Reviewerly/exHarmony huggingface dataset:
Transformasi Model Bisnis Museum Ke Pariwisata Digital Di Indonesia

Background – Because of the Covid-19 pandemic, human travel was severely restricted and reliant on digital technology. Tourism is one of the businesses that has been obliged to adapt to digitalization in order to keep its primary source of income from travelers. The present transition to digital tourism is taking the shape of virtual tours or long-distance interactive tours, such as those seen in museums. To reach more tourists, some museums in Indonesia already entered the digitization stage by offering virtual tours and edutainment.&#x0D; Aim – This study intends to provide emphasis on the advantages and disadvantages of disruptive innovation in the sense of digitization in the tourism industry, particularly museums.&#x0D; Design / Methodology / Approach – An detailed review of existing literature regarding digital technology, disruptive digital innovation, smartphone technology, social media, internet, and mobile applications from the perspective of museum tourism was used.&#x0D; Findings – Digital museums provide a new perspective to enjoy their collections and as a diversification strategy that has the potential to bring in tourists virtually. Curators should develop websites using communication strategies that relate to their collection and focus on their visitor profile. On the other hand, there is a risk that there is a conservative opinion that digitization will reduce the integrity of physical artwork and an unstable digital ecosystem.&#x0D; Conclusion - The digitization and publication of collections online has the potential to enable access to content. It is projected that disruptive innovation in the form of changing the museum's business model will provide financial benefits and become a business diversification that can support the sustainability of the museum itself in the future.&#x0D; Research implication – In the field of management, disruptive innovation in the form of changing the museum's business model will provide financial benefits and become a business diversification that can support the sustainability of the museum itself in the future. In the field of architecture, the preservation of cultural heritage objects through digitization guarantees digital archives and provides wider educational opportunities virtually.&#x0D; Research Limitations – The breadth of coverage regarding the digitization of museums and also the many things that still need to be done in order to implement it perfectly, makes research on digitization will continue to be needed. Future studies can complement and continue to update research results so that museums can also continue to evolve.
Medical Discourse in Social Movies as a Means of Broadcasting the Normativity

The article is devoted to the consideration of medical topics in social movies, which means film production as an instrument for the formation of social norms and models of behavior in society. Relying on the Entertainment-Educational (E-E) approach in the study of mass media, authors consider the impact of films and medical series on increasing public interest in health care problems, the formation of professional medical communities and the dissemination of knowledge in the field of medicine. According to the socio-cognitive theory of A. Bandura, a person is able to learn by observing and imitating actions broadcast on television. Starting from this situation, the authors analyzed the educational potential of social movies, using the phenomenon of the series "Simply Maria", "Happy Days", "Hum Log", "House M.D.", etc. The article provides examples of the worldview attitudes and strategies of behavior formation in relation to their health through the use in cinema of plots and scenes that demonstrate the work of doctors and talk about medical problems. Social films with medical topics contributed to a change in the attitude of society towards the elderly and people with special needs, considered outsiders in society, radically influenced the perception of HIV-infected people and played an important role in popularizing donation and solving the problems associated with the growth of cardiovascular diseases. Medical cinema and TV shows are not only case in social cinema, that determined the norms of human behavior in a modern society immersed in the media environment, but it performs an educational rule-making function in the development of health care and a healthy lifestyle.
Normativity in the Philosophy of Cinema (Review of the Conference)

The article is devoted to the All-Russian scientific conference "Normativity in the Philosophy of Cinema", organized jointly by Volgograd State University, Lomonosov Moscow State University, and the Russian Philosophical Society. Lomonosov Moscow State University and the Volgograd branch of the Russian Philosophical Society. The participants of the conference focused their attention on the fact that cinema inevitably reflects the nature of normativity because, in accordance with the traditions of European dramaturgy, the storyline is based on the event of disorder, and the conflict structure requires that the figure of the violator is opposed by the antagonist, that is, the follower and defender of the social norm. At the same time, cinetext can reflect both the author's ideas and purely typical notions of law prevailing in culture. At the same time, the cinema, among other things, can be used as an experimental ground for working out a new way of social action. In addition to the philosophical approach proper, interdisciplinary approaches to the problems in question were presented: legal, historical, sociological, and theological. In the framework of the thematic sessions and plenary lectures of the conference, various aspects of philosophical comprehension of cinema in general and the idea of normativity as its substantial leitmotif were discussed, including genre specificity (crime films, horror, serials); the works of certain masters (A. Tarkovsky, F. Fellini, M. Scorsese, W. Anderson, M. Zakharov, E. Ryazanov, G. Daneliya, etc.); national codes of film cultures; reflection of historical events, including traumatic ones, and their processing by means of film language; representation of religious symbols and meanings in cinema; normative modes of perception of a film production. Thus, we have seen that cinema, as a fractal way of seeing modern culture, is an exceptionally rich and grateful material for philosophical thinking.
Medium and Low-Level Energy Saving Control Strategies for Electric-Powered UAVs

Flight endurance of an electric-powered Unmanned Aerial Vehicle (UAV) is restricted by its limited on-board energy, which might endanger the accomplishment of any mission it has been sent on. Therefore, the vehicle’s energy consumption should be reduced as much as possible to prolong its flight. This paper deals with the minimization of the energy consumed by an electric-powered UAV as it tracks a desired target point by designing the necessary energy saving control techniques. Two approaches are proposed. The first one addresses the energy consumption problem by optimizing the UAV’s low-level controller. The second approach makes use of the powerful Artificial Bee Colony algorithm to optimize the medium-level controller which guarantees not only target point tracking but also minimization of energy consumption. The effectiveness of both proposals is validated by simulations on MATLAB/Simulink.
New digital signature scheme based on MDLP and multinacci matrices

A new digital signature scheme based on Matrices Discrete Logarithm Problem (MDLP) and generalized Fibonacci or Multinacci matrices is proposed. The security of the scheme is based on the difficulty of solving the Discrete Logarithm Problem (DLP) in matrices. MDLP is a new one-way function based on matrices that provides the same security as the DLP. The use of matrices increases the complexity of the scheme, as it involves matrix exponentiation rather than integers. In the proposed scheme, the signer uses a Multinacci matrix Fkn to generate the signature and an inverse Multinacci matrix Fn-k to verify it. The computational complexity and security of the scheme are also discussed.
Correction to: Python Programming Recipes for IoT Applications

Correction to: J. S. Parab et al., Python Programming Recipes for IoT Applications, Transactions on Computer Systems and Networks, https://doi.org/10.1007/978-981-19-9466-1
An Interpretable Multivariate Time-series Anomaly Detection Method in Cyber-Physical Systems Based on Adaptive Mask

The high complexity and wide applications of Cyber-Physical Systems (CPSs) pose a large requirement on both accuracy and interpretability of the time-series anomaly detection algorithms. While a large number of deep learning algorithms have achieved excellent accuracy, the interpretability is often limited, especially when considering retaining correlations in multivariate time-series. In this paper, we propose a novel multivariate time-series anomaly detection method based on adaptive masking mechanism to improve both accuracy and interpretability, which contains a specially designed series saliency module. For more intuitive and interpretable results, a learnable adaptive mask is introduced in the series saliency module, which can disclose the influence on anomalies in both feature and temporal dimensions. The original time-series and their versions with adaptive perturbations added are then mixed via the mask forming an adaptive data augmentation method to improve the accuracy of anomaly detection. Furthermore, the anomaly detection module is model-agnostic, whether based on forecasting or reconstruction. The optimization of the training objectives will lead to more accurate and interpretable detection results. With four real-world datasets, we demonstrate that the adaptive mask can provide more accurate anomaly detection results with meaningful interpretations in the form of a mask matrix.
Energy Complexity of Computation

Computational complexity theory is the study of the fundamental resource requirements associated with the solutions of different problems. Time, space (memory) and randomness (number of coin tosses) are some of the resource types that have been examined both independently, and in terms of tradeoffs between each other, in this context. Since it is well known that each bit of information “forgotten” by a device is linked to an unavoidable increase in entropy and an associated energy cost, one can also view energy as a computational resource. Constant-memory machines that are only allowed to access their input strings in a single left-to-right pass provide a good framework for the study of energy complexity. There exists a natural hierarchy of regular languages based on energy complexity, with the class of reversible languages forming the lowest level. When the machines are allowed to make errors with small nonzero probability, some problems can be solved with lower energy cost. Tradeoffs between energy and other complexity measures can be studied in the framework of Turing machines or two-way finite automata, which can be rewritten to work reversibly if one increases their space and time usage.
Optimization of Reversible Control Flow Graphs

Growing interest in reversible computation has led to an accelerated development of reversible programming languages and software, which reinforces the need for optimizing compilers. In this paper, we report on our recent progress on optimizing reversible intraprocedural control flow. Like previous work on the optimization of reversible programs, the techniques in this paper are based on the reversible intermediate language RSSA. A formalization of RSSA’s control flow as an extended directed multigraph is introduced. This serves as a basis for three analysis and optimization techniques for reversible control flow, which enable the identification and removal of a) unreachable code, b) branches between strictly consecutive code sequences, and c) immediately redirected branches. To our knowledge, this is the first work being done to investigate the optimization of reversible control flow.
Improved Synthesis of Toffoli-Hadamard Circuits

The matrices that can be exactly represented by a circuit over the Toffoli-Hadamard gate set are the orthogonal matrices of the form $$M/\sqrt{2}{}^k$$ , where M is an integer matrix and k is a nonnegative integer. The exact synthesis problem for this gate set is the problem of constructing a circuit for a given such matrix. Existing methods produce circuits consisting of $$O(2^n\log (n)k)$$ gates, where n is the dimension of the matrix. In this paper, we provide two improved synthesis methods. First, we show that a technique introduced by Kliuchnikov in 2013 for Clifford+T circuits can be straightforwardly adapted to Toffoli-Hadamard circuits, reducing the complexity of the synthesized circuit from $$O(2^n\log (n)k)$$ to $$O(n^2\log (n)k)$$ . Then, we present an alternative synthesis method of similarly improved cost, but whose application is restricted to circuits on no more than three qubits. Our results also apply to orthogonal matrices over the dyadic fractions, which correspond to circuits using the 2-qubit gate $$H\otimes H$$ , rather than the usual single-qubit Hadamard gate H.
Optimal Data Placement for Scientific Workflows in Cloud

The deployment of datasets in the heterogeneous cloud computing has received increasing attention in current research. However, due to their large sizes and the existence of private scientific datasets, finding an optimal data placement strategy remains a persistent problem. The primary goal of this work is to discover an optimum placement while satisfying the security demand (SD) at the lowest cost. To effectively address this problem, a security-based optimal workflow scheduling (OWS) is proposed for privacy-aware applications over data. During negotiation, the user can submit the SD to the cloud. This work is initialized with list-based heuristics with Particle Swarm Hybridized Red Deer (PSRD). The proposed system can assign tasks for the scientific workflow in the cloud according to the virtual machine (VM). The results show that the workflow schedule provides better security yielding good makespan than the conventional methods with minimum iteration suited for a cloud environment.
A Problem Space for Designing Visualizations

Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, and evaluate the things we create. The literature has many task structures (taxonomies, typologies, etc.), design spaces, and related “frameworks” that provide abstractions of the problems a visualization is meant to address. In this Visualization Viewpoints article, we introduce a different one, a problem space that complements existing frameworks by focusing on the needs that a visualization is meant to solve. We believe it provides a valuable conceptual tool for designing and discussing visualizations.
Rankability and linear ordering problem: Probabilistic insight and algorithms

The linear ordering problem (LOP), which consists in ordering M objects from their pairwise comparisons, is commonly applied in many areas of research. While efforts have been made to devise efficient LOP algorithms, verification of whether the data is rankable, that is, if the LOP solutions have a meaningful interpretation, received much less attention. To address this problem, we adopt a probabilistic perspective where the results of pairwise comparisons are modeled as Bernoulli variables with a common parameter, and we estimate the latter from the observed data. The enumeration over the space of permutations, required to solve the problem, has a prohibitive complexity of O(M!) if implemented explicitly. We thus reformulate the problem and introduce a concept of the Slater spectrum that generalizes the Slater index, and then devise an algorithm to find the spectrum with complexity O(M32M) that is manageable for moderate values of M. Furthermore, with a minor modification of the algorithm, we are able to find all solutions of the LOP with the complexity O(M2M). Numerical examples are shown on synthetic and real-world data, and the algorithms are publicly available.
Tips for Effective Machine Learning in NDT/E

The proliferation of machine learning (ML) advances will have long-lasting effects on the nondestructive testing/evaluation (NDT/E) community. As these advances impact the field and as new datasets are created to support these methods, it is important for researchers and practitioners to understand the associated challenges. This article provides basic definitions from the ML literature and tips for nondestructive researchers and practitioners to choose an ML architecture and to understand its relationships with the associated data. By the conclusion of this article, the reader will be able to identify the type of ML architecture needed for a given problem, be aware of how characteristics of the data affect the architecture’s training, and understand how to evaluate the ML performance based on properties of the dataset.
Improving text detection by generating images with curved text instances

Modern text detection algorithms rely on deep neural networks, which are trained on labeled datasets to achieve high performance. Despite the increasing popularity of text detection, accurate detection of text in natural images remains a challenging problem due to variations in text size, shape, color, and font. In particular, curved text instances present a unique challenge for detection algorithms, yet they are seldom found in existing text detection datasets. In this paper, we present an approach to improve curved text detection performance by generating synthetic images with curved text instances and polygon bounding regions as annotations. We train a deep neural network-based text detector on these synthetic images and evaluate its performance on test sets. Our findings highlight the importance of utilizing diverse and realistic datasets for training robust text detection systems.
A proposal of Android services generator for inter-connection with ADAS

The integration of software in the automotive industry has become increasingly complex and time-sensitive, necessitating the implementation of efficient tools. One such tool is the utilization of a generator. Over the past decade, the implementation of In-Vehicle-Infotainment systems has become ubiquitous, occupying a central position within vehicles. Another system present in vehicles is the Advanced Driver Assistance System. Despite their prevalence, these systems operate in isolation. However, the utilization of Android services and a service-client architecture can facilitate communication between disparate systems through the implementation of various service-client-based protocols. This study proposes the development of a generator for Android services that enable communication between Advanced Driver Assistance System systems through the use of CommonAPI proxy. The implementation of this generator will expedite the production process of code that integrates these independent systems.
You Don’t Know Search: Helping Users Find Code by Automatically Evaluating Alternative Queries

Tens of thousands of engineers use Sourcegraph day-to-day to search for code and rely on it to make progress on software development tasks. We face a key challenge in designing a query language that accommodates the needs of a broad spectrum of users. Our experience shows that users express different and often contradictory preferences for how queries should be interpreted. These preferences stem from users with differing usage contexts, technical experience, and implicit expectations from using prior tools. At the same time, designing a code search query language poses unique challenges because it intersects traditional search engines and full-fledged programming languages. For example, code search queries adopt certain syntactic conventions in the interest of simplicity and terseness but invariably risk encoding implicit semantics that are ambiguous at face-value (a single space in a query could mean three or more semantically different things depending on surrounding terms). Users often need to disambiguate intent with additional syntax so that a query expresses what they actually want to search. This need to disambiguate is one of the primary frustrations we’ve seen users experience with writing search queries in the last three years. We share our observations that lead us to a fresh perspective where code search behavior can straddle seemingly ambiguous queries. We develop Automated Query Evaluation (AQE), a new technique that automatically generates and adaptively runs alternative query interpretations in frustration-prone conditions. We evaluate AQE with an A/B test across more than 10,000 unique users on our publicly-available code search instance. Our main result shows that relative to the control group, users are on average 22% more likely to click on a search result at all on any given day when AQE is active. We share our technique, learnings, and implementation that made it possible for a substantial number of users to now see and click on results that they would not have seen otherwise.
Artifact: Implementation of an Adaptive Flow Management Framework for IoT Spaces

This paper presents the implementation and guideline of PlanIoT, an adaptive flow management framework for IoT-enhanced spaces. Such spaces are composed of applications deployed at the Edge with varying QoS requirements in terms of response time, timely delivery, throughput, etc. Configuring the Edge infrastructure requires tuning multiple parameters for optimal QoS satisfaction of applications. This is a complex task especially when the system has to be re-adapted (e.g., emergency situations). The PlanIoT framework manages application data flows in an adaptive manner. This is achieved via the following core software components: (i) a queueing network composer; (ii) an automated planning modeler; and (iii) an AI planner. This artifact presents implementation details of these components as well as guidelines for using the PlanIoT framework.
NILM-Net: Anonymous Coordination of Real-Time Power Monitors for Smart Grid Applications

Coordination of decentralized energy resources, condition based maintenance, and energy conservation all benefit from visibility of itemized energy demand throughout the power distribution network. Nonintrusive load monitoring (NILM) can provide itemized power demand for an installation but sharing this information without sacrificing privacy is a challenging and unsolved problem. This work presents NILM-Net, a gossip protocol for aggregating itemized load events into an anonymous central database. Unlike traditional gossip protocols, NILM-Net provides monetary incentive for participation and malicious nodes can be efficiently detected.