Reviewerly/exHarmony huggingface dataset:
Cloud Computing for Secure Services in E-Government Architecture

E-government tries to take advantage of new technology to provide better service to citizens. Some of the main challenges in the face of E-government are query processing high volume applications, data center management, data security and E-government services. Cloud computing can be a good option for responding to these issues and fixing them, and guarantee the realization of E-government, with maximum efficiency and maximum safety. In this paper, the authors propose a novel architecture for E-government by using Cloud computing architecture which can largely increase the integrity and security service in E-government, and also increase users' confidence in the system and may lead to increased participation.
A Novel Pixel Merging-Based Lossless Recovery Algorithm for Basic Matrix VSS

Lossless recovery in visual secret share (VSS) is very meaningful. In this paper, a novel lossless recovery algorithm for the basic matrix VSS is proposed. The secret image is reconstructed losslessly by using simple exclusive XOR operation and merging pixel. The algorithm not only can apply to the VSS without pixel expansion but also can apply to VSS with pixel expansion. The condition of lossless recovery of a VSS is given by analyzing the XOR all columns of basic matrixes. Simulations are conducted to evaluate the efficiency of the proposed scheme.
A New Approach to Construct (K, N) Threshold Secret Sharing Schemes Based on Finite Field Extension

With increase in use of internet there is need to keep passwords, secret keys, important information secret. One way to do this is encryption. But it also need key which should be kept secure. Sometimes key is secure. But what will happens if the key is lost, forgotten etc. This problem can be solved using secret sharing. Instead of sharing whole secret, it is divided into pieces and distributed to finite set of pieces and some subset of pieces called access structure of scheme, which can recover secret. Here we propose a new way to construct threshold secret sharing schemes based on finite field extension using Blakley's secret sharing as a base. It is useful in many cryptographic applications and security. Because of finite fields the size of numbers stays within a specified range, doesn't matter how many operations we apply on number.
Intake

OpflowVolume 46, Issue 8 p. 2-2 Departments Intake First published: 04 August 2020 https://doi.org/10.1002/opfl.1404Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume46, Issue8August 2020Pages 2-2 RelatedInformation
Triplet Decoupling Network for Masked Face Verification

Face verification has been widely applied to identity authentication in many areas. However, due to the mask information embedded into the facial feature representation, existing face verification systems generally fail to identify the faces covered by masks during the COVID-19 coronavirus epidemic period. To address this issue, we propose a new triplet decoupling network (TDN) for the challenging masked face verification. Different from existing works, our proposed TDN seeks to remove the mask information included in extracted facial features by feature decoupling, such that more discriminative facial feature representations can be obtained for masked face verification. In addition, a new triplet similarity margin loss (TSM) is designed to enlarge the margin between the intra-class similarity and the inter-class similarity of faces. Experimental results show that the proposed method significantly outperforms the other state-of-the-art methods on masked face datasets, which demonstrates the effectiveness of our proposed method.
Russian Team

Work in the Russian Federation took place during the entire duration of the project, with pedagogical work in primary and secondary education spreading over two school years between summer 2016 and spring 2017. The team undertook both rounds of data collection.
Practical works as a component of the geography course (on the example of grade 11th - standard level)

The purpose of the article is to determine the main problems in implementation and methodological support of the practical component in geography lessons in 11th grade for further substantiation of the authors’ system of didactic support of practical works in 11th grade in geography (standard level). Main material. The article presents the analysis of methodological support for the implementation of practical works, theoretical aspects of their implementation, identified problems, violating principles of scientificity and consistency in studying specific topics of the cross-cutting course of geography in grades 6-11th. The analysis of the topics of practical works introduced in different grades has showed problems in the sequence and deepening of knowledge, especially in such topics of 11th grade as "Topography", "Atmosphere and Earth System", "Economy of Ukraine in the international division of labor". The methodological support for practical works is diverse and offered by all leading publishers of educational literature, but the structure and approaches to the formulation of content are radically different. Almost no attention is paid to modern methods of mastering geographical information. Based on the analysis of theoretical and practical aspects of works in 11th grade (standard level), the authors’ structure and content of such workshops have been proposed, the main differences are the variability of time and individualization of students' work. Conclusions and further research. The implementation of practical works creates favorable conditions for the development of students’ mental abilities and the creative approach to the teachers’ work. The current program in geography is mostly inconsistent with the principles of modern education, including scientificity, formation of the scientific picture of the world. However, methodological support for practical works does not allow us to implement the principles of individualization of educational process, time saving and prevention of students’ overload. The offered methodical developments for practical works in 11th grade allow us to implement the specified principles qualitatively. Further research should be aimed at scientific substantiation of methodological requirements for practical works and reduction of the cross-cutting system in them introduced in secondary education, to the logical structure on the principles of increasing scientificity, thoroughness, complexity, diversity, consistency.
Non-Markovian Dynamics of Macroscopic Quantum Systems in Interaction with Non-equilibrium Environments

We study the dynamics of a macroscopic superconducting qubit coupled to two independent non-stationary reservoirs by using time-dependent perturbation theory. We show that an equilibrium environment surpasses the coherent evolution of the macroscopic qubit completely. When the qubit couples to two different reservoirs, exemplifying a non-equilibrium environment, the short-time dynamics is affected by the interference between two reservoirs, implying the non-additivity of effects of two reservoirs. The non-additivity can be traced back to a non-Markovian effect, even though two reservoirs are independently assumed to be Markovian. Explicitly, the non-equilibrium environment intensifies both coherent and incoherent parts of the evolution. Therefore, the macroscopic qubit would evolve more coherently but at the price of a shorter decoherence time.
Co-quasiordered residuated systems: An introduction

In this paper, we introduce and discuss a concept of co-quasiordered residuated relational systems. The setting of this research is Bishop’s constructive mathematics — a mathematics based on the Intuitionisic logic and particular principle-philosophical orientation of this attitude. Moreover, we introduce the concept of co-filters in such relational system. Additionally, some of the fundamentals properties of these substructures we have been shown.
Generic compact representation through visual-semantic ambiguity removal

Zero-Shot Hashing (ZSH) aims to learn compact binary codes that can preserve semantic contents of the images from unseen categories. Conventional approaches project visual features to a semantic space that is shared by both seen and unseen categories. However, we observe that such a one-way paradigm suffers from the visual-semantic ambiguity problem. Namely, the semantic concepts (e.g. attributes) cannot explicitly correspond to visual patterns, and vice versa. Such a problem can lead to a huge variance in the visual features for each attribute. In this paper, we investigate how to remove such semantic ambiguity based on the observed visual appearances. In particular, we propose (1) a novel latent attribute space to mitigate the gap between visual appearances and semantic expressions; (2) a dual-graph regularised embedding algorithm called Visual-Semantic Ambiguity Removal (VSAR) that can simultaneously extract the shared components between visual and semantic information and mutually align the data distribution based on the intrinsic local structures of both spaces; (3) a new zero-shot hashing framework that can deal with both instance-level and category-level tasks. We validate our method on four popular benchmarks. Extensive experiments demonstrate that our proposed approach significantly performs the state-of-the-art methods.
An Experience Report on Second Workshop on Emerging Software Engineering Education

This experience report presents the summary, outcomes and experiences of the 2nd Workshop on Emerging Software Engineering Education (WESEE), co-located with Innovations in Software Engineering Conference (ISEC 2019) which was held on 14th February 2019 at College of Engineering, Pune (India). WESEE is an activity-oriented workshop and consists of an expert talk, two hands-on activities, and an open discussion session. We have collected a variety of data from the participants while conducting the two activities namely, 'wall of ideas' and 'design thinking'. We analyze the data gathered in the form of sticky notes, responses to worksheets, documented ideas, and feedback sheets. The data helped us to determine whether the workshop was successful and simultaneously we can plan for the next edition of the workshop by incorporating the feedback.
Practical Computation with Linear Groups Over Infinite Domains

We survey recent progress in computing with finitely generated linear groups over infinite fields, describing the mathematical background of a methodology applied to design practical algorithms for these groups. Implementations of the algorithms have been used to perform extensive computer experiments.
Universal Forgery and Multiple Forgeries of MergeMAC and Generalized Constructions

This article presents universal forgery and multiple forgeries against MergeMAC that has been recently proposed to fit scenarios where bandwidth is limited and where strict time constraints apply. MergeMAC divides an input message into two parts, $$m\Vert \tilde{m}$$ , and its tag is computed by $$\mathcal {F}( \mathcal {P}_1(m) \oplus \mathcal {P}_2(\tilde{m}) )$$ , where $$\mathcal {P}_1$$ and $$\mathcal {P}_2$$ are PRFs and $$\mathcal {F}$$ is a public function. The tag size is 64 bits. The designers claim 64-bit security and mention that it might be insecure to accept beyond-birthday-bound queries. This paper presents the first third-party analysis of MergeMAC. Firstly, it is shown that limiting the number of queries up to the birthday bound is crucial, because a generic universal forgery against CBC-like MAC can be applied. Afterwards another attack is presented that works with very few queries, 3 queries and $$2^{58.6}$$ computations of $$\mathcal {F}$$ , by applying a preimage attack against weak $$\mathcal {F}$$ . This breaks the claimed security. The analysis is then generalized to a MergeMAC variant where $$\mathcal {F}$$ is replaced with a one-way function $$\mathcal {H}$$ . Finally, multiple forgeries are discussed in which the attacker's goal is to improve the ratio of the number of queries to the number of forged tags. It is shown that the number of achievable forgeries is quadratic in the number of queries in the sense of existential forgery, and this is tight when messages have a particular structure. For universal forgery, tags for 3q arbitrary chosen messages can be obtained by making 5q queries.
An Experimental Approach for Information Extraction in Multi-party Dialogue Discourse

In this paper, we address the task of information extraction for transcript meetings. Meeting documents are not usually well structured and are lacking formatting and punctuations. In addition, the information are distributed over multiple sentences. We experimentally investigate the usefulness of numerical statistics and topic modelling methods on a real dataset containing multi-part dialogue texts. Such information extraction can be used for different tasks, of which we consider two: contrasting thematically related but distinct meetings from each other, and contrasting meetings involving the same participants from those involving other. In addition to demonstrating the difference between counting and topic modeling results, we also evaluate our experiments with respect to the gold standards provided for the dataset.
New character of a laser channel for squeezed chaotic state

We in this paper report a new character of laser channel, namely, during squeezed chaotic state evolving in the laser channel. Its density operator keeps form-invariant, only two newly found typical parameters evolve with time in a well-regulated way, so they can describe the features of this physical process well. The typical parameter is comparable to the variance of normal distribution.
Research on Transformer Fault Diagnosis Based on Online Sequential Extreme Learning Machine

Background: Transformer is one of the most important pivot equipment in an electric system which undertakes major responsibility. Therefore, it is very important to identify the fault of the transformer accurately and transformer fault diagnosis technology becomes one topic with great research value. Methods: In this paper, after analyzing the shortcomings of traditional methods, we have proposed a transformer fault diagnosis method based on Online Sequential Extreme Learning Machine (OS-ELM) and dissolved gas-in-oil analysis. This method has better precision than some commonly used methods at present. Furthermore, OS-ELM is more efficient than ELM. In addition, we analyze the effect of different parameter selection on the performance of the model by contrast experiments. Results: The experimental result shows that OS-ELM has certain promotion in precision than some traditional methods and can obviously improve the speed of training than ELM. Besides, it is known that the number of neurons in the hidden layer and the size of dataset have a great effect on the model. Conclusion: The transformer fault diagnosis method based on OS-ELM can effectively identify the faults and more efficient than ELM.
An Exploration of Multimedia Supports for Diverse Learners During Core Math Instruction

In the present study, mobile technology was leveraged as a learning tool for core math instruction during a whole number multiplication and division unit. The researchers redesigned paper–pencil wo...
Occlusion-aware pedestrian detection

Failure in pedestrian detection systems can be extremely crucial, specifically in driverless driving. In this paper, failures in pedestrian detectors are refined by re-evaluating the results of state of the art pedestrian detection systems, via a fully convolutional neural network. The network is trained on a number of datasets which include a custom designed occluded pedestrian dataset to address the problem of occlusion. Results show that when applying the proposed network, detectors can not only maintain their state of the art performance, but they even decrease average false positives rate per image, especially in the case where pedestrians are occluded.
Reply to “Reply to [Comments on “Classification of solar radiation zones and general models for estimating the daily global solar radiation on horizontal surfaces in China” [Energy Convers. Manage. (2017) 10.043] [Energy Convers. Manage. (2018) 05.051], by Liu et al.”

This study presents a discussion about the presented responses at “Reply to [Comments on “Classification of solar radiation zones and general models for estimating the daily global solar radiation on horizontal surfaces in China” [Energy Conversion and Management, 2017.10.043.] [Energy Convers. and Manage., (2018) 05.051], proposed by Liu et al. [1]”. In their letter they presented responses to Gouda and Yuan’s comments. The illustration and responses to their replies were presented in the present work.
SVR-AMA: An Asynchronous Alternating Minimization Algorithm With Variance Reduction for Model Predictive Control Applications

This paper focuses on the design of an asynchronous dual solver suitable for model predictive control (MPC) applications. The proposed solver relies on a state-of-the-art variance reduction (VR) scheme, previously used in the context of proximal stochastic gradient methods (Prox-SVRG) and on the alternating minimization algorithm (AMA). The resultant algorithm, a stochastic AMA with VR (SVR-AMA), shows geometric convergence (in the expectation) to a suboptimal solution of the MPC problem and, compared to other state-of-the-art dual asynchronous algorithms, allows one to tune the probability of the asynchronous updates to improve the quality of the estimates. Two novel accelerated versions of the Prox-SVRG (and, by duality, of SVR-AMA) are also provided. We apply the proposed algorithm to a specific class of splitting methods, that is, the decomposition along the length of the prediction horizon. Numerical results on the longitudinal control problem of an Airbus passenger aircraft show the benefits that we can gain in terms of computation time when using our proposed solver with an adaptive probability distribution.
Teacher Professional Development

Education plays a vital role in human capital formation in a knowledge economy. The situation of education sector in Pakistan has not been encouraging due to multiple reasons. High skilled workforce has become a basic need to meet the challenges of contemporary era of competitiveness and efficiency. National Education Policies have realization that teachers have to play a pivotal role in delivering quality education at all levels. Quality and effectiveness of school education depend on quality of properly trained teachers. Pre and in-service training of secondary level teachers in formal and/or non-formal systems are keys to equip students with necessary knowledge before entering to higher grades. This book presents a comparative analysis of formal and non-formal streams and findings of survey study of teachers, tutors, student, staff and experts engaged in teacher training programs in both systems. It concludes that both systems are equally good, interdependent and complimentary if implemented and are availed in letter and spirit. Trained and professional teachers can lead to create a vibrant generation of high skilled work force in Pakistan.
Effective Facial Expression Recognition System Based on Hybrid Classification Technique

In our daily life, facial expression recognition has possible functions in various sectors but still it is not understand, because the absence of efficient expression identification methods. Many methods are used to develop the effectiveness of the identification through indicating issues in face detection and extraction aspects in identification expressions. In the first phase, the noise is eliminating from the image by using of preprocessing techniques and to obtain the quality image in order to decrease the computational complexity. The following phase is feature extraction phase. In this phase, we are extracting related features like eyes, mouth and nose. The shape feature of eye part can be extracted by active appearance model (AAM). The texture feature of nose and mouth can be extracted using grey-level co-occurrence matrix (GLCM). Then in the final phase, we have to categorise a facial expression for this categorisation process by introducing an adaptive genetic fuzzy classifier (AGFC) and neural network (NN). Finally, score level fusion of this two classification result will be done to obtain the face emotions.
Data Security Threats Sources

Driven by the difficulty in achieving complete security with technical tools, business investigators are looking into organizational and behavioral issues that could help make systems more secure. This chapter looks at the security of systems from the organizational perspective. Specifically, this study attempts to identify if different organizations have different predisposition to particular type(s) of security threat sources. Using publicly available security breach data from a privacy rights clearinghouse to investigate which organizational characteristics predisposes an institution to an external or internal threat source, it was concluded that as size of organization and the number of its valuable documents increase by one unit, the organization's probability of suffering an internal attacks decrease. Furthermore, when executive members have a business degree rather than information-security-related degrees, the likelihood of suffering an internal attack increases. Also, the probability of an organization suffering an internal or external attack is not based on its industry type.
PortraitGAN for flexible portrait manipulation

Previous methods have dealt with discrete manipulation of facial attributes such as smile, sad, angry, surprise etc, out of canonical expressions and they are not scalable, operating in single modality. In this paper, we propose a novel framework that supports continuous edits and multi-modality portrait manipulation using adversarial learning. Specifically, we adapt cycle-consistency into the conditional setting by leveraging additional facial landmarks information. This has two effects: first cycle mapping induces bidirectional manipulation and identity preserving; second pairing samples from different modalities can thus be utilized. To ensure high-quality synthesis, we adopt texture-loss that enforces texture consistency and multi-level adversarial supervision that facilitates gradient flow. Quantitative and qualitative experiments show the effectiveness of our framework in performing flexible and multi-modality portrait manipulation with photo-realistic effects.
Semantic Query Language for Temporal Genealogical Trees

Computers play a crucial role in modern ancestry management, they are used to collect, store, analyse, sort and display genealogical data. However, current applications do not take into account the kinship structure of a natural language. In this paper we propose a new domain-specific language KISP, based on a formalisation of the English’s kinship system, for accessing and querying traditional genealogical trees. KISP is a dynamically typed LISP-like programming language with a rich set of features, such as kinship term reduction and temporal information expression. Our solution provides a user with a coherent genealogical framework that allows for a natural navigation over any traditional family tree.