Reviewerly/exHarmony huggingface dataset:
To Cloud or Not to Cloud? Deciding on Blockchain Infrastructure

&lt;p&gt;In the rapidly evolving landscape of blockchain technology, businesses are confronted with the pivotal decision of selecting the appropriate infrastructure for their blockchain implementations. This article delves into the intricacies of cloud-based versus on-premise blockchain solutions, offering a comprehensive comparison of their respective advantages and challenges. Through real-world case studies, the practical implications of each choice are illuminated, emphasizing factors such as scalability, cost-efficiency, control, and security. Recognizing that no single solution fits all, the article provides a guide for businesses to evaluate their specific needs, budgetary constraints, and future expansion plans. By presenting a balanced view, this article aims to equip businesses with the knowledge to make informed decisions that align with their strategic objectives in the blockchain domain. &lt;/p&gt;
Knowledge management based on the dynamism of the character of students, who are members of teams implementing social projects

Education for social work requires students to perform many tasks, ensuring interdisciplinary preparation for this profession. The usefulness of social design and its didactic value should be seen in this context. Didactic projects, thanks to multi-tasking, stimulate students' activity, teach responsibility, moreover, they enable combining knowledge with action, and develop reflectiveness. The implementation of social projects requires cooperation of students in project teams. However, the efficiency of team cooperation is determined by the proper configuration of the individual characteristics of team members, in accordance with the assumptions of M. Mazur's (1999) psychocybernetic theory of character. In terms of this theory, a man with a specific dynamism of character has a better chance of effective cooperation when he cooperates with people of the same dynamism. These chances are greater because allied people have a greater sum of their powers (synergy effect), it is easier for them to take challenges together. The aim of that paper is to present the results of the conducted diagnostic research - questionnaire research, in the field of the character of students in psychocybernetic terms. In total, 19 students, who were registered for the implementation of didactic social projects, took part in the study. Based on the estimations of character parameters, the most favorable configuration of members of 3-person project teams was indicated. This procedure is part of the knowledge management process - as improving the education process in the field of dynamic, time-limited, temporary and team-implemented didactic projects, where the problem is sharing knowledge in order to achieve team effects (through a group), resulting in low effectiveness undertaken projects, low quality of results, etc. Research objective: researching the usefulness of knowledge in the field of individual, autonomous character traits of students for designing effective teams implementing didactic social projects.&#x0D;
An Improved DEFAULT-like Cipher via Dynamic Secret S-Boxes Against Differential Fault Attack

DEFAULT block cipher presented at ASIACRYPT 2021 was specially designed against differential fault attack (DFA). However, the security of DEFAULT against Information Combining Differential Fault Attack (IC-DFA) was further checked at EUROCRYPT 2022. It is illustrated that IC-DFA can recover the secret key of DEFAULT with less than 100 faults and negligible computational complexity. In this article, a variant cipher based on linear structure and dynamic secret S-box (called DEFAULT-DS) is proposed. More precisely, DEFAULT-DS introduces 15 secret S-boxes, where the selection of these S-boxes is determined by using the round subkey. Moreover, the experimental results show that DEFAULT-DS achieves better security level and stronger resistance against DFA compared with original DEFAULT. In particular, DEFAULT-DS can resist to both the classical DFA and IC-DFA. Furthermore, the software implementation complexity of DEFAULT-DS is similar as DEFAULT.
Conceptual considerations for the paperless production of ophthalmic lenses

In addition to reducing paper consumption, paperless production offers the possibility of automating further work steps and additionally gaining further process information in the production of ophthalmic lenes.
A Case Study of Internet Banking Security of Banks Operated in Bangladesh

Now a day, Internet Banking is a popular service for the customer of the Banks. As a convenient way of doing banking more and more customers are registering for the internet banking. The banks also getting benefits of providing services to the customer round the clock without any manual involvement of the banker. As all the services done through an automated process, the security features should be implemented properly to protect the customers for any fraudulent transactions. The system should be available round the clock and transactions should be monitors as well as the systems should also monitored for any abnormal behavior of transactions and the system. The hacker group continuously try to penetrate the system and if become successful, the bank and customer both will bear loss. for banks, if the hackers cannot be protected, the bank may go out of business. This study intends to find out the issues of different internet banking site of Bangladeshi banks and recommend the best practices for the banks to be followed to do banking business securely. This will also secure the economy of the Country as a whole, as the banking system is the key to the Financial system of a country.
Mediating Role of Knowledge Management in the Relationship between Organizational Memory Building and Human Resource Management

This paper aims for verify the role of knowledge management as a mediator in the relationship between organizational memory building and human resource management to develop high education institutions into human resource management organizations. In this study, the researchers relied on empirical study to test the relationship between the variables. Therefore, a survey questionnaire was conducted. The study population consisted of faculty members in Palestinian universities, whose number is (7,367) members. The study sample consisted of (360) professors from Palestinian universities. The results show that the mediating variable (KM) affects the dependent variable (HRM) by (0.675); and it is statistically significant at a significance level less than (0.001). Including the independent variable (OM) in the same model, its effect on the dependent variable (HRM) vanished, and the value of the statistical significance became (0.051).
Mobile Forensic for Body Shaming Investigation Using Association of Chief Police Officers Framework

Body shaming is the act of making fun of or embarrassing someone because of their appearance, including the shape or form of their body. Body shaming can occur directly or indirectly. MOBILEdit Forensic Express and Forensic ToolKit (FTK) Imager are used to perform testing of evidence gathered through Chat, User ID, Data Deletion, and Groups based on digital data obtained on IMO Messenger tokens on Android smartphones. This study aimed to collect evidence of conversations in body shaming cases using the Association of Chiefs of Police (ACPO) framework with MOBILedit Forensic Express and FTK Imager as a tool for testing. Based on the research findings, MOBILedit Forensic Express got an extraction yield of 0.75%. In contrast, using the FTK Imager got an extraction yield of 0.25%. The ACPO framework can be used to investigate cases of body shaming using mobile forensics tools so that the extraction results can be found. The results of this study contributed to forensic mobile knowledge in cases of body shaming or cyberbullying ACPO framework as well as for the investigators.
A Study on the Design and Implementation Plan of Computer Network Architecture in Education and Teaching

With the rapid development of information technology, computer network has penetrated all aspects of education and teaching and become an indispensable infrastructure in modern teaching. On the one hand, the reasonable design and effective implementation of network architecture provide teachers with rich and diverse teaching means and platforms, greatly widening the teaching space and improving teaching efficiency; on the other hand, it also provides students with a more open and independent learning environment, making the time and space for learning greatly extended. However, it is an extremely challenging problem to design and implement a scientific and reasonable, safe, and reliable education and teaching computer network architecture to meet the growing diversified educational needs. Based on this, the article discusses in depth the design and implementation plan of computer network architecture in education and teaching, to provide some useful references and ideas for the construction of education informatization.
Improved BEGAN Algorithm Based on Edge Image Processing

Image edge refers to the set of pixels in the image that have strong contrast with the neighboring graylevel. It is the basic feature of an image and often carriesthe most useful information about the image, which provides a valuable and important basis for people to describe or identify the target and interpret the image. Image enhancement technology is to highlight some features in an image and filters out some unnecessary features according to specific needs. Based on the improved BEGAN data enhancement method, this article proposes a new edge blur background conversion algorithm by optimizing the flow chart of the gray image recognition system, which improves the accuracy of image recognition, and analyzes the advantages and disadvantages of the algorithm and the feasibility of practical use. In order to verify the effectiveness of the improved BEGAN data enhancement method in this article, the algorithm simulation experiment is carried out. The test results show that the accuracy of the improved BEGAN data enhancement method is as high as 95.86%, which is about 15% higher than that of the traditional method. In addition, the MSE and RMSE of the improved algorithm can be stabilized at around 4.11 and 0.518, both of which are at a low level. The test results verify the superiority and reliability of the proposed algorithm.
Hyperchaotic Image Encryption Algorithm Based on Deep Neural Network Key Generation and Dynamic DNA Coding

This paper proposes a super chaotic image encryption scheme based on deep neural network key generation and dynamic DNA coding, First, we use deep convolutional neural networks to extract features from plaintext images, and use the feature values as the initial values of the chaotic system, and then iterate the super chaotic Lorenz system to obtain the chaotic sequence for encryption, and use the chaotic sequence to dynamically select the DNA coding rules for image pixel matrix and The DNA encoding and operation of the chaotic sequence are used to change the image pixel values, and finally the dislocation and diffusion operations are performed to realize the encryption. The experimental results show that the image encryption scheme proposed in this paper can effectively resist differential attacks and various statistical analyses, and has higher security compared with other algorithms.
DeepSFM: Robust Deep Iterative Refinement for Structure From Motion

Structure from Motion (SfM) is a fundamental computer vision problem which has not been well handled by deep learning. One of the promising solutions is to apply explicit structural constraint, e.g. 3D cost volume, into the neural network. Obtaining accurate camera pose from images alone can be challenging, especially with complicate environmental factors. Existing methods usually assume accurate camera poses from GT or other methods, which is unrealistic in practice and additional sensors are needed. In this work, we design a physical driven architecture, namely DeepSFM, inspired by traditional Bundle Adjustment, which consists of two cost volume based architectures to iteratively refine depth and pose. The explicit constraints on both depth and pose, when combined with the learning components, bring the merit from both traditional BA and emerging deep learning technology. To speed up the learning and inference efficiency, we apply the Gated Recurrent Units (GRUs)-based depth and pose update modules with coarse to fine cost volumes on the iterative refinements. In addition, with the extended residual depth prediction module, our model can be adapted to dynamic scenes effectively. Extensive experiments on various datasets show that our model achieves the state-of-the-art performance with superior robustness against challenging inputs.
Reconfigurable Distributed Quantum Metrology with Continuous-Variable States

Distributed quantum metrology can enhance measurements that are spatially distributed. However, a reconfigurable scheme for distributed phase sensing using continuous-variable states is missing. We propose such a scheme and discuss the fundamental sensing limits.
Towards a Continuous Variable Quantum Compiler

We present initial work towards an experimental implementation of a nonuniversal continuous variable quantum compiler capable of learning a linear phase operation with increased precision when quantum resources are used.
Generation of Two-Dimensional Cluster States Using Hyperentanglement

We present a technique for generating a two-dimensional cluster state, with a graphene topology. We exploit hyperentangled states, delay loops, and geometrical phase masks that act as beam splitters for different degrees of freedom.
Progress towards photon-photon nonlinearities based on multi-cavity quantum electrodynamics

Creating photon-photon nonlinearities is the key scientific challenge to converting current quantum networks into a user-defined quantum internet. We report on our progress building a universal multi-cavity quantum electrodynamics (mcQED) system.
Effective-Spin Models From a Single Atom for Steady-State Nonclassical Light Generation

Raman transitions between atomic sublevels in a continuously-driven, single-atom cavity QED system are explored for the generation of a variety of nonclassical states of the output light.
Enabling Multi-Quantum Emitter based Quantum Networks: Spectrally Uniform and Indistinguishable On-Demand Photons from Spatially-Ordered Arrays

Unique spatially-ordered and spectrally-uniform solid state quantum emitter arrays show promise towards realizing multisource and multipartite quantum networks. Optical and structural characteristics of these quantum emitters in large (~10000) arrays are statistically sampled and discussed.
Highly fault-tolerant quantum computing using both discrete and continuous variables of light

Fault-tolerant photonic quantum computing schemes have suffered low photon-loss thresholds and heavy resource requirements particularly when using single-photon qubits. Recently, several approaches utilizing both discrete and continuous variables of light have been proposed to reach high photon-loss thresholds with relatively low resource requirements. Here we present two schemes that outperform known previous schemes in terms of photon-loss thresholds and resource overheads. The first one is a hybrid scheme that combines discrete-variable (DV) and continuous-variable (CV) states of light. This scheme is nearly ballistic in the sense that passive measurements with hybrid entangled states are sufficient with little feedforwards. The second scheme is based on the parity-based encoding and Bayesian error tracking that enables one to reach a significantly high photon-loss threshold of ~8.5% with moderate resource requirements compared to previous known schemes.
Deep Learning-Based Refactoring with Formally Verified Training Data

Refactoring source code has always been an active area of research. Since the uprising of various deep learning methods, there have been several attempts to perform source code transformation with the use of neural networks. More specifically, Encoder-Decoder architectures have been used to transform code similarly to a Neural Machine Translation task. In this paper, we present a deep learning-based method to refactor source code, which we have prototyped for Erlang. Our method has two major components: a localizer and a refactoring component. That is, we first localize the snippet to be refactored using a recurrent network, then we generate an alternative with a Sequence-to- Sequence architecture. Our method could be used as an extension for already existing AST-based approaches for refactoring since it is capable of transforming syntactically incomplete code. We train our models on automatically generated data sets, based on formally verified refactoring definitions and by using attribute grammar-based sampling.
Structuring of an evaluation model of informational services in a library of an educational institution

This study aims to structure an evaluation model of informational services performed by the library of an educational institution. To this end, the Multicriteria Methodology for Decision Support-Constructivist (MCDA-C) was used, obtaining, as main results: (1) the identification of 41 Primary Elements of Evaluation (PEEs) and 75 Concepts, which resulted in five areas of concern; (2) the identification of five performance indicators of the "Basic Services", being one descriptor with “Commitment” performance, three descriptors with “Market” performance and one descriptor with “Excellence”; and (3) the proposition of improvement actions through the 5W2H technique.
Noise Driven Coupled Nonlinear Systems: A “Dynamical Multilayer Perceptron” Demonstrating XOR Functionality

Coupled dynamical systems, especially those comprised of hysteretic elements, possess remarkable behavioral similarities to some aspects of neural activity in living systems. While some features of this similarity have been explored, the results have not yet been leveraged to improve machine learning techniques or artificial neural networks. In this work, a dynamical system of coupled overdamped bistable elements subject to a noise floor assists in information transfer. With the noise allowing the system elements to switch randomly between their stable states, the system response is quantified via a steady state probability distribution. A simple five element realization of this network is used to produce the analog equivalent of an XOR gate, an “XOR transform”, through the proper choice of coupling coefficients and controllable external biases. The demonstration of the XOR transform indicates the ability of the system to synthesize more general functions, a necessary prerequisite for machine learning and computing applications. Finally, a silicon implementation is proposed and simulated using a verified process model that could be fabricated to generate a working analog computing system.
Penggunaan Peralatan dan Bahan Audio-Visual dalam Pengajaran di Kelas: Tinjauan Keefektifan

This research aims to assess the availability of audiovisual equipment and materials in schools and their practical usage in classroom teaching. The research design used is quantitative descriptive, and the instrument utilized for this research is a questionnaire. The data analysis technique employed is the Miles and Huberman Interactive analysis model. This study was conducted in 5 middle schools, with seven teachers as research subjects. The findings of this research indicate that the status of audiovisual equipment needs to be improved. Computers, televisions, tape recorders, and public address systems are only owned by 64.62% of the schools. Variables such as school management type, school age, school resources, and school strength do not significantly influence the possession of adequate or inadequate equipment in the schools. A total of 87.4% of the schools have effectively used audiovisual equipment. The school administration has yet to make any efforts to properly procure and utilize audiovisual equipment and materials, primarily due to the financial challenges associated with equipment maintenance.
Research on Computer Aided Laboratory Based on Cross-Multiplier Multi-Data Flow Collaborative Algorithm

&lt;p&gt;The paper develops a set of mobile laboratories based on the grid data cloud platform. The laboratory proposed a multi-data flow cooperative algorithm based on a cross-bus four-layer temporal space model and a cross-directional multiplier. This algorithm achieves the purpose of updating most data streams as a whole. The system establishes a statistical analysis system of data flow from multiple perspectives and mines and monitors multiple data flows. The paper divides most data streams into several linear modules, and corresponding matrices are formed. Finally, the simulated test results of the paper show that the CPU usage of the mobile laboratory computer-aided system based on the power network is very small. The system processing efficiency is high.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Augmented Reality-Based Lactic Acid Bacteria Diversity Flash Card Traditional Pakati'ng Rape’ Food

The impact of the Industrial Revolution 4.0 on education is to position education for modern learning. Modern learning must certainly involve learning media that can optimize the learning process. This study aims develop flash card media of lactic acid bacteria diversity of traditional food Pakati’ng Rape’ based on augmented reality. This research uses a research and development (R&amp;D) method with the Alessi and Trollip development model and involves 9 validators to validate flash card learning media. This research instrument uses validation sheets consisting of language validation sheets, media validation sheets and material validation sheets with quantitative analysis techniques. For the practicality test, there is a student response questionnaire instrument. The results of this study are the development of flash card media diversity of lactic acid bacteria traditional food Pakati’ng Rape’ based augmented reality has been declared feasible with an average of 90.39% (is very practical). Based on the result of student responses, the average wa 79% (practical) in the small-scale test and 80% (practical) in the large-scale test. Flash card media diversity of lactic acid bacteria tradisional food Pakati’ng Rape’ based on agumented reality to be valid and practical so that it can be used in learning.