Reviewerly/exHarmony huggingface dataset:
Impact of passive and negative sentences in automatic generation of static UML diagram using NLP

In this research work, we propose a rule based approach for the automatic extraction of UML diagram from the unstructured format of software functional requirements. The existing work provides decent results for active sentences and positive sentences but the challenge in our work is to automatic extract class diagram elements from passive voice type sentences and negative sentences. Furthermore, there is scope to do more research in extraction process using multi-word terms. Thus, we have endeavored to automatic extract the class diagram elements by overcoming these challenges. The methodology uses the Stanford CoreNLP Tools along with Java for the practical implementation of formulated rules. Our approach has proved that without supplant the human being and their decision making, one could reduce the human effort while designing functional requirements. Several case studies were performed to compare class diagrams generated by our methodology to the ones created by experts. Our methodology outperforms the existing work and provides impressive Average completeness (0.82), Average correctness (0.92) and Average redundancy (0.15). Results show that class diagram elements extracted by our methodology are precise as well as accurate and hence, in practice, such class diagrams would be a good preliminary diagram to converge towards to precise and comprehensive class diagrams.
Intelligent Robotics in the Structure of the Direction "Information Systems and Technologies"

The use of the anthropomorphic robot NAO Evolution in the educational process of training bachelors and masters at the Department of Informatics and Information Technology of the Vologda State University is considered. The contents of a set of laboratory works on studying the possibilities of controlling robot mechanisms in the Choregraphe software package, methods for constructing real-time behavior scenarios, and the possibility of organizing a dialogue with the robot in a natural language are discussed. Fragments of programs that implement the studied possibilities are given.
COMPLETELY SEPARABLE MAD FAMILIES AND THE MODAL LOGIC OF βω

Abstract We show in ZFC that the existence of completely separable maximal almost disjoint families of subsets of $\omega $ implies that the modal logic $\mathbf {S4.1.2}$ is complete with respect to the Čech–Stone compactification of the natural numbers, the space $\beta \omega $ . In the same fashion we prove that the modal logic $\mathbf {S4}$ is complete with respect to the space $\omega ^*=\beta \omega \setminus \omega $ . This improves the results of G. Bezhanishvili and J. Harding in [4], where the authors prove these theorems under stronger assumptions ( $\mathfrak {a=c}$ ). Our proof is also somewhat simpler.
Highly Interactive Hybrid Honeypot

Security aspect of the computer systems represents a massive expanding area within the IT segment. The current security approach is focused on the defense against attacks, with the current trend being ready in advance for a potential threat. This approach can be achieved by using more aggressive forms of security, which includes Honeypot technology - expert devices simulating weaknesses in system security to initiate interaction with the attacker and then analyze the valuable data on the course of the attack. The recorded data can be analyzed and used to improve the security of the computer system itself. The presented paper focuses on the design of a security architecture based on the high-cluster Honeypot cluster, with the architecture itself divided into individual clusters to fulfill their specific role.
Patent Protection for Artificial Intelligence in Europe

In order to increase the possibility of patent entitled of artificial intelligence related inventions at the European Patent Office, applications should focus on what technical problems the invention are solving or identify the specific technical improvements. From the perspective of patent analysis, European artificial intelligence technology is leading the world and in this field, the European Patent Office is one of the most important intellectual property offices, and its legislation and practice of patent eligibility examination for artificial intelligence related Inventions have an important impact on the world. the European Patent Office takes the position in the Guidelines that artificial intelligence and machine learning technologies are based on mathematical methods and are therefore generally excluded from patent eligibility unless linked to a technical application. The updated Guidelines did not make substantial changes to the "technical " requirements of the patent eligible subject, but only further clarified and refined it.
Preemptive Resource Provisioning for Container-Based Audio/Video Encrypted Collaboration Applications

The massive industrial adoption of cloud technology has led to research into cloud-enabling traditional applications. The EMD research project proposes an elastic, reliable, and secure cloud-enabled Audio and Video (A/V) collaboration platform in replacement of a reliable hardware appliance based which had fixed constraints in terms of scalability. In this context, this article introduces heuristics and architectures that efficiently and preemptively allocate EMD’s A/V encrypted and container-based software components in the cloud. A software solution based on Kubernetes, a production-grade container orchestration platform, is compared with another solution focused on dedicated VMs. Both implement resource allocation heuristics that take into account the project’s requirements and location-aware encryption enforcement necessities: encryption is enforced for more sensitive data. A company training scenario with dynamically distributed instructors is modelled using existing A/V stream concepts, and component prototypes are extended to support encryption and containerisation, whose prototype performance evaluation drives the investigation of heuristics and architectures and feeds their larger-scale simulation-based assessment. Results show that container orchestration costs are at least 52% lower than dedicated VMs for this scenario, but rely on relaxing a project requirement: the time taken to establish a new streaming session was to be kept below 2 s. The switch to orchestrated containers raised this up to a maximum of 2.5 s.
Vibration analysis of moving machine tool axes based on phase information in video data

Vibrations of machine tools limit quality and productivity and therefore need to be analyzed. Video based vibration analysis using spatial phase information could in principle reduce measuring effort significantly. However, feasibility of these approaches for moving machine tool axes and relative movement between camera and object is yet to be shown. This paper investigates an approach for stabilizing linear axis movement to analyze vibration. It is shown that shaker induced vibration on a linearly moving clamping tower can be derived for low frequencies. However, influences of actual cutting processes as well as compensation of unwanted camera vibration needs further investigation.
Cascaded Detail-Aware Network for Unsupervised Monocular Depth Estimation

Existing unsupervised learning methods usually reformulate the depth estimation into the image reconstruction problem by training on stereo image pairs to circumvent the need of dense labeled ground truth depth information. Most of them are designed based on a simple encoder-decoder backbone architecture, which has limited expression for context information and suffers from the loss of depth details. In this paper, we propose a cascaded detail-aware network which contains a contextual network (CN) followed by consecutive spatial networks (SNs) to make an unsupervised coarse-to-fine prediction. CN aims to provide good initialized depth estimation results by introducing a multi-scale attention fusion module to enhance the ability of feature representation. Then, SN is progressively applied on the coarse depth map to produce refined depth outputs by exploiting abundant spatial details from input color image. Moreover, we design a robust loss function that further considers the penalty of photometric errors and the occlusion, and strengthens the recovery of spatial details for better depth estimation. Experimental results show that the proposed method achieves promising performance.
RELEVANCE OF PRODUCT INTEGRATION IN SCALED AGILE MECHATRONIC PRODUCT DEVELOPMENT

Abstract Industrial automotive development differs significantly from ideal agile conditions. Complex development structures, interlinkages between teams and non-functional physical dependencies between components result in agile constraints of scale and physicality. This qualitative study researches the influence of the product integration process on these constraints. The results show, that automotive integration characteristics such as duration, frequency, scope and transparency fail agile requirements and therefore cause constraints. Alternatives regarding IT and process design are discussed.
On the Generation of Random Data for Auto-Generative Learning Objects

Learning by repetition is a way of learning that involves repeated actions allowing to develop a skill. For STEM disciplines one way of learning by repetition is to use Auto-Generative Learning Objects. They are used to create content variations in each of the designed learning scenarios. One solution to create variation is to use random numbers produced by random number generators. The problem with random numbers is that they cannot be used directly in learning objects except for a few simple cases. They need to be transformed into consistent or controlled random values necessary for the learning scenario in sections like: question, answer and feedback. One possible solution for the transformation of random data into consistent or controlled random data is to design specialized and reusable libraries in this sense. Thus, Auto-Generative Learning Objects creation will rely heavily on controlled random data produced by these libraries.
Vector Operation Function Library Optimization Based on BWDSP104X

In order to cooperate with the promotion of high-performance processor BWDSP1042, the cooperation of hardware and software is required, and the library function is one of the most basic and core software in high-performance computing. Its performance will directly affect the efficiency of various upper-level scientific and engineering calculations. Therefore, the implementation of library functions is closely related to the development of hardware platforms. To this end, this study designed an optimized algorithm function library with common algorithm standards based on its unique instruction characteristics and resource structure. First, based on the signal processing requirements of the basic function library, based on the Matlab function library, and The experience in signal processing selects the development functions required for each module, and based on the selected functions, the C language library is developed. Then, combined with the C language algorithm framework, the assembly language is written. The assembly language function library should be consistent with the algorithm flow of the C language function library, and the calculation error with the Matlab language library function is within a reasonable range. Finally, the running time is compared with the actual running period and the theoretical running period by using the clock cycle as a unit to check whether the operation efficiency of the assembly function meets the efficiency requirements of the library function. By making full use of bwdsp1042's computing resources in the study of this subject, the effects of reducing cycle and improving efficiency have been achieved. The relative error of the results obtained by the test function is in the order of 10-7, which is within the tolerance range. In summary, the library function development work based on the bwdsp1042 processor in this research can actively cooperate with the launch of the processor, laying a foundation for the localization of core devices.
Semantic Trajectory Planning on the Edge for Optimized Context-Aware Autonomous Navigation of Mobile Robots

Autonomous mobile transport systems are a key enabler for flexible production organization. In order to enhance the software life cycle management and the overall function range, service-based offloading of software function towards cloud and edge is a valid alternative to monolithic onboard software architectures. We introduce an approach towards an edge-computing-based improvement of the classic autonomous navigation stack in terms of considering semantic policies using visual object detection and localization. Thus, context-aware navigation in regards to safety and efficiency can be implemented, e.g. to fulfill directions of standards and guidelines for production, hospital or public domains.
video compression based on sphere‐rotated frame prediction

360 video is very popular due to its 360 views of a scene. Although 360 videos are also compressed by a hybrid coding framework like 2D video, its high resolution and serious shape deformation affect coding efficiency. In equirectangular projection (ERP) format of 360 videos, if an object moves from equator regions to pole regions or vice versa, large deformation will be introduced and motion estimation cannot find the best-matched part. To solve the above problem, the authors propose to generate a better reference frame for the current to be encoded frame. First, they project the frame prior to the current one from ERP to the sphere and rotate it at an appropriate angle depending on motion vectors. Subsequently, they insert this generated frame to the rear of the reference queue and let the encoder work as usual. The advantage is that the inserted frame has a more similar shape deformation as the current frame, which greatly helps motion estimation and makes full use of 360 video characters. Their method is simple and friendly compatible with the existing compression standard. Experiments prove that their method achieves 1.57% Bjøntegaard Delta (BD)-gain compared with standard high efficiency video coding.
Automated Construction and Analysis of Scientific and Educational Profiles of the University Department

The article proposes an automated method for building scientific and educational profiles of the university department based on the use of Data and Text Mining tools. We form two samples: a sample of publications from the digital library eLibrary.ru (to construct a scientific profile of department) and a sample of courses from electronic versions of educational programs (to construct profiles of educational courses). We describe the algorithms of processing and analysis of text documents. We present the results of approbation of the developed software, algorithmic and methodological support (on the example of the departments of the National Research University "Moscow Power Engineering Institute"). We discuss the advantages, disadvantages and different ways and methods of using our approach.
Efficient GPS Scheduling in Wildlife Tags using an Extended Kalman Filter-based Uncertainty Suppression Strategy

Animal-mounted GPS-based location tracking has become a core tool for wildlife ecologists. However, the lifetimes of animal-mounted devices (or “tags”) are typically limited by battery life, and GPS tracking occupies a large portion of their energy budgets. In this paper, we propose several Kalman filter-based algorithms that reduce the GPS duty cycle while still maintaining a threshold of tracking accuracy, and test these algorithms using a human subject. These algorithms leverage low-power accelerometry measurements to estimate the uncertainty in the tag's location, then schedule GPS measurements to suppress that uncertainty. We show that these strategies can reduce average GPS uptime, though at the cost of fidelity in some cases.
Multimedia Academic Manual "Database Application Development"

A review of the current state of open access multimedia academic manuals and electronic learning resources in the field of programming and database application development is provided. A review of similar online courses hosted on national and global platforms in the field was conducted. The experience of developing a multimedia tutorial on the use of the Delphi programming language for developing applications designed for integrated work with databases is described. The integration of a multimedia academic manual in an interdisciplinary learning management system (LMS), implemented on a dedicated server in the modular object-oriented distance learning environment Moodle and the organization of the final knowledge control, is considered.
Hygienic macro technology

The fully parenthesized Cambridge Polish syntax of Lisp, originally regarded as a temporary expedient to be replaced by more conventional syntax, possesses a peculiar virtue: A read procedure can parse it without knowing the syntax of any expressions, statements, definitions, or declarations it may represent. The result of that parsing is a list structure that establishes a standard representation for uninterpreted abstract syntax trees. This representation provides a convenient basis for macro processing, which allows the programmer to specify that some simple piece of abstract syntax should be replaced by some other, more complex piece of abstract syntax. As is well-known, this yields an abstraction mechanism that does things that procedural abstraction cannot, such as introducing new binding structures. The existence of that standard representation for uninterpreted abstract syntax trees soon led Lisp to a greater reliance upon macros than was common in other high-level languages. The importance of those features is suggested by the ten pages devoted to macros in an earlier ACM HOPL paper, “The Evolution of Lisp.” However, na'ive macro expansion was a leaky abstraction, because the movement of a piece of syntax from one place to another might lead to the accidental rebinding of a program’s identifiers. Although this problem was recognized in the 1960s, it was 20 years before a reliable solution was discovered, and another 10 before a solution was discovered that was reliable, flexible, and efficient. In this paper, we summarize that early history with greater focus on hygienic macros, and continue the story by describing the further development, adoption, and influence of hygienic and partially hygienic macro technology in Scheme. The interplay between the desire for standardization and the development of new algorithms is a major theme of that story. We then survey the ways in which hygienic macro technology has been adapted into recent non-parenthetical languages. Finally, we provide a short history of attempts to provide a formal account of macro processing.
The Application of The Logistic Model in Analyzing the Risk of Bankruptcy of Small and Medium Enterprises (SMEs): A Case Study

Using the data of 46 unlisted small and medium enterprises divided into two categories, consisting of 23 bankrupted and non-bankrupted enterprises, the study examined some aspects of bankruptcy risk prediction based on the logistic regression model to identify the most important financial factors related to viability of small businesses. The most notable findings of the study are that businesses in suburban areas are at a higher risk of bankruptcy than firms concentrated in the central districts. The age of enterprises also affects the risk of bankruptcy. For financial indicators, the research results show that economic profitability, firm size, revenue growth and sales to capital investment are important and meaningful factors related to forecasting the exhaustion. Small businesses truly face financial crises in the context of the transition economy, developing along with the young financial market in Vietnam today. Based on the research results, some limitations and further research directions are also proposed.
IHS for QoS Satisfaction Degree Based Web Service Composition Optimal Model

To solve the problem of web service composition optimization, intelligent optimization algorithms have been used to get the optimal composition solution. Yet, most of the current work lacks consideration of users' subjective feelings. In this paper, the concept of QoS satisfaction degree is introduced to take the user's subjective feelings into consideration. And an optimal model is proposed for maximizing the user's QoS satisfaction degree based on the current QoS web service composition model. Besides, an improved harmony search algorithm (IHS) is prompted to solve the problem. Learning strategy is used in the fine-tuning operation of IHS, and a competition mechanism is introduced in the harmony library updating operation. IHS overcomes the disadvantages of the high random and non-directional searching process of the original harmony search algorithm. IHS and HS are applied in the experiments. Test results show that IHS can get better time efficiency and solution than the HS algorithm does.
System of Automated Operative Control of Radiation Situation of Fast Reaction on the Literal Apparatus Base

Introduction.The disaster at the Chornobyl nuclear power plant (ChNPP) resulted in releasing a huge amount of radioactive material into the atmosphere, the total amount of which is difficult to estimate reliably.Problem Statement.Radioecological works are radiation reconnaissance with detailed mapping of contamination levels and systematic monitoring of radiation situation.One of the most effective methods for surveying the areas contaminated with radiation, as well as for searching radioactive sources is remote measurements of ground-level gamma radiation by aerial gamma-ray spectrometry.Therefore, it is important to design and to test a modern system of operational radiation, infrared, and visual control using airborne vehicles to solve these problems.Purpose.Development of modern domestic equipment for automated operational control of the radiation environment using airborne vehicles.Materials and Methods.The methods of mathematical and computer simulation, full scale layout, machine design have been used.In order to study the technical characteristics of the system, its features, field tests of its individual channels have been conducted in the Chornobyl exclusion zone.Results.An automated system for rapid radiation, infrared, and visual radiation operational control and monitoring of the natural environment has been created based on the R-Navigator airborne vehicle for solving problems of remote control of NPPs and adjacent territories in the case of emergency or accidents with nuclear and radioactive materials.Conclusions.The proposed development provides high-sensitivity detection of gamma radiation, video recording and remote data transmission to ground control centers for prompt response to emergencies, as well as contributes to reducing the cost of aero-gamma spectrometric works.