achieve fully driverless driving, the perception ability of vehicle should be accurate, fast, continuous, and wide-ranging. In this paper, an interactive perception framework is proposed, which combines the visual perception of AV and information interaction of CVIS. Based on the framework, an interactive perception-based multiple object tracking (IP-MOT) method is presented. IP-MOT can be divided into two parts. First, a Lidar-only multiple object tracking (L-MOT) method obtains the status of surroundings using the voxel cluster algorithm. Second, the preliminary tracking result is fused with the interactive information to generate the trajectories of target vehicles. Two simulation platforms are established to verify the proposed methods: CVIS simulation platform and Virtual Reality (VR) test platform. The L-MOT algorithm is tested on a public dataset and the IP-MOT algorithm is tested on our simulation platform. The results show that the IP-MOT algorithm can improve the accuracy of object tracking as well as expand the vehicle perception range via combination of CVIS and AV.
Online Handwriting Signature Verification Based on Template Clustering

Template-based and template-matching methods are commonly used in online signature verification, and it is very important to select a suitable template signature. Generally, template signatures are chosen from the enrollment signatures, but when the number of enrollment signatures is large, the computation time is long, and some enrollment signatures are not representative. This paper submits a two-level signature verification method based on template clustering. Firstly, a similarity score matrix is obtained by comparing the enrolled signatures one by one, and the median of all similarity scores is taken as a clustering threshold. Then the signature threshold clustering algorithm is used to cluster the enrolled signatures. In each signature cluster, the signature with the highest aggregate score is chosen as the signature representative of the signature cluster, and the other signatures in each signature cluster are used as the second-level template signatures. In each one-to-one signature matching process, a fusion feature weighted by the similarity distance and time-speed ratio of the fusion curve is considered as the basis for signature similarity evaluation. Finally, on two open signature datasets, SVC2004 Task 1 and SUSIG Visual, different numbers of genuine signatures are selected as training set for template clustering. Remaining genuine signatures and skilled forged signatures are used as test set for experimental comparison. Depending on the number of training signature samples, our best equal error rate (EER) on two datasets is 2.50% and 0.83%, respectively. The experimental results test the effectiveness of the proposed method.
Timing Leaks and Coarse-Grained Clocks

Timing-based side-channel attacks have matured from an academic exercise to a powerful attack vector in the hand of real-world adversaries. A widely deployed countermeausure against such attacks is to reduce the accuracy of the clocks that are available to adversaries. While a number of high-profile attacks show that this mitigation can be side-stepped, there has not been a principled analysis of the degree of security it provides until now. In this paper, we perform the first information-flow analysis with respect to adversaries with coarse-grained clocks. To this end, we define an adversary model that is parametric in the granularity of the clock and connect it with a system model based on timed automata. We present algorithms for translating such a system to an information-theoretic channel, which enables us to analyze the leakage using standard techniques from quantitative information-flow analysis. We use our techniques to derive insights about the effect of reducing clock resolution on security. In particular, (1) we show that a coarse-grained clock might leak more than a fine-grained one, (2) we give a sufficient condition for when increasing the grain of the clock we achieve better security, and (3) we show that the attack techniques used in the literature form a strict hierarchy in terms of the information an adversary can extract using them. Finally, we illustrate the expressiveness of our development on a case study of a system that uses RSA signatures.
Introduction to Optimization and Metaheuristic Methods

This chapter presents an introduction of optimization techniques considering their principal properties. The objective of this chapter is to stimulate the use of metaheuristic approaches for solving complex optimization problems. The analysis is carried out so that it results clear the need of employing metaheuristic schemes for the solution of parameter identification system schemes.
Generalizing Topological Set Operators

It is well-known that topological spaces can be axiomatically defined by the topological closure operator, i.e., Kuratowski Closure Axioms. Equivalently, they can be axiomatized by other set operators reflecting primitive notions of topology, such as interior operator, derived set operator (or dually, exterior operators, co-derived set operators), or boundary operator. It is also known that topological closure operators (and dually, topological interior operators) can be weakened as in generalized closure (interior) systems. What about boundary operator, exterior operator, and derived set (and co-derived set) operator in the weakened systems? Our paper completely answers this question by showing that these six operators can all be weakened in an appropriate way such that their relationships remain essentially the same as in topological spaces. Our results indicate that topological semantics can be fully relaxed to the weakened systems.
Trends Review of the Contemporary Security Problems in the Cyberspace

The information security problems include a wide range of possible threats that affect almost every aspect of human life. This article makes a survey about the trends of the latest problems in cybersecurity reviewing the security reports issued by some major information security companies. These problems are not static, nor equally distributed. Some of them have more significant impact than others in a specific time but at the next period the situation is changed. The purpose of this paper is to summarize the existing trends in the cyberspace security and to point out the future research tasks in the area.
A Mixed Reality Environmental Simulation to Support Learning about Maritime Habitats

Environmental simulations allow for an easy and safe acquisition of knowledge about hard-to-reach habitats. We present a mixed-reality simulation that enables the user to convert (parts of) an arbitrary place like his or her own living room into a maritime habitat, using the example of the Baltic Sea. The user explores the virtual underwater world by walking in the real world. Typical characteristics and elements of the simulated habitat are integrated by adjusting light refraction and textures, and by adding animals, plants, and stones. The virtual animals respond to the user's movement. Rearranging real world objects causes the virtual world to change its appearance as well. User tests show that the environmental simulation provides an authentic insight into the Baltic Sea habitat and is well received with regard to the overall user experience. However, for first-time users, conveying more formal knowledge does not seem to work as well (yet) as compared to a conventional textbook approach.
Cosine Similarity Drift Detector

Concept drift detection algorithms have several applications. For example, nowadays many systems are interconnected by computer networks and generate a lot of data constantly over time (data stream). Thus, it is essential to detect when this data flow presents an abnormal behavior as this might be an attack on the security of the network. This paper proposes CSDD, a new method that uses the Cosine similarity and windowing techniques to compare recent and older data and detect concept drifts. To validate it, experiments were run with both synthetic and real-world datasets and using Naive Bayes and Hoeffding Tree as base learners. The accuracy results were evaluated using a variation of the Friedman test and the Bonferroni-Dunn post-hoc test, whereas the detections were evaluated using several metrics including the mean distance ( $$\mu $$ D), False Positives (FP), false Negatives (FN), precision, recall, and Matthews Correlation Coefficient (MCC). The experimental results show the effectiveness of CSDD in scenarios with abrupt and gradual changes as it delivered the best results in nearly all artificial datasets.
Identifying Personality Traits Using Overlap Dynamics in Multiparty Dialogue

Research on human spoken language has shown that speech plays an important role in identifying speaker personality traits. In this work, we propose an approach for identifying speaker personality traits using overlap dynamics in multiparty spoken dialogues. We first define a set of novel features representing the overlap dynamics of each speaker. We then investigate the impact of speaker personality traits on these features using ANOVA tests. We find that features of overlap dynamics significantly vary for speakers with different levels of both Extraversion and Conscientiousness. Finally, we find that classifiers using only overlap dynamics features outperform random guessing in identifying Extraversion and Agreeableness, and that the improvements are statistically significant.
ERMOCTAVE: A Risk Management Framework for IT Systems Which Adopt Cloud Computing

Many companies are adapting cloud computing technology because moving to the cloud has an array of benefits. During decision-making, having processed for adopting cloud computing, the importance of risk management is progressively recognized. However, traditional risk management methods cannot be applied directly to cloud computing when data are transmitted and processed by external providers. When they are directly applied, risk management processes can fail by ignoring the distributed nature of cloud computing and leaving numerous risks unidentified. In order to fix this backdrop, this paper introduces a new risk management method, Enterprise Risk Management for Operationally Critical Threat, Asset, and Vulnerability Evaluation (ERMOCTAVE), which combines Enterprise Risk Management and Operationally Critical Threat, Asset, and Vulnerability Evaluation for mitigating risks that can arise with cloud computing. ERMOCTAVE is composed of two risk management methods by combining each component with another processes for comprehensive perception of risks. In order to explain ERMOCTAVE in detail, a case study scenario is presented where an Internet seller migrates some modules to Microsoft Azure cloud. The functionality comparison with ENISA and Microsoft cloud risk assessment shows that ERMOCTAVE has additional features, such as key objectives and strategies, critical assets, and risk measurement criteria.
VITALab.Mobile - A Mobile Living Lab

VITALab.Mobile is a mobile VR/AR laboratory for case and field studies as well as clinical trials to evaluate novel forms of virtual therapies and scientific research. The laboratory is build into a truck, which can reach a variety of different user groups everywhere. The focus of this interdisciplinary project is the creation of a user-friendly and real-world research and interactive environment with the topic of diagnostics and therapy in the future within a medico-therapeutic context. The project provides a platform for other scientists, doctors, therapists and patients.
Integration of Dialog-based Product Advisors into Filter Systems

Different techniques such as search functions or recommendation components are used today to support the often complex product search on the Internet. Faceted filter systems that successively limit the result set according to the set filter settings have proven to be quite successful. However, this method requires clear objectives and domain knowledge on the part of the users. As an alternative, conversational product advisors who select suitable products on the basis of a sequence of questions have gained more importance in recent times, whereby the questions are based more on the tasks and application scenarios of the users than on the technical properties of the products. However, there is currently a lack of approaches that integrate filter systems and conversational advisors in a meaningful and closely coupled way. In this paper an integrated approach is presented, where users can switch between filter systems and advisory dialogues, whereby selection actions in one component have a consistent and transparent effect on the other component and can be further adjusted there. The aim is to better support users with different levels of knowledge of the product type concerned. We describe the requirements for such integrated systems resulting from our approach and report on a user study in which the user behavior and the subjective evaluation were examined in a prototypical implementation.
Dual Hashing-Based Algorithms for Discrete Integration

Given a boolean formula F and a weight function $$\rho $$ , the problem of discrete integration seeks to compute the weight of F, defined as the sum of the weights of satisfying assignments. Discrete integration, also known as weighted model counting, is a fundamental problem in computer science with wide variety of applications ranging from machine learning and statistics to physics and infrastructure reliability. Given the intractability of the exact variant, the problem of approximate weighted model counting has been subject to intense theoretical and practical investigations over the years. The primary contribution of this paper is to investigate development of algorithmic approaches for discrete integration. Our framework allows us to derive two different algorithms: WISH, which was already discovered by Ermon et al. [8], and a new algorithm: SWITCH. We argue that these algorithms can be seen as dual to each other, in the sense that their complexities differ only by a permutation of certain parameters. Indeed we show that, for F defined over n variables, a weight function $$\rho $$ that can be represented using p bits, and a confidence parameter $$\delta $$ , there is a function f and an NP oracle such that WISH makes $$\mathcal {O} \left( f(n,p,\delta )\right) $$ calls to NP oracle while SWITCH makes $$\mathcal {O}\left( f(p,n,\delta )\right) $$ calls. We find $$f(x,y,\delta )$$ polynomial in x, y and $$1/\delta $$ , more specifically $$f(x,y,\delta ) = x\log (y)\log (x/\delta )$$ . We first focus on striking similarities of both the design process and structure of the two algorithms but then show that despite this quasi-symmetry, the analysis yields time complexities dual to each other. Another contribution of this paper is the use of 3-wise property independence of XOR based hash functions in the analysis of WISH and SWITCH. To the best of our knowledge, this is the first usage of 3-wise independence in deriving stronger concentration bounds and we hope our usage can be generalized to other applications.
INFORMATIZATION OF MATHEMATICS EDUCATION: DIDACTIC OPPORTUNITIES, EXPERIENCE AND FOREIGN TRENDS

The article discusses modern trends in the informatization of mathematical education in different countries. Two important phenomena of the 21st century that determine the development of various spheres of life, including education, are noted, that is Big Data and informatization based on the development of information and communication technologies. It is shown what impact Big Data has on changing methods of scientific research and how the introduction of information technologies in the learning process changes the theory and methodology of teaching mathematics. Examples of practical experience of Poland and other countries in the field of informatization of mathematical education are presented, a critical analysis of this experience is carried out, and conclusions are drawn about the need to improve the informatization of mathematical education of schoolchildren and students.
Enumeration and Coding of Compact Code Trees for Binary AIFV Codes

We extend the concept of compact code trees, i.e., canonical code trees, of Huffman codes to the case of binary AIFV (almost instantaneous fixed-to-variable length) codes. We give an algorithm to enumerate the number of all compact AIFV code trees by using a bijection between the compact AIFV code trees and the proper sequences defined in this paper. Based on the enumeration of compact AIFV code trees, we give an efficient coding scheme to describe the compact AIFV code trees, which is required when we send a decoder the information of code trees used in the encoding of source sequences.
Private Polynomial Computation from Lagrange Encoding

Private computation is a generalization of private information retrieval, in which a user is able to compute a function on a distributed dataset without revealing the identity of that function to the servers that store the dataset. In this paper it is shown that Lagrange encoding, a recently suggested powerful technique for encoding Reed-Solomon codes, enables private computation in many cases of interest. In particular, we present a scheme that enables private computation of polynomials of any degree on Lagrange encoded data, while being robust to Byzantine and straggling servers, and to servers that collude in attempt to deduce the identities of the functions to be evaluated. Moreover, incorporating ideas from the well-known Shamir secret sharing scheme allows the data itself to be concealed from the servers as well. Our results extend private computation to non-linear polynomials and to data-privacy, and reveal a tight connection between private computation and coded computation.
Interdisciplinary Cybersecurity: Rethinking the Approach and the Process

The need for cybersecurity professionals continues to grow and education systems are responding in a variety of ways. This study focusses on the “interdisciplinarity” of cybersecurity that contributes to the emerging dialogue on the direction, content and techniques involved in the growth and development of cybersecurity education and training. The study also recognizes the contributions of other disciplines to the field of cybersecurity by the discussion of relevant theories that contribute to understanding security in the context of legal, economics and criminology perspectives. Finally, quantitative analysis (security metrics) is done to understand the existing knowledge of security behaviors and beliefs among students from technical and non-technical majors, helps measure the interest fostered towards an academic pathway in cybersecurity and substantiates on the need for providing a level of cyber education for all individuals appropriate to their role in the society.
USING VOTE E-RECAPITULATION AS A MEANS TO ANTICIPATE PUBLIC DISORDERS IN ELECTION SECURITY IN INDONESIA

Purpose: General elections in Indonesia until the last election were carried based on a manual system and complex checks. This process is always vulnerable to errors and fraud. As a result of these errors and frauds, the election results are always debated and doubtful. The dissatisfaction with general election results which causes security disturbances is an example of political threats and political instability. To fulfill the principles of elections, the presence of e-recapitulation is vital.&#x0D; Methodology: The method used in this study qualitatively with data sources consisting of primary data, namely the results of observations and interviews, as well as secondary data, namely the results of literature studies and search for documents and articles in the media.&#x0D; Main Findings: Based on field studies, the efficiency and effectiveness of e-recapitulation are believed to be the solution to current problems in Indonesia. It can be concluded that the use of e-recapitulation must begin immediately in a large scope in all regions of Indonesia to realize better, more effective and efficient general election.&#x0D; Implications/Applications: The implementation is believed to minimize the emergence of post-election conflicts caused by fraud in the vote-counting process. Free bribery and fraud can be guaranteed in the future.
Building an ASR Corpus Based on Bulgarian Parliament Speeches

This paper presents the methodology we applied for building a new corpus of Bulgarian speech suitable for training and evaluating modern speech recognition systems. The Bulgarian Parliament ASR (BG-PARLAMA) corpus is derived from the recordings of the plenary sessions of the Bulgarian Parliament. The manually transcribed texts and the audio data of the speeches are processed automatically to build an aligned and segmented corpus. NLP tools and resources for Bulgarian are utilized for the language specific tasks. The resulting corpus consists of 249 hours of speech from 572 speakers and is freely available for academic use. First experiments with an ASR system trained on the BG-PARLAMA corpus have been conducted showing word error rate of around 7% on parliament speeches from unseen speakers using time-delay deep neural network (TD-DNN) architecture. The BG-PARLAMA corpus is to our knowledge the largest speech corpus currently available for Bulgarian.
A Secure Authentication and Key Establishment Scheme for Wearable Devices

With the rapid development of micro-electronics and Information and Communication Technology (ICT), users can utilize various service such as Internet of Things(IoT), smart-healthcare and smart-home using wearable devices. However, the sensitive information of user are revealed by attackers because the medical services are provided through open channel. Therefore, secure mutual authentication and key establishment are essential to provide secure services for legitimate users in Wireless Body Area Networks(WBAN). In 2019, Gupta et al. proposed a lightweight anonymous user authentication and key establishment scheme for wearable devices. We demonstrate that their scheme cannot withstand user impersonation, session key disclosure and wearable device stolen attacks. We also propose a secure and lightweight mutual authentication and key establishment scheme using wearable devices to resolve the security shortcomings of Gupta et al.'s scheme. The proposed scheme can be suitable to resource-limited environments.
Inclusive Education as a Basis for Sustainable Development of Society

According to statistics, currently, approximately 4% of individuals with disabilities or incapacity for work are enrolled in higher education institutions of the Russian Federation. Thus, according to this figure, it is clear that higher education in the Russian Federation is available to a limited number of individuals with disabilities or incapacity for work. Involvement of a greater number of people with disabilities to the higher education system requires the creation of special conditions that make training for these people available and attractive.