Reviewerly/exHarmony huggingface dataset:
The Method of Restoring Parameters of Mobile Agents in a Unified Dynamic Environment Considering Similarity Coefficients

We described the placing of the mobile agents in a dynamic environment. It formed a dynamic environment for a complex of dynamically changing mobile agents. We described a two-level system of connections at the global and local levels of interaction. Such a scheme allows you to support the survivability of a dynamic environment. We presented the model of placement of mobile agents in a dynamic environment, which forms the basis of the trajectory of interaction between mobile agents, enabling us to combine the dynamic environment into a unified dynamic environment. The proposed method for mobile agents parameters restoring in a unified dynamic environment, taking into account the similarity coefficients, allows restore 80% parameters of an inaccessible mobile agent. This indicates the high efficiency of the objects description in the form of a unified dynamic environment in order to maintain its integrity.
SEGANet: 3D object detection with shape-enhancement and geometry-aware network

3D object detection approaches from point clouds develop rapidly. However, the distribution of point clouds is unbalanced in the real scene, and thus the distant or occluded objects suffer from too few points to be perceived. This case damages the overall detection accuracy. Hence, we propose a novel two-stage 3D object detection framework, the Shape-Enhancement and Geometry-Aware Network (SEGANet), which aims to mitigate the negative impact of unbalanced point distribution for boosting detection performance. In stage 1, we first capture fine-grained structural knowledge with the assistance of point-wise features from voxels to generate proposals. And in stage 2, we construct a shape enhancement module to reconstruct complete surface points for objects within proposals, then establish an elaborate geometric relevance-aware Transformer module to aggregate high-correlated feature pairs of reconstructed-known parts and decode vital geometric relations of aggregated features. Thus, critical geometric clues are supplied for objects from the data and feature levels, achieving enhanced features for box refinement. Extensive experiments on KITTI and Waymo datasets show that SEGANet achieves low model complexity and excellent detection accuracy, especially leading the baseline method by 2.18% gain in overall detection accuracy and 1.8% gain in average accuracy of weakly sensing objects. This verifies that SEGANet effectively alleviates the impact of point imbalance to significantly boost detection performance.
A Survey of Blockchain for Video Integrity

Blockchain has become an important alternative in plenty of industries due to its features such as traceability, transparency and data integrity. Blockchain is not only present in the management of structured data-like names, timestamps, addresses and so on, but also in the management of unstructured data such as videos or images. In the present work, we focus on videos because nowadays, they are potentially exposed to be modified or altered from plenty of sources and platforms. However, we found that there are hardly any surveys or systematic literature reviews containing applications of both blockchain and integrity of videos. Thus, in this survey, we state a literature review for primary articles about the use of blockchain for video integrity to update and provide a better comprehension about this topic. As results, we encountered Ethereum and internet of vehicles as the largest underlying blockchain and field of application, respectively. At the end, we explain our findings about blockchains for video integrity and why it is an emerging topic.
HERO vs Zombie: Destroying Zombie Guests in Virtual Machine Environments

Virtual servers are now standard in data centres. Multiple virtual machines (guests) are consolidated on much fewer hosts on-site or on “the cloud”, Thus saving most of the hosting costs. Virtual servers serve most of our computational needs. However, virtual machines consume no physical space. Thus abandoned servers are often unnoticed. The system administrators do not delete the servers. Sometimes the administrators do not know the servers are not in use. (Some servers often “become” unused as business processes changes, and the System administrators are not informed when the last user no longer uses the server) These servers are known as “zombie” machines. “Zombie” machines waste resources and (as they are left unattended and unpatched) pose a cyber security risk. We present HERO (Host Environment Resource Optimization). HERO is a novel tool to optimize resource use and security. HERO uses multiple tests and machine learning approaches to assist system administrators in identifying and removing “zombie” machines.
Comparing Goal-Oriented Analysis Techniques: A Controlled Experiment

Background: Goal models are usually used during the early phases of requirement elicitation, since they help to understand the motivations underlying the system to be developed. Goal-oriented analysis techniques help analysts reason and make decisions regarding the analyzed goal model. Aims: In this paper, we present an empirical evaluation of two goal-oriented analysis techniques: i) VeGAn, which we proposed in a previous work, and which follows a value-driven approach and a fuzzy logic approach and ii) GRL-Quant, which follows a value-neutral approach and a quantitative approach. Method: We conducted an experiment with a population of 64 Computer Science undergraduate students. The participants were asked to analyze a goal model with one of the techniques and to answer a questionnaire to assess their perceptions. The techniques were compared with respect to the accuracy of goal model element prioritization, the participants’ prioritization time, and their perceptions of the quality of the analysis results (perceived satisfaction), ease of use, usefulness, and intention to use. Results: The results of the experiment show that both techniques are very similar since no significant differences could be found in most of the variables analyzed. However, the participants perceived the results of VeGAn more satisfactorily than those of GRL-Quant, although the prioritization accuracy of GRL-Quant was better for one particular system. Conclusions: This paper provides new insights have emerged from this study, and also opportunities to improve both techniques. The experiment provides preliminary results on the usefulness of both goal-oriented analysis techniques, but further research is required in order to strengthen these results.
Acknowledging Implementation Trade-Offs When Developing with Units of Measurement

Physical quantities expressed as units of measurement (UoM) are used regularly in scientific and engineering applications. The loss of the Mars climate orbiter, attributed to a confusion between the metric and imperial unit systems, popularised the disastrous consequences of incorrectly handling measurement values. We aim to classify the many solutions that have been proposed by looking at their capabilities and computational overheads. We assume an overall view, starting with a quantity aware Software Model, and then looking at the various approaches which allow these annotations to be transferred into code. Through a formal definition of both dimension checking and UoM conversion we are able to categorise the various options with regards to the stage at which they can be undertaken, their useability, and their coverage of potential errors.
A certain Bruhat order on doubly substochastic matrices

AbstractDenote by ωn the convex polytope of n×n doubly substochastic matrices and by Ωn the convex polytope of n×n doubly stochastic matrices. We generalize the Bruhat order for permutation matrices and doubly stochastic matrices to the subpermutation matrices and doubly substochastic matrices, respectively. Moreover we study the Bruhat shadow of a subpermutation matrix and the Bruhat faces of ωn. The relations between the Bruhat faces in ωn and those in Ωn are also given.COMMUNICATED BY: R. PereiraKeywords: Bruhat orderBruhat shadowBruhat facessubpermutation matricesdoubly substochastic matrices2010 Mathematics Subject Classifications: 05B2006A0715B5152B05 AcknowledgmentsThe author is very grateful to the anonymous referees for pointing out the errors in the original manuscript and giving valuable suggestions. The author also wants to thank Professor Jiuyu Fan and Lei Cao for helpful discussions.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is supported by the National Natural Science Foundation of China (No. 11601233); the Natural Science Foundation of Jiangsu Province (No. BK20160708).
FAIR-Enabling Resources - Identifier Services

Here are some identifier services listed as such by FIP Wizard, a free-to-signup online tool to guide a user in creating and publishing a machine-actionable FAIR Implementation Profile (FIP): Old IGSN International Generic Sample Number before integration with DataCite SDN CDI PID | SeaDataNet CDI PID SeaDataNet Common Data Persistent Identifier U.S. Department of Energy Office of Scientific and Technical Information (OSTI) Data ID Service Through the DOE Data ID Service, OSTI assigns...
Agile Insight ‐ Gating Alternatives for Agile Projects

Abstract Current technical oversight approaches (e.g., Stage‐Gate reviews) are not agile – their expectations are not aligned with agile development cadences, and they are not adequately responsive to continuous unpredictable change. These mismatches lead to the (incorrect) assertion that agile projects don't need technical oversight, and to more accurate concerns that current gate reviews do not effectively provide insight into gaps and risk on agile projects. Large complex agile efforts need a light weight, interactive approach to technical oversight that provides insight in the form of good predictive feedback to agile projects with minimal burden of labor on the project and the reviewers. Fixed expectations of how oversight is done, and non‐agile oversight approaches written into contracts and processes impede the evolution of gating for agile projects. This paper explores ways to provide insight and responsive forward looking actionable guidance for agile projects in the context of government and defense programs. It proposes a general oversight approach that produces minimal drag and disruption and keeps pace with agile product development.
An Introduction to Semantic Threat Analysis for Systems Security Engineering

Abstract The objectives of this paper are (a) to motivate the adoption of semantic graphical models of threat relations and countermeasures in the design and operation of cyber‐physical systems (CPS), and (b) to raise awareness of the various benefits which systems security engineers (SSEs) stand to gain by adopting such practices. Specifically, we propose that a Semantic Threat Analysis (STA) can endow SSEs with a comprehensive, extensible, machine‐readable, and logically inferable model of system features. An STA shaped to the specific architecture and security requirements of a CPS environment can support the identification and visualization of system interdependencies and process flows among network, computing, mechanical, security, and access control components. The proposed STA process presupposes a team‐oriented systems engineering approach employing a combination of subject matter experts (SMEs) and ontologists who can bring their respective expertise together to bear on the task.
Systems Engineering Integration and Test Challenges due to Security Measures in a Cloud‐Based System

Abstract Cloud based systems have become popular with company's Chief Information Officers and Chief Technical Officers due to their ability to support a wide range of Web based applications and services including; scalability to allow users to increase/decrease their cloud footprint real time based on demand, load balancing to optimize computing performance, and failover which allows processing/memory assets to be reassigned real time when a failure is detected or predicted on the current processing assets. In addition, organizations can lower their Information Technology (IT) costs by deferring their infrastructure maintenance/costs to the Cloud Service Provider (CSP). However, Cloud‐based security threats and mitigations are well documented in literature, and address multiple client side, network, and cloud side (service/application and data) vulnerabilities. Defined mitigations include the use of access control, encryption, key management, digital signatures, and intrusion detection/prevention systems to yield a secure cloud‐based system. Implementing these security measures adds significant system functionality to the already complex cloud‐based system that must be assessed by the system architect. The additional requirements and development must be managed by the systems engineering team, and the increased integration and test must be addressed by the systems engineering integration and test lead. This paper will highlight the scope growth realized when a system interfaces into the cloud, relative to equivalent non‐cloud based systems. The added scope will be shown to include the development, integration and test of security related hardware and software configuration items, development of significant integrated test equipment/test vectors to verify the security functionality over a wide range of conditions, multiple cooperative systems/software led activities to analyze and test software throughout its development, and the system accreditation efforts to get authorization to tie into the cloud. With this information, the systems engineering leads will have a better understanding of the challenges involved with integrating and testing a cloud‐based system and can then properly plan and budget for this activity. This paper will focus specifically on a public cloud based implementation. Hybrid and private cloud implementations will not be addressed herein.
Practical Experience Applying Feature‐based Product Line Engineering in a DevOps Environment: Achieving the Best of Both Worlds

Abstract Systems and Software Product Line Engineering (PLE) is an engineering discipline to produce and maintain a family of similar products in an efficient manner. It has long been known that managing a product portfolio as a single entity, as opposed to a multitude of separate products, can bring substantial improvements in schedule, cost, and quality. DevOps is an engineering discipline, practiced within an infrastructure of test and deployment automation, that seeks to minimize the time that a change to a product is made, and the product is built, validated, deployed, and made available to the end users. Many organizations find themselves willing to employ both disciplines – that is, to employ DevOps for products in a product line. This paper shows how that can be done, relates a case where it was done, and reports on the substantial benefits that were realized.
Establishing Quality Metrics for Systems Engineering Process

Abstract Software engineering companies such as Motorola have clearly defined, robust processes to ensure overall process and system quality. Using Motorola's approach as a baseline, the authors established a process to determine system complexity to support the Systems Engineering &amp; Integration (SE&amp;I) lifecycle. To quantify complexity, the authors established a process including structural complexity (focused on system form), dynamic complexity (focused on system function), and social complexity (focused on identified stakeholders), the sum of which define complexity points. The authors further expanded the process by defining key metrics and parameters to support evaluation throughout the SE&amp;I phases from concept to operationalization. This process, which utilizes fundamentals of Agile Software Development, allows systems engineers (SEs) and program managers (PMs) to quantitatively compare SE&amp;I phases, systems, or projects of different sizes and dollar values to categorize, assess, forecast lifecycle costs, and performance to improve performance with customer satisfaction in mind. Through a satellite system example, the authors present the metrics to support associated analysis through the SE&amp;I lifecycle.
Automatic Text Classification of PDF Documents using NLP Techniques

Abstract One of the regular activities performed by engineers during the design and development of the technical systems is to determine which sentences in a PDF specification document represent a requirement, functional architecture, design solution, variability, or other types of systems engineering (SE) data. Extracting such data from these PDF documents and transferring it into system model elements is still performed manually, requires high effort, and is error prone. Hereby, automatic extraction and classification of such SE data has a great potential, but it is still relatively scarce and a challenging task for engineers working with large PDF specification documents. One solution is to follow a suitable writing formulation which provide an immediate and easy way to classify and analyze the PDF documents. However, such formulations are not always followed strictly. As part of our work towards adopting Artificial Intelligence (AI) for Model‐Based Systems Engineering (MBSE), we have been researching the data extraction and data classification topics from PDF files in order to transfer it to system models elements. In this paper, we present the early status of a solution based on AI that uses Natural Language Processing (NLP) techniques to label the SE data existing in PDF files, extract them, and classify them into predefined classes.
Keynote talk: The most innovative methods are sometimes the simplest

Keynote presented by Juan Pablo Alperin at the 13th annual EBSI-SIS Information Science Symposium on April 28, 2021. Thank you very much for this invitation. Before I begin, let me begin by acknowledging that I am speaking to you from the traditional unceded territories of the Coast Salish people, including the xʷməθkʷəy̓əm (Musqueam), Skwxwú7mesh (Squamish), and səl̓ilwətaɁɬ təməxʷ (Tsleil-Waututh) Nations. I am incredibly fortunate to have the opportunity to live, work, and...
Three questions with…Lina!

Our lab is growing! In our Three Questions series, we’re profiling each of our members and the amazing work they’re doing. Today, we’re highlighting Lina Marie Harper: a master’s student in Information Science at the University of Ottawa, a researcher at the ScholCommLab, and the proud owner of a “chiweenie” (part Dachshund, part Chihuahua). In this post, she tells us about the joys of open data, graduate school, true crime, and more. Lina and...
Predicting aging transition using Echo state network

It is generally known that in a mixture of coupled active and inactive nonlinear oscillators, the entire system may stop oscillating and become inactive if the fraction of active oscillators is reduced to a critical value. This emerging phenomenon, called the "aging transition," can be analytically predicted from the view point of cluster synchronization. One can question whether a model-free, data-driven framework based on neural networks could be used to foretell when such a system will cease oscillation. Here, we demonstrate how a straightforward ESN with trained output weights can accurately forecast both the temporal evaluation and the onset of collapse in coupled paradigmatic limit-cycle oscillators. In particular, we have demonstrated that an ESN can identify the critical fraction of inactive oscillators in a large all-to-all, small-world, and scale-free network when it is trained only with two nodes (one active and the other inactive) selected from three different pre-collapse regimes. We further demonstrate that ESN can anticipate aging transition of the network when trained with the mean-field dynamics of active and inactive oscillators.
52.2: Research on Industrial Application and Standards of Ultra HD Video

Ultra high definition(UHD) industrial applications play a huge role, which can improve production efficiency, enhance product quality, and reduce resource waste. In the future, the industrial application of UHD video will be more extensive, but UHD is a long way to go to achieve total popularity. Therefore, there is an urgent need to develop a unified and open standard to promote the industrialization of UHD video. In this paper, we summarize the key technical aspects of UHD video industrial applications from the requirements of the UHD video industry. The standardization needs of industrial application areas are analyzed. According to the common problems and constraints in UHD video application, the standard system of UHD video industrial application is proposed, which contains five aspects: basic commonality, testing and certification, business presentation, auxiliary management, and field application. Finally, the shortcomings of UHD video industrial applications are pointed out, and possible solutions are given.
Superdense coding for V-shaped channel and cylindrical geometry

Abstract We have examined the possibility of quantum dense coding for the V-shaped channel and cylindrical geometry of plasmonic waveguides by assuming certain initial states at different dipole-dipole distances. It is found that the dense coding capacity initially decreases and then gradually increases until it becomes steady ( χ = 1) at later time. We also revealed the optimal time valid for super-dense coding regarding each initial state. It is worth noting that dense coding capacity is valid for all other states for a time less than optimal time ( t &lt; τ o ) except for pure state. The estimated optimal time for a V-shaped channel is prominent due to greater β -factor accomplishing it as a prosperous geometry for Superdense coding. The greater optimal time for V-shaped channel entitles this geometry a benchmark for the practical applications of quantum information technology.
Reversible Data Hiding With Pattern Adaptive Prediction

Abstract In the area of reversible data hiding (RDH), one of the most popular techniques is prediction-error expansion (PEE), which hides data in the prediction errors with well-preserved image fidelity. The key to a successful PEE-based RDH implementation usually lies in prediction algorithms with high accuracy. Existing PEE-based RDH works often employ one single prediction algorithm, which is usually globally optimized, but with less consideration of the pixel distribution characteristics within local neighborhoods. In this manuscript, the technique of pattern adaptive prediction is proposed for pixel estimation according to the type of local binary pattern (LBP), which is obtained from the pixel’s eight neighborhood. Theoretically speaking, pattern-based predictors can be designed for each and every LBP patterns to create multiple prediction-error histograms (PEHs). However, the process of performance optimization with multiple PEHs requires extremely heavy computing power. To speed up the optimization process, LBP patterns are classified into various groups based on the degree of histogram concentration. Experiments demonstrate that the prediction accuracy is obviously improved and the image fidelity is well preserved.
A Blockchain-Based Public Key Infrastructure For IoT-Based Healthcare Systems

Abstract Secure exchange of data among the various stake holders of healthcare systems is of prime importance. As the size of the healthcare networks grew, several variants of Public Key Infrastructures (PKIs) were proposed as a means to achieve reliable authentication, confidentiality, non-repudiation, etc. The most prevalent approach to PKI has been the use of Certificate Authorities (CAs). But, events like the breach of the CA DigiNotar, and the ensuing fake certificates for Google, among other noteworthy high-profile domains, has cast doubts on the reliability of a CA, and therefore on PKIs modelled as CAs too. In this paper, we propose a new approach to a healthcare PKI modelled on a blockchain, incorporating Elliptic Curve Cryptographic methods for secure key generations.