Reviewerly/exHarmony huggingface dataset:
Analysis of Two Countermeasures Against the Signal Leakage Attack

In 2017, a practical attack, referred to as signal leakage attack, against reconciliation-based RLWE key exchange protocols was proposed. In particular, this attack can recover a long-term private key if a key pair is reused. Directly motivated by this attack, recently, Ding et al. proposed two countermeasures against the attack. One is the RLWE key exchange protocol with reusable keys (KERK), which is included in the Ding Key Exchange, a NIST submission; the other is the practical randomized RLWE key exchange (PRKE) (TOC'18). Meanwhile, there exits another key reuse attack on RLWE key exchange (ACISP'18 and Africacrypt'18), which is called key mismatch attack. In this paper, we find that KERK and PRKE are vulnerable to key mismatch attack. In particular, we propose a simpler key mismatch attack and apply it to KERK and PRKE, respectively. In fact, key mismatch attack shares the same idea with the signal leakage attack, which is one of the communicators chooses a RLWE sample with special structure as his/her public key. In order to resist key mismatch attack, we extend KERK and give an improved one, where any party can construct a new "public key" of the other party. And we also extend PRKE by increasing randomization further. Finally, by comparison, we get that the improved PRKE is more practical.
Extracting Fuzzy Gradual Patterns from Property Graphs

A property graph in a NoSQL graph database engine provides an efficient way to manage the data and knowledge due to its native graph-structure storage. A property graph is a labeled directed graph having nodes and relationships with a set of attributes or properties in form of (key:value) pairs. In this work, we aim at mining such graphs in order to extract frequent gradual patterns in the form of "the more/less A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ,..., the more/less A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> " where A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> are information from the graph, should it be from the nodes or from the relationships. In order to retrieve more valuable patterns, we consider fuzzy gradual patterns in the form of "The more/less the A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> is F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ,...,the more/less the A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> is F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> " where A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> are attributes retrieved from the graph nodes or relationships and F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> are fuzzy descriptions. For this purpose, we introduce the definitions of such concepts, the corresponding method for extracting the patterns, and the experiments that we have led on synthetic graphs using a graph generator. We show the results in terms of time and memory consumption.
Online and stable parameter estimation based on normalized brain emotional learning model (NBELM)

Summary Recently, a computational model of Amygdala based on the brain emotional learning is presented by psychologists. This brain emotional learning model (BELM) that has a neuro‐inspired architecture is utilized to train the weights which are in Amygdala and Orbitofrontal. In this paper, unknown parameters of dynamic systems are estimated by developing the normalized BELM (NBELM). To this end, after proving the stability of the model output, the sufficient condition for weights convergence is extracted while the sensitivity analysis is applied for this model. In order to evaluate the performance of NBELM, in the first example, the matrices of a twin rotor MIMO system are estimated and compared with the equation error method (EEM). In the second example, the nonlinear model of a servomotor is utilized as a case study. In the third example, the performance of the NBELM in experimental systems is validated using a reaction wheel with a DC motor. An important feature of the brain emotional system is its fast response, leading the NBELM to have a high speed performance in estimating the parameters of dynamic systems. A few number of adjustable parameters and low computing complexity also cause the NBELM to be an appropriate method for online estimation of the unknown parameters of dynamic systems.
Using Constraint Mining to Analyze Software Development Processes

Most software development organizations nowadays use issue-tracking tools to manage software processes throughout the life-cycle. Still, understanding development processes, keeping track of process execution, and reacting to deviations in projects remains challenging. In particular, the actual process usually differs from the process perceived by developers, making it hard to define the processes developers are expected to carry out. This is further challenged by frequently changing processes and process variations in different projects and teams. In this paper we describe an empirical study in which we applied a constraint mining approach from the field of software monitoring to automatically extract process definitions in the form of constraints. Specifically, we applied the approach to datasets extracted from four real-world projects (using the Jira issue-tracking tool) in a company developing a recreational activities platform. The mined constraints describe the boundaries of the actual processes and thus help to understand process behavior. Constraints can be frequently re-mined to understand process evolution. The mined constraints can also be used to monitor future processes to detect problems in the development process early on. We involved a domain expert to evaluate the usefulness of our results and investigated to what extent the mined constraints reflect the official development process of the company. We also report mining results for different issue types, across projects, and over different time windows.
A Systematic Literature Review for Service-Oriented Architecture and Agile Development

This research presents a Systematic Literature Review (SLR) involving Agile Methods and Service-Oriented Architecture (SOA). Is this combination of solutions capable of handling rapid changes in the environment, business objectives, and requirements? To answer this question and give confidence to this review, a rigorous protocol was followed and relevant studies were selected, data were extracted and analyzed. Some studies propose a mature solution, although they do not present data that are more consistent and capable of being evaluated. Other studies are superficial. In addition, few studies have gone through the protocol. So the main conclusion is that combining SOA and Agile methods can be a good way to solve the problem, but more studies are needed.
Fraud Detection of Facebook Business Page Based on Sentiment Analysis

Growing technological development is making our daily purchases totally online based. People are no more interested to visit shops and waste time to buy things. Moreover, they prefer online shopping. Because it saves time and has almost everything people need in daily basis. Therefore, many tool and techniques have been developed to prevent fraud for e-commerce sites and more are under development. Being a social networking website Facebook is also acting as an online market place for many people. This research proposes a method to prevent fraud and identify fraud business pages. Because nowadays a lot of frauds are happening through many Facebook business pages, it is important to identify fraud pages.
Analysis and Improvement of a NTRU-Based Handover Authentication Scheme

Recently, Chen and Peng proposed a NTRU-based handover authentication scheme for wireless networks, aiming to provide a quantum-resistant solution with low complexity. Unfortunately, we find that there may exist an inside attack against their scheme. Specifically, in their scheme any mobile node or access point can recover the authentication server's long-term secret. Since this secret plays a vital role in Chen and Peng's scheme, any one with this secret can impersonate the authentication server. Fortunately, we have come up with a simple and efficient solution to thwart the proposed attack, which can maintain all the features of the original protocol while incurring little additional communication and computational costs.
Virtual Patient Interaction via Communicative Acts

In the context of assisting informal caregivers of Alzheimer Disease patients, this article presents the design and preliminary implementation of a serious game in which two agents -a user-controlled caregiver and a virtual patient- communicate via specifically-designed dialog acts, reflecting both pedagogically appropriate and inappropriate behaviors.
Chinese Social Media Entity Linking Based on Effective Context with Topic Semantics

On social media, entity linking is very important for natural language processing tasks, such as Sentiment Analysis, Question Answering (QA) and Machine Translation. Compared to English-oriented entity linking, Chinese entity linking has its special difficulties. Just like the entity linking for short text, Chinese microblogs have lots of noise and the mention lacks effective context information. In order to solve these problems, we present a new model for Chinese microblogs entity linking. Entity linking usually includes two steps: candidate entities generation and candidate entities ranking. First, based on the characteristics of Chinese, we put forward multi-method fusion strategies for candidate generation to improve the recall rate of candidate entities. Second, we propose a new neural network model called TAS (Topic attention Siamese) for candidate entities ranking. In TAS model, we add effective topic semantics on Siamese network to learn representations of context, mention and entity, and rank the mention-entity similarity. The representation of mention incorporates information from multiple sentences on the same topic, which can effectively solve the problem of the lack of contextual information. We also use Character-enhanced Word Embedding model (CWE) to pre-train both word embedding and characters embedding to work out noise and word segmentation impact. Experimental results demonstrate that our method significantly outperforms the state-of-the-art results for entity linking on Chinese social media.
Subjective Assessment of Image Quality Induced Saliency Variation

Our previous study has shown that image distortions cause saliency distraction, and that visual saliency of a distorted image differs from that of its distortion-free reference. Being able to measure such distortion-induced saliency variation (DSV) significantly benefits algorithms for automated image quality assessment. Methods of quantifying DSV, however, remain unexplored due to the lack of a benchmark. In this paper, we build a benchmark for the measurement of DSV through a subjective study. Sixteen experts in computer vision were asked to compare saliency maps of distorted images to the corresponding saliency maps of the original images. All saliency maps were rendered from ground truth human fixations. A statistical analysis is performed to reveal the behaviours and properties of human assessment of the saliency variation. The benchmark is made publicly available to the research community.
Collateral Use of Deployment Code for Smart Contracts in Ethereum

Ethereum is still the most prominent platform for smart contracts. For the deployment of contracts on its blockchain, the so-called deployment code is executed by Ethereum's virtual machine. As it turns out, deployment code can do a lot more than merely deploying a contract. This paper identifies less-anticipated uses of contract deployment in Ethereum by analyzing the available blockchain data. In particular, we analyze the specifics of deployment code used beyond actually deploying a contract in a quantitative and qualitative manner. To this end, we identify code patterns in deployment code by distilling recurring code skeletons from all external transactions and internal messages that contain deployment code. Tracking the use of these patterns reveals a set of vulnerabilities in contracts targeted by skillfully crafted deployment code. We summarize the encountered exploitative cases of collateral use of deployment code and report respective quantities. Example scenarios illustrate the recent usage. Collateral use of deployment code starts to appear in the middle of 2018 and becomes dominant among contract creations in autumn of 2018. We intend to raise awareness about the less obvious uses of deployment code and its potential security issues.
Engineering Multi-agent Systems Anno 2025

Modern software-intensive systems are increasingly blending cyber, physical, and social elements, demanding higher degrees of autonomy and adaptability than ever before. In combination with the ever growing integration and scale of systems, and the inherent uncertainties modern systems face, the principles from MAS engineering remain particularly attractive for engineering systems in a wide variety of domains today. In this chapter, we reflect on the role and potential of MAS engineering on a selection of key facets that characterize modern software engineering practice. We focus at facets that we believe are important in relation to MAS engineering. Concretely, we look at agile development, Cloud and edge computing, distributed ledgers and blockchain, Cyber-Physical Systems and Internet-of-Things, and finally green computing. For each of these facets we highlight opportunities to EMAS engineering, but also the challenges these facets raise. We conclude with highlighting a number of ethical issues that the engineers of modern software-intensive systems and thus also MAS will face in the years to come.
A path planning method for a surface inspection system based on two-dimensional laser profile scanner

In this article, a method for two-dimensional scanning path planning based on robot is proposed. In this method, a section division algorithm based on neighborhood search method for scanning orientation determination is firstly produced. The scanning paths which meet constraints of the system are then generated. Finally, the experiment is carried out on robot-based scanning platform. The two-dimensional data from scanner and the robot position are combined to form three-dimensional surface data of measured workpiece. The experiment results verify the effectiveness of proposed method.
Multi-Objective Security Hardening Optimisation for Dynamic Networks

Hardening the dynamic networks is a very challenging task due to their complexity and dynamicity. Moreover, there may be multi-objectives to satisfy, while containing the solutions within the constraints (e.g., fixed budget, availability of countermeasures, performance degradation, non-patchable vulnerabilities, etc). In this paper, we propose a systematic approach to optimise the selection of the security hardening options for the dynamic networks given multiple constraints and objectives. To do so, we evaluate potential attack scenarios for a given time period, and then use a multi-objective optimisation based on Non-dominated Sorting Genetic Algorithm to find the optimal set of security hardening options. We measure the effectiveness of the options using various security metrics, which is demonstrated through experimental analysis. The results show that our approach can be applied to select the optimal set of security hardening options to be deployed for the dynamic networks given multiple objectives and constraints.
Safe and Efficient UAV Navigation Near an Airport

Much recent effort has been devoted to employing Unmanned Aerial Vehicles (UAVs) to implement airport-related tasks. However, a critical issue, collision avoidance, must be fully considered in this scenario. Herein, we study the efficient UAV navigation problem considering the safety issue near an airport. In detail, we first define the safe separation between the UAV and airplanes according to related aviation regulations. Thereafter, an effective tree-based scheme for navigating the UAV has been proposed to cope with the extra uncertainties induced by keeping the safe separation. An analytical derivation of the UAV's flying time is conducted to determine the optimal battery life. Extensive simulation is conducted to verify our proposed navigation scheme and the analytical derivation.
Translating the Pen and Paper Brainstorming Process into a Cognitive and Immersive System

Within this work, we introduce a digital sticky note tool to be used by analysts for a brainstorming session within a cognitive and immersive system (CAIS). This tool was setup to mimic and enhance the traditionally pen-and-paper process. By utilizing a digital interface, we allow for more feature-rich note taking including pictures and hyperlinks in addition to just text, as well as an increased amount of captured metadata about each created note. To achieve parity with the non-digital process, our interface allows for both individual usage via personal devices (e.g. tablets, laptops) as well as for coming together as a group and collaborating via a multi-modal interface, supporting commands through a mixture of voice and gestures.
Linear and nonlinear isotherm modeling of nitrate removal from aqueous solution by alternating current electrocoagulation

Aims: Nitrates in drinking water which may come from nitrogen fertilizers applied to crops are a potential health risk. The present study was conducted to investigate the application of alternating current (AC) in electrocoagulation (EC) process for nitrate removal from aqueous solution and linear and nonlinear isotherm modeling.Materials and Methods: The experiments were performed in pilot scale. The effective parameters including solution pH, the initial concentration of nitrate, total dissolved solids, contact time, and current density were studied. Results: The obtained results showed that with increasing solution pH from 3 to 10, the sinusoidal removal efficiency was observed. With increasing current density from 0.5 to 2 A/cm2, the nitrate removal efficiency was ascended from 32% to 58%. The optimum electrolyte was 2 g/L of NaCl. With increasing contact time and decreasing initial nitrate concentration, the nitrate removal efficiency was enhanced. In addition, the adsorption NO3by AC EC was preferably fitted with Langmuir isotherm. Conclusion: The results showed that the EC process could remove the nitrate to less than Iranian standard limit. The solution pH, current density, and contact time were showed the direct effect and initial concentration of nitrate depicted the reverse effect on nitrate removal efficiency.
Exploiting the meCUE Questionnaire to Enhance an Existing UX Evaluation Method Based on Mental Models

Several definitions of User eXperience (UX) are present in the literature, representing the references for different UX evaluation methods and tools. Among these methods and tools, the irMMs-based method and the meCUE questionnaire show different peculiarities and seem good candidates to speculate on their integration, aiming at improving applicability, completeness and effectiveness of UX evaluation activities. The goal of this research is indeed to integrate the irMMs-based method with the meCUE questionnaire in order to enhance the former by exploiting the stronger points of the latter. To achieve this, we analyze the lacks of the irMMs-based method and verify the meCUE questionnaire capabilities in overcoming these lacks. Once verified, we proceed with the integration by modifying the evaluation activities of the irMMs-based method. Finally, we perform a first validation of the enhanced release by comparing it to the old one in the field. Researchers can exploit the same procedure to integrate other methods and tools in order to improve them; on the other hand, industrial practitioners can use the enhanced release for their UX evaluations since it is ready to be applicable even by non-developers.
A Fusion Measurement Approach to Improve Quantum State Tomography Efficiency and Accuracy

Quantum state tomography (QST) is an important tool for estimating an unknown quantum state, which includes a measurement process and a reconstruction process. The state estimation error involves the measurement-induced (probability estimation) error in the measurement process and the calculation error in the reconstruction process. Via the mean-square error methods, we propose two fusion measurement schemes with multiple measurement devices (MMDs) to improve the efficiency and accuracy of quantum state measurement and QST by using information fusion theory. These two schemes are founded on the parallel synchronous measurements of MMDs and, therefore, can improve the efficiency of quantum state measurement and tomography. At the same time, by fusing measurement data from different measurement devices in optimal and suboptimal manners, the proposed multiple-measurement-device fusion measurement schemes achieve the improvement of quantum state measurement and tomography accuracy. Numerical simulations are presented to demonstrate the proposed method.
A Gamified Mobile-Based Virtual Reality Laboratory for Physics Education: Results of a Mixed Approach

Virtual reality has an important role in learning physics since it provides students a virtual environment that simulates real-world situations. Virtual laboratories are a new alternative for teaching, as they provide safe environments where the student can repeat a practice without risk of damaging the equipment. Gamification allows motivating students through the application of game-design elements. The objective of this paper was to perform a mixed evaluation of the influence of immersive virtual reality and gamification on the learning of physics in a mobile learning environment. The proposed application is a low-cost alternative for both schools and universities that do not have the infrastructure to create a physics laboratory and a tool for distance learning in physics. 86 students of university education were tested and we analyzed the information generated by the students.
Spoofing Attacks on Speaker Verification Systems Based Generated Voice using Genetic Algorithm

Speaker verification has played a significant role in authentication with the booming development of smartphones and intelligent terminals in recent years. However, most speaker verification systems directly store the users original voiceprint template data (or called acoustic features). In this paper, we reveal the insecurity and sensitiveness of voiceprint template data by carrying out spoofing attacks on speaker verification systems using genetic algorithm. Meanwhile, multiple generation models based on different genetic algorithms (standard genetic algorithm, multiple population genetic algorithm) are proposed, but also the effects of these generation models are compared. Moreover, experimental results on state-of-the-art text-independent speaker verification techniques (such as i-vector, GMM-UBM) clearly demonstrate that our generated attack voice with leaked voiceprint template data can completely imitate users and pass the speaker verification.