Reviewerly/exHarmony huggingface dataset:
On the Perspectives of the Scientific Precariat

This paper is a part of the discussion about creativity and the scientific precariat, initiated by I.T. Kasavin’s article. Proceeding from his proposal to revise the ideology of creativity in science through the desire of certain precariat groups for independence and freedom, the author questions the nowadays perspectives for the scientific precariat. This paper discusses the varieties of the precariat (or related to it phenomena), such as freelancing and digital nomadism. The author considers a number of advantages (independence, freedom) and disadvantages of precarization (lack of stability, uncertainty, lack of social guarantees, etc.). The author questions whether scientists can be seriously considered as candidates for the precariat and how widespread the scientific precariat is in contemporary society. It is pointed out that the collective nature of modern science and its institutionalization impose certain obligations on scientists, which sometimes confront their individual internal aspirations, including the desire for freedom. The tension between the institutional conditions for the existence of science and the personal motives of scientists, noted once by M. Weber, lead to a decrease in personal autonomy, the emergence of a “world of specialists” and make it difficult to realize scientists’ aspirations for independence and freedom. On the one hand, a number of current trends (such as academic mobility) can be viewed as a kind of precarization in science. On the other hand, the status of an independent researcher without research and educational affiliation hinders scientists’ social recognition and financial returns. The author admits that representatives of “garage science”, some public intellectuals, science, communicators, etc. can be attributed to the scientific precariat; however, in general, the scientific precariat is not a common trend. At the same time, modern postscience and post-normal science potentially make this phenomenon quite legitimate.
An Overview of SAP ECC System Conversion

This chapter provides an overview of the system conversion process and explains the important tools that are necessary. The system starting point determines which tools consultants have to use. Consultants should refer to SAP Help documents, SAP Notes, and the SAP Conversion Guide while performing the system conversion.
Modal Logic S5 in Answer Set Programming with Lazy Creation of Worlds

Modal logic S5 is used extensively for representing knowledge that includes statements about necessity and possibility, owing to its simplicity in handling chained modal operators. Significant research effort has been devoted in developing efficient reasoning mechanisms over complex S5 formulas, resulting in various solvers taking advantage of the boolean satisfiability problem (SAT). Among them, the most performant solver implements a heuristic for identifying worlds that can be merged, hence reducing the size of SAT instances to be checked. Recently, Answer Set Programming (ASP) has also been considered, and different ASP encodings were proposed and tested, reaching state-of-the-art performance. In particular, a heuristic for identifying the propositional atoms that are relevant in every world resulted in a performance gain in previous experiments. This work addresses the open question of whether the aforementioned two heuristics can be combined, as well as possibly enabling lazy instantiation of the resulting encodings, and what their potential impact is on the performance of the ASP-based solver. Experiments show that lazy creation of worlds provides some further performance gain to the ASP-based solver on the tested instances.
CRITERIA FOR THE ANALYSIS OF SERIOUS GAMES INTERFACES IN VIRTUAL REALITY

The article presents an analysis of two games considered serious games in the context of virtual reality platforms: Bus Simulator Drive and EarthQuake Simulator VR.The objective is to analyze how the interaction process occurs in these types of games, which elements make up the interfaces in serious games, how they are used, how they integrate into the context, which aspects are relevant to virtual reality, among other aspects.Both games interfaces were analyzed according to the criteria: Virtual world, Interactivity, Graphical interface, Metaphors, and Feedback.The analysis possible to establish a systematic decomposition of the serious game itself, discussing the elements that make up the interfaces, how they are used, how they integrate into the context, which aspects are relevant to virtual reality, among other contributions.
Schatten Graph Neural Networks

Graph Neural Networks (GNNs) have been intensively studied in recent years because of their promising performance over graph-structural data and have provided assistance in many fields. Recalling recent works on graph neural networks, we found that imposing graph smoothing via Frobenius norm was proven to be effective in the architecture of graph neural networks from the standpoint of the graph signal processing. In this paper, we aim to model the graph smoothness of graph neural networks using a Schatten <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-norm with <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> in the interval <inline-formula> <tex-math notation="LaTeX">$[1,2$ </tex-math></inline-formula>) to characterize smoothness and propose a novel architecture called Schatten graph neural networks. This architecture stems from a primal-dual solution scheme for a graph signal denoising problem. There is difficulty in solving subproblems with respect to the Schatten <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-norm. We propose a fixed point iteration scheme and prove that it tracks with the linear convergence rate with solid mathematical analysis. Extensive experiments demonstrate the effectiveness of the proposed architecture of graph neural networks and their robustness to the graph adversarial attacks.
The Method of Realize the Cloud Based Generic Function Safety Platform

The Cloud based safety system is facing the technical challenges, such as the Cloud system is based on the no boundary concept designed but the traditional safety system was based on the certainty. Traditional safety system requires the dedicated hardware and operating systems, but the cloud computing system that is based on the generic hardware and virtually software-based system to approach the cost-effective. Safety coded processing is a software solution, which can achieve high diagnostic coverage without depending on specific hardware, but has high performance requirements. As a more lightweight computing unit in the cloud, Docker has the characteristics of better isolation, independent deployment, dynamic migration and elastic expansion. Based on the failure handling model, the multi-channel heterogeneous technology solution of Docker is combined by using the safety coded processing technology, which can detect all kinds of the failures and approach the safety requirement over the cloud computing. Meanwhile by building ecosystem of safety platform which can make the safety system migrate on the cloud computing available.
MinCentre: using clustering in global optimisation

A common problem that arises in many scientific fields is locating the global minimum of a multi-modal function. A novel clustering technique that tackles this problem is introduced here. The proposed method creates clusters from uniform samples of the objective function with the usage of the K-means clustering technique. For every cluster a centre is created. Finally, a simple rejection procedure is applied to the created clusters in order to remove clusters that are close to others. The proposed method is tested on a series of well-known optimisation problems from the relevant literature and the results are reported and compared against the simple multi-start global optimisation method.
Kernel Learning Estimation: A Model-Free Approach to Tracking Randomly Moving Object

Kernel learning estimation (KLE) is a kernel-based method, where the original spatial data is mapped into a high-dimensional Hilbert space by a nonlinear mapping, hiding the nonlinear mapping in a linear learning framework. The kernel function of the method can be used to replace the complex inner product operation in the high-dimensional space and avoid the Curse of Dimensionality caused by high-dimensional calculation effectively. The kernel-based method has advantages on learnability, computational complexity, precise linearization and generalization performances, providing a promising way to solve the problem of nonlinear target tracking. In traditional tracking methods, nonlinear tracking models are usually built as a priori to predict the current state of target motion, emphasizing on tracking accuracy and real-time performance. However, kernel-based method provides a general way of linearization processing, which can be independent of specific models to achieve highly efficient data-driven computation. Introducing the kernel learning mechanism into target tracking problem is expected to improve the environmental adaptability. In this paper, a review on kernel learning method with application to randomly moving target tracking is presented, including kernel-based algorithms for target detection, kernel-based algorithms for generative tracking and for discriminant tracking, and multi-kernel learning methods with multiple kernel functions. Further research is prospected in optimization of kernel function, long-term robust tracking, feature extraction, target occlusion and other potential aspects on moving target tracking using kernel learning theory.
Detection of phishing websites using data mining tools and techniques

Phishing, a prevailing cyber-security issue, is one of the most common attacks to obtain user's sensitive information. To eradicate it, the users or software should detect it first. A popular approach to carry out phishing is through generating phishing URLs. A URL could be legitimate or phishy which fits phishing into a perfect classification-type problem in data mining. Hence, data mining algorithms - C4.5 (J48), SVM, Random Forest, Treebag and GBM have been trained to carry out a comparison on measures - accuracy, recall and precision to determine the most suited model. Rules have been listed that categories the features which make a website phishy or legitimate. Work has been done using R language on RStudio. The dataset used comprises of 11,055 tuples and 31 attributes. It is trained, tested and used for detection. Among the five classifiers used, the best accuracy is obtained through Random Forest model which is 97.21%.
Security Testing and Attack Simulation Tools

This chapter lists several security testing and attack simulation tools by type. These tools must be operated in a contained environment like an isolated network segment, or when used in other types of environments, they need to be executed with a well-defined, clear scope and duration explicitly authorized by the system’s owners.
Two-direction two-scale similarity transformation of two-direction refinable function

In this paper, a special group is used to introduce the two-direction two-scale similarity transform (TDTST) of the two-direction refinable function, and the existence of the solution of the two-direction refinable equation is discussed by the TDTST transform. The approximation order of the two-direction refinable function is discussed by the TDTST transform. Whether the TDTST transform can maintain the orthogonality of the two-direction refinable function is discussed, and it is pointed out that a special real orthogonal matrix can maintain the orthogonality. It is pointed out that the TDTST transform can maintain the symmetry of the two-direction refinable function. Finally, an example is given.
Cryptography

Cryptography is a necessary component in many parts of a secure architecture. However, just adding cryptography to the code does not make it more secure; care must be given to such topics as secrets generation, secret storage, and plain-text management. Properly designing secure software is complicated, especially when cryptography is involved.
Creating a platform "Archive of Scientific Research" to increase the international ranking of the university

The article discusses the use of foreign experience to enhance the investment attractiveness of the higher education system in Uzbekistan, access to the list of the ranking of world universities TOP-1000 internationally recognized organizations (Quacquarelli Symonds World University Rankings, Times Nigher Education or Academic Ranking of World Universities), Webometrics ranking of World Universities
Draft: A Double Layer for Raft-Based Blockchain Consensus Mechanism

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HARDWARE AND SOFTWARE TESTING OF COMMUNICATION PROTOCOLS FOR ON-BOARD NETWORKS

The article deals with the problem of hardware-software research of communication protocols for on-board networks. A system is presented that allows testing the developed SpaceWire and SpaceFibre network equipment. Determination of the main stages of development of the system under consideration for SpaceWire technology demonstrates various network structures that meet the stated requirements for hardware and software testing of network equipment and determines the necessary devices for implementing the theory in practice. One of the sections of the article demonstrates the successful implementation of the proposed theory in practice. The described problems of implementing such a research complex for SpaceFibre technology help to determine the vector of further research.
Visual Representation of Bibliographic Production Data from Lattes Platform]Visual Representation of Bibliographic Production Data from Lattes Platform

Based on analysis of bibliometric data extracted from the Lattes platform. By collecting data from Lattes, the data will be prepared with textual preprocessing and multidimensional projection techniques was applied to verify the existence of patterns, observing the general distribution of the data and its correlations. A total of 1038 articles published by groups at the School of Arts, Sciences and Humanities of the University of Sao Paulo were evaluated. The groups˜ analyzed in this study belong to the Postgraduate Program in Information Systems, Textile and Fashion and the Astrophysics group. We obtained results from the multidimensional projection that visually projected articles belonging to groups that are related to each other and from research groups that work with different themes. Overall, the study showed that the projection techniques Least Square Projection and Multidimensional Scaling - Isomap showed the best results for visually projecting and separating research groups studying distinct topics.
Perancangan sistem informasi antrian service motor sebagai pendataan bengkel berbasis Android (Studi kasus : M2 Motor Bogor)

M2 Motor Workshop is a workshop in the process of its service in the field of two-wheeled vehicle repair services and the sale of spare parts and other components at M2 Motor Bogor is still carried out manually. The manual process in the M2 workshop is the collection of spare parts stock that is still recorded in the book, the service process to customers, the process of assigning tasks to technicians, and also the workshop owner still receives all transaction reports manually. This study aims to design a motorcycle service queue information system as an android-based workshop data collection which is expected to make it easier for customers to service motorbikes by taking the service queue number first through this application and customers can see service status, service cost data and spare parts data. in real time. Employees or admins can manage payment invoices, customer data, technician data, service data, spare parts data and make monthly reports for workshop owners through the system. Workshop owners can easily find out monthly reports, service data and spare parts data through the system. The research method for developing this system is to use the waterfall model and Unified Modeling Language (UML) to visualize the modeling.
Simple multi-scale human abnormal behaviour detection based on video

Aiming at the problem of real-time and low accuracy of automatic recognition of human abnormal behaviour in a public area surveillance video, a simple multi-scale human anomaly behaviour detection algorithm based on video was proposed. Firstly, the binary image sequence of human body in surveillance video is acquired by background modelling method based on visual background extraction (ViBe). Then, the simple multi-scale algorithm is constructed by combining the aspect ratio, motion trajectory and video continuous interframe motion acceleration of the minimum circumscribed rectangle of the binarised image. The human target behaviour is judged, and then the normal behaviour of the human body - standing, walking, jogging, and abnormal behaviour - shouting for help, falling, punching, wandering, and sudden running are identified. The experimental results show that the human body moving target recognition by ViBe combined with simple multi-scale algorithm for abnormal behaviour detection has good real-time performance and high accuracy.
Recursive Visual Cryptography Scheme with PRWP and Additional Basis Matrix

Recursive visual cryptography scheme (RVCS) is a high-security image secret sharing scheme in which the shares are recursively encoded into sub-shares at numerous levels. Here we presented a new scheme for RVCS with a perfect reconstruction of white pixels (PRWP) and an additional basis matrix (ABM) which boosts contrast. The method has been illustrated on the basis of investigational examinations. We made an evaluation between the conventional schemes and the proposed scheme through investigational analysis. The results revealed that our scheme improves the visual quality and ensures security and reliability.
Interpreting Reo Circuits as PDL models

Reo is a coordination-based language with the proposal of connecting different systems and interfaces. It aims to develop communication between different systems with a high level of abstraction and without many restrictions. PDL is a multimodal logic tailored to reason about programs. It is proved to be sound, complete, decidable and has a simple Kripke semantics. This work intends to provide an interpretation of Reo circuits as PDL models. These are the first steps towards providing a dynamic logic tailored to reason directly about Reo circuits.
A Multi-Information Detection Model for Violent Images based on YOLOv3-SPP and DenseNet

The Internet has become an important carrier of people&#x0027;s daily life, and it is constantly developing and growing. In order to create a healthy and benign Internet environment, these sensitive pictures need to be identified and filtered. In the field of sensitive image detection, the violent image detection technology is still in an immature stage, and there is still a lot of room for development in the detection accuracy in the real world. Current research mainly uses classification models ResNet, DenseNet and target detection model YOLOv3 to detect violent images. However, the classification model has the problem of paying attention to the global information and ignoring the target&#x0027;s location information and local target information. Target detection has the problem of only identifying specific local targets and ignoring the global information. In order to solve this problem, this paper proposes a multi-information violence image detection model based on YOLOv3-SPP and DenseNet. Combining the information of the two models through the multi-information model improves the detection accuracy of violent images by 1.3&#x0025; compared with DenseNet and 2.2&#x0025; compared with the ResNet model.
A New Image Encryption Scheme Based on Hyperchaotic System and SHA-2

This paper presents a new image encryption scheme by using a four-dimensional hyperchaotic system and adopting permutation-diffusion architecture. The initial conditions of the hyperchaotic system are modified by the 256-bit digest of the plain image to increase the sensitivity of the cipher to the plain image. An enhanced nonlinear equation is applied in the diffusion process for the better encryption result. The experiment results show that the proposed scheme has large key and subkey space, high key sensitivity, good information entropy, and capability to resist statistical and differential attacks.
Review of Patents Issued to Computer Architecture Companies in 2021 [Micro Law]

This two-part article takes a break from my series on the Analysis of Historical Patenting Behavior and Patent Characteristics of Computer Architecture Companies in order to analyze the patents that were issued to 18 computer architecture companies in 2021. Part III of the series will return in the July/August issue of IEEE Micro. This two-part article first examines the number of total patents and the number of computer architecture patents that were issued to each company in 2021. Second, it compares the distribution of those patents across different patent classes. Third, it highlights one patent from each company that may be particularly notable.
Quantifying Trustworthiness in Decentralized Trusted Applications

Decentralized systems play an important role in many modern data processing applications. Due to the distributed nature of these applications, participating system components are often operated by different stakeholders with potentially conflicting interests. To prevent malicious participants from manipulating critical system components, trusted computing technologies such as Trusted Platform Modules (TPMs) or Intel's Software Guard Extensions (SGX) can be employed. These technologies provide hardware-based access control to sensitive data and allow users to remotely verify the integrity of critical software stacks. However, not all trusted computing technologies are equally suitable for all use cases. As different technologies offer different benefits and drawbacks, it becomes quite challenging to determine if the decentralized system can be fully trusted in its current state. In this work we present a methodology for estimating the trustworthiness of decentralized systems that are being protected by trusted computing hardware. Our approach is based on a formal model describing the operational dependencies between distributed system components, as well as the required protection goals for a secure component operation. Based on this model we then show how stakeholders can calculate the trustworthiness of a specific system operation as a subjective probability (degree-of-belief). We then generalize this approach to obtain trust estimations for the entire decentralized system. Finally we demonstrate the application of our proposal using the real-world scenario of distributed usage control as an example.
Research on the application ability of GaoFen satellite data in monitoring changes in mine land use

With the improvement of the temporal and spatial resolution of domestic satellites, it has gradually replaced foreign data and has been widely used in geological surveys and other fields. This article uses the GF satellite data to extract the mine land information. By comparing the extraction results in different years and the existing regional survey results, the ability of the GF satellite data to judge the boundaries and changes of the mine land is evaluated, so as to monitor the changes of the mine land. The results show that the GF data can identify information such as mine stope, restoration and governance, and can be used for monitoring changes in mine land.