Reviewerly/exHarmony huggingface dataset:
Trends of Software Development Methodologies Toward DevOps: Analysis and Review

Background: The trend of software development has always been challenging for industry experts and software developers. There is tremendous growth in software development methodologies under the influence of evolving technologies and the rising demands of society. The 2019 pandemic forced software developers to shut down their offices and begin working from home, thereby, highlighting the critical necessity for a shared development and operations teams platform. As a result, the development trend moves from waterfall and Agile towards DevOps. Objective: The objective of the research is to review and comparatively analyze the availability factor of different selective and required features in software development methodologies. Software development industries will be benefited in appropriate methodology selection based on the requirement. Methods: The analysis is based on review of different development methodologies based on existing literature study, Google, and Stack Overflow Trends followed by tabular comparison of Waterfall, Iterative, Prototype, Spiral development models under Traditional and Rapid Application Development (RAD), Scrum, Kanban, XP for Agile methods with DevOps automation culture on essential features. Results: The moving trend towards DevOps, from Traditional and Agile development, demonstrate the most recent market swings for these models. Although Traditional models adhere to outdated software development methodologies, they are included in this high-quality survey and evaluation because of their widespread use in the software industry and prominent researcher’s survey work. Conclusion: Software developers, students, and researchers will all find it simple to comprehend the workings of development processes as a result of this analytical review. Additionally, it will also make it easier for these target audiences to choose relevant and effective models for software development.
The expediency of using the digital components of the educational platform «Urait» in teaching academic disciplines with dynamic content (on the example of the discipline «Financial accounting»)

The article presents and argues the author's opinion regarding the degree of demand for and expediency of using digital tools and services of the educational platform (EP) «Urait» in the educational process of a higher school in the course of teaching academic disciplines, the content of which is highly dynamic. A classic example of such an academic discipline is «Financial accounting». The introductory part of the article contains a general description of the named academic discipline and a description of the specifics of its teaching. The main content of the article is devoted to the description of the author's experience in using the main digital components of the EP «Urait», such as a flexible course constructor, an interactive assessment system and an online bank of the EP «Urait», as well as free templates for work programs. The final part of the article presents the author's vision regarding the need for a future expansion of the existing functionality of the EP «Urait» and expectations from the emergence of new functions of this platform.
Spatiotemporal Networks in Ryoji Ikeda’s Electronic Music: Loop, variation and re-contextualisation of sound

Ryoji Ikeda’s sonic composition has often been considered to prioritise a physical, immersive experience of space over temporal musical progression. This article challenges this commonly held view, arguing that the static nature of his work should be understood in terms of complex interactions between space and time rather than in dualistic terms. By analysing a large-scale sonic transformation within his 2005 album Dataplex , the article uncovers complex rhizomatic networks of materials that expand across multiple tracks. The links between the album tracks leads to an unconventional quality of musical time that contains a high degree of statis yet nevertheless presents a non-linear progression, which is created through repetition (loops), variation and re-contextualisation of sounds. The analysis suggests that experiencing the ordered series of tracks in the album means accumulating information and exploring memory within a non-interchangeable process of sonic flow and metamorphosis. Despite the fragmentary nature of these internal continuities, the resulting rhizomatic networks provide a means to understand and even to listen structurally to Ikeda’s sonic composition.
Design of artificial intelligence cultural creative industry based on machine learning

At present, social production and people's lifestyle have been revolutionized and globally affected by the rapid development of artificial intelligence technology. This technology has been reasonably applied in many fields, such as medical treatment, economy, transportation and manufacturing, so it has been unanimously recognized and supported by the market, society and the government. At the same time, artificial intelligence is more and more applied to the field of cultural industry, which brings a new development model of cultural design creative industry and promotes its production and management reform. Based on this point, this paper focuses on the practical problems in the process of small sample single label classification of cultural and creative product images, comprehensively establishes the mainstream machine learning model, and classifies DPM data with mechanical transfer learning algorithm. From the experimental data, the prediction accuracy of the resnet50 model is 87%. Not only that, this paper also proposes a multifeature algorithm by integrating machine learning and deep learning technology, in order to solve the problem of differences between large and small types of cultural and creative products. The algorithm can combine convolution calculation and point combination for learning, so as to further improve the accuracy. Finally, it can realize that the accuracy is 5% higher than DPM data set, which is conducive to the development of cultural and creative industries. Through the in-depth analysis of artificial intelligence, it is found that the technical level of artificial intelligence needs to be improved at this stage, and there are limitations in its application; Artificial intelligence laws and regulations are imperfect and information protection is misplaced; Artificial intelligence technology is easy to be overused, which affects the healthy development of cultural industry and leads to public opinion. This paper applies machine learning and artificial skill technology to the field of cultural and creative design, so as to promote the development of cultural and creative industry.
Utilization of electronic resources: an analysis of awareness and perception of users of Kashmir University

Purpose This paper focuses on the use of e-resources by research scholars and post-graduate students at Kashmir University. The main aim is to determine the use of e-resources, users skills in handling e-resources and the purpose of their use. Further, this paper aims to highlight the problems faced by research scholars and post-graduate students in accessing e-resources. Design/methodology/approach The survey was conducted through a structured questionnaire circulated among 250 research scholars, both (M.Phil./Ph.D.) and post-graduate students, from different departments of Kashmir University, and the response rate was 80%. Random sample method was used for the selection of respondents and interacting with them. The responses received from the research scholars to 14 questions are presented in the form of tables. Findings Major findings of the study reveal that the majority of the students reported using electronic journal resources for various purposes including working on assignments, research proposal writing, literature review writing, research report writing, current awareness and leisurely exploration of ongoing scientific debates through peer-reviewed papers. The challenges encountered in the use of electronic journal resources include a power outage, inadequate bandwidth, slow download speed, inability to access the resources from home, lack of training, lack of awareness, limited access to computers and difficulty in searching. The paper concludes that electronic resources have become an integral part of the information needs of research scholars’ post-graduate students at Kashmir University. Further, it finds that e-resources can be good substitutes for conventional resources, if the access is fast, and more computer terminals are installed to provide fast access to e-resources. Finally, recommendations for improving the use of electronic journal resources are provided. Practical implications The paper restrains the study exclusively to use of e-resources by the research scholars and post-graduate students of Kashmir University. Originality/value The paper highlights the use of e-resources by research scholars and post-graduate students of Kashmir University and makes some constructive suggestions for the improvement of electronic resources and services. This is the first time an effort has been made to assess the use of electronic resources by post-graduate students at Kashmir University. The study could be used to assess the post-graduate students’ needs for electronic resources at the Kashmir University and other users in higher learning institutions.
Convergence rates of training deep neural networks via alternating minimization methods

Training deep neural networks (DNNs) is an important and challenging optimization problem in machine learning due to its non-convexity and non-separable structure. The alternating minimization (AM) approaches split the composition structure of DNNs and have drawn great interest in the deep learning and optimization communities. In this paper, we propose a unified framework for analyzing the convergence rate of AM-type network training methods. Our analysis is based on the non-monotone j-step sufficient decrease conditions and the Kurdyka-Łojasiewicz (KL) property, which relaxes the requirement of designing descent algorithms. We show the detailed local convergence rate if the KL exponent $$\theta$$ varies in [0, 1). Moreover, the local R-linear convergence is discussed under a stronger j-step sufficient decrease condition.
Practice These Tips to Get Promoted

Women in Higher EducationVolume 32, Issue 6 p. 9-9 The Reflective Leader Practice These Tips to Get Promoted Dawn Z. Hodges, Dawn Z. HodgesSearch for more papers by this author Dawn Z. Hodges, Dawn Z. HodgesSearch for more papers by this author First published: 21 June 2023 https://doi.org/10.1002/whe.21287Read 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 onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume32, Issue6June 2023Pages 9-9 RelatedInformation
A handwritten ancient text detector based on improved feature pyramid network

Text detection is the primary task for digitization of ancient books. Different from the common scene text detection tasks (ICDAR, TotalText, etc.), the texts in handwritten ancient documents are more densely distributed and generally small objects; at the same time, the layout structure is also more complex, with problems such as mixed arrangement of pictures and texts and high background noise, all of which pose challenges for detection. According to the characteristics of ancient book images, this paper proposes a new fusion structure based on Feature Pyramid Networks, and takes FCOS as the baseline model to form a new detector (named RFCOS). We enhance the detection capability for dense and small text instances by adding bottom-up fusion paths, cross-layer connections and weighted fusion. Meanwhile, the loss of high-level feature maps during fusion is reduced by new upsampling method and lateral connections. We verified the effectiveness of our RFCOS on the HWAD (Handwritten Ancient Books Dataset), a dataset containing samples in four languages - Yi, Chinese, Tibetan and Tangut, and verify the generalization of RFCOS on another public dataset MTHv2. The results show that RFCOS outperformed most of the existing text detectors in terms of precision, recall and F-measure.
A secure authentication protocol for healthcare service in IoT with Q-net based secret key generation

The major intention of this research is to propose a secure authentication protocol for healthcare services in IoT based on a developed Q-Net-based secret key. Nine phases are included in the model. The sensor node, IoT device center, gateway node, and medical professional are the four entities involved in the key generation process. The designed model derived a mathematical model, which utilized hashing function, XOR, Chebyshev polynomial, passwords, encryption algorithm, secret keys, and other security operations for performing effective authentication. Here, the secret key is generated with the Deep Q-Net-based sub-key generation approach. The proposed method achieved the minimum computation time of 169xe9 ns, minimum memory usage is 71.38, and the obtained maximum detection rate is 0.957 for 64 key lengths. The secure authentication using the proposed method is accurate and improves the effectiveness of the system’s security.
Looking Through the Algorithmic Unconscious

This paper concerns the role of the unconscious in technology. The central thesis is that there exists an experience of non-acceptance and failed incorporation of technology, which (a) does not depend on the technical engineering dimension of the artifact but (b) instead concerns the relationship between the human unconscious and the artifact. This thesis is supported and developed through the analysis of a case study – that is, the creation and development of the first version of Google Glass. The failure of the first version of Google Glass is explained in terms of the non-acceptance of this technology. This paper presents an analysis of users’ experiences and comments as a basis for interpreting the relationship between the unconscious and technology. Their non-acceptance of this technology is explained and further clarified from a postphenomenological point of view, utilizing the concept of “technological uncanny.” The analysis suggests that antimediation can be understood as a form of noise. In fact, as non-acceptance, antimediation directly concerns the relationship between contingency and control.
ON THE NUMBER OF POINTS OF GIVEN ORDER ON ODD-DEGREE HYPERELLIPTIC CURVES

For integers N≥2 and g≥1, we study bounds on the cardinality of the set of points of order dividing N lying on a hyperelliptic curve of genus g embedded in its jacobian using a Weierstrass point as base point. This leads us to revisit division polynomials introduced by Cantor in 1995 and strengthen a divisibility result proved by him. Several examples are discussed.
Phonic Convergence in Estonian Yiddish

Abstract Multilingualism is a characteristic feature of Yiddish speakers in the Baltic region, and contact-induced language change is natural in this case. To date, some Baltic German impact on the local varieties of Yiddish has been discussed in the literature. This article focuses on the phonic impact of Estonian on Estonian Yiddish. The study is based on acoustic analysis of Estonian Yiddish sound recordings. The North Baltic area forms a separate region in the Baltic Sprachbund; Yiddish spoken in Samogitia and Courland as well as Estonian Yiddish exhibit several features typical of this language area. It is demonstrated that there is an overlap of basic prosodic categories with co-territorial languages, such as centralized stress and a quantity opposition. A distinctive feature common to Estonian and Estonian Yiddish is the limited reduction of vowels and a tendency to maintain stable durational ratios of the primary stressed syllable and following unstressed syllables.
An analysis of the increasing cases of data breaches in india

The number of data breaches in India has increased significantly in recent years. This is due to a number of factors, including the growing use of digital technologies, the lack of adequate data security measures, and the increasing sophistication of cybercriminals. The impact of data breaches can be far-reaching. Individuals may suffer financial losses, identity theft, and other forms of harm. Businesses may lose customers, suffer reputational damage, and incur significant costs to remediate the breach. The Indian government has taken some steps to address the problem of data breaches. However, more actions should be taken to strengthen data security measures and to educate businesses and individuals about the risks of data breaches. This research examines the rise of data breaches in India and uses the Air India case study to demonstrate the possible attacks in an airline company's infrastructure and how easily the customers' personal information can be stolen.
‘Citycoin’: Solving Issues of Payments Across the Cyprus Green Line

The Green Line divides the island of Cyprus, and despite the existence of the Green Line Regulation, regulating commerce and crossing, the digital divide between the communities creates obstacles to payments and thus greater economic interaction. ‘Citycoin’ is a conceptual framework that seeks to evaluate if creating a payment infrastructure can be socially beneficial and potentially profitable. ‘Citycoin’ as conceptually presented here, is a payment rail created using a stablecoin, allowing for the reduction of obstacles to digital payments across the Green Line. By removing the high cost of transactions and providing the missing part of the necessary infrastructure to support full and unencumbered economic activity, ‘Citycoin’ can provide a significant increase in trade, especially in the areas near the Green Line, which have been traditionally more disadvantaged by the conflict. This can be especially true if the initiative is supported by the two municipalities of Nicosia, who have a track record of successful cooperation. The article estimates the volume of current transactions as well as suggesting how in practical terms this concept can take form in the island of Cyprus.
Interaction Strategies in Composition for Karlax and Acoustic Instruments

The Karlax is a gestural controller which arose substantial interest among composers since its inception in 2010 and continues to be commonly used in solo and group performances. One of the reasons for its longevity is the device’s remarkable adaptability, especially in musical contexts involving acoustic instruments. This article analyses six chamber music pieces for Karlax and acoustic instruments by comparing performance videos, sounds generated, and the writing process (scores, sound synthesis, and mapping strategies in each piece). We further discuss the various composition strategies using interaction metaphor concepts from the computer music literature. These metaphors prove to be powerful analysis tools that allow describing the use of a digital musical instrument in a chamber music context. In the last part of this article, we discuss five such interaction strategies and their use in sketches of an original composition for Karlax and ensemble.
Privacy preserving dynamic data release based on non-synonymous diverse anatomy

The publishing and using of big data brought unprecedented convenience to users. However, it also results in the disclosure of personal privacy information. In order to mitigate the privacy leakage risk of sensitive information during dynamic data updating, this paper envisages a non-synonymous diverse anatomy method for the privacy preserving dynamic data publishing. The envisaged method inherits the advantages of the traditional anatomy method, retains the availability of the original data to the greatest extent, and avoids the loss of information caused by the generalisation process. A series of indicators are designed to evaluate the synonymous linkage between non-numerical sensitive values. A novel grouping mechanism is further proposed to achieve l-diversity anatomy by combining the concept of synonymous linkage and synonymous entropy with the dynamic update procedure. Experimental analysis suggests that the envisaged method can provide better privacy protection effect on the published data.
Continuous Parameter Control Using an On/Off Sensor in the Augmented Handheld Triangle

In this work, we present Triaume, an augmented musical percussion instrument based on the triangle. The augmentation proposal for this instrument is based on a capacitive thumb sensor, that allows controlling digital musical devices and at the same time, preserves the original instrument idiomatic inside the context in which it is inserted. Triaume’s interaction proposals were built upon Brazilian music genres idiomatic, such as Forró, Xote, and Baião. The instrument invasiveness is further reduced through the use of an external device (an application running on a smartphone) for emulating faders related to sound parameter configuration. At first, we used the sensor as an on/off button able to trigger pre-programmed percussion samples, which can be synchronized with the triangle’s acoustic sounds. This mechanism can be adjusted for triggering on pressing or releasing the sensor. Next, we convert the digital signals acquired by the sensor to continuous values by the on/off signal filtering. Such signal rectification and filtering system allows gradual change of continuous sound synthesis parameters, dealing with the on/off signal low robustness, turning it into a more controlled signal. Triaume can be inserted in the contexts of traditional and avant-garde music, also motivating further studies for applying the mechanism used on it in other percussion instruments.
Privacy-preserving cost-effective work distribution with fine-grained access control for mobile crowdsensing

Crowdsensing is a new paradigm for data collection in the internet of things environment, in which the data aspirant outsource sensing tasks to sensing devices such as smart mobile phones through a crowdsensing server (CSS). Despite its numerous advantages, the vulnerability of sensitive data disclosure in crowdsensing generates a severe obstacle against its participants and restricts its use in privacy-sensitive domains. The semi-honest CSS tries to learn sensitive information such as the identity, and attributes of both the data requester and data collectors. Also, the malicious data collector nodes who are unable to execute the data collection task will make an effort to learn the task description and thereby infer the data being collected. We propose a privacy-preserving cost-effective work distribution system with a fine-grained access control (PPA) scheme. A ciphertext-policy attribute-based encryption (CP-ABE) method with hidden access policy is used to choose data collectors and safeguard both the data requester and data collector's privacy.