Reviewerly/exHarmony huggingface dataset:
An Analogical Study of Hyperledger Fabric and Ethereum

Hyperledger Fabric is one of the most popular blockchain framework which is hosted by the Linux Foundation. As a basis for the development of applications or solutions with a modular architecture, Hyperledger Fabric offers plug - and - play components such as consensus and membership services. Ethereum is a decentralized platform running smart contracts, applications running exactly as programmed without any possibility of downtime, censorship, fraud or interference from third parties. These apps are based on a custom built blockchain, an enormously powerful global shared infrastructure that can change value and represent property ownership. This study deals with comparison of Hyperledger Fabric and Ethereum platforms while covering various factors like architecture, performance, use cases, ease of algorithm etc.
Package-Level stability evaluation of object-oriented systems

Software stability is an important object-oriented design characteristic that contributes to the maintainability quality attribute. Software stability quantifies a given systems sensitivity to change between different versions. Stable software tends to reduce the maintenance effort. Assessing software stability during the object-oriented design phase is one of the measures to obtain maintainable software. To determine software stability, there are several metrics at the architecture, system and class levels, but few studies have investigated stability at the package level. In this paper, we propose a new package stability metrics (PSM) based on the notion of change between package contents, intra-package connections and inter-package connections. We validate the PSM theoretically and empirically. The theoretical validation is based on a study of the mathematical properties of the metrics. The empirical validation is carried out using five open source software programs and we also present a comparison with comparable existing stability metrics packages. For the empirical validation, we perform correlation analysis, principal component analysis and prediction analysis. Correlation analysis shows that our proposed metrics provides a better indication of package stability than the existing stability metrics and they are negatively correlated with the maintenance effort. Principal component analysis shows that the proposed metrics captures new dimensions of package stability and helps to increase the maintenance prediction accuracy. We found there was a negative correlation between our metric and maintenance effort. We also found a positive correlation between the existing package stability metrics which are based on changes in lines of code and class names.
Bounding Algorithms for Persistent Monitoring of Targets using Unmanned Vehicles

Persistent monitoring of targets in civil and military applications require a team of Unmanned Vehicles to visit the targets repeatedly over time. The vehicles visit the targets and transmit the collected information to the base station for further processing. The frequency of monitoring any given target is intuitively specified by its target revisit time, i.e., the maximum time elapsed between any two successive visits to the target. The persistent monitoring problem considered in this article is as follows: Given m vehicles and k allowed visits to n targets, find an optimal route for each vehicle such that each target is visited at least once, each target is visited at most by one vehicle and the maximum revisit time over all the targets is minimized. This problem is a generalization of the minmax, multiple Traveling Salesman Problem and is NP-Hard. Bounds on the optimal revisit times are provided for the case when the number of visits is large. Optimal revisit times are also developed for the single vehicle problem with tighter bounds. These results are practically useful in reducing the computational burden as one only needs to solve two problems for any large number of visits to find a good feasible solution.
An Effective Trajectory Planning for a Material Handling Robot Using PSO Algorithm

This paper utilizes the potentiality of PSO algorithm to design and optimize the trajectory for a material handling robot. This approach is based on the behavior of fish schooling and birds flocking. Layout of the Institute machine shop is selected as an environment for determining the trajectory length. Total fifteen numbers of obstacles (machines) are acknowledged during this analysis. The selected approach not only delivers curtail path length but also generates a traffic-free trajectory. The material handling robot is not colliding with any machines during movement. The programming codes for the selected approach are written, compiled, and run through a software: MATLAB.
Characterizing the Social Interactions in the Artificial Bee Colony Algorithm

Computational swarm intelligence consists of multiple artificial simple agents exchanging information while exploring a search space. Despite a rich literature in the field, with works improving old approaches and proposing new ones, the mechanism by which complex behavior emerges in these systems is still not well understood. This literature gap hinders the researchers' ability to deal with known problems in swarms intelligence such as premature convergence, and the balance of coordination and diversity among agents. Recent advances in the literature, however, have proposed to study these systems via the network that emerges from the social interactions within the swarm (i.e., the interaction network). In our work, we propose a definition of the interaction network for the Artificial Bee Colony (ABC) algorithm. With our approach, we captured striking idiosyncrasies of the algorithm. We uncovered the different patterns of social interactions that emerge from each type of bee, revealing the importance of the bees variations throughout the iterations of the algorithm. We found that ABC exhibits a dynamic information flow through the use of different bees but lacks continuous coordination between the agents.
How to Run an Evaluation Task

This chapter provides a general guideline for researchers who are planning to run a shared evaluation task for the first time, with a primary focus on simple ad hoc Information Retrieval (IR). That is, it is assumed that we have a static target document collection and a set of test topics (i.e., search requests), where participating systems are required to produce a ranked list of documents for each topic. The chapter provides a step-by-step description of what a task organiser team is expected to do. Section 1 discusses how to define the evaluation task; Sect. 2 how to publicise it and why it is important. Section 3 describes how to design and build test collections, as well as how inter-assessor agreement can be quantified. Section 4 explains how the results submitted by participants can be evaluated; examples of tools for computing evaluation measures and conducting statistical significance tests are provided. Finally, Sect. 5 discusses how the fruits of running the task should be shared to the research community, how progress should be monitored, and how we may be able to improve the task design for the next round. N.B.: A prerequisite to running a successful task is that you have a good team of organisers who can collaborate effectively. Each team member should be well-motivated and committed to running the task. They should respond to emails in a timely manner and should be able to meet deadlines. Organisers should be well-organised!
Polypropylene/nanoclay Composite: A solution to refrigerated vehicles

Refrigerated vehicles are insulated vehicles used in the transportation of foods or drugs to prolong shell life. The invention of the refrigeration system, led to the invention of refrigerated vehicles (RVs). Conventional aluminium or steel sheet in use for refrigerated vehicles insulation panel causes high energy consumption, carbon emission, and also reduces the longevity of insulation material in the sandwiched panel. Low thermal conductive polymer based and lightweight materials will reduce energy consumption, cost, carbon emission, and prolong the longevity of insulating material. In this study polypropylene (PP), maleic-anhydride-grafted-polypropylene (MAPP), and nanoclay were melt intercalated in a rheomixer in the proportion of 100/0/0, 95/4/1, 93/4/3, 91/4/5, 89/4/7 and 86/4/10 respectively. Test results revealed that tensile strength and stiffness improved with low clay contents. Thermal conductivity analysis showed that composites with high proportion of clay have high resistance to heat. PP98MAPP4NC3 composite was optimal, and could be used as a better replacement to the conventional sheets.
Towards Gamified Alcohol Use Disorder Therapy in Virtual Reality: A Preliminary Usability Study

The combination of virtual reality (VR) and gamification opens up new vistas for innovative forms of therapy for alcohol use disorder (AUD) and have enormous potential to improve traditional therapy methods. In this paper, three gamified and one non-gamified AUD therapy applications for VR are introduced and evaluated. The games are based on two behavioral therapy methods, which are Cue Exposure Therapy (CET) and Approach Avoidance Training (AAT). The games are realized in the context of a virtual supermarket, which is considered as a relapse-risky environment. The aim is to help AUD patients practice avoiding alcohol first in a VR-based simulation and later in a real supermarket. In preparation for a long-term clinical study, a usability study was conducted with 13 healthy participants. The results show that the VR game was enjoyed, increased the motivation, and fewer errors were made than in the comparable non-gamified application.
Can direct address affect user engagement with chatbots embodied in physical spaces?

This paper investigates how direct addressing the user, such as using a vocative, affects the user experience with chatbots embodied in an interactive space context. Direct addressing increases user engagement in presentations and in performing arts, and we investigated its use in an artwork where visitors ask questions to three chatbots using interactive text projected on a table surface. The study comprised two versions of the system; the first was neutral while the second employed direct address in the answers from the chatbots. We logged 1188 interaction sessions with the exhibit and conducted observational studies and semi-structured interviews with 92 visitors in the wild. The analysis of the visitor's interactions showed that direct address had almost no direct effect on user engagement regarding what kind of questions were asked. The field study brought richer perspectives on how visitors interact with chatbots and their reported experiences with the two versions. Based on our findings we provide general recommendations for the design of chatbots in public spaces.
Game Theory and Cyber Defense

The extensive use of information technology systems in military sector has changed the face of the battlefield and the nature of war. A growing body of literature argues that the game-theoretic reasoning is well-suited to many problems in cyber defense. A game between a defender and an attacker trying to gain access to computers remotely is a typical strategic interaction in this domain. This chapter discusses how game theory can be applied in cyberspace. It offers a comprehensive review of literature on the application of game theory in this area. It proposes and illustrates a new game formulation combining game theory and other techniques. The chapter highlights the recognized challenges associated with the applicability of game theory in the cyber world. It discusses how the game-theoretic formalism can be adapted to obtain sound solutions in a reasonable time.
New Results on Modular Inversion Hidden Number Problem and Inversive Congruential Generator

The Modular Inversion Hidden Number Problem (MIHNP), introduced by Boneh, Halevi and Howgrave-Graham in Asiacrypt 2001, is briefly described as follows: Let $${\mathrm {MSB}}_{\delta }(z)$$ refer to the $$\delta $$ most significant bits of z. Given many samples $$\left( t_{i}, {\mathrm {MSB}}_{\delta }((\alpha + t_{i})^{-1} \bmod {p})\right) $$ for random $$t_i \in \mathbb {Z}_p$$ , the goal is to recover the hidden number $$\alpha \in \mathbb {Z}_p$$ . MIHNP is an important class of Hidden Number Problem. In this paper, we revisit the Coppersmith technique for solving a class of modular polynomial equations, which is respectively derived from the recovering problem of the hidden number $$\alpha $$ in MIHNP. For any positive integer constant d, let integer $$n=d^{3+o(1)}$$ . Given a sufficiently large modulus p, $$n+1$$ samples of MIHNP, we present a heuristic algorithm to recover the hidden number $$\alpha $$ with a probability close to 1 when $$\delta /\log _2 p>\frac{1}{d\,+\,1}+o(\frac{1}{d})$$ . The overall time complexity of attack is polynomial in $$\log _2 p$$ , where the complexity of the LLL algorithm grows as $$d^{\mathcal {O}(d)}$$ and the complexity of the Gröbner basis computation grows as $$(2d)^{\mathcal {O}(n^2)}$$ . When $$d> 2$$ , this asymptotic bound outperforms $$\delta /\log _2 p>\frac{1}{3}$$ which is the asymptotic bound proposed by Boneh, Halevi and Howgrave-Graham in Asiacrypt 2001. It is the first time that a better bound for solving MIHNP is given, which implies that the conjecture that MIHNP is hard whenever $$\delta /\log _2 p<\frac{1}{3}$$ is broken. Moreover, we also get the best result for attacking the Inversive Congruential Generator (ICG) up to now.
Region-Based Nonparametric Model for Interactive Image Segmentation

In this paper, we present a novel framework for interactive segmentation problems.It integrates a nonparametric model into the Conditional Random Field (CRF) framework, which can effectively combine high-level features with low-level features to represent image information.In the nonparametric model, multiple region layers are used to estimate data likelihood terms to overcome the bad regions generated by unsupervised methods.The likelihood values of each layer are calculated separately to reduce the computational cost.In addition, we analyze that the pixel layer has little effect on data estimation, so we remove it to further reduce the complexity of the algorithm.We employ the label consistency between pixels and their corresponding regions in smooth term estimation, which can be regard as a higher order potential for pixels.The data term and the smooth term are then performed together in Conditional Random Fields (CRFs) as a fine-tuning of the results.Experimental results show that the proposed method can segment images efficiently and accurately with fewer user inputs.
Opportunistic live migration of virtual machines

Summary Live migrations of virtual machines are required in cloud data centers in various contexts such as evacuating a host machine for maintenance, balancing the workloads on host machines, optimizing physical resource utilization, and meeting the custom demands of the user applications. Virtual machine migrations can, however, be costly in terms of both resources consumed for the migration as well as in terms of service level agreement (SLA) violations during the migration window. The cost is determined by many factors and they, in turn, are impacted by WHEN the migration happens during the lifetime of the virtual machine. Empirical studies show that if we have a window in which the migration is to be done (proactive rather than reactive where no such window exists), we can do it by carefully choosing the starting point within the window so that the SLA violation is minimum. In this paper, we propose a model to migrate virtual machines opportunistically to minimize the SLA violations. The idea is to find the time instants, called opportunities , at which, if the migration starts, the number and extent of SLA violations are minimal. Our experiments show that the migrations time savings with opportunistic migrations are up to 25%.
LogLInc: LoG Queries of Linked Open Data Investigator for Cube Design

By avoiding the 'data not invented here' syndrome (NIH) (Data not invented here (NIH) syndrome is a mindset that consists in focusing solely on using data created inside the walls of a business ( https://urlz.fr/9Yo9 )), companies realized the benefit of including external sources in their data cube. In this context, Linked Open Data (LOD) is a promising external source that may contain valuable data and query-logs materializing the exploration of data by end users. Paradoxically, the dataset of this external source is structured whereas logs are "ugly", and in the case, they are turned into rich structured data, they will contribute to building valuable data cubes. In this paper, we claim that the NIH syndrome must be also considered for query-logs. As a consequence, we propose an approach that investigates the particularity of SPARQL query logs performed on the LOD and augmented by the LOD to discover multidimensional patterns when leveraging and enriching a data cube. To show the effectiveness of our approach, different scenarios are proposed and evaluated using DBpedia.
Fast Continuous Structural Similarity Patch Based Arbitrary Style Transfer

Style transfer is using a pair of content and style images to synthesize a stylized image which has both the structure of the content image and the style of style image. Existing optimization-based methods are limited in their performance. Some works using a feed-forward network allow arbitrary style transfer but cannot reflect the style. In this paper, we present a fast continuous structural similarity patch based arbitrary style transfer. Firstly, we introduce the structural similarity index (SSIM) to compute the similarity between all of the content and style patches for obtaining their similarity. Then a local style patch choosing procedure is applied to maximize the utilization of all style patches and make the swapped style patch continuous matching with respect to the spatial location of style at the same time. Finally, we apply an efficient trained feed-forward inverse network to obtain the final stylized image. We use more than 80,000 natural images and 120,000 style images to train that feed-forward inverse network. The results show that our method is able to transfer arbitrary style with consistency, and the result comparison stage is made to show the effectiveness and high-quality of our stylized images.
Planning Unmanned Aerial System (UAS) Takeoff Trajectories To Minimize Third-Party Risk

Large unmanned aerial systems (UAS) pose risks when they fly over inhabited areas. This paper presents a motion planning approach to minimize these risks by determining risk optimal motions for a fixed-wing UAS. This approach estimates the crash probability distribution (CPD) of a UAS as a function of its current state in the configuration space, which allows for planning risk optimal UAS maneuvers. This approach also includes several new extensions to the RRT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">#</sup> algorithm for optimal motion planning, including a method for using an initial solution within RRT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">#</sup> and a new method for locally computing the connection radius which RRT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">#</sup> uses to connect configurations together. A new method for handling threedimensional (3D) Dubins curves for a fixed-wing UAS is also proposed in order to handle the risk objective considered. The approach is tested on an example takeoff trajectory planning problem in which a UAS must climb to a set cruising altitude at a predetermined location and heading; the results illustrate several trade-offs between risk and flight time that make use of how the UAS's CPD varies with its current state.
Learning Motion Planning Policies in Uncertain Environments through Repeated Task Executions

The ability to navigate uncertain environments from a start to a goal location is a necessity in many applications. While there are many reactive algorithms for online replanning, there has not been much investigation in leveraging past executions of the same navigation task to improve future executions. In this work, we first formalize this problem by introducing the Learned Reactive Planning Problem (LRPP). Second, we propose a method to capture these past executions and from that determine a motion policy to handle obstacles that the robot has seen before. Third, we show from our experiments that using this policy can significantly reduce the execution cost over just using reactive algorithms.
Evolution of the PAN Lab on Digital Text Forensics

PAN is a networking initiative for digital text forensics, where researchers and practitioners study technologies for text analysis with regard to originality, authorship, and trustworthiness. The practical importance of such technologies is obvious for law enforcement, cyber-securityCyber-security , and marketing, yet the general public needs to be aware of their capabilities as well to make informed decisions about them. This is particularly true since almost all of these technologies are still in their infancy, and active research is required to push them forward. Hence PAN focuses on the evaluation of selected tasks from the digital text forensics in order to develop large-scale, standardized benchmarks, and to assess the state of the art. In this chapter we present the evolution of three shared tasks: plagiarism detection, author identification, and author profiling.
Research and Design of Theme Image Crawler Based on Difference Hash Algorithm

Abstract For the problem of high repetition rate of image resources collected by general theme crawler, a theme image crawler system is designed to reduce image similarity. The main contents of the design include the main function modules of the crawler, the workflow of the system and the implementation method of the key modules. The difference hash algorithm is used to solve the problem of image similarity effectively. Combined with Web text cosine correlation algorithm and link PageRank algorithm, the paper comprehensively evaluates the relevance between Web resources and topics. The experimental results show that the subject image crawler can effectively reduce the similarity of the collected images and improve the efficiency of crawler image resources acquisition.
Graduated Fidelity Lattices for Motion Planning under Uncertainty

In this work we present a state lattice based approach for motion planning in mobile robotics. Sensing and motion uncertainty are managed at planning time to obtain safe and optimal paths. To do this reliably, our approach estimates the probability of collision taking into account the robot shape and the uncertainty in heading. We also introduce a novel graduated fidelity approach and a multi-resolution heuristic which adapt to the obstacles in the map, improving the planning efficiency while maintaining its performance. Results for different environments, shapes and motion models are reported, including experiments with real robots.