Reviewerly/exHarmony huggingface dataset:
Library U-Turn into Virtual Service to Support Clients Amidst COVID19 Global Lockdown in South Africa

The study sought to investigate a framework for Library virtual service as the main alternative modus operandi amidst COVID19 global lockdown encounter in South Africa. It is a common fact that COVID19 has brought the entire world to a standstill with most of the services and businesses put on-hold as every country forces its citizens to remain in their households under lockdown in a state of emergency. This paper uses literature to present the arguement that a virtual library service is the main alternative mode of operation that libraries may use to continue rendering their services to their clients. The study discovered that the virtual library is the main alternative in this case where libraries want to help to defeat the coronavirus outbreak and to avoid it from affecting their services to their clients. The study provides a framework for virtual library services that is believed any kind of library may reshape to suit their own environmental needs. Library may in a ways successfully render their services with or without covid 19 pandemic lockdown. It is believed that this may also enable clients to enjoy library services even when under covid 19 lockdown in their respective countries.
Geometric Construction of Video Stereo Grid Space

The construction of digital twin cities is a current research hotspot. Video data are one of the important aspects of digital twin cities, and their digital modeling is one of the important foundations of its construction. For this reason, the construction and digital analysis of video data space has become an urgent problem to be solved. After in-depth research, this study found that the existing video space construction methods have three shortcomings: first, the problem of high requirements for objective conditions or low accuracy; second, the lack of easy and efficient mapping algorithms from 2D video pixel coordinates to 3D; and third, the lack of efficient correlation mechanisms between video space and external geographic information, making it difficult to integrate video space with external information, and thus prevent a more effective analysis. In view of the above problems, this paper proposes a video stereo grid geometric space construction method based on GeoSOT-3D stereo grid coding and a camera imaging model to form a video stereo grid space model. Finally, targeted experiments of video stereo grid space geometry construction were conducted to analyze the experimental results before and after optimization and compare the variance size to verify the feasibility and effectiveness of the model.
Constitutions vs. COVID-19: CrowdLaw as an Alternative in Crisis and Recovery

Coronavirus has activated the main constitutional mechanisms set in place to face exceptional circumstances in all countries that can be considered consolidated democracies. Constitutional systems make it possible for constituent powers to limit fundamental rights that are the cornerstone for the full exercise of citizenship in a democracy. Thus, for example, lockdowns and limitations on gatherings, de iure and de facto , limit or eliminate the right to assembly. Exception—constitutional instruments, that also allow for the transfer of parliamentary functions to the Executive power, are mostly designed, and many times thought to be exclusively used in extreme circumstances: wars or natural disasters that have an immediate impact on millions of people (causing death, the loss of the home or massive displacement, etc.). In these cases, it is assumed that parliaments and citizens must enter survival mode, and because of that, there is no reason to think that any type of citizen participation is possible. However, despite the gravity of COVID-19, the situation does not conform to the pattern I have just described. Most citizens, surely those that tend to participate in the ordinary democratic process, have been able to adapt their lives to the confines of their own homes thanks to civic responsibility and technology: work, education, socialization, shopping, etc. If this is so, why has the decision-making process not been able to adapt to the COVID pandemic? Furthermore, if citizen input is essential to control the situation and social distancing is a must, why is technology not the cornerstone of citizen's data recollection? This work analyzes the existing constitutional framework and the main governmental measures (norms and actions) adopted, in order to detect in which stages (out of the five basic policy and law-making stages) citizen participation could have been integrated, and how CrowdLaw might have helped to make participation more effective, and if CrowdLaw can help palliate the constitutional impact resulting from a pandemic, particularly in regard to the exercise of citizen participation, and in improving the quality and effectiveness of any measure that has been adopted. I argue that constitutional norms are compatible with CrowdLaw because they do not rule out the activation of CrowdLaw procedures neither in normal nor in exceptional circumstances.
Balancing Privacy Risk and Benefit in Service Selection for Multiprovision Cloud Service Composition

The popularity of cloud computing has fueled the growth in multiprovision cloud service composition (MPCSC), where each cloud service provider (CSP) can fulfill multiple tasks, i.e., offer multiple services, simultaneously. In the MPCSC, users would rather disclose some private data for more benefits (e.g., personalized services). However, the more private data is released, the more serious the privacy risk faced by users. In particular, the multiservice provision characteristic of MPCSC further exacerbates the privacy risk. Therefore, how to balance the privacy risk and benefit in service selection for MPCSC is a challenging research problem. In this paper, firstly we explore the service selection problem of balancing privacy risk and benefit in MPCSC (SSBM), then we propose an improved Kuhn–Munkres (KM) algorithm solution to the SSBM problem. Furthermore, we conduct a series of simulation experiments to evaluate the proposed approach. The experimental results show that the proposed approach is both efficient and effective for solving the SSBM problem.
Distance-Preserving Embedding Adaptive Bipartite Graph Multi-View Learning with Application to Multi-Label Classification

Graph-based multi-view learning has attracted much attention due to the efficacy of fusing the information from different views. However, most of them exhibit high computational complexity. We propose an anchor-based bipartite graph embedding approach to accelerate the learning process. Specifically, different from existing anchor-based methods where anchors are obtained from key samples by clustering or weighted averaging strategies, in this article, the anchors are learned in a principled fashion which aims at constructing a distance-preserving embedding for each view from samples to their representations, whose elements are the weights of the edges linking corresponding samples and anchors. In addition, the consistency among different views can be explored by imposing a low-rank constraint on the concatenated embedding representations. We further design a concise yet effective feature collinearity guided feature selection scheme to learn tight multi-label classifiers. The objective function is optimized in an alternating optimization fashion. Both theoretical analysis and experimental results on different multi-label image datasets verify the effectiveness and efficiency of the proposed method.
Resin moulded Electro Optic Termination Assembly – design, procedure, testing and qualification

This paper discusses the design, procedure, testing and qualification of Sub-sea Resin-moulded Electro-optic Termination Assembly (SRETA) undertaken on Nexans make umbilical of model number DO-478. In general the electro optic termination assembly can be built for any umbilical cable for the commercial oil and gas extraction at a sub-sea depth rating up to 3000m mean sea level (MSL). The Medium voltage (MV) electrical power conductors and the Single Mode (SM) fibre optic cables in the resin moulded assembly will be terminated and distributed to respective systems at sub-sea. The complete termination assembly was designed and developed at NIOT for the specific requirement of umbilical cable. The Single mode (SM) fibre optic cable was spliced using an arc splicing machine and was encapsulated within a pressure tolerant enclosure made of Aluminium metal. The high voltage electrical conductors were spliced and insulated with suitable rated air tight heat shrink sleeves called boot sleeves. The whole of the termination arrangement was filled with a PDM 69T two part polyurethane resin. The details on the termination procedure and assembly are explained in the sections under. The integrity of the termination undertaken was tested through an Optical Time Domain Reflectometer (OTDR) for fibre optic cables and Insulation testing system for the electrical joints. The functionality of the termination assembly was tested and qualified up to an operating depth of 3200 m MSL during NIOT underwater mining system sea trials undertaken at Bay of Bengal (BoB) during 2020.
Improved design of ePub reader based on web

There are many popular e-book formats on the market, ePub3.0 is very prominent among them, and many software and hardware manufacturers have adjusted their products to be compatible with the ePub format. ePub3.0 has the advantages of being cross-platform, perfectly supporting scripts and supporting the interaction of multimedia contents such as sound and video. Based on the development trend of mobile phone readers and the characteristics of Web App with low development cost, fast iteration cycle, and excellent cross-platform, a web-based ePub e-book reader system is designed. This system will realize the integration of the local service of the Web App mobile terminal and the operation mode of the traditional web application. This system uses Html 5 and Vue 3.0 for client writing, adopts B/S architecture as the entire project architecture, and Nginx provides static resource guarantee for the server. In the early stage of development, according to the current situation at home and abroad, the demand analysis was carried out, and the current development trend of mobile web readers was understood. Finally, a functional test was carried out to test the usability, reliability and practicality of the project.
An Authentication System For Online Question Paper Delivery using Visual Cryptography

Visual Cryptography (VC) can be used for sharing a secret image. The image is distributed among the valid participants in the form of transparencies that are random noise-like images. When the required number of participants superimpose their transparencies, the secret image gets revealed without using any computational power. In this paper, we have proposed an authentication system which uses VC for encrypting the passwords required for downloading and opening the question papers from the server. Two transparencies are created for encrypting two passwords. These transparencies are sent to the internal and external supervisor on their email. To reveal the passwords, both the examiners have to download their transparency and give it as an input to a simple software on a computer, which overlaps them and reveals the passwords. The passwords can also be revealed by physically printing the transparencies and overlapping them. The results are tested using MATLAB.
Hierarchical latent variables structure for topic aware multi-turn conversation

Hierarchical structures have emerged as a powerful framework for response generation, which can generate fluent responses in multi-turn conversation. However, the generated responses are often generic and bland. Some researchers have adopted latent variables to improve the diversity of responses, but they can not make full use of the information from multi-turn background, leading to meaningless replies with irrelevant topics. In order to fully utilize the background information for generating diverse and informative responses, we propose a Variational Hierarchical Conversation RNNs model with Topic aware latent variables (VHCR-T). The model contains three levels of latent variables: the global level latent variable to represent background information, the topic level latent variable to capture topic-related information, and the sentence level latent variable to increase the response diversity. When modeling the topic information, we design two different topic level latent variables to maintain the dialog coherence and role preference, and to enhance the context sensitiveness, respectively. Experimental results on Cornell Movie Dialog and Ubuntu Dialog Corpus show that our model outperforms the state-of-the-art models for multi-turn conversation generation in terms of diversity and informativeness, verifying the effectiveness of our VHCR-T model.
An MDE-based methodology for closed-world integrity constraint checking in the semantic web

Ontology-based data-centric systems support open-world reasoning. Therefore, for these systems, Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) are not suitable for expressing integrity constraints based on the closed-world assumption. Thus, the requirement of integrating the open-world assumption of OWL/SWRL with closed-world integrity constraint checking is inevitable. SPARQL, recommended by World Wide Web (W3C), is a query language for RDF graphs, and many research studies have shown that it is a perfect candidate for closed-world constraint checking for ontology-based data-centric applications. In this regard, many research studies have been performed to transform integrity constraints into SPARQL queries where some studies have shown the limitations of partial expressivity of knowledge bases while performing the indirect transformations, whereas others are limited to a platform-specific implementation. To address these issues, this paper presents a flexible and formal methodology that employs Model-Driven Engineering (MDE) to model closed-world integrity constraints for open-world reasoning. The proposed approach offers semantic validation of data by expressing integrity constraints at both the model level and the code level. Moreover, straightforward transformations from OWL/SWRL to SPARQL can be performed. Finally, the methodology is demonstrated via a real-world case study of water observations data.
Digital Reconciliation: A Social Media Reconciliation Model (SMRC)

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsJuma KasadhaJuma Kasadha, is a Post Doctoral Fellow in the Department of Media and Communication at City University of Hong Kong Hong Kong, SAR China. E-mail: jkasadha2-c@my.cityu.edu.hk
To distinguish and clarify the concepts of "technique", "technology", "technical environment"

The article clarifies the concepts of technique and technology and introduces the concept of "technical environment". The author, based on his research, points to two lines of technology development: one uses the effects of the first nature and technical art, the second uses the effects of the second nature (collective activity and sociality) and technical art. Engineering is formed in the first line, technology in the second. The question is raised about the essence of ideas about the technical environment, which N. Berdyaev and M. Heidegger began to discuss. The author problematizes the concept of nature and tries to show that under certain conditions, analyzing the second nature, it is also possible to talk about laws. В Discussing the concept of "technical environment", he turns to the analysis of two cases. The first presents the reconstruction of the formation of the ancient Egyptian pyramids, the second presents the development of electrical engineering. In both cases, we are talking about the formation of technology and the technical environment under the influence of not so much practical needs as the pressure of semiotic and cultural ideas. The author concludes that the space in which the main hypostases of technology converge and interact (technology as engineering and technology, as a technoprime, as an environment, as a field of activity) is due to the peculiarities of the first and second nature, while the development is the essence of technology, and it goes both under the influence of external factors and internal. One of the important conditions for the development of technology is the formation of meaning, which is associated with natural science research, engineering, technology, as well as social needs and requirements.
Generating image description aiding blind people interpretation

In this paper, we present the model developed to transform images into audibly recognizable sentences (or) captions useful for blinds. We have used Deep learning and the Beam Search technique to summarize the image contents. Image summarization is a powerful, yet challenging problem that opens up many applications for machine learning like a screen reader or scenery describer for the blind which can explain the contents of an image using Text to Speech (TTS), Automatic content filtering on the web etc. This project explores a deep learning solution to identify the objects, their relationship and summarize the events on a given image.
Trucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis

Algorithms provide powerful tools for detecting and dissecting human bias and error. Here, we develop machine learning methods to to analyze how humans err in a particular high-stakes task: image interpretation. We leverage a unique dataset of 16,135,392 human predictions of whether a neighborhood voted for Donald Trump or Joe Biden in the 2020 US election, based on a Google Street View image. We show that by training a machine learning estimator of the Bayes optimal decision for each image, we can provide an actionable decomposition of human error into bias, variance, and noise terms, and further identify specific features (like pickup trucks) which lead humans astray. Our methods can be applied to ensure that human-in-the-loop decision-making is accurate and fair and are also applicable to black-box algorithmic systems.
Complete classification of negacyclic codes of length 3ps over 𝔽pm + u𝔽pm + u2𝔽pm

In this paper, we classify completely the negacyclic codes of length [Formula: see text] over [Formula: see text] when [Formula: see text] by using six-cyclotomic codes.
A centralized matching scheme to solve the role-partner allocation problem in collaborative networks

In the current constantly changing business and economic environment, partners (i.e., individuals and/or enterprises) create Collaborative Networks to join efforts and undertake new projects together, thus allowing them to face business opportunities that would not be possible if attempted by them individually. In this situation, an assignment problem arises, since these projects involve the performance of a group of tasks or processes (named roles) that have to be distributed among the partners. Specifically, this problem, called the Role-Partner Allocation (RPA) problem in Collaborative Networks is a two-sided matching problem with lower and upper quotas on the partner’s side, and incomplete and partially ordered preference lists on both sides. A matching problem, and thus also the RPA problem, should be solved by a centralized matching scheme. However, allocations in Collaborative Networks continue to be mainly created by ad hoc arrangements, which takes a long time and is hard work. Looking for a reliable and faster way of distributing roles among partners in a Collaborative Network, the existing centralized matching schemes expected to solve the RPA problem (e.g., DA algorithm, SOSM, CA-QL algorithm, and EADAM) are studied in this paper, concluding that none of them obtain a matching that properly meets the requirement of the RPA problem. Therefore, a new centralized matching scheme to solve the RPA problem is proposed, discussed and exemplified.
A real-time safe path planning system for cooperative robots

<ns3:p>Background: A cooperative robot is a robot requested to co-work with humans efficiently and safely in an environment with flexible arrangements. Safe path planning is a crucial issue which must be resolved during human-robot cooperation. In this paper, we present a safe path planning system that could plan the manipulation path in real-time based on the environmental changes and guarantees safety when the robot interacts with the environment and humans.</ns3:p><ns3:p> Methods: In this system, we first build a real-time obstacle Octomap from the environment RGB-D (red green blue-depth) images, which can effectively differentiate the robot from other obstacles in the environment and eliminate the robots influence during the map building. And then, we adopt the rapidly exploring random trees-Connect method to plan the safe path in the Octomap. When the planning path is obstructed by the dynamic objects, the system will re-plan the new safe path based on the changed Octomap.</ns3:p><ns3:p> Results: The experimental results show that our system can effectively avoid obstacles in a dynamic environment and safely reach the manipulation destination.</ns3:p><ns3:p> Conclusions: We propose a real-time safe path planning system for cooperative robots, which can guarantee the safety of manipulation.</ns3:p>
Statistical Estimation of Strain Using Spatial Correlation Functions

Ex-situ estimation of strains from deformed micrographs is not possible as there are no persistent features which can be tracked. Two point spatial statistics enable the rigorous quantification of spatial patterns in heterogeneous media. In this paper, we propose a novel method for estimating strains directly from dissimilar micrographs using a continuum mechanics approach. Rather than operating directly on images from sequential frames, as is done in digital image correlation, we operate on different microstructure realizations. This is made possible by comparing the spatial autocorrelation maps of deformed and undeformed micrographs rather than direct comparison of images. A Bayesian framework is proposed for quantifying uncertainty. We first illustrate the efficacy of this method on speckle pattern images from digital image correlation experiments. Then, we demonstrate that the method is capable of operating on dissimilar micrographs using deformed synthetic binary microstructures. Finally, we present a case study on polycrystalline additively manufactured 316L deformed via tension. The proposed method works well and we discuss implications and limitations of the presented work.
Analysis on the Application of Internet Multimedia Technology in College Music Education

In order to improve the effect of college music teaching, this paper combines Internet multimedia technology to construct a college music intelligent teaching system and uses the DASH multihypothesis framework to improve the transmission effect of Internet multimedia. Moreover, this paper manages the teaching resources generated in the process of music teaching and collects these resources into the library. The dynamic addition and editing of classifications are realized in the background, which is convenient for easy expansion and flexible adjustment of classifications. In addition, this paper combines the actual needs of music teaching in colleges and universities to construct the system function and get the system frame structure and work flow. Finally, this paper verifies the system of this paper in conjunction with experiments. The analysis shows that Internet multimedia technology has good effects in college music education, can effectively handle various resources of college music teaching, and can effectively improve the efficiency of college music education.