Reviewerly/exHarmony huggingface dataset:
Calliope: A Co-creative Interface for Multi-Track Music Generation

Calliope is a web application for co-creative multi-track music composition (MMM) in the symbolic domain. It is built to facilitate the use of multi-track music machine (MMM). The user can upload Musical Instrument Digital Interface (MIDI) files, visualize and edit MIDI tracks, and generate partial (via bar in-filling) or complete multi-track content using the Multi-Track Music Machine (MMM). Generation of new MIDI excerpts can be done in batch and can be combined with active playback listening for an enhanced Computer-assisted Composition (CAC) workflow. The user can export generated materials as MIDI files or directly stream MIDI playback from the system to their favorite Digital Audio Workstation (DAW). Calliope can be used for creative ideation and for exploring alternatives of musical phrases in composition.
GENRE BASED APPROACH TO IMPROVE STUDENTS’ WRITING ABILITY OF TENTH GRADERS OF SENIOR HIGH SCHOOL

The purpose of this study is to portray the effect of Genre-Based Approach on the writing skills of tenth-grade high school students from three major islands in Indonesia; Sulawesi, Sumatra and Java. This study employs a qualitative research design, which describes the effectiveness of the genre-based approach on students' writing skills. The data collection technique used in this study is library research (literature study) where the data was collected from scientific journals and other publications that were worthy of being research sources. The results of this study indicate that the genre-based approach has a positive effect in improving students' abilities on several big islands in Indonesia (Sulawesi, Sumatra, and Java) as evidenced by pre-test to post-test results which have increased. The significant of this study is to add insight for readers about the effectiveness of the genre-based approach in teaching writing in senior high school levels especially in tenth grade
Statistics in corpus linguistics: A practical guideVaclavBrezinaCambridge University Press, 2018

The peer review history for this article is available at https://publons.com/publon/10.1111/ijal.12430
Emotional Closeness by Means of Intelligent Thoughts and Memory Spaces

This blue sky paper envisions a novel system which promotes emotional closeness through storytelling. Family members, who may be separated, collaboratively build a spatial hypertext of images and text fragments to express and structure their thoughts and memories. The system observes their reactions as well as their media while they work. Live recommendations prompt users in their thinking and storytelling. Family stories are thus collaboratively adapted to more tightly connect the thoughts and emotions of their loved ones.
Minimizing Risk of Disputes Among Telecommunication Carriers With Blockchain Technologies

In recent years, blockchain technologies are constantly transforming many business processes. A shared, distributed ledger has revolutionized transaction recording, handling trust, and robustness in business network participants. In the telecommunication sector, the primary concern of voice over internet protocol (VoIP) providers when exchanging calls is the transparent storage of call detail records (CDRs) to avoid billing discrepancies, disputes, and interruption of services. In this chapter, the authors aim to investigate the utilization of permissioned blockchain in carriers' business models in telecommunication. They propose a business model architecture based on hyperledger fabric for developing smart contracts, which are invoked to store information about each CDR generated and business cases. The necessary steps and configurations for integrating the different technologies and building a development network are presented. Finally, the performance testing results regarding the latency for a transaction submission are shown.
Two-step robust control design of quantum gates via differential evolution

Designing highly accurate and robust controls for quantum unitary operations is vital for practical quantum computation. In this paper, we demonstrate that the robustness of quantum gate controls can be enhanced by optimizing the sampling-based infidelity variance, which is formulated as a multi-objective optimization task to achieve high robustness while maintaining high gate fidelity. A two-step approach that first optimizes the average fidelity and then turns to the infidelity variance is proposed, where two modified differential evolution (DE) algorithms, i.e., mixed-guided-strategy DE (MGSDE) and multi-objective mixed-strategy DE (MOMSDE), are designed to search fields for the two steps of robust quantum gate control, respectively. Both MGSDE and MOMSDE adopt the mixed strategy, and in particular, MGSDE adopts a guided mutation scheme to accelerate the convergence, and MOMSDE uses an optimal buffer to explore the Pareto front. Numerical results demonstrate that the proposed approach enhances the control robustness and provides an efficient in-situ learning paradigm to tackle the disturbance problem for the control design of quantum gates.
Sand Playground: Designing Human-AI physical Interface for Co-creation in Motion

In this paper, we investigated the potential of using a tangible interaction interface for creative activities as a preliminary step to achieve human-AI co-creation. We conducted a preliminary study to explore sand as a medium for co-creation and identify potential opportunities of AI mediating the process. We created Sand Playground, a co-creation interface that uses sand as an interaction medium. We describe details for building the interface. We selected two opportunities from the study and developed them as two modes, Artistic Mimicry and Zen Garden. We also conducted a workshop study using Sand Playground to evaluate collaboration and the characteristics of the tangible interface. We identified findings responding to drawing strategies, multisensorial experience, and performative and ephemeral quality of creation. We discuss next steps of achieving our ultimate goal: an AI-mediated interface that collaborates with users physically in real-time on sand.
The Effects of Spatial Visualization versus Ranked Lists on Quality, Time Efficiency, and Interaction

Hypertext systems support users in navigating structured data sets and to find relevant information. Various interaction and visualization concepts aim to give users better insight into the data set, by suggesting queries and visualizing elements of interest in a meaningful way. Ranked lists are very common to show some sort of priority, while spatial layouts often help users to trace relations in the data. Only little research has been done in user studies that systematically show and reason about the differences of such spatial layouts and ranked lists. In this paper we report on a systematic comparison of a spatial visualization versus a ranked list layout. For this purpose, we did an between-subject study with 43 participants. One group performed a task with a system providing semantic visualization in 2D, the other group performed the same task with a ranked list. Both interfaces are very similar and only differ in how suggestions are visualized. The results show that users of the spatial layout finished their task in shorter time and have a tendency towards higher satisfaction. At the same time, they had more interactions with the system. Furthermore we discuss some in-depth data of the test sessions, which show that the visualization influences the users’ behavior.
Banking Supervision and Nonperforming Loans in Africa: <i>Does Institutional Quality Matter in the Ghanaian Banking Space</i>?

In this paper, we reexamine the determinants of nonperforming loans through the impact of supervisory devices in credit risk management in Africa. The paper employs bank-specific, macroeconomic and institutional data for a panel of 14 universal banks over the period 2009 to 2020. We develop models that capture the role of regulatory supervision on credit risk. Findings from the Panels Corrected Standard Errors (PCSE) and the system GMM shows that previous year’s NPL and inflation significantly affect NPLs in the banking space of Gana. Bank size and financial development are inversely associated with NPLs. The interactive term of regulatory quality and government effectiveness on NPLs has net negative effect. This suggest that regulatory quality enhances the reductive effects of government effectiveness on NPLs. Our findings in general lends credence to the financial instability theory as NPLs in the Ghanaian context has been the outcome of activities of speculative borrowers.
Blockchain for SMEs

Blockchain technology is spreading across many sectors as many firms are understanding its potential. In particular, such a technology may impact the way in which many SMEs compete, offering them new ways to achieve competitive advantage. However, many of them are struggling to embrace blockchain, thus requesting that the discussion on the issue be deepened. For this reason, in this chapter, the authors propose a review of the literature about blockchain and they show the main areas in which such technology is actually used. Moreover, they propose a discussion of the public policies adopted by Europe and they highlight possible future challenge for SMEs aiming at adopting the new technology.
The Web At War: Hypertext, Social Media, and Totalitarianism

In 2022, much of the world faced the prospect of a prolonged conventional war with a totalitarian state. The origins of hypertext lie in the wars of the 20th Century, and efforts to avoid a repeated conflict — and confidence that conflict could be contained if not entirely avoided— is deeply embedded into the architecture of the World Wide Web. The Web was not designed to confront a war, and it remains deeply vulnerable to totalitarian subversion. Our systems, platforms, and our discipline will need to adapt.
Improving the visual quality of a size deterministic visual cryptography scheme for Grayscale Images

AbstractAbstractTo enhance the security choices in transmission of information over the web, various methods such as cryptography, steganography and digital watermarking have been developed. Visual cryptography has developed in the past decade as an entity that splits the information into two parts in order to complete integration. This system is also secured in a lesser quantity. In this paper a secret message multi-share method is used. In the proposed work input picture is divided into eight portions. The eight portions shares are encrypted before embedding the image in the patchwork image, photo sharing and the image retrieved is the same as the hidden starting image. Results show that the proposed method has optimized the optimal time by 8%, improved PSNR by 11% and lower overhead communication.Subject Classification: 68M1068M1268M15Keywords: CryptographySecurityImagePSNR
Morphing Matter for Girls

Morphing Matter (MM) is an emerging multidisciplinary field that combines material science and digital fabrication. It empowers people to engineer materials that respond to a specific energy or stimuli and transform its shape or other characteristics such as stiffness, opacity, and phase. This poster introduces creative pathways with MM to engage girls in science, technology, engineering, and mathematics (STEM) learning, sparking interest in the field. We share our experience designing a set of learning tools that introduce novices to MM by fabricating morphing artifacts triggered by water. Further, we present a pilot MM workshop highlighting our reflections on designing learning experiences to foster high-school-aged girls' curiosity and interest in STEM.
NeuroView-RNN: It’s About Time

Recurrent Neural Networks (RNNs) are important tools for processing sequential data such as time-series or video. Interpretability is defined as the ability to be understood by a person and is different from explainability, which is the ability to be explained in a mathematical formulation. A key interpretability issue with RNNs is that it is not clear how each hidden state per time step contributes to the decision-making process in a quantitative manner. We propose NeuroView-RNN as a family of new RNN architectures that explains how all the time steps are used for the decision-making process. Each member of the family is derived from a standard RNN architecture by concatenation of the hidden steps into a global linear classifier. The global linear classifier has all the hidden states as the input, so the weights of the classifier have a linear mapping to the hidden states. Hence, from the weights, NeuroView-RNN can quantify how important each time step is to a particular decision. As a bonus, NeuroView-RNN also offers higher accuracy in many cases compared to the RNNs and their variants. We showcase the benefits of NeuroView-RNN by evaluating on a multitude of diverse time-series datasets.
PENYEBAB DAN ALTERNATIF MITIGASI BENCANA BANJIR DI GRESIK SELATAN

One of problems that often occur in Gresik Regency in Gresik City is Floods. As a result of flood, the biggest impact occurred in the Districts of Cerme, Benjeng, Menganti, and Balongpanggang. The research has a purpose, namely, to find out what factors cause flooding in the South Gresik City Region. The methods used are interviews and questionnaires. Interviews were used to determine the type of flood mitigation that was suitable for the southern Gresik City area. While the questionnaire was given to determine the appropriate mitigation according to the existing conditions in the area or the factors causing flooding in the southern Gresik City area. Mixed Methods were used to collect data with qualitative and quantitative data types. Qualitative data was conducted through direct observation and interviews. While the quantitative data was obtained from questionnaire results. From the results of the analysis using Nvivo 12 plus©, the cause of flooding that often occurs in Gresik City is caused by the overflow of the Lamong River. Rather than that caused by the river experiencing siltation. This causes runoff to overflow. Mitigation is one thing that can be done when there is a flood in the southern Gresik City area. Analytic Hierarchy Process (AHP) is a river improvement and regulation system which includes benchmarks with the highest yield of 0.558. The best alternative is River improvement, namely river dredging with a weight of 0.404.
Blockchain and Financial Market Innovation

The financial sector, which witnesses millions of transactions every day, is exploring the possibilities with blockchain and how it can leverage this technology for a safer and secured investment environment. This chapter explains the innovative products and services that have been introduced in the financial markets based on this technology. It further explains the benefits derived in the securities market and the insurance sector through the adoption of this technology. Usage of blockchain also faces many challenges in the technical, business, and regulatory areas, which are discussed in the chapter.
Social Media and School Libraries in the Wake of the COVID-19 Pandemic

The COVID-19 pandemic has presented school libraries with opportunities and challenges that are unprecedented in the history of humankind as evidenced by total shutdowns, lockdown rules and regulations, and adaptation of emerging technologies for supporting teaching and learning in educational institutions. This chapter provides a general overview of the experiences of school libraries in a selected district in Manicaland, Zimbabwe. It highlights how the digital divide disadvantages school libraries that are resource famished. Using a qualitative methodology, the chapter interrogates how the adaptation of social media platforms has helped school libraries to contribute towards learning amidst the complications of the COVID-19 pandemic.
Analysis of the Style Characteristics of National Dance Based on 3D Reconstruction

National dance is an important symbol of national spiritual culture, as it embodies each nation's unique history, living habits, ideology, and culture. Many Chinese ethnic groups have developed their own dance forms and styles, each with their own set of charms. Strengthening our understanding of its style and characteristics is critical to our understanding of the national dance. To begin with, this paper proposes a patch-based multiview stereo reconstruction scheme that can accurately reconstruct 3D character models. The movement capture system then collects national dance movement data and uses them to drive a three-dimensional character model that generates dance visual animation. In the human skeleton model, a spatial-temporal HMM (hidden Markov model) is proposed that not only studies the temporal information of human movements but also the spatial information of adjacent connection points. The recognition rate of this algorithm increases to 95.68 percent when the number of setting points is increased to ten and to 98.28 percent when the number of setting points is increased to twenty, according to the research. The experimental results show that the 3D reconstruction model of ethnic dance developed in this paper is capable of meeting the goal of ethnic dance digitalization while being simple to use, being low in cost, and with a good display effect.
Application of Blockchain Technology for Distributed Management of Digital Research Library Holdings

Technological advancement is gradually shifting the paradigm of how network records and transactions are processed and secured without third-party intervention. The importance of blockchain technology in performing these roles cannot be overstated. This technology has a wide application in the health, banking, insurance, real estate, media, and transportation sectors. Nevertheless, the role of blockchain technology in the distributed management of digital research library resources has received limited attention. This chapter discusses the distributed management of digital research library resources through blockchain technology. It explains the meaning, features, and components of blockchain technology. Concepts such as distributed library management and digital research library were clarified. The digital research library materials were highlighted along with how they can be managed. The chapter thus argues that blockchain technology can be used in the distributed management of digital research library resources.
Copyright Infringement Detection of Multimedia Objects using K-L Transform

Presents the copyright information for the conference. May include reprint permission information.
Otus: A Gaze Model-based Privacy Control Framework for Eye Tracking Applications

Eye tracking techniques have been widely adopted by a wide range of devices (e.g., AR/VR headsets, smartphones) to enhance user experiences. However, eye gaze data is private in nature, which can reveal users’ psychological and physiological features. Privacy protection techniques can be incorporated to preserve privacy of eye tracking information. Yet, most existing solutions based on Differential Privacy (DP) mechanisms cannot well protect privacy for individual users without sacrificing user experience. In this paper, we are among the first to propose a novel gaze model-based privacy control framework called Otus for eye tracking applications, which incorporates local DP (LDP) mechanisms to preserve user privacy and improves user experience in the meanwhile. First, we conduct a measurement study on real traces to illustrate that direct noise injection on raw gaze trajectories can significantly lower the utility of gaze data. To preserve utility and privacy simultaneously, Otus injects noises in two steps: (1) Extracting model features from raw data to depict gaze trajectories on individual users; (2) Adding LDP noises into model features so as to protect privacy. On one hand, established models can be used to recover user gaze data in order to improve service quality of eye tracking applications. On the other hand, we only need to add LDP noises to distort a small number of model parameters rather than every point on a trajectory to preserve privacy, which has less impact on the utility of gaze data given the same privacy budget. By applying the tile view graph model in step (1), we illustrate the entire workflow of Otus and prove its privacy protection level. For evaluation, we conduct extensive experiments using real gaze traces and the results show that Otus can effectively protect privacy for individual users without significantly compromising gaze data utility.
Order Matters: On the Impact of Swapping Order on an Entanglement Path in a Quantum Network

In this paper, we study the properties of path metrics of an entanglement path for a given entanglement swapping order of the path. We show how to efficiently compute the path metrics of an entanglement path for any given swapping order. We show that different entanglement swapping orders for the same path can lead to different expected throughputs. A key finding is that the binary operator corresponding to entanglement swapping along a path is not associative. We further show that the problem of computing an s-t path with maximum expected throughput under any entanglement swapping order does not have the subpath optimality property, which is a key property most path finding algorithms such as Dijkstra’s algorithm rely on. We use extensive simulations to validate our theoretical findings.
Optimal Routing for Stream Learning Systems

Consider a stream learning system with a source and a set of computation nodes that solves a machine learning task modeled as stochastic convex optimization problem over an unknown distribution D. The source generates i.i.d. data points from D and routes the data points to the computation nodes for processing. The data points are processed in a streaming fashion, i.e., each data point can be accessed only once and is discarded after processing. The system employs local stochastic gradient descent (local SGD), where each computation node performs stochastic gradient descent locally using the data it receives from the source and periodically synchronizes with other computation nodes. Since the routing policy of the source determines the availability of data points at each computation node, the performance of the system, i.e., the optimization error obtained by local SGD, depends on the routing policy.In this paper, we study the influence of the routing policy on the performance of stream learning systems. We first derive an upper bound on the optimization error as a function of the routing policy. The upper bound reveals that the routing policy influences the performance through tuning the bias-variance trade-off of the optimization process, and gives rise to a framework for optimizing the routing policy for stream learning systems. By minimizing the upper bound, we propose an optimal static routing policy that achieves the best trade-off for stream learning systems with deterministic data generation process. We then propose a routing policy that can approximate the optimal static routing policy arbitrarily closely for systems where the data points are generated according to a stochastic process with unknown rate. Finally, we conduct simulations using Support Vector Machine as the machine learning task on a real data set, and show that the optimal static routing policy has excellent empirical performance in terms of minimizing the optimization error and the proposed stochastic routing policy closely matches the optimal static routing policy.