Reviewerly/exHarmony huggingface dataset:
Hybrid Quantum-Classical Heuristic to Solve Large-Scale Integer Linear Programs

We present a method that integrates any quantum algorithm capable of finding solutions to integer linear programs into the branch-and-price algorithm, which is regularly used to solve large-scale integer linear programs with a specific structure. The role of the quantum algorithm is to find integer solutions to subproblems appearing in branch-and-price. Obtaining optimal or near-optimal integer solutions to these subproblems can increase the quality of solutions and reduce the depth and branching factor of the branch-and-price algorithm and hence reduce the overall running time. We investigate the viability of the approach by considering the tail assignment problem and the quantum approximate optimization algorithm (QAOA). Here, the master problem is the optimization problem set partitioning or its decision version exact cover and can be expressed as finding the ground state of an Ising spin glass Hamiltonian. For exact cover, our numerical results indicate that the required algorithm depth decreases with the number of feasible solutions for a given success probability of finding a feasible solution. For set partitioning, on the other hand, we find that for a given success probability of finding the optimal solution, the required algorithm depth can increase with the number of feasible solutions if the Hamiltonian is balanced poorly, which in the worst case is exponential in the problem size. We therefore address the significance of properly balancing the objective and constraint parts of the Hamiltonian. We empirically find that the approach is viable with QAOA if polynomial algorithm depth can be realized on quantum devices.
On-line Education as a New Industry and Market: Changing the Thematic Agenda, Demand Parameters and Leadership Principles

This paper is devoted to the topical issues of online education development trends in Russia taking into account changing external conditions and the demands of different groups. The survey was based on a comparative analysis of the Russian universities' online courses presented on educational platforms to identify the leaders in this area and the most popular courses, on the results of a survey of the professional engineering community to form an audience request for the format and principles of education. The results allowed us to identify the leading universities in the field of online education, the coefficient of demand for individual courses (to determine the demanded thematic agenda) and formed the basis of the author's position on the principles of online education leadership.
Keyword Guessing Attacks on Some Proxy Re-Encryption with Keyword Search Schemes

Public key encryption with keyword search (PEKS) is a practical cryptographic paradigm that enables one to search for the encrypted data without compromising the security of the original data. It provides a promising solution to the encrypted data retrieval issue in public key cryptosystems. As a combination of PEKS and proxy re-encryption (PRE), proxy re-encryption with keyword search (PRES) allows a semi-trusted proxy to simultaneously re-encrypt and search a delegator’s encrypted data. So far, several PRES schemes have been proposed in the literature. However, most of these schemes did not consider the keyword guessing attack. In this paper, we analyze the security of some PRES schemes and demonstrate that they are vulnerable to the keyword guessing attack. The presented attacks show that a malicious proxy can reveal the keyword encoded in any keyword trapdoor generated by these PRES schemes.
Is it civic duty? An exploratory study of factors that influenced the public's decision to download the NHS COVID-19 app

Background/Aims The UK Government piloted a COVID-19 digital contact tracing smartphone app on the Isle of Wight, England, in June 2020 in attempt to contain the spread of the virus. This study aimed to investigate the factors that affected the decision to download the app among individuals in the Isle of Wight. Methods Online questionnaires were distributed over social media to the sample population. Quantitative data were analysed, both descriptively and using a Chi-square or Fisher's test. Qualitative data were analysed through content analysis. Results Overall, 74.2% of participants downloaded the COVID-19 app, citing compliance, protection and fighting the pandemic or returning to normal as their main reasons. There was a significant negative correlation between having concerns about the app and downloading the app (P=&lt;0.01). Concerns were split into the three themes of privacy or data security concerns, technology issues and increased complacency. There was a significant negative correlation between being in a COVID-19 high-risk group and downloading the app (P=0.042). Conclusions Concerns about the COVID-19 app, particularly in terms of its security, significantly affected whether participants were likely to download it. The results provide insight into factors influencing mass public health behaviours and can form the basis for future research into app-based interventions.
Overview of Blockchain Technology in urrent Times

Blockchain is a distributed transaction and data management technology that was developed initially for the Bitcoin cryptocurrency. Since 2008 when this idea was coined, the interest in Blockchain technology has been on the rise due to its core qualities that provide data integrity, security and anonymity without third party organizations in control of the transactions, and therefore it creates interesting research areas, especially from the view of technical challenges and limitations thus the reason for the interest in Blockchain. The objective is to understand the current research topics, challenges and future scope regarding Blockchain technology.
Generating Sea Surface Object Image Using Image-to-Image Translation

Abstract Sea objects training, the conditional adversarial networks require a large number of images to solve image-to-image translation problems. In the case of insufficient samples, it leads to network overfitting and poor training results. This project proposes a conditional adversarial generative model that retains the original background features in the absence of paired samples. The goal of this project is to reduce the deviation of the corresponding output from the original input. Firstly, the object images of different categories are labeled with color masks. Second, sea objects are generated randomly in the original background using model of this project. Finally, the generated results of this approach are compared with other approaches. The experimental results show that, compared with results from other conditional adversarial generative models, the generated object images using model of this project have the characteristics of richer texture and clearer structure.
Analyzing Co-occurrence Networks of Emojis on Twitter

Emojis have become an integral part of digital communication in recent years. They promote the expression of emotions and ideas through visual icons of people, animals, and symbols. Twitter provides a platform for discussion and commentary in real time with a diverse and global audience, making it a good candidate for studying the usage of emoji across various topics. In this paper, 296260 tweets containing emojis have been used to create undirected-weighted co-occurrence networks of emojis with respect to dating, music, US politics, Olympic Games, epidemics, in addition to a control group. For each co-occurrence network, we find related tweets by searching Twitter using associated terms. Node weight and Eigenvector centrality measures are used to compare the co-occurrence networks to one another. We find that and are the most influential emojis in the epidemics co-occurrence network, occupying first and second place, respectively in terms of eigenvector despite not being in the top 10 emojis in terms of node weight.
Sustainable Intelligent Prediction and Price Recommendation System

Abstract Online brief time frame period condominium stages, comprising of Airbnb, had been transforming into mainstream, and a higher evaluating technique is indispensable for hosts of most recent postings. In this paper, the association is broken down among the portrayal of each rundown and its charge, and proposed a content essentially based absolutely charge counsel gadget alluded to as TAPE to suggest a moderate charge for recently brought postings. The deep knowledge utilized makes them more familiar with strategies (for example, feed-forward networks, longer short-term memory, and recommended moves) to design and put in an influential TAPE. By using a data set of 4 indistinguishable urban areas that were deleted sequentially, it was found that basic elements (such as small indoor objects and high-thickness areas) would undoubtedly have an adverse effect on the charges of each property, and evaluated that it is basic and more attractive style of. Our style is completed with 33.73 in Boston, 20.50 in London, 34.68 in Los Angeles and 26.31 in New York. This is related to the use of other current forms of highlighting.
An Algorithm for Target Tracking of the Car in Accident

Abstract At present, the target tracking algorithm for the video of the vehicle involved in the accident is not perfect, which causes the target to rotate and the target is blocked, and the tracking effect is not good. This paper uses a CamShift tracking algorithm that combines HLBP feature matching and unscented Kalman filtering. Firstly, the vehicle features are extracted through the algorithm to obtain more accurate features, thereby reducing the interference caused by the target rotation on the feature extraction. Secondly, the degree of occlusion of the target is judged by the Bhattacharyya distance, and finally the UKF algorithm is used to predict the target position. The vehicle efficiently solve the problem of poor tracking performance when the target is occluded. Experiments have proved that, in the actual application of tracking the accident vehicle, the algorithm can effectively reduce the influence of external factors on the tracking effect, and the tracking accuracy is greatly improved.
Shape-Changing Control Interface Design: Augmenting Physical Affordances to Enhance a Digital Interface Experience in Cross-Device Interaction

Multiple distributed interfaces in cross-device interaction increase users’ cognitive load when switching from one device to another. A clear spatial reference and physical affordances can help reduce additional cognitive efforts users pay in a multi-device system. However, increasing physical affordances may adversely affect users’ cognitive process in comprehending the desired interaction. By providing physical affordances in sequential order, interfaces can limit the number of physical affordances at one affordance for each step of the interaction. When assisted by digital contents, these sequential physical affordances can better communicate possible actions of an interface. Tangible Dial, an integrated control interface system with a shape-changing dial and digital displays, was designed and tested with users to validate the principle of spatial references and sequential affordances in cross-device interaction.
First-class concepts: reifying architectural knowledge beyond the dominant decomposition

In software engineering, programs are ideally partitioned into independently maintainable and understandable modules. As a system grows, its architecture gradually loses the capability to modularly accommodate new concepts. While refactoring is expensive and the language might lack appropriate primary language constructs to express certain cross-cutting concerns, programmers are still able to explain and delineate convoluted concepts through secondary means: code comments, use of whitespace and arrangement of code, documentation, or communicating tacit knowledge.
An Overview of Improved Gradient Descent Algorithms for DNN Training within Significant Revolutions of Training Frameworks

We absolutely need to train parameters for a given Deep Neural Networks (DNN). One of the most common training algorithms is Gradient Descent (GD). This article looks to bring back classical and emerging GD-based algorithms, against poor convergence, for DNN training within transforming training framework-non-distribution/distribution. We also concentrate on asynchronous/synchronous training framework under distributed training. Additionally, we introduce some evolutionary improved methods for deep learning as alternatives to GD, which have proved to be superior to GD in terms of convergence.
Digital Content Portability and its Relation to Conformity with the Contract

In this paper the author analyses the possible convergences and divergences of two current legislative proposals of the European Commission: the Portability Regulation and the Digital Content Directive. Both proposals address the issue of access to digital content from different perspectives and complement each other, although they use different legal terminology and in some respects have a different scope of application in the question of cross-border portability of the digital content provided for monetary counter performance to consumers. The Portability Regulation focuses on the cross-border portability of digital content [Art. 3 (1) Portability Regulation), while the Digital Content Directive specifies the consumer rights related to the distribution of digital content and subsumes the accessibility of digital content under the concept of “conformity of the digital content with the contract” [Art. 6 (1), (2) Digital Content Directive). The author aims to answer whether a consumer who is not allowed to use the digital content in EU Member States besides the Member State of his residence will be entitled to pursue claims arising from the non-conformity of the digital content with the contract.
Complex mathematical model of the underwater robot operation

Abstract The article is devoted to a complex mathematical model of the functioning of an underwater robot that allows solving the problem of operational correction of a service task directly during its execution. The successful usage of UAV largely depends on the quality of preparation and programming of the UAV mission, including the current factors of the water environment. Since UAV works in an aquatic environment, the modeling of its functioning should be carried out taking into account both the environment itself and the dynamics of changes in its properties. The developed mathematical model was implemented in the form of a computer model and confirmed its operability within the declared ranges of initial conditions and initial data. The proposed complex mathematical model can be used for planning of assignments given available energy on board the UAV and allows to evaluate the energy for the operation of the on-board equipment after performing the UAV maneuver in the operating zone and the necessary reserves for the ascent of the unit, its detection and receiving aboard the carrier.
Fundamentally Important Ideas of Socio-Integrative Approach in University Education

the article is devoted to clarifying the content and principles of socially-integrative approach in university education based on the fundamentalization of education. The purpose of the study is to consider the socio-integrative approach as a significant idea in the implementation of university education. The following research methods were used: theoretical analysis of interdisciplinary literature, interpretation, synthesis, generalization and summarization. As a result, the theoretical basis of integration was formalized, and a set of principles was identified: voluntariness, adequacy, variability, integration and differentiation, motivation and stimulation, with a description of the requirements contained in them for effective implementation of the socio-integrative approach in the implementation of higher university education at the present stage of society development. This is presented for discussion. The conclusions give the reasons for ineffective activity of universities: departmental limitations and interdepartmental disunity; lack of unified organizational and methodological approaches in the implementation of interaction; lack of wide and rationally organized support of public initiatives, activities of non-governmental organizations, which violates their coherence, common understanding of goals and objectives of higher education.
On False Heine/Borel Compactness Principles in Proof Mining

The use of certain false Heine/Borel compactness principles is justified in source theories of proof mining. The justification rests on the metatheorems of the theory of proof mining. Ulrich Kohlenbach recently produced a counterexample showing that the metatheorems do not apply unrestrictedly to Heine-Borel compactness principles. In this short note, we present a simpler counterexample than Kohlenbach’s, showing that the metatheorems can fail because the source theory is already inconsistent.
How to Support Communication among Stakeholders during Software Requirements Prioritization

Existing prioritization techniques do not support communication among stakeholders and this makes it difficult for stakeholders to understand the meaning and essence of requirements before prioritization commences.When this happens, the ordered list of requirements can be misleading.The aim of this research is to develop a method capable of supporting and computing ranks of requirements based on the criteria defined for each requirement.The proposed method is developed based on fuzzy logic.Results show that ordered requirements reproduced ranks with strong correlations when compared to their linguistic values provided by the stakeholders.The contribution of this paper centers on an improved way of prioritizing requirements with understanding.
Focusing on the hybrid quantum computing - Tabu search algorithm

Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community. Widely conceived as the next frontier of computation, Quantum Computing is still at the dawn of its development. Thus, current solving systems suffer from significant limitations in terms of performance and capabilities. Some interesting approaches have been devised by researchers and practitioners in order to overcome these barriers, being quantum-classical hybrid algorithms one of the most often used solving schemes. The main goal of this paper is to extend the results and findings of the recently proposed hybrid Quantum Computing - Tabu Search Algorithm for partitioning problems. To do that, we focus our research on the adaptation of this method to the Asymmetric Traveling Salesman Problem. In overall, we have employed six well-known instances belonging to TSPLIB to assess the performance of Quantum Computing - Tabu Search Algorithm in comparison to QBSolv, a state-of-the-art decomposing solver. Furthermore, as an additional contribution, this work also supposes the first solving of the Asymmetric Traveling Salesman Problem using a Quantum Computing based method. Aiming to boost whole community's research in QC, we have released the project's repository as open source code for further application and improvements.
Example of internal function for Sponge scheme built on the basis of the generalized AES design methodology

The purpose of this article is to construct an internal function underlying the “Sponge” scheme for constructing cryptographic hash functions. An internal function in the “Sponge” scheme is a fixed-length transformation or permutation that operates on a fixed number of bits that make up the internal state of the function. There are various constructive approaches to functiondesign. The most common approach is to use a permutation based on a symmetric block encryption algorithm with constants as the key. This article builds an internal function using the generalized AES design methodology. This methodology makes it easy to design block ciphers to encrypt large blocks of plaintext with small components, representing the processed data as multidimensional arrays. The internal function is a block cipher that processes 2048 bits, represented as a 9-dimensional array of 512 4-bit elements with size 2 × 2 × 2 × 2 × 2 × 2 × 2 × 2 × 2. Each round of encryption consists of three transformations (S-blocks, linear transformation, and permutation), similar to the three round transformations of AES SubBytes, MixColumns, and ShiftRows. The constructed function can be used as an internal function in the modified “Sponge” schemefor constructing cryptographic hash functions.
Design of a problem-based curriculum: A constructive approach for Mobile APP Learning

It has became possible and realistic due to more bandwidth provided by mobile communication that anyone can access the Internet anywhere and anytime, even he/she is in moving. The mobile application, denoted as APP, integrating the computing power of clouds and the mobility of smart-phones, changes the modern living of humans totally, and provides more comfort and convenience. As the APP has been more important, the demand of APP programmers has also been more strong. This paper proposes a work which trains the undergraduate students to develop the mobile APP via a constructive problem-based approach. It is a one-semesters course project. The study basically shows the effectiveness of the proposed approach and the expectation of the students.
Evaluation of the Executional Power in Windows using Return Oriented Programming

Code-reuse techniques have emerged as a way to defeat the control-flow defenses that prevent the injection and execution of new code, as they allow an adversary to hijack the control flow of a victim program without injected code. A well-known code-reuse attack technique is Return-OrientedProgramming (ROP), which considers and links together (relatively short) code snippets, named ROP gadgets, already present in the victim’s memory address space through a controlled use of the stack values of the victim program. Although ROP attacks are known to be Turing-complete, there are still open question such as the quantification of the executional power of an adversary, which is determined by whatever code exists in the memory of a victim program, and whether an adversary can build a ROP chain, made up of ROP gadgets, for any kind of algorithm. To fill these gaps, in this paper we first define a virtual language, dubbed ROPLANG, that defines a set of operations (specifically, arithmetic, assignment, dereference, logical, and branching operations) which are mapped to ROP gadgets. We then use it to evaluate the executional power of an adversary in Windows 7 and Windows 10, in both 32- and 64-bit versions. In addition, we have developed ROP3, a tool that accepts a set of program files and a ROP chain described with our language and returns the code snippets that make up the ROP chain. Our results show that there are enough ROP gadgets to simulate any virtual operation and that branching operations are the less frequent ones. As expected, our results also indicate that the larger a program file is, the more likely to find ROP gadgets within it for every virtual operation.