Reviewerly/exHarmony huggingface dataset:
20 Years of Experience in Organizing and Holding of Programming Competitions at the Novosibirsk State University

The paper contains a list of school and student contests in computer science and programming with a brief description, which have been held by Novosibirsk State University (NSU) for the last 20 years. The practice of using the automated system NSUts for checking programming tasks in the educational process and in programming contests at various levels is considered.
Seamless Update of a Hypervisor Stack

For security, performance, and competitive reasons, the hypervisor must be regularly updated in order to maintain the cloud infrastructure. This work provides an overview of three novel techniques of updating a hypervisor stack with a minimal disruption for the running virtual machines. HVPlexing: The first technique involves using a cooperative multi-OSing paradigm to share the same machine between the two operating systems while the new OS is booting, and the old OS is still servicing the running virtual machine instances. HVInception: The second method introduces a way of starting the new operating system in the virtual machine, and once boot is finished, transfer it from the virtual to physical environment, thus, fully replacing the old hypervisor stack with the new one. HVPartitioning: The third method is to start the new operating system on a subset of a physical machine. This method involves using CPU and memory dynamic reconfiguration in order to change the number of active processing units and the amount of memory in the running operating system. Once the new operating system has finished booting, it is resized to take over the full machine. In all three cases the running VMs are absorbed by the new hypervisor without noticeable interrupts by checkpointing and restoring them in the updated environment.
Syllabification of the Divine Comedy

We provide a syllabification algorithm for the Divine Comedy using techniques from probabilistic and constraint programming. We particularly focus on the synalephe , addressed in terms of the "propensity" of a word to take part in a synalephe with adjacent words. We jointly provide an online vocabulary containing, for each word, information about its syllabification, the location of the tonic accent, and the aforementioned synalephe propensity, on the left and right sides. The algorithm is intrinsically nondeterministic, producing different possible syllabifications for each verse, with different likelihoods; metric constraints relative to accents on the 10th, 4th, and 6th syllables are used to further reduce the solution space. The most likely syllabification is hence returned as output. We believe that this work could be a major milestone for a lot of different investigations. From the point of view of digital humanities it opens new perspectives on computer-assisted analysis of digital sources, comprising automated detection of anomalous and problematic cases, metric clustering of verses and their categorization, or more foundational investigations addressing, e.g., the phonetic roles of consonants and vowels. From the point of view of text processing and deep learning, information about syllabification and the location of accents opens a wide range of exciting perspectives, from the possibility of automatic learning syllabification of words and verses to the improvement of generative models, aware of metric issues, and more respectful of the expected musicality.
CVaR Q-Learning

In this paper we focus on reinforcement learning algorithms that are sensitive to risk. The notion of risk we work with is the well-known conditional value-at-risk (CVaR). We describe a faster method for computing value iteration updates for CVaR markov decision processes (MDP). This improvement then opens doors for a sampling version of the algorithm, which we call CVaR Q-learning. In order to allow optimizing CVaR on large state spaces, we also formulate loss functions that are later used in a deep learning context. Proposed methods are theoretically analyzed and experimentally verified.
The Implement of Packet Tracer as UI to Monitor and Control Real IoT Devices

IoT technologies use sensors and controllers to collect information and control devices vi network and organize as one ecosystem. IoT developer should try many devices and combinations to build a system for smart environment. Cisco Packet Tracer is a powerful network simulation tool to experiment network behavior. Packet Tracer can be a simulation environment for IoT Development, in additional, which provides an API to communicate with real devices. This paper implements the Packet Tracer as user interface(UI) to monitor and control the real word IoT devices.
The factory must grow

The video game Factorio has a myriad of gameplay scenarios which are analogous to real-world problems, and is a useful simulator for developing solutions for them. In this paper we define the logistic transport belt problem, we provide an interface to allow optimizers in any programming language to interact with Factorio, and we provide an initial benchmark. Results are presented for three different meta-heuristic techniques to optimize solutions to this novel problem.
A Theoretical Underpinning for Examining Insider Attacks Leveraging the Fraud Pentagon

The problem of the insider threat is extremely challenging to manage as it involves trusted entities who have legitimate authorization to the information infrastructure of an organization. It has been reasoned that the framing of the Fraud Pentagon may assist in predicting and preventing white collar crimes such as fraud. The Fraud Pentagon considers the elements of motivation, capability, rationalization, opportunity and arrogance which converge in a crime scenario. The current study considers the value of using the Fraud Pentagon in examining insider attacks. This paper evaluates this theoretical framing from an insider threat perspective, thereby assisting researchers, organizations and information security practitioners in understanding its complexity and its application to the insider threat problem.
EDUCATIONAL ASPECTS OF THE ELECTRONIC LEARNING PROCESS IMPLEMENTATION IN THE CONDITIONS OF THE ECONOMIC CRISIS

The COVID-19 pandemic that began a year ago was marked by mass isolation of the population and transition to the remote interaction in many areas of human life. In this regard the ability of the domestic vocational education system to fully function through electronic, mobile and remote forms and means of carrying out educational activities is of particular importance. Thus, the problem arises of choosing a software platform for a distance education system that can meet the criteria for organizing and implementing a high-quality and uninterrupted educational process at a university under conditions of distance learning. The article presents the experience of implementing e-learning in the conditions of isolation of students and teachers of Rostov State University of Economics (RINH). The purpose of the article is to analyze the educational capabilities of the Module distance education system based on the experience of its practical application. The research methods used are methods for collecting and accumulating data, methods of assessment and experiential learning. The practical use of the Module system has revealed such shortcomings as the lack of the possibility of conducting interactive lessons in the mode of videoconferencing and the built-in system for testing students' knowledge. Nevertheless, the authors have concluded that the platform is acceptable for solving educational problems. The experience gained in distance learning made it possible to determine the main subsystems that software tools for implementing the distance learning process must meet
Performance Analysis of Cloud Computing for Distributed Data Center using Cloud-Sim

Cloud Computing, a key enabling technology for speedy wide-area networks are one of the emerging technologies in Computer Science. One of the pressing challenges in the ongoing research in this particular domain is data confidentiality. There is an immense need to preserve important data and confidentiality in cloud computing, which means a more critical requirement for robust mechanisms to protect it from attackers or intruders. This paper proposes a broad and thorough probing multiple simulation-based software that examines and evaluates the execution, extensibility, strength, and intricacy of Cloud data center. This paper analyzes different Cloud services using Cloud-Sim, Cloud Analyst, and OPNET simulation tool. Services, cloud management, load-distributing, cloud strength, and expand-ability are the main scope of this paper. Hence, results are compared in the real-time framework to identify the performance and extensibility, as well as consider the experiment as challenges for further discussion.
The Business Case for Media Architecture: Modelling Project Benefits to Justify Investment

A growing portfolio of global media architecture projects and sustained research interest in the domain suggest that the discipline is here to stay. With practical knowledge becoming easily accessible to clients, architects and urban planners, we notice a shift from traditional advertising screens to integrated context-aware installations. The challenge now becomes to understand investment return of media architecture in order to ensure ongoing support by clients and funders. In this paper we study The Digital Bricks, a 208 megapixel media façade integrated within a university building. We describe the project vision, engagement strategy and design outcome, and analyse in detail the business case for the project. We share considerations to support development of business cases for media architecture projects that favour engagement, cultural and innovation capacity over financial returns. As the discipline matures, our insights will help in the endeavour to convince clients to invest in media architecture that inspires and engages audiences.
Investigation on the Influence of English Expertise on Non-native English-Speaking Students’ Scholastic Performance Using Data Mining

This investigation reports about an understanding of the connection between English skill and scholastic accomplishment of science students in Bahrain. Data from student information system were investigated by applying data mining techniques mainly decision tree algorithm. The results demonstrated a significant effect of English expertise on students’ final cumulative grade point average (CGPA). These discoveries demonstrate that the English expertise of graduate students in a non-western polyglot scholastic background is significant for their scholarly accomplishment. Results from this investigation affirm the requirement for colleges in polyglot backgrounds to put resources into non-native English-speaking (L2) graduate students’ English expertise toward the beginning of their scholastic projects. Instructional proposals are made, alongside recommendations for additional investigation.
Analysis of Homomorphic Cryptosystems of Benaloh and Paillier for the Construction of an Electronic Voting System

The analysis of the performance of two cryptographic algorithms (Paillier and Benaloh), in order to apply them in the construction of electronic voting systems is carried out. A description of each system and their homomorphic properties is given. Electronic voting systems based on these schemes are described. The requirements for the voting system are formulated and a comparative analysis of the voting systems based on the schemes of Paillier and Benaloh is carried out. The analysis showed that the Paillier scheme is the best and simplest method for building secure electronic voting systems, while the Benaloh scheme is more complex and computationally more time-consuming.
Design and Application of HMI System for Robot Based on Vision

In view the common problems existing in traditional HMI technology, a HMI system for robot based on vision is proposed. The robot obtains the gesture image of human through camera, and uploads the image to Baidu AI server through PC to realize the understanding of gesture and make corresponding feedback action, so as to achieve the purpose of human-machine interaction. The application of robot in intelligent home service is taken as an example for technical application. The user interacts with the robot to request water pouring service through gestures, and the results showed that the system responded quickly, the gesture recognition rate was high, and the overall experience was good. The scheme makes the HMI more intelligent and natural, improves the robot experience, and is conducive to the robot into entertainment, office, assistance for the elderly and other areas of life. It has application prospects, and can provide reference for technicians in related fields.
On the Joint Activity of the Socialist Countries in the Field of Creating Computer Systems at the Last Stage (1980s-Early 1990s)

A brief description of the Conception of new generations of computer systems, that was developed by academies of sciences of the socialist countries is given. The work on implementing the Conception in the part of developing personal computers was held within the framework of problem 1.1.4 “The development and extension of PC's industrial production created as part of the ES computers and SM computers” of the Integrated Program of Scientific and Technological Progress of the COMECON countries (IPSTP). The results of creating PC's in 1980s in the socialist countries are presented.
Overview of the NLPCC 2021 Shared Task: AutoIE2

This is an overview paper of the NLPCC 2021 shared task on AutoIE2, which aims to evaluate the sub-event identification systems with limited annotated data. Given definitions of specific sub-events, 100K unannotated samples and 300 annotated seed samples, participants are required to build a sub-event identification system. 30 teams registered and 14 of them submitted results. The top system achieves \(8.43\%\) and \(8.25\%\) accuracy score improvement upon the baseline system with or without extra annotated data respectively. The evaluation result indicates that it is possible to use less human annotation and large unlabeled corpora for the sub-event identification system. ALL information about this task can be found at https://github.com/IIGROUP/AutoIE2.
Technological and Legal Aspects of the Use of Machine Learning Elements in Chaotic Information Processing Systems

The technological and legal aspects of using the basic element of machine learning, namely the reservoir computing formed on the basis of a chaotic scheme, are considered in the work. An algorithm for generating a wide range of input values of the reservoir to obtain the required output functions is proposed.
Deep Learning in Healthcare

Through the enormous increase of several tools, the position of data analytics in health data systems has increasingly extended, which has also generated trust in the invention of data-oriented frameworks focused on the learning of sensors in health info systems. A technique that is being researched with funding of artificial neural networks is a versatile machine that will redefine the vision of artificial intelligence of recent age. In the aspect of its conceptual control and capacities in the production of mechanically designed high-level functional and semi-relevant input details, rapid improvements in computing capability, rapid reality processed, and parallelizing have often sacrificed rapid technology return. This section provides an advanced analysis of fundamental learning of health info systems and includes thorough research on the comparative importance and future drawbacks of the method and its mindset. The key areas of translational bioinformatics, scientific imaging, continuous sensing, scientific computing sciences, and public health concentrate on the essential tasks of comprehensive research.
Improving accuracy of an existing semantic word labelling tool using word embeddings

Annotated corpora allow researchers to carry out studies that include linguistic phenomena such as grammatical categories or even knowledge by means of semantic annotation. Semantic annotation in corpus linguistics is often included into every lexical unit of the corpus using a word labelling tool. Resources such as lexicons or ontologies are very useful for this purpose. However, current sizes of these resources for languages different from English are not always appropriate. This paper proves that an updated version of an existing NLP baseline can be extended for different domains and, as a consequence, it is able to improve Spanish token accuracy by up to 30% in comparison with using only a small lexicon.
Analisa Keruntuhan Bendungan Malahayu Kabupaten Brebes Dengan Aplikasi HEC-RAS dan Perhitungan Kerugian Dengan Aplikasi InaSAFE

In the simulation using HEC-RAS 5.0.7 the part to be simulated is the condition of the Malahayu Dam which collapsed due to 7 conditions causing inundation in the downstream area of the Malahayu Dam. Obtained from 7 conditions of dam collapse, the overtopping collapse scenario is the most extreme collapse scenario with an inundation area of 143.54 km2 with a maximum flood inundation height of 19.943 m. The purpose of this dam collapse simulation is to get the most extreme inundation so that in the next process of the inundation, the calculation of economic losses will be carried out with the help of the InaSAFE application. Losses resulting from the Malahayu Dam collapse scenario cover 53 villages from 6 sub-districts so that the evacuation victims reached 22400 people. With this amount, it can be determined that the Malahayu Dam is a dam with a hazard level 4, which is very high. The estimated losses incurred as a result of this collapse reached Rp. 515,521,114,788. The purpose of this study is to determine the level of danger of a dam, to know the characteristics of the flood, and to know the losses caused by flooding due to dam collapse.
Multi-Layered CP-ABE Scheme for Flexible Policy Update in Industry 4.0

Industry 4.0 connectivity requires ensuring end-to-end (E2E) security for industrial data. This requirement is critical when retrieving data from the OT network. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) guarantees E2E security by encrypting data according to a policy and generating user keys according to attributes. To use this encryption scheme in manufacturing environments, policies must be updatable. This paper proposes a Multi-Layered Policy Key Encapsulation Method for CP-ABE that allows flexible policy update and revocation without modifying the original CP-ABE scheme.
On WL-Rank and WL-Dimension of Some Deza Circulant Graphs

The WL-rank of a digraph $$\Gamma$$ is defined to be the rank of the coherent configuration of $$\Gamma$$ . The WL-dimension of $$\Gamma$$ is defined to be the smallest positive integer m for which $$\Gamma$$ is identified by the m-dimensional Weisfeiler–Leman algorithm. We classify the Deza circulant graphs of WL-rank 4. In additional, it is proved that each of these graphs has WL-dimension at most 3. Finally, we establish that some families of Deza circulant graphs have WL-rank 5 or 6 and WL-dimension at most 3.
Coevolutionary computation for adversarial deep learning

tutorial Open AccessCoevolutionary computation for adversarial deep learning Authors: Jamal Toutouh MIT CSAIL MIT CSAILView Profile , Una-May O'Reilly MIT CSAIL MIT CSAILView Profile Authors Info & Claims GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2021 Pages 983–1001https://doi.org/10.1145/3449726.3461419Published:08 July 2021Publication History 0citation201DownloadsMetricsTotal Citations0Total Downloads201Last 12 Months66Last 6 weeks15 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
A novel approach for the analysis of time-course gene expression data based on computing with words

• Analysis of time-course gene expression data based on Zadeh’s Computing with Words. • A new time-series pattern mining technique for dynamical analysis of gene expression. • Pattern discovery in terms of both linguistic and type-2 fuzzy-logic descriptions. • Case study: Analysis of transcriptional response of cancer cells to anticancer drugs. • FuzzGene: An open-source software package for implementation of the proposed method. In this paper, a novel approach is proposed for the analysis of time-course gene expression data based on the path-breaking work of Zadeh, Computing with Words . This method can automatically discover the patterns of temporal gene expression profile in terms of two distinguishing descriptions: linguistic description that is understandable and interpretable for human inference; and type-2 fuzzy description that is suitable for robust machine inference in the presence of uncertainty. In contrast to conventional static data mining methods which focus on the steady-state gene expression levels, the proposed scheme is a new time-series pattern mining technique for dynamical modeling of gene expression. To evaluate the performance of this paradigm, it is applied to a case study dataset from Gene Expression Omnibus (GEO) which includes the temporal transcriptional profile of human colon cancer cells. The goal is to investigate the pharmacodynamics of two anticancer drugs. The transient and steady-state analysis of the transcriptional response clearly demonstrates the ability of the proposed approach to reveal the pharmacodynamical effects of drug type and dosage on the expression of genes.
Lab-on-a-chip: wearables as a one stop shop for free-living assessments

As clinical characterization of mobility abnormalities can be highly dependent on examiners’ expertise, wearable technologies have the potential to access aspects of mobility measured in free-living. Over the past 20 years, advances in wireless and miniaturized technologies have emerged as viable tools to move from laboratory-based measures of mobility to free-living. In fact, as it is known that patients with various conditions do paradoxically well when they know that they are being observed, unobtrusive home monitoring has the untapped potential to provide quantitative mobility measures that may be even more sensitive markers of subtle changes, compared to measures in the laboratory. This chapter will provide an overview of the potential uses, benefits, and obstacles of utilizing wearable technology for assessment of mobility in clinical populations.
Photonic decision-making for arbitrary-number-armed bandit problem utilizing parallel chaos generation

In this paper, we propose and experimentally demonstrate a novel scheme that helps to solve an any-number-armed bandit problem by utilizing two parallel simultaneously-generated chaotic signals and the epsilon ( ɛ )-greedy strategy. In the proposed scheme, two chaotic signals are experimentally generated, and then processed by an 8-bit analog-to-digital conversion (ADC) with 4 least significant bits (LSBs), to generate two amplitude-distribution-uniform sequences for decision-making. The correspondence between these two random sequences and different arms is established by a mapping rule designed in virtue of the ɛ-greedy-strategy. Based on this, decision-making for an exemplary 5-armed bandit problem is successfully performed, and moreover, the influences of the mapping rule and unknown reward probabilities on the correction decision rate (CDR) performance for the 4-armed to 7-armed bandit problems are investigated. This work provides a novel way for solving the arbitrary-number-armed bandit problem.