Reviewerly/exHarmony huggingface dataset:
The Communication Complexity of Functions with Large Outputs

We study the two-party communication complexity of functions with large outputs, and show that the communication complexity can greatly vary depending on what output model is considered. We study a variety of output models, ranging from the open model, in which an external observer can compute the outcome, to the XOR model, in which the outcome of the protocol should be the bitwise XOR of the players’ local outputs. This model is inspired by XOR games, which are widely studied two-player quantum games. We focus on the question of error-reduction in these new output models. For functions of output size k, applying standard error reduction techniques in the XOR model would introduce an additional cost linear in k. We show that no dependency on k is necessary. Similarly, standard randomness removal techniques, incur a multiplicative cost of $$2^{k}$$ in the XOR model. We show how to reduce this factor to O(k). In addition, we prove analogous error reduction and randomness removal results in the other models, separate all models from each other, and show that some natural problems – including Set Intersection and Find the First Difference – separate the models when the Hamming weights of their inputs is bounded.
Lockless Blockchain Sharding with Multiversion Control

Sharding is used to address the performance and scalability issues of the blockchain protocols, which divides the overall transaction processing costs among multiple clusters of nodes. Shards require less storage capacity and communication and computation cost per node than the existing whole blockchain networks, and they operate in parallel to maximize performance. However, existing sharding solutions use locks for transaction isolation which lowers the system throughput and may introduce deadlocks. In this paper, we propose a lockless transaction method for ensuring transaction isolation without using locks, which improves the concurrency and throughput of the transactions. In our method, transactions are split into subtransactions to enable parallel processing in multiple shards. We use versions for the transaction accounts to implement consistency among the shards. We provide formal proof for liveness and correctness. We also evaluate experimentally our proposed protocol and compare the execution time and throughput with lock-based approaches. The experiments show that the transaction execution time is considerably shorter than the lock-based time and near to the ideal (no-lock) execution time.
Boundary Sketching with Asymptotically Optimal Distance and Rotation

We address the problem of designing a distributed algorithm for two robots that sketches the boundary of an unknown shape. Critically, we assume a certain amount of delay in how quickly our robots can react to external feedback. In particular, when a robot moves, it commits to move along path of length at least $$\lambda $$ , or turn an amount of radians at least $$\lambda $$ for some positive $$\lambda \le 1/2^6$$ , that is normalized based on a unit diameter shape. Then, our algorithm outputs a polygon that is an $$\epsilon $$ -sketch, for $$\epsilon = 8\sqrt{\lambda }$$ , in the sense that every point on the shape boundary is within distance $$\epsilon $$ of the output polygon. Moreover, our costs are asymptotically optimal in two key criteria for the robots: total distance travelled and total amount of rotation. Additionally, we implement our algorithm, and illustrate its output on some specific shapes.
Knowledge Retrieval by Exploring Correlation Between Texts with Different Genre Perspectives

Clustering and topic modelling are among the most widely used methods for knowledge retrieval in computational linguistics. These methods have many applications in cognitive, discursive, psycholinguistic, and stylistic studies. To date, the application of these methods has mostly been limited to one field per study. This work explores the relationship between different branches of linguistics complementing each other in finding effective, valid, and low-time-consuming methods for the knowledge mediation methodology. Namely, in this paper, we explore the correlation between texts devoted to the same theme viewed from different genre perspectives. The procedure is carried out on the KNIME analytical platform. We adopted the workflow using the elbow method and K-means available on the KNIME hub to determine latent topics in a scientific text, historical novel, and science fiction novel. We reviewed four to five latent topics in each text and provided experts’ reasoning for their relevance. The results reported here provide further evidence for the relevance of genre-specific features in knowledge communication. The data presented here highlight that despite genre specificity, correlations in latent topics are evident and can be applied for mediation purposes. We have obtained encouraging results demonstrating that the interdisciplinary approach enriches our tool base in solving nontrivial tasks.
Divide &amp; Scale: Formalization and Roadmap to Robust Sharding

Sharding distributed ledgers is a promising on-chain solution for scaling blockchains but lacks formal grounds, nurturing skepticism on whether such complex systems can scale blockchains securely. We fill this gap by introducing the first formal framework as well as a roadmap to robust sharding. In particular, we first define the properties sharded distributed ledgers should fulfill. We build upon and extend the Bitcoin backbone protocol by defining consistency and scalability. Consistency encompasses the need for atomic execution of cross-shard transactions to preserve safety, whereas scalability encapsulates the speedup a sharded system can gain in comparison to a non-sharded system. Using our model, we explore the limitations of sharding. We show that a sharded ledger with n participants cannot scale under a fully adaptive adversary, but it can scale up to m shards where $$n=c'm\log m$$ , under an epoch-adaptive adversary; the constant $$c'$$ encompasses the trade-off between security and scalability. This is possible only if the sharded ledgers create succinct proofs of the valid state updates at every epoch. We leverage our results to identify the sufficient components for robust sharding, which we incorporate in a protocol abstraction termed Divide & Scale. To demonstrate the power of our framework, we analyze the most prominent sharded blockchains (Elastico, Monoxide, OmniLedger, RapidChain) and pinpoint where they fail to meet the desired properties.
Degree Realization by Bipartite Multigraphs

The problem of realizing a given degree sequence by a multigraph can be thought of as a relaxation of the classical degree realization problem (where the realizing graph is simple). This paper concerns the case where the realizing multigraph is required to be bipartite. The problem of characterizing degree sequences that can be realized by a bipartite (simple) graph has two variants. In the simpler one, termed BDR $$^P$$ , the partition of the degree sequence into two sides is given as part of the input. A complete characterization for realizability in this variant was given by Gale and Ryser over sixty years ago. However, the variant where the partition is not given, termed BDR, is still open. For bipartite multigraph realizations, there are again two variants. For BDR $$^P$$ , where the partition is given as part of the input, a complete characterization was known for determining whether the bi-sequence is r-max-bigraphic, namely, if there is a multigraph realization whose underlying graph is bipartite, such that the maximum number of copies of an edge is at most r. We present a complete characterization for determining if there is a bipartite multigraph realization such that the total number of excess edges is at most t. As for the variant BDR, where the partition is not given, we show that determining whether a given (single) sequence admits a bipartite multigraph realization is NP-hard. On the positive side, we provide an algorithm that computes optimal realizations for the case where the number of balanced partitions is polynomial, and present sufficient conditions for the existence of bipartite multigraph realizations that depend only on the largest degree of the sequence.
Terminology Transfer in the Field of Bioethics of Assisted Reproductive Technologies

The article aimed to analyze the terminology of a new field of bioethics, that is bioethics of assisted reproductive technologies. The initial step-by-step selection of terms from English language specialized scientific materials was made. As a result, five thematic groups of multicomponent term borrowings from donor areas, such as law, philosophy, medicine, economics and technology were identified. It was revealed that in the process of transterminologization the thematic group “Bioethics and reproductive technologies” is most represented as the source of borrowing for the recipient area of bioethics of assisted reproductive technologies.
Technogenic Subjectivity and Its Social Projections

The studies of digital technologies impact refer to the development of radical technologies, exploration of new embodiments, development of a new theory of media, and the issues of artificial intelligence. However, these studies focus on either the psychological or social implications of these changes but do not question the essence of new technogenic subjectivity. The key idea of the study is to identify the nature of technogenic factors and their impact on subjectivity. Methodologically, the study compares the archetype of classical intelligence and technogenic subjectivity. The paper shows that affect is virtualized under the impact of digital technologies, when affect is perceived apart from its local embodiment in the form of material and energy processes in digital infrastructure. This virtual residue of affect is not perceived, and the subject is turned into “actant-without-ego”. Under this affectation, space is only the function of a mobile device. Now, time is similarly reproduced by technical devices. In this context, the only thing which is left from the reality of time is digital code, while the modi of the past, present, and future turn out to be virtual constructions. Consciousness is defined by external technogenic factors rather than by its own logical structures. All categories of the intellect become the forms of reality representation pre-installed in the options of digital devices. That is why technogenic thinking performs an adaption function only, is deprived of its subject, and substitutes the subject with artificial intelligence. So, subjectivity affectation is defined by the external rational structure of digital reality.
Ethical-Legal-Technical Challenges for Lawyers and Their Clients with the Internet of Things

We examine how consideration of one system of ethics relating to the, Internet of Things (“IOT”) and litigation resulting from implementations may forewarn of legal-technical conflicts. In particular, we will examine this in the context of a developed set of ethical rules and professional conduct precepts for information processing and map those to potential issues with AI and the Internet of Things. Those are the rules of professional conduct for attorneys within the United States considered in light of the Code of Ethics of the Association for Computing Machinery.
The Growth of Appreciation of Distance Learning Among Students in Russia During New Waves of the COVID-19 Pandemic

The transition of higher education in Russia to distance learning due to the COVID-19 pandemic makes it necessary to analyse the opinion of students based on their experience of distance learning during the pandemic. Since the COVID-19 virus tends to mutate and remains highly pathogenic for a long time, universities should improve the quality of distance education taking into account the needs of today’s students. The purpose of our study was to identify the changes in the opinion of students about the advantages of distance learning over a period from the beginning of the COVID-19 pandemic and up to the present moment, when we are facing another wave. The study was based on a sociological survey. The article presents the results of the survey of students from two leading universities in Russia. It determines the aspects of distance learning that are now viewed significantly more positively by students as compared to the beginning of the pandemic two years ago. It also presents the factors that influenced students’ opinion about the quality of distance education. The results of our study contribute to the development of distance learning models employed by higher education institutions in Russia and can also be used as a basis for managerial decisions, since they present feedback from students. (150–250 words).
simbIoTe: A Simulator for Building Cyber-Physical System and Internet of Things Environments

Simulation of physical environments during the development of Industrial Cyber-Physical Systems (ICPS) offers a way to rapidly validate control interactions. Since production hardware for both aerospace and industrial machinery is not always immediately available, simulation allows software development to begin earlier on safety-critical projects. This study presents the early-stage design thinking that influenced the development of our simbIoTe physical environment simulator. This tool allows engineers to rapidly create realistic simulations that can interact with their ICPS during development. Aspects of the simbIoTe architecture are detailed as well as the Views and Beyond methodology adopted by the designers. Two case studies that evaluated the first prototypes of the simulator are discussed. The future research directions outline how simbIoTe will be evolved into a mature Open Source simulation development platform to foster robust and resilient ICPS design practices.
Virtual Reality: A Paradigm Shift in Architecture and Urban Design Education

Technology is constantly evolving and has radically changed the way societies behave and operate. These advancements have brought enormous benefits - dramatically highlighted in 2020 by the emerging use of remote learning worldwide. The COVID-19 outbreak has served as a tipping point for the technological advances in architecture education in particular and higher education in general. Virtual reality is considered one of the innovative technologies that have been widely applied in different fields. This study, therefore, aims to examine the potential of VR applications in architecture education. The adopted methodology is reviewing articles from the Scopus Database under the Title/Abstract/Keyword field search using the following keywords: (“Virtual Reality” AND “Architecture Education” AND “Urban Design” AND “Design Studio”). Findings provide valuable insights for researchers, educators, and practitioners on integrating virtual reality in education to improve the educational process.
A dependable and secure consensus algorithm for blockchain assisted microservice architecture

One of the integral components in the architectural design and development of Internet of Things (IoT) is Microservice. Microservices are basically an architectural and organizational approach in the process of software development where the software is composed of small but independent services that would communicate over well-defined APIs (Application Programming Interfaces). It is quite challenging to ensure data integrity and data availability in the architecture design of microservices. As Blockchain technology has emerged as a panacea to many of the other domains, the distributed microservice architecture can also utilize it. We know that the consensus algorithms are used in the Blockchain technology to validate the transactions alongside providing extra level of security. Taking the advantage of consensus algorithms in blockchain-based architecture models, in this paper, we propose TCA (Trustworthy Consensus Algorithm), which is designed to solve the data integrity and availability challenges in microservice architectures. We have evaluated the proposed algorithm against the known alternatives and it shows good level of efficiency.
Cross that boundary: Investigating the feasibility of cross-layer information sharing for enhancing ABR decision logic over QUIC

With HTTP Adaptive Streaming (HAS), client-side Adaptive Bitrate (ABR) algorithms drive the (quality-variant) scheduling and downloading of media segments. These ABR algorithms are implemented in the application layer and can therefore base their logic only on relatively coarse and/or inaccurate application-layer metrics. The recently standardized QUIC transport protocol has many userspace implementations, which paves the way for cross-layer optimizations by exposing transport-layer metrics to application-layer algorithms. In this paper, we investigate whether the availability of fine-grained transport-level throughput metrics can positively impact the operation of ABR algorithms and hence the Quality of Experience (QoE) of HAS users in Video on Demand (VoD) settings. Our results show that QUIC-level throughput data can indeed aid ABR algorithms to more accurately predict playout buffer under-runs, which in turn allows the ABR logic to take reactive measures in a timely fashion such that playback stalls can be avoided under challenging network conditions. Overall, our work presents a step towards improving ABR operation via cross-layer data exchange.
RepCaM: Re-parameterization Content-aware Modulation for Neural Video Delivery

Recently, content-aware methods have been utilized to reduce the bandwidth and improve the quality of Internet video delivery. Existing methods train corresponding content-aware super-resolution (SR) models for each video chunk on the server and stream low-resolution (LR) video chunks along with SR models to the client. Previous works introduce additional partial parameters to privatize the models of different video chunks. However, this still leads to the accumulation of parameters and even fails to modulate when the length of video increases, bringing extra delivery costs and performance degradation. In this paper, we introduce a novel Re-parameterization Content-aware Modulation (RepCaM) method to modulate all the video chunks with an end-to-end training strategy. Our method adopts extra parallel-cascade parameters during training to fit multiple chunks while removing the additional parameters through re-parameterization during inference. Therefore, RepCaM increases no extra model size compared with the original SR model. Moreover, in order to improve the training efficiency on servers, we propose an online Video Patch Sampling (VPS) method to speed up the training convergence. We conduct extensive experiments on VSD4K and newly collected dataset (VSD4K-2022), achieving state-of-the-art results in video restoration quality and delivery bandwidth compression. Code is available at: https://github.com/Neural-video-delivery/RepCaM-Pytorch-NOSSDAV2023.
Design of embedded software architecture for spacecraft electric propulsion system

Abstract With the rapid growth of the number of spacecraft tasks and the complexity of the system, spacecraft software development is faced with the challenges of high-quality and rapid delivery, increased complexity, and frequent changes in requirements. The reuse rate of software assets needs to be improved urgently. In order to realize cross-platform and cross-project reuse of software design, this paper studies the design of electric propulsion software architecture. Carry out requirements decomposition and subsystem division of electric propulsion systems for different platforms, extract common requirements and variability requirements at the system level and subsystem level based on the Feature-Oriented Domain Analysis method, and establish a requirements model. Based on the requirements model, an electric propulsion software architecture integrating “event-driven + components” is proposed, and the classic event-driven model of “publish-subscribe” is adaptively improved. The architecture has been instantiated and applied to 16 projects on 4 platforms, and the reuse rate of core assets has reached 70%. This paper has certain guidance and reference significance for spacecraft software asset reuse and platform construction.
Development of a mobile application for forest and land fire patrol using Prototype method

Abstract A previous study has developed a mobile application for recording field data during Sumatra, Indonesia’s forest and land fires patrol. After users tested the usability, the user’s need for the system increased due to the new environmental characteristics in the forest and land fire patrol area. This study aims to develop a mobile application that is easy to use by the patrol team to support forest and land fire prevention patrols. The system development continues the mobile application proposed in the previous study. The system development method used is Prototyping, with stages starting from communication; quick design; rapid design modelling; prototyping; dissemination, delivery, and feedback. The application was built using the Ionic 3 framework using the REST API from the back-end module. The development was conducted in two iteration stages, namely the third and fourth iterations. The third and fourth iterations resulted in changes in the user interface, added auto-fill features, and downloaded reports. Applications developed in each iteration were tested using the Black-Box method. The test results from each iteration show that all functions in the application work properly and meet the user requirements.
Smart wheelchair controlled by head gesture based on vision

Abstract Head Gesture Recognition has been developed using a variety of devices that mostly contain a sensor, such as a gyroscope or an accelerometer, for determining the direction and magnitude of movement. This paper explains how to control a smart wheelchair using Head-Gesture Recognition based on Computer Vision. Using the Haar Cascade Algorithm Method for determining the position of the face and nose, determining the order of the head gesture would be easy to do. We classify head gestures to become four, namely: Look down, Look up/center, Turn right and Turn left. The four gesture information is used to control the smart wheelchair as Brake, Accelerate, Turn right and Turn left. The experiment result shows that our system has successfully controlled the smart wheelchair using head gestures.
The Implementation of Best Practices of International Projects as the Way of Enhancement of Higher and Business Education in Belarus

The development of education around the world is facilitated by the exchange of experience and interaction between education providers from different countries and regions. International programs and projects have become one of the drivers to improve the quality of education, the development of information and communication educational technologies, as well as the dissemination of innovative educational programs at Belarusian universities. Among them, there are the projects of the European Union ERASMUS+ CBHE program, as well as projects and exchange programs of the United States. In this publication, the authors share the experience of implementation of the best practices at universities in the European Education Area (Sweden, Britain, Germany, Italy, Spain, Latvia, Turkey) and the results of the United States experience application, which enabled the improvement of the educational process at the Sukhoi State Technical University of Gomel (Belarus). Also, it is shown how the implementation of the Detroit experience gained at the international internship contributed to the development of ties between Belarusian communities, including formation of inclusive business education and the development of skills for employment and social entrepreneurship of people in Belarus.