Reviewerly/exHarmony huggingface dataset:
Software Engineering for Quantum Programming: How Far Are We?

Quantum computing is no longer only a scientific interest but is rapidly becoming an industrially available technology that can potentially overcome the limits of classical computation. Over the last years, all major companies have provided frameworks and programming languages that allow developers to create their quantum applications. This shift has led to the definition of a new discipline called quantum software engineering, which is demanded to define novel methods for engineering large-scale quantum applications. While the research community is successfully embracing this call, we notice a lack of systematic investigations into the state of the practice of quantum programming. Understanding the challenges that quantum developers face is vital to precisely define the aims of quantum software engineering. Hence, in this paper, we first mine all the GitHub repositories that make use of the most used quantum programming frameworks currently on the market and then conduct coding analysis sessions to produce a taxonomy of the purposes for which quantum technologies are used. In the second place, we conduct a survey study that involves the contributors of the considered repositories, which aims to elicit the developers' opinions on the current adoption and challenges of quantum programming. On the one hand, the results highlight that the current adoption of quantum programming is still limited. On the other hand, there are many challenges that the software engineering community should carefully consider: these do not strictly pertain to technical concerns but also socio-technical matters.
Optimization of Quantum Read-Only Memory Circuits

Quantum computing is a rapidly expanding field with applications ranging from optimization all the way to complex machine learning tasks. Quantum memories, while lacking in practical quantum computers, have the potential to bring quantum advantage. In quantum machine learning applications for example, a quantum memory can simplify the data loading process and potentially accelerate the learning task. Quantum memory can also store intermediate quantum state of qubits that can be reused for computation. However, the depth, gate count and compilation time of quantum memories such as, Quantum Read Only Memory (QROM) scale exponentially with the number of address lines making them impractical in state-of-the-art Noisy Intermediate-Scale Quantum (NISQ) computers beyond 4-bit addresses. In this paper, we propose techniques such as, predecoding logic and qubit reset to reduce the depth and gate count of QROM circuits to target wider address ranges such as, 8-bits. The proposed approach reduces the number of gates and depth count by at least 2X compared to the naive implementation at only 36% qubit overhead. A reduction in circuit depth and gate count as high as 75X and compilation time by 85X at the cost of a maximum of 2.28X qubit overhead is observed. Experimentally, the fidelity with the proposed predecoding circuit compared to existing optimization approach is also higher (as much as 73% compared to 40.8%) under reduced error rates.
Identifying Difficulties of Software Modeling Through Class Diagrams: A Long-Term Comparative Analysis

Software modeling is a creative activity in which software components and their relationships are identified based on customer requirements. Based on the literature, object-oriented software modeling is based on four fundamental pillars which are abstraction, encapsulation, decomposition, and inheritance. However, despite the existence of guidelines and recommendations for implementing the object-oriented approach, novice software designers do not make good design decisions, leading to inefficient designs that cannot be modifiable, understandable, or user-friendly distribute at the development level. The literature reveals that the most common difficulties faced by software designers is a lack of understanding and confusion of concepts related to the object-oriented approach, as well as difficulties in creating Unified Modeling Language diagrams, especially class diagrams. The work presented in this article uses a qualitative and quantitative approach to determine, in a group of university students, what are the most recurrent difficulties and their persistence during the time. The qualitative case study is the method that allowed to generate the documents: <i>diagnostic</i> and <i>evaluation</i> tests. Additionally, a thematic analysis was used to identify, analyze and report patterns within the data. In order to know the occurrences of the problems in the case study, as part of our quantitative approach, a comparative study was applied to compare the results obtained between the diagnostic and evaluation tests and thus establish the similarities and differences among the cases observed, through the hierarchical clustering technique. The findings of this study show us 16 difficulties identified after the qualitative analysis, while the quantitative analysis shows us the number of occurrences and their persistence over time. The difficulties reported in both analyzes focus on these three difficulties: a) Definition of attributes that could be a class, b) Classes with inadequate or insufficient behavior and, c) Incorrect use of multiplicity between classes. Each of these difficulties is analyzed in depth in this study.
UV detection technology of insulator discharge based on UAV platform

Under the action of long-term electrical, thermal and mechanical stress, insulators in transmission lines may have insulation deterioration, aging and even defects, which seriously endangers the stable operation of power system. Corona discharge of insulator will radiate light wave, electric pulse and other signals, which represents the operation state of insulator string to a certain extent. However, it is difficult to judge the discharge phenomenon of insulator through manual detection. With the development of transmission line inspection in recent years, multi rotor UAV has great advantages as a non-contact detection platform. In this paper, the UV detection system of UAV degraded insulator is designed based on the sun blind UV sensor. A large number of experimental studies are carried out on the inspection mode of UAV and the characteristics of UV detection system on the actual live line. The results show that the UV detection system of UAV is divided into two parts: airborne detection terminal and ground display terminal, The airborne terminal and ground terminal cooperate in real time to adjust the angle of UAV and UV detector, which can detect the insulator in different directions, collect the UV photon information of three target points on the insulator surface, and then evaluate the insulation performance of insulator string in combination with the position information; The M600 six rotor UAV is equipped with a deteriorated insulator UV detection device, which can accurately detect the corona discharge of the deteriorated insulator, accurately master the insulator performance, improve the safety, efficiency and automation of power inspection, and have practical significance for the non-contact operation and maintenance of power grid.
Auto insurance fraud detection based on Logistic-SVM algorithm

In recent years, with the continuous expansion of the business scope of auto insurance, the crime of auto insurance fraud is becoming frequent. The establishment of auto insurance fraud detection model has become an important measure to ensure the stable development of auto insurance industry. This paper builds an auto insurance fraud detection model based on Logistic-SVM, which could solve the problem that the original model needs lots of variables. Firstly, the importance of characteristic variables is sorted by SVM model, and ten characteristic variables are selected according to the objective reality. By comparing with the traditional single logistic regression and SVM algorithm, it is found that the Logistic-SVM algorithm has a better detection effect on auto insurance fraud. The accuracy of Logistic-SVM is 96.1%, which is 2% higher than that of logistic-regression and 0.7% higher than that of SVM. The research of this paper could not only improve the practicability of machine learning model in the field of auto insurance fraud detection, but also escort the prosperity and development of auto insurance industry.
How Are Communication Channels on GitHub Presented to Their Intended Audience? -- A Thematic Analysis

Communication is essential in software development, and even more in distributed settings. Communication activities need to be organized and coordinated to defend against the threat of productivity losses, increases in cognitive load, and stress among team members. With a plethora of communication channels that were identified by previous research in open-source projects, there is a need to explore organizational issues in how these communication channels are introduced, explained, and motivated for use among all project members. In this study, we wanted to understand which communication channels are used in GitHub projects and how they are presented to the GitHub project audience. We employed thematic analysis to analyze 151 artifacts in 90 GitHub projects. Our results revealed 32 unique communications channels that can be divided into nine different types. Projects mostly provide channels of different types, but for some types (e.g., chat) it is common to provide several channels. Maintainers are aware that channels have different properties and help the developers to decide which channel should be used in which case. However, this is not true for all projects, and often we have not found any explicit reasons why maintainers chose to provide one channel over another. Different channels can be used for different purposes and have different affordances, so maintainers have to decide wisely which channels they want to provide and make clear which channel should be used in which case. Otherwise, developers might feel overwhelmed of too many channels and information can get fragmented over multiple channels.
Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learning

Recent work has shown that NLP tasks such as Relation Extraction (RE) can be recasted as Textual Entailment tasks using verbalizations, with strong performance in zero-shot and few-shot settings thanks to pre-trained entailment models. The fact that relations in current RE datasets are easily verbalized casts doubts on whether entailment would be effective in more complex tasks. In this work we show that entailment is also effective in Event Argument Extraction (EAE), reducing the need of manual annotation to 50% and 20% in ACE and WikiEvents respectively, while achieving the same performance as with full training. More importantly, we show that recasting EAE as entailment alleviates the dependency on schemas, which has been a road-block for transferring annotations between domains. Thanks to the entailment, the multi-source transfer between ACE and WikiEvents further reduces annotation down to 10% and 5% (respectively) of the full training without transfer. Our analysis shows that the key to good results is the use of several entailment datasets to pre-train the entailment model. Similar to previous approaches, our method requires a small amount of effort for manual verbalization: only less than 15 minutes per event argument type is needed, and comparable results can be achieved with users with different level of expertise.
Satellite Imagery Application for Searching Buried Intrusive Structures

Introduction. At the current stage of information technology development, methods for remote sensing have been increasingly used for mineral exploration.Problem Statement. Significant capital intensity of geological works for intrusive bodies search when the crystalline basement is overlapped by a thin sedimentary cover requires the implementation of advanced methods that, on the one hand, allow reducing the costs of exploration and, on the other hand, enable increasing theaccuracy of objects identification.Purpose. The development of methodological framework for the application of remote sensing data to identify prospective areas in search of buried intrusive bodies.Materials and Methods. Medium (Landsat, Sentinel) and high (WorldView) resolution optical satellite imagery data in the thermal infrared and visible ranges of the electromagnetic radiation spectrum; radar satellite data (SRTM), multispectral aerial survey data obtained by unmanned aerial vehicles; methods for structuralinterpretation, digital terrain model analysis, results of field thermometry have been used in this research.Results. A few prospective sites for the search for buried intrusions within the Hubkivska and AnastasivskoBolyarska squares of the Novohrad-Volynskyi block of the Ukrainian Shield, regardless of the geophysical data, have been identified. These objects were later confirmed by detailed geomagnetic surveying and drilling. Withinthe detected thermal anomalies, several small (60—120 m long and 30—50 m wide) dikes have been detected. Four of the 5 wells drilled have confirmed the presence of dike bodies, and 1 well enters the fracture zone. In other areas, where detailed geophysical survey was carried out within the detected thermal anomalies, new dike bodieshave been discovered.Conclusions. The developed technique may be used as an additional tool in geological prospecting.
An Evaluation of a Language Processor for an African Native Language-based Programming Language

Abstract The design and prototype implementation of a subset of an African indigenous language-based programming language has been carried out and reported. In this study, an evaluation of the processor developed for the native language-based programming language was carried out in order to assess its level of conformance to the characteristics required of a good software product as set by the international organization for standardization (ISO). The developed language processor was evaluated using some metrics for evaluating the quality of software systems including structural and time complexity. A usability test was also conducted to assess users’ perception of the system concerning its relevance and ease of use. The result of system evaluation indicated that the system contains 1558 lines of code, its cyclomatic complexity is 14 and its asymptotic time complexity is of order big oh O (n 3 ), where n is the size of the input to the system. Over 86% of the participants in the usability test attested to the system’s relevance while the usability rating was 86%. The developed system can be inferred to be of good quality as the results of its evaluation are positively on the high side for satisfying most of the ISO criteria for adjudging a software product as being of good quality. Furthermore, the high usability rating for the system indicates that the programming language whose compiler was evaluated satisfies most of the criteria set by the Department of Defense (DOD) for assessing the ‘goodness’ or otherwise of a programming language.
Scientific research information management based on blockchain technology

As a supporting technology of Bitcoin to achieve the function of account management, blockchain technology has received extensive attention from all walks of life, especially in the financial field. Based on the successful experience of blockchain in the application of digital cryptocurrency, blockchain technology has also exerted an important influence on some aspects of scientific research information management, such as declaration, implementation, and conclusion. Thus, for resolving the problems of academic misconduct in scientific research information management, blockchain technology can be targeted for improvement according to each link of information management to improve the security of the management system. Combining the existing achievements and requirements in real applications, this paper explains characteristics of the blockchain technology and analyzes its disadvantages in scientific research information management compared with the traditional methods. Finally, this paper puts forward some suggestions for applications to provide a reference for the effective application of blockchain technology in scientific research information management.
Image Watermarking in Frequency Domain using Hu’s Invariant Moments and Firefly Algorithm

Preventing the digital content from being copied, manipulated and illegal ownership claims is one of the biggest challenges that appeared with the widespread usage of computing facilities.Watermarking is one way to tag a digital document with a watermark, perceptible or imperceptible, so as to later prove the ownership or authenticity of the document, in case the need arises.Robust and Fragile watermarking is used in case of proving ownership and authenticity, respectively.This paper proposes a watermarking approach based on Discrete Wavelet Transform (DWT), Hessenberg Decomposition (HD) and Singular Value Decomposition (SVD) approach, augmented with Firefly Algorithm (FA).To make the approach blind, the proposed technique uses Hu's invariant moments which are invariant against rotation, scaling and translation (RST) attack over the image.In the resulting watermarked image, the watermark is imperceptible, which make it suitable for a large class of watermarking applications.In the proposed approach, a given colour image is subjected to 2 Level DWT for decomposing into sub-bands, namely LL, LH, HL and HH bands.These coefficients of HH band are fed as input for HD.The output is operated for SVD for obtain U, S and V matrices.The Hu's invariant moments are scaled and mapped to binary string using logarithm scaling.The binary matrix, corresponding to binary watermark, is XoRed with the invariant moments, in a repeated manner, to obtain a new binary matrix, of the same dimension as count of 2X2 partitions of S. The watermark is embedded by changing the orthogonal V matrices.The magnitude of the change is computed with Firefly algorithm considering the robustness and imperceptibility as the trade-off parameters.The firefly algorithm is one of the nature inspired optimization algorithm.The proposed watermarking approach is capable of withstanding JPEG compression attack, filtering attacks and noise.PSNR and SSIM are used as the quality metric for accessing the watermarked image quality.It turns out that the proposed watermarking technique gives a considerable improvement over robustness and imperceptibility as compared to the benchmark approaches.The performance of the proposed approach as compared to the benchmark approach, increases in linear manner with the dimension of the image under consideration, reaching from 1 percent to 4 percent for image dimensions ranging from 400X400 to 1200X1200 pixels.
Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language

Spurious correlations are a threat to the trustworthiness of natural language processing systems, motivating research into methods for identifying and eliminating them. However, addressing the problem of spurious correlations requires more clarity on what they are and how they arise in language data. Gardner et al (2021) argue that the compositional nature of language implies that \emph{all} correlations between labels and individual "input features" are spurious. This paper analyzes this proposal in the context of a toy example, demonstrating three distinct conditions that can give rise to feature-label correlations in a simple PCFG. Linking the toy example to a structured causal model shows that (1) feature-label correlations can arise even when the label is invariant to interventions on the feature, and (2) feature-label correlations may be absent even when the label is sensitive to interventions on the feature. Because input features will be individually correlated with labels in all but very rare circumstances, domain knowledge must be applied to identify spurious correlations that pose genuine robustness threats.
The Developments of the Digital Technologies in the Accounting Scientific Research in the Light of the Corona Pandemic - An Exploratory Study in the Hashemite Kingdom of Jordan

This study aims at identifying the uses of the digital technologies in the field of scientific research in general and the accounting scientific research; the study also has illustrated the importance of these technologies in developing the accounting scientific research and enhancing its efficiency; in addition, it has identified a set of the obstacles which the researchers may face while using the digital technologies. Inductive and descriptive analytical analyses have been used; previous studies touching upon the digital technologies in the field of scientific research have been examined in order to develop the theoretical framework and design the questionnaire; the researcher has used one of technical means; the questionnaire has been prepared by Google Drive Program and distributed through private or university e-mail technologies and WhatsApp groups in academic context placed in educational forums. The study has concluded that there are justifications and reasons such as closures during the Corona pandemic which encourage the use of the digital technologies in the accounting scientific research. Furthermore, there are various aspects of the use of the digital technologies in the field of accounting scientific research in obtaining and exchanging the data; in addition, the study has found that the digital technologies play an important role in developing the accounting scientific research and achieve various advantages while using these technologies in the accounting scientific research. However, the researcher in the accounting scientific field faces various obstacles which limit the use of the digital technologies in the accounting scientific research such as a lack of knowledge of the uses of the digital technologies, as well as a lack of trust in information exchanged by these technologies and a high cost of subscription of some scientific websites (i.e research and dissertation repositories). Finally, the study has concluded that scientific research curriculum shall be developed in order to include the digital technologies used in the scientific research and the mechanism of their use.
Image establishment of a higher education institution lecturer in the new educational environment

The article justifies the need to transform the lecturer’s (professor’s) image in a changing environment, formulates the requirements for the image of a higher school lecturer (professor) in a new digital reality, determines the image formation stages. The study uses institutional and structural analysis methods, system analysis methods, human capital research methods, panel research and data collection method. The research paper can be used for the purposes of organising professional development for educational institutions lecturers (professors), organising trainings and courses on shaping and correcting the lecturer’s (professor’s) image. The article also gives an opportunity to understand the role of high education institution image in ensuring the effectiveness of his professional activities in the new information environment and substantiate the need for in-depth research in such areas as the psychology of teacher personality in professional activities, the impact of teacher personality on the educational process efficiency, the impact of lecturer’s (professor’s) image on the university’s rating indicators.