Reviewerly/exHarmony huggingface dataset:
<i>Ergodynamics of the Open Machine</i> : Material Engagement and Modular Synthesis Performance Practice

ABSTRACTThis paper analyses some theoretical and philosophical concerns related to modular synthesis performance practice. Taking an interdisciplinary approach drawing upon concepts from cognitive archaeology, anthropology and the philosophy of technology, the paper seeks to frame modular synthesis practice as a dance of agencies in the context of human–machine performance. In this paper, I explore how musical ideas, technical objects and performances co-evolve as part of a set of interdependent practices. To contend with this entangled human–machine relationship, I propose a consideration of how material agency helps define the direction of these creative practices, through the process of material engagement. In doing so, we consider the unique ergodynamics of modular systems, and examine the interdependent relationship that exists between the two core sites of musical performance in this practice: that of ‘patching’, and of live performance. Through reflective practice and theoretical discussion, this paper analyses how an entanglement between human and material agencies challenges traditionally understood notions of musical authorship and agency.KEYWORDS: Modular synthesiselectronic musicmaterial engagement theoryGilbert Simondonergodynamicsexperimental music Disclosure StatementNo potential conflict of interest was reported by the author(s).Notes1 In Magnusson’s work, this aspect of ergodynamics is analysed with respect to the Heideggerian concepts of the ‘ready-at-hand’ and ‘present-at-hand’ (Citation2019, 170). See also (Hamman Citation1999) for a related discussion in the context of computer music practice.Additional informationFundingThis work has been supported by the University of Sydney as part of the 2022/23 SOAR Prize, a two-year internally funded programme of research awarded to Early and Mid-Career Researchers at the University of Sydney.Notes on contributorsBenjamin CareyBenjamin Carey is a Sydney-based composer, improviser and educator. He makes electronic music using the modular synthesiser, develops interactive music software and creates audio-visual works. Ben’s research and practice is concerned with musical interactivity, generativity and the delicate dance between human and machine agencies in composition and performance. Ben has released ten albums, including METASTABILITY (2023), Hypertelic (2021) and ANTIMATTER (2019), and has collaborated with a variety of artists including JACK Quartet, Sydney Chamber Opera, ELISION ensemble and others. His work has been performed internationally at the Huddersfield Festival of Contemporary Music (UK), IRCAM Live @ La Gaité Lyrique (France) and elsewhere. Ben is a Senior Lecturer in Composition and Music Technology at the Sydney Conservatorium of Music, University of Sydney. In recognition of his research, Ben was recently awarded the University’s SOAR Prize for 2022/23.
Certain procedural aspects of the institute of interim measures in protection of copyright and related rights

The article analyses the peculiarities of the institute of interim measures and preliminary interim measures provided by the section 144.1 of the Civil Procedural Code of the Russian Federation in the part of their taking by the court. The authors draw attention to the temporary nature of interim measures, which involves the return of the parties to the initial position in the event that the claims are recognized by the court as unfounded. However, difficulties of a technical nature arise in this part when the court takes preliminary injunctive relief under section 144.1 of the Code of Civil Procedure of the Russian Federation in the form of obliging the Federal Service for Supervision of Communications, Information Technology and Mass Communications and other persons to stop creating technical conditions for the placement, distribution and other use of the disputed musical work. As a rule, after the filing of an application for interim measures by the applicant claiming that his rights have been violated by placing an object of copyright and related rights on the Internet, either the defendant himself or the Federal Service for Supervision of Communications, Information Technology and Mass Media essentially removes the corresponding work or a link to it. After filing an action to prohibit the creation of technical conditions for the placement, distribution and other use of the disputed work, in accordance with the procedure stipulated by part 5 section 144.1 of the Civil procedural code of the Russian Federation for its consideration on the merits sometimes requires the expertise to establish the identity of the work posted on the Internet by the defendant and the work in respect of which the plaintiff claims the exclusive rights. This is particularly relevant when disputes arise regarding the posting of phonograms, since multiple phonograms are allowed and the court needs to establish the identity of the phonogram claimed by the plaintiff and the phonogram posted by the defendant and in respect of which the court has taken preliminary injunctions. Even the mere possibility for the defendant to re-post the phonogram on its website after the plaintiff’s claims have been found unfounded does not undermine the fact that the restoration of the defendant&amp;apos;s rights to post the phonogram on its website is not through the lifting of provisional measures to resume access to the previously posted work, but through its new posting by the defendant. The foregoing contradicts the provisional nature of the interim measures.
Re-Thinking Virtuosity for the Hybrid Era of Multifarious Approaches

Virtuosity in the twenty-first century is undergoing a transformation. Technological changes have altered the relations between artists, audience, critics and tools, requiring a redefinition of virtuosity. In recent years, these changes have caused musicians in the contemporary classical music tradition to adopt an increasingly varied set of workflows, tools and approaches, necessitating a recontextualisation of the ideas of technique and expertise. This article discusses how new music repertoire involving the use of technology relates to five new formulations of virtuosity and connects them to three brief case studies. In exploring how hybrid virtuosity, interdisciplinary virtuosity, virtuosity of adaptability, eco-systemic virtuosity, and the New Virtuosity relate to XR performance, collaboration with an AI, and inclusive co-creation between deaf and hearing artists, I question what virtuosity means in these examples and how technology is impacting the way virtuosity is transforming.
Software Effort Estimation Based on Ensemble Extreme Gradient Boosting Algorithm and Modified Jaya Optimization Algorithm

Software development effort estimation is regarded as a crucial activity for managing project cost, time, and quality, as well as for the software development life cycle. As a result, proper estimating is crucial to the success of projects and to lower risks. Software effort estimation has drawn much research interest recently and has become a problem for the software industry. When results are inaccurate, an effort may be over- or under-estimated, which can disastrously affect project resources. In the sector, machine learning methods are becoming more and more prominent. Therefore, in this paper, we propose a Modified Jaya algorithm to improve the effectiveness of the estimated model; Modified JOA selects the ideal subset of components from an extensive feature collection. Then, the ensemble machine learning-based Enhanced Extreme gradient boosting algorithm and Ensemble Learning machine approach are employed to estimate the software effort. On the PROMISE SDEE repository, the proposed methodologies are empirically assessed. In this approach, applying machine learning techniques to the effort estimation process increases the likelihood that the time and cost estimates will be accurate. The proposed approach yields a greater performance. The key benefit of this approach is that it lowers the computational cost. This approach can also inspire the development of a tool that could reliably, effectively, and accurately estimate the effort required to complete different software projects.
An efficient framework for obtaining the initial cluster centers

Abstract Clustering is an important tool for data mining since it can determine key patterns without any prior supervisory information. The initial selection of cluster centers plays a key role in the ultimate effect of clustering. More often researchers adopt the random approach for this purpose in an urge to get the centers in no time for speeding up their model. However, by doing this they sacrifice the true essence of subgroup formation and in numerous occasions ends up in achieving malicious clustering. Due to this reason we were inclined towards suggesting a qualitative approach for obtaining the initial cluster centers and also focused on attaining the well-separated clusters. Our initial contributions were an alteration to the classical K-Means algorithm in an attempt to obtain the near-optimal cluster centers. Few fresh approaches were earlier suggested by us namely, far efficient K-means (FEKM), modified center K-means (MCKM) and modified FEKM using Quickhull (MFQ) which resulted in producing the factual centers leading to excellent clusters formation. K-means, which randomly selects the centers, seem to meet its convergence slightly earlier than these methods, which is the latter’s only weakness. An incessant study was continued in this regard to minimize the computational efficiency of our methods and we came up with farthest leap center selection (FLCS). All these methods were thoroughly analyzed by considering the clustering effectiveness, correctness, homogeneity, completeness, complexity and their actual execution time of convergence. For this reason performance indices like Dunn’s Index, Davies–Bouldin’s Index, and silhouette coefficient were used, for correctness Rand measure was used, for homogeneity and completeness V-measure was used. Experimental results on versatile real world datasets, taken from UCI repository, suggested that both FEKM and FLCS obtain well-separated centers while the later converges earlier.
A novel ensemble approach for estimating the competency of bank telemarketing

Having a reliable understanding of bank telemarketing performance is of great importance in the modern world of economy. Recently, machine learning models have obtained high attention for this purpose. In order to introduce and evaluate cutting-edge models, this study develops sophisticated hybrid models for estimating the success rate of bank telemarketing. A large free dataset is used which lists the clients' information of a Portuguese bank. The data are analyzed by four artificial neural networks (ANNs) trained by metaheuristic algorithms, namely electromagnetic field optimization (EFO), future search algorithm (FSA), harmony search algorithm (HSA), and social ski-driver (SSD). The models predict the subscription of clients for a long-term deposit by evaluating nineteen conditioning parameters. The results first indicated the high potential of all four models in analyzing and predicting the subscription pattern, thereby, revealing the competency of neuro-metaheuristic hybrids. However, comparatively speaking, the EFO yielded the most reliable approximation with an area under the curve (AUC) around 0.80. FSA-ANN emerged as the second-accurate model followed by the SSD and HSA with respective AUCs of 0.7714, 0.7663, and 0.7160. Moreover, the superiority of the EFO-ANN is confirmed against several conventional models from the previous literature, and finally, it is introduced as an effective model to be practically used by banking institutions for predicting the likelihood of deposit subscriptions.
Developing Live-Interactive Approaches to New Music for Organ and Electronics Through Collaboration

In this article, I argue for a shift of focus from mechanical/technological and sonic approaches to music for organ and electronics towards the role of the organist as a performing musician in the collaborative development of new work. To do so, I address the roles and limitations of technologies in performance, taking an embodied approach to understanding and critiquing the work of the organist in the context of my collaboration with Alistair Zaldua (live electronics). I consider the practical solutions we have devised to allow performance in diverse spaces with diverse instruments as a hybrid instrumental practice, considering this an affordance rather than a problem to be solved. I offer three case studies: the preparation of an historical work for organ and electronics (Mesias Maiguashca, Nemos Orgel, 1971–1990); the realisation of the same concert in 5 contrasting spaces (orgel, orgel, orgel, orgel, orgel, 2021); and a collaboration focused on our performance practice (Annette Schmucki, 54 stops, 2020). By examining the development of live-interactive approaches through collaboration I seek to show what this hybrid practice offers for the realisation of this music, and what it means for the consideration of the performing experience of the organist.
Smart Job Advisor using NLP

This paper presents a novel automated system designed to streamline the resume short listing process, thereby facilitating the candidate selection procedure for the human resources department. In this system, HR personnel are required to simply upload the resumes, which are subsequently normalized and categorized based on a range of relevant parameters. The grouped resumes are then evaluated and assigned scores according to the specific criteria outlined by the HR department. Subsequently, the resumes are organized in descending order of their scores
Creative Technologies: A Conversation with Roy Magnuson

Click to increase image sizeClick to decrease image size Disclosure statementNo potential conflict of interest was reported by the author(s).
USING GIS SOFTWARE AND THE IMPORTANCE OF DIGITAL HISTORY IN THE STUDY OF HISTORY

The relevance of digital technologies in the study of history is the importance of conducting historical research in today's fast-moving picture era. Information about convenient and common ways of using them was given.
Unpaired Image-to-Image Translation Based Artwork Restoration Using Generative Adversarial Networks

Artworks assume huge significance in humankind’s culture and history. Artworks assimilate history and have the precise ability to tell history to the future generation. However, as time passes, environmental factors severely affect artworks, and these damages are often complicated to repair manually and through traditional methods. Conventional artwork restoration methods can not conserve the artist’s style and the artwork's semantic details. Restoration of the artworks through virtual restoration methods can be done using generative adversarial networks. After that, the virtually restored artwork can guide the physical restoration task of artworks. However, most of the methods based on generative adversarial network performs paired image-to-image translation for restoration, which necessitates the presence of the original version of the damaged artwork. This work proposes an unpaired image-to-image translation-based artwork restoration method using cycle-consistent generative adversarial networks. The proposed method does not require the availability of the original version of each damaged artwork for restoration. The network has been trained on a publicly available dataset of artwork images. The experimental results have been compared with other methods used for artwork restoration, and quantitative results demonstrate that the proposed approach performs better than the current and previous methods for the restoration of damaged artwork.
Data Rakshak

Abstract: Information security is essential as data exchange moves towards an electronic system. In today's visual communication system, picture, text, and video protection are crucial. Unauthorized uses of private videos, text, and image data must be prevented. It can be difficult to find and identify unauthorized users. Several researchers have proposed several methods for protecting the transfer of texts. We created an encryption and decryption technique with security in mind. We have primarily concentrated on data security, which may be utilized by security agencies, the IT sector, SMBs, the healthcare industry, governmental organizations, the legal industry, financial and banking institutions, etc
Creating Serverless Web Applications with AWS

Abstract: Serverless computing has emerged as a groundbreaking innovation, allowing organizations to alleviate the complexities associated with provisioning, scaling, and managing infrastructure. The surge in serverless adoption poses challenges in choosing optimal solutions amid a myriad of proposed designs by experts. This paper categorizes serverless patterns using a multivocal literature review, highlighting benefits and challenges in coordination, aggregation, event management, availability, communication, and validation. To illustrate the practical application of serverless computing, we present a case study involving the use of AWS Lambda, Amazon DynamoDB, and other services to process real-time data streams for a fictional ride-sharing company. The study showcases the advantages of serverless computing, emphasizing its ability to free developers from server-related concerns, enabling them to focus on building scalable and reliable applications. This paper contributes to the understanding of serverless computing's role in the broader context of cloud technologies and its application in real-world scenarios
Unravelling DevOps Agile Methodologies: A Comprehensive Review of Recent Research

Abstract: This study report offers a thorough analysis of current studies on DevOps Agile techniques. The study summarizes and dissects the major discoveries made in peer-reviewed literature, conference proceedings, and other academic publications. The article examines the most recent DevOps Agile practice trends and advances, as well as how they affect software development, testing, deployment, and operations. The analysis emphasizes the advantages of applying DevOps Agile approaches, including enhanced collaboration, faster time to market, and higher-quality software products. The paper also examines the challenges and potential limitations of DevOps Agile adoption, such as cultural resistance, lack of skills, and integration issues. Finally, the study concludes with recommendations for practical implications for software development teams and organizations seeking to implement DevOps Agile methodologies. The review provides valuable insights and guidance for researchers, practitioners, and decision-makers in the field of software engineering and information technology.
Fan translation and affective mediation

Abstract This study seeks to foreground the concept of ‘affective mediation,’ which is defined as an interventionist process in translation wherein affect is matched, managed, and modulated between communicating bodies. Situated in the context of fan translation, this study utilizes a multimodal analysis of the subtitling practice of Hiddles’ Translation Army of China, a Chinese internet-based, celebrity-oriented fan translation group, and identifies three ways its fansubbers mediate affect toward the object of fandom, i.e., British actor, Tom Hiddleston. The findings suggest that the fansubber’s mediation is conducive to restructuring the affective configuration in the target text and creates a site for emotive performance in fansubbing. The study also argues that affect-mediated fansubbing opens a new space outside the diegetic zone for an imagined interaction and relationship between the entire fandom community and the object of fandom.
VVIR-OM: Efficient Object Manipulation in VR with Variable Virtual Interaction Region

AbstractManipulating with virtual objects is a fundamental requirement in virtual environments. A good manipulation method needs to consider efficiency, accuracy, and comfort. This paper proposes VVIR-OM, an object manipulation method in virtual reality (VR) based on a variable virtual interaction region (VVIR). A hand interaction hemisphere region (HIHR) is introduced and constructed in real space, where the user is more comfortable manipulating the objects. Then a VVIR is introduced, and an interaction heat volume (IHV) based method is proposed to update VVIR during the process of the manipulation. At last, a mapping algorithm is proposed to map the user hand position in HIHR to the position in VVIR. Two user studies are designed to evaluate the performance of VVIR-OM. Compared to the state-of-the-art methods, VVIR-OM achieves significant improvements in task completion time, manipulation precision, and a significant reduction in fatigue. Moreover, VVIR-OM outperforms other methods in terms of task load and usability without the cost of cybersickness.Keywords: Virtual realityobject manipulationvariable virtual interaction regioninteraction heat volume Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is supported by the National Natural Science Foundation of China through Project 61932003, 62372026, by Beijing Science and Technology Plan Project Z221100007722004, and by National Key R&D plan 2019YFC1521102.Notes on contributorsQinwen ZhengQinwen Zheng is a master student in the School of Computer Science and Engineering of Beihang University, China. His current research focuses on virtual reality, augmented reality, and HCI.Lili WangLili Wang received her PhD degree from Beihang University, Beijing, China. She is a professor with the School of Computer Science and Engineering of Beihang University and a researcher with the State Key Laboratory of Virtual Reality Technology and Systems. Her interests include virtual reality, real-time rendering and HCI.Wei KeWei Ke received his PhD degree from Beihang University, Beijing, China. He is currently a professor at the Faculty of Applied Sciences, Macao Polytechnic University. His research interests include programming languages, image processing, computer vision, and tool support for component-based engineering and systems.Sio Kei ImSio Kei Im received his PhD degree from Queen Mary University of London, United Kingdom. He is a professor at the Faculty of Applied Sciences, Macau Polytechnic University. His research interests include video coding, image processing, machine learning for NLP and multimedia.