Reviewerly/exHarmony huggingface dataset:
Fulfilling social needs through anthropomorphic technology? A reflection on existing research and empirical insights of an interview study

Abstract As interactive technologies, such as chatbots or voice assistants, increasingly become social counterparts and resemble human interaction partners in many ways, the question arises whether they are also able to address users’ social needs. This paper explores whether interaction with technology can address social needs and what role technology anthropomorphism plays in this. While previous research shows somewhat contradictory results potentially related to challenges of applied assessment methods of anthropomorphism and social needs, we complement this by means of a qualitative interview study ( n = 8). Our study findings support a potential of anthropomorphic technology to address users’ social needs but also highlight differences between the quality of human-technology and interpersonal interaction. In addition, our findings hint at a social desirability bias, since people see social need fulfillment through technology as silly or inappropriate. Design and societal implications are discussed. Practical Relevance: This article explores the potential of technology to address users’ social needs and discusses practical implications for marketing and design, e.g., how technologies should be designed in order to affect users’ social needs and which contexts of application might be suitable. Moreover, the article also reflects on societal implications resulting from a potential effect of interaction with technology on users’ social needs.
Integrodifferential equation in the multimode Jaynes-Cummings model

We investigate the multimode Jaynes-Cummings model. The population of the excited state of an atom is expressed by an integrodifferential equation. The exact solution is found in an idealized case by taking the infinite limit of the number of modes. The solution shows a mathematical reason why the kinklike behavior of the excited-state population appears. We also confirm that numerical calculations agree with the exact solution.
Bounds on the Capacity of Private Information Retrieval Over Graphs

In the private information retrieval (PIR) problem, a user wants to retrieve a file from a database without revealing any information about the desired file’s identity to the servers that store the database. In this paper, we study the PIR capacity of a graph-based replication system, in which each file is stored on two distinct servers according to an underlying graph. This paper aims to provide upper and lower bounds to the PIR capacity of graphs via various graph properties. In particular, we provide several upper bounds on the PIR capacity that apply to all graphs. We further improve the bounds for specific graph families (which turn out to be tight in certain cases) by utilizing the underlying graph structure. For the lower bounds, we establish optimal rate PIR schemes for star graphs via edge-coloring techniques. Lastly, we provide an improved PIR scheme for complete graphs, implying an improved general lower bound on all graphs’ PIR capacity.
Scale Invariant low frame rate tracking

The cameras used for road surveillance present low image quality and significant variability of objects’ scale, making real-time vehicle detection and tracking challenging. This paper proposes Scale Invariant Low Frame Rate Tracking, called SILFT, a new methodology to track vehicles in most surveillance systems whose frame rate and resolution are low. This architecture uses the fusion of a dense optical flow with object detection in a 6-step pipeline. The detections are masks for the optical flow that later will be used for finding the object correspondence between frames, making it effective in low frame rate sequences with large object scale variability. SILFT achieved average precision for detection of 65.97%, surpassing the YOLO and FASTER R-CNN models in the proposed database. For the tracking task, SILFT achieved a PR-MOTA of 0.45, whereas the YOLO model with intersection over union tracking achieved 0.13 in the proposed dataset.
EDUCATE AND LEARN IN THE DIGITAL AGE: THE PRESENT AND THE FUTURE OF THE PROFESSIONAL DEVELOPMENT SYSTEM FOR LIBRARY USERS AND STAFF

The article presents the experience of creating the professional development system for users and staff of Research and Technical library of Tomsk Polytechnic University. It includes such courses as the «Information culture of students», «How to Write a Scientific Article», «Information resources and citation indexes for scientific activity», «Digital tools for supporting research activities», «E-resources and services of TPU library», and different webinars, seminars and professional development courses for library staff. Special attention is paid to the application of online learning technologies, that was actively used during the pandemic and distance and hybrid learning formats at the university. The article presents the comparative analysis of users' requests to the library services before and after the introduction of this system. The proposals for its development and improvement are given.
Online learning attributes on overall tourism and hospitality education learning satisfaction: Tourism Agenda 2030

Purpose Promoting “Quality Education” as part of Sustainable Development Goal 4 requires educational stakeholders to understand the nature of online learning from the learners’ perspective. This study aims to explore the asymmetric effects of online learning attributes on overall learning satisfaction in tourism and hospitality education. Design/methodology/approach The authors adopt the three-factor satisfaction theory and the three analytical steps penalty–reward contrast analysis, impact range performance analysis (IRPA) and impact asymmetry analysis. The authors then juxtapose the results of such analytical approaches to the traditional importance–performance analysis (IPA) for further insights. Findings Traditional IPA suggests nine high importance and performance online attributes. However, the IRPA reveals that only four attributes fall within high performance and high range of impact on satisfaction. The attribute “secure” had a low performance despite a significant impact on satisfaction. Research limitations/implications By exploring asymmetric effects, scholars, service providers and participants of online education can have a deeper insight into the nature and dynamic effect of attributes on overall satisfaction. Originality/value By exploring the asymmetric impacts of online learning attributes on overall learning satisfaction, the findings provide a novel insight into the multidimensionality of online learning attributes.
Improving the Efficiency of Report and Trace Ring Signatures

Ring signatures allow signers to produce verifiable signatures and remain anonymous within a set of signers (i.e., the ring) while doing so. They are well-suited to protocols that target anonymity as a primary goal, for example, anonymous cryptocurrencies. However, standard ring signatures do not ensure that signers are held accountable if they act maliciously. Fraser and Quaglia (CANS’21) introduced a ring signature variant that they called report and trace ring signatures which balances the anonymity guarantee of standard ring signatures with the need to hold signers accountable. In particular, report and trace ring signatures introduce a reporting system whereby ring members can report malicious message/signature pairs. A designated tracer can then revoke the signer’s anonymity if, and only if, a ring member submits a report to the tracer. Fraser and Quaglia present a generic construction of a report and trace ring signature scheme and outline an instantiation for which it is claimed that the complexity of signing is linear in the size of the ring |R|. In this paper, we introduce a new instantiation of Fraser and Quaglia’s generic report and trace ring signature construction. Our instantiation uses a pairing-based variant of ElGamal that we define. We demonstrate that our instantiation is more efficient. In fact, we highlight that the efficiency of Fraser and Quaglia’s instantiation omits a scaling factor of $$\lambda $$ where $$\lambda $$ is a security parameter. As such, the complexity of signing for their instantiation grows linearly in $$\lambda \cdot |R|$$ . Our instantiation, on the other hand, achieves signing complexity linear in |R|. We also introduce a new pairing-free report and trace ring signature construction reaching a similar signing complexity. Whilst this construction requires some additional group exponentiations, it can be instantiated over any prime order group for which the Decisional Diffie-Hellman assumption holds.
Generation of Perfectly Entangled Two and Three Qubits States by Classical Random Interaction

Abstract This study examines the possibility of finding perfect entanglers for a Hamiltonian which corresponds to several quantum information platforms of interest at the present time. However, in this study, a superconducting circuit is used that stands out from other quantum‐computing devices, especially because transmon qubits can be coupled via capacitors or microwave cavities, which enables to combine high coherence, fast gates, and high flexibility in its design parameters. There are currently two factors limiting the performance of superconducting processors: timing mismatch and the limitation of entangling gates to two qubits. In this work, a two‐qubit SWAP and a three‐qubit Fredkin gate is presented, additionally, a perfect adiabatic entanglement generation between two and three programmable superconducting qubits is also demonstrated. Furthermore, the impact of random dephasing, emission, and absorption noises on the quantum gates and entanglement is also demonstrated in this study. It is demonstrated by numerical simulation that CSWAP gate and W ‐state generation can be achieved perfectly in one step with high reliability under weak coupling conditions. Hence, this scheme could contribute to quantum teleportation, quantum communication, and some other areas of quantum information processing.
An efficient facial expression recognition system with appearance-based fused descriptors

Facial expressions have always been defined as the most efficient way to characterize emotions. Therefore, they have been used in various fields of applications such as human-computer interaction. With the continuous progress in terms of image processing and machine learning techniques, several new methods are proposed each year. However, their performance still needs to be improved and this task remains challenging. In this paper, we propose an automatic emotion recognition system through facial analysis. We compare the use of two distinct image descriptors namely, Local Binary Pattern and Histogram of Oriented Gradients with two different dimensionality reduction techniques namely, Principal Component Analysis and Locally Linear Embedding. Moreover, we also combine both descriptors in order to improve the system efficiency. For the classification part of the system, we choose to use the multi-class Support Vector Machine classifier for its generalization capabilities to distinguish between the six basic emotions. Finally, we assess the performance of the proposed system using three different benchmark facial expression datasets namely, JApanese Female Facial Expression (JAFFE), Karolinska Directed Emotional Faces (KDEF) and Radboud Faces Database (RaFD) which yield promising recognition rates with 97.16%, 90.12% and 95.54%, respectively.
Enhanced photonic time-stretch reservoir computing using all-optical input masks

Input masks are essential in reservoir computing to enhance its performance.Here we report a novel all-optical masking scheme for photonics time-stretch reservoir computing based on optical spectral filtering.This approach overcomes the electronic bottleneck in digital temporal masking and offers better performance in classification tasks.
Comparison Between Acoustic Spectral Evolutions of Violins Before and After Varnishing

The construction of the violin involves numerous technological processes and materials that influence the acoustic quality of the violins. Over time, the influence of the various factors that can influence the acoustics of the musical instrument, from material to geometry, has been studied. An important factor, highlighted in the specialized literature, is the varnish that covers the violin body, as it can change the stiffness of the plates. The purpose of this study was the comparative analysis of the spectral evolution of a violin before and after varnishing in order to observe the changes in frequency that occur shortly after covering the violin with varnish, respectively after one year.
Evolutionary Echo State Network: evolving reservoirs in the Fourier space

The Echo State Network (ESN) is a class of Recurrent Neural Network with a large number of hidden-hidden weights (in the so-called reservoir). Canonical ESN and its variations have recently received significant attention due to their remarkable success in the modeling of non-linear dynamical systems. The reservoir is randomly connected with fixed weights that don't change in the learning process. Only the weights from reservoir to output are trained. Since the reservoir is fixed during the training procedure, we may wonder if the computational power of the recurrent structure is fully harnessed. In this article, we propose a new computational model of the ESN type, that represents the reservoir weights in the Fourier space and performs a fine-tuning of these weights applying genetic algorithms in the frequency domain. The main interest is that this procedure will work in a much smaller space compared to the classical ESN, thus providing a dimensionality reduction transformation of the initial method. The proposed technique allows us to exploit the benefits of the large recurrent structure avoiding the training problems of gradient-based method. We provide a detailed experimental study that demonstrates the good performances of our approach with well-known chaotic systems and real-world data.
Peculiarities of Training Future Teachers of Music Art in Higher Educational Institutions in Terms of Distance Learning

The article highlights the main aspects of distance learning in the context of training future teachers of musical art. The study identifies the main approaches to the implementation of distance learning, identifies the pedagogical features and the most effective technologies and methods of distance learning in higher education institutions. The article forms the objectives, providing for the implementation of conceptual foundations for the training of future teachers of musical art in higher education institutions. The study presents theoretical and methodological substantiation of the concept of distance education, the profession of music art teacher and pedagogical foundations for higher education based on the conclusions of researchers and scientists on the relevant problem. Distance learning is widespread in today's global development, especially in the pandemic. This type of learning is an alternative to traditional learning, because it simplifies the educational process and is available to more people, develops the individual traits of each person in an online learning environment. Distance learning encourages the creation of online platforms that involve individual tasks and build competencies in various fields and branches. The study used the integrative method of synthesis and analysis of the main trends of distance learning. Research, descriptive and scientific methods were also applied to study aspects of the training of future teachers of musical art. The results of the study identified effective foundations for teacher education that improve distance learning.
Emotion Detection on Indonesian Tweets Using CNN and Contextualized Word Embedding

Twitter is one of the popular social media to share information through text with a limit of 280 characters called tweets. Many tweets express the emotions of their users, and many studies have been conducted to detect emotions in tweets. In this paper, we train machine learning models to classify Indonesian tweets into five emotion class labels: happy, angry, fear, sadness, and love. The models are based on Convolutional Neural Network (CNN) combined with ELMo (Embedding from Language Models, BERT (Bidirectional Encoder Representations from Transformers), or Word2Vec. Based on the experiment result, we conclude that the best CNN model on tweet data without stemming is BERT-CNN, with a macro-averaged f1-score of 72.83%, compared with the ELMo-CNN model, which has a macro-averaged f1-score of 55.69% and Word2Vec-CNN, which has a macro-averaged f1-score of 65.57%.
Classification of some cosets of the Reed-Muller code

This paper presents a descending method to classify Boolean functions in 7 variables under the action of the affine general linear group. The classification determines the number of classes, a set of orbits representatives and a generator set of the stabilizer of each representative. The method consists in the iteration of the classification process of $$RM(k, m)/RM(r-1, m)$$ from that of RM(k, m)/RM(r, m). We namely obtain the classifications of RM(4, 7)/RM(2, 7) and of RM(7, 7)/RM(3, 7), from which we deduce some consequences on the covering radius of RM(3, 7) and the classification of near bent functions.
Uncertainty relation based on metric-adjusted skew information with quantum memory

Abstract The uncertainty principle is one of the most essential features of quantum mechanics. Recently, uncertainty relations of skew information have been widely studied. In this paper, general and conditional uncertainty relations based on metric-adjusted skew information are put forward to study the case of the uncertainty relation with the existence of a quantum memory for the bipartite quantum system. These uncertainty relations include the product form and the sum form. The results show that the lower bounds contain two parts: one is characterizing the degree of compatibility of two measurements, and the other one is the quantum correlation between the measured system and the quantum memory. These results may play an important role in witnessing entanglement and quantum key distribution.
Development of Application for Entity-Relationship Diagram Conversion to Logical Schema of NoSQL Column Oriented

The increasing usage of column-oriented NoSQL drives people to define methods to model the data structure of this technology. The data modelling methods require the support of tools or applications to make the modelling process faster and more accurate. In this research, we develop an application for converting conceptual data model depicted in Entity Relationship Diagram (ERD) to logical schema of column-oriented NoSQL and conversion of the logical schema to a data definition language for column-oriented NoSQL. First, we analyze how to convert data models drawn in the ERD to the logical model of column-oriented NoSQL based on an existing work. We provide an algorithm to perform the conversion from the ER model to the logical model of the NoSQL and produces a data definition language in the form of Cassandra Query Language (CQL), one of the column-oriented NoSQL database. The application is then built based on the analysis result and the algorithm. We employed software analysis models to design of the application. The testing of the application shows that the conversion from ERD to logical schema of column-oriented database as well as generation of data definition language to CQL are successfully carried out by the application. The test is done on various scenarios which cover various aspects of the ERD to show the broad capability of the application.
THE MAIN STAGES OF THE FORMATION OF THE KRASNOYARSK WRITERS' ORGANIZATION

The article considers the main stages of the formation of the Krasnoyarsk writers' organization. The purpose of the study is to consider the prerequisites and stages of formation of the Krasnoyarsk writers' organization. On the basis of the historical-genetic method of research, the author examines the fact of the emergence of a writers' organization in 1946 and highlights the main stages of its formation. Based on the results of the analysis of literature, documentation and archival sources, the author singled out and characterized two main stages in the formation of the Krasnoyarsk writers' organization.
AI inventors: deference for legal personality without respect for innovation?

Journal Article AI inventors: deference for legal personality without respect for innovation? Get access Ernest Kenneth-Southworth, Ernest Kenneth-Southworth Search for other works by this author on: Oxford Academic Google Scholar Yahong Li Yahong Li Search for other works by this author on: Oxford Academic Google Scholar Journal of Intellectual Property Law & Practice, Volume 18, Issue 1, January 2023, Pages 58–69, https://doi.org/10.1093/jiplp/jpac111 Published: 20 December 2022 Article history Received: 08 December 2022 Accepted: 11 December 2022 Corrected and typeset: 20 December 2022 Published: 20 December 2022
Service composition based on genetic algorithm and fuzzy rules

The expansion of service-oriented architecture and the increasing number of web services has led to an increase in demand for their use. But since a single service alone may not be enough to meet the most relatively complex business processes requirements, it is necessary to combine several individual services to deliver user satisfaction. By increasing the number of services that have the same functionality, the quality of service provided by each service will play an important role in the service selection process; in the process of service composition, different services with different quality parameters come together to provide a new task. Therefore, offering the best quality service to the user is considered an important issue. The challenging issues in the service composition process include how to combine the web services with quality parameters based on user preference, long response time for the composition process, large search space, and the correlation between the services. In this paper, the quality-based service composition is modeled by considering the relationship between the services to improve the quality of service (QoS) parameters. The proposed model consists of several steps. In the first step, the inappropriate services will be pruned by applying the correlation between the services. In the second step, by determining the quality levels for the QoS, the APSO algorithm is used to select the best levels and, finally, the best services. In the service combination stage, the services selected from the previous stage are combined using a fuzzy genetic algorithm (FGA) to create a suitable combination service. The results show that when the correlation between the services is considered, the response time criterion improves significantly by integrating the quality parameters and pruning the candidate services, and reduces the search space.