Reviewerly/exHarmony huggingface dataset:
Dynamic Pricing for Non-fungible Resources: Designing Multidimensional Blockchain Fee Markets

Public blockchains implement a fee mechanism to allocate scarce computational resources across competing transactions. Most existing fee market designs utilize a joint, fungible unit of account (e.g., gas in Ethereum) to price otherwise non-fungible resources such as bandwidth, computation, and storage, by hardcoding their relative prices. Fixing the relative price of each resource in this way inhibits granular price discovery, limiting scalability and opening up the possibility of denial-of-service attacks. As a result, many prominent networks such as Ethereum and Solana have proposed multi-dimensional fee markets. In this paper, we provide a principled way to design fee markets that efficiently price multiple non-fungible resources. Starting from a loss function specified by the network designer, we show how to compute dynamic prices that align the network's incentives (to minimize the loss) with those of the users and miners (to maximize their welfare), even as demand for these resources changes. Our pricing mechanism follows from a natural decomposition of the network designer's problem into two parts that are related to each other via the resource prices. These results can be used to efficiently set fees in order to improve network performance.
PERSONAL DEVELOPMENT IN AN INFORMATION AND EDUCATIONAL ENVIRONMENT BY MEANS OF ONLINE EVENTS

Modern online culture can provoke telephone, gaming, Internet addiction. The question arises, how can the sources of potential destructions be used for the creation of personality. The proposed materials describe the content of online activities aimed at personal development by assigning students the values of freedom from both traditional tobacco smoking and the consumption of electronic cigarettes. The authors show one of the ways to check the effectiveness, as well as a statistical method of objectifying the effectiveness of such measures.
PEDAGOGICAL CASE-COMPETITION AS A WAY TO TRAIN FUTURE TEACHERS

Pedagogical case competitions are an innovative form of training future teachers and professional development of current teachers. It is widespread in many areas and directions of training, but it is practically not used in pedagogical universities. The article presents the goals and objectives of pedagogical case competitions, evaluation criteria, examples of author’s cases, and suggests one of the possible formats for their conduct. The experience of implementing pedagogical case-championships has demonstrated their high efficiency, as well as the high interest of students.
PEDAGOGICAL SUPPORT OF PROFESSIONALLY ORIENTED RESEARCH ACTIVITIES OF STUDENTS IN THE STUDY OF GENERAL EDUCATION DISCIPLINES AT THE UNIVERSITY

The article presents the results of testing the system of pedagogical support of professionally oriented research activities of students in the study of general education disciplines of the natural and humanitarian block at the university. The role of the system used in improving both the motivation and quality of mastering general education disciplines and the formation of general research competencies is shown.
READINESS OF TEACHERS OF THE HUMANITIES TO FORM THE INNOVATIVE POTENTIAL OF FUTURE ENGINEER

The article is devoted to the study of readiness teachers of humanities to form the innovative potential of future engineers. The essence of the basic concepts is revealed, the results of empirical research are presented, proving the relevance of finding effective means to optimize the process of studying humanities disciplines in a technical university, one of which could be the development of a professional development course.
And history repeats itself ...Fractional tree

This article aims to present some important points within the evolution of fractional calculus, which today in the field of scientific research has become a field of great relevance with its important contributions to the development of science.It is important to note that this article is a transcription of the lecture given by Professor E. Capelas de Oliveira as the closing lecture of the II Brazilian Congress of Fractional Calculus, which gives a brief explanation of fractional calculus and some of their contributions throughout his career at Unicamp, addressed to its former master and doctoral students.Even more, as the lecture was given in Portuguese, a lot is lost in the transcription to another language.
Enhanced Modulation Recognition by Time-series Data Augmentation Based Spatiotemporal Multi-channel Framework

Abstract Automatic modulation recognition with deep learning has great prospective owing to computing power and big data. However, modulation recognition accuracy depends highly extent on massive volume of data and model applicability. Here, to overcome difficulties such as small sample dataset, manual extraction of features and low accuracy, we proposed an efficient recognition method that combined time-series data augmentation with spatiotemporal multi-channel learning framework. The results showed that the method provided positive indicators on the order of 93.5 percent for ten modulation signal types, which can be improved by at least 15 percent. Especially for QAM16 and QAM64 signals, the average recognition accuracy is increased by nearly 50 percent at SNRs as low as -2 dB, revealing remarkable recognition performance. Effectiveness of the proposed method provides an attractive approach for signal modulation recognition for wired or wireless communication fields.
Role of Whatsapp in Teaching and Learning Process in Schools in Pakistan

The purpose of this study was to explore the effects of the use of WhatsApp in education and discover the opinions of all stakeholders towards the teaching and learning process in private schools.The study was designed in descriptive research using quantitative as well as qualitative data.We used close-ended questionnaires for quantitative data and semistructured interviews for qualitative data.The sample of the study consisted of all the key stakeholders of the education system: principals, students, teachers, and parents.We conducted interviews with school principals and gathered quantitative data from parents, teachers, and students.The study was limited to private sector schools of Mandi Bahauddin district, Phalia city, in the Punjab province of Pakistan.We used thematic analysis and descriptive statistics to identify the opinions of all the stakeholders about the role of WhatsApp in the teaching-learning process.The use of WhatsApp was encouraged as a supportive technology and recommended by the stakeholders.We also discussed the theoretical and practical implication of using WhatsApp.
Instructors’ Perceptions of Teaching Online during Emergency Remote Teaching: The Case of a Teacher Education College

This paper explored instructors' perceptions of teaching online during emergency remote teaching.The sample consisted of instructors from a teacher education college in Israel.Data were collected from a survey and were analyzed using descriptive and inferential statistics.The results suggested an overall tendency towards positive perceptions of online learning and teaching practices.While quantitative data revealed undecided opinions regarding institutional support, qualitative data suggested a need for pedagogical and technical support for students and instructors.Correlations concerning specific demographics and categories were detected.Significant differences in perceptions according to specific demographics, categories, and statements were found.The study recommends more comprehensive institutional support for students and instructors that incorporates: 1) self-learning; 2) assessment and provision of technical and pedagogical training; 3) a robust technological infrastructure; 4) a professional learning community; and 5) peer mentoring programs that respect diversity and include the more experienced online instructors as valuable resources.
The Prototype of Blended Learning's Support System to Improve the Pre-Service Teacher's Digital Literacy

Various blended learning models have been developed, but none of them have focused on support systems to improve the digital literacy of preservice teachers.This study aims to produce a prototype of a blended learning support system that can improve the digital literacy of preservice teachers.This type of research is research and development using a 4D model.This research was conducted at Universitas Negeri Padang and started with a needs analysis of 168 students to develop a blended learning prototype.The prototype was tested on six experts, six lecturers, and six students in the limited test and 50 students at the dissemination stage.The data collection instrument used observation and questionnaires.The data were analyzed using descriptive statistical analysis.The results show that the validity of the blended learning support system to improve the digital literacy of preservice teachers was in the very valid category.All indicators from the experts were higher than indicators from the lecturers.Although each support system was assessed differently by the experts and the lecturers, overall the digital literacy components in each support system were declared valid.The results of this study contribute to the development of digital literacy for preservice teachers by integrating digital literacy skills into a blended learning support system that includes lesson plans, content, and activities on the LMS as well as digital literacy-based assessments.
Analisis Sistem Akuntansi dan Pengendalian Internal Produk Tabungan Emas Pada PT Pegadaian (Persero) Cabang Pasar Mawar

Gold can be an alternative investment, one of which will be very profitable and safest, because the investment value does not have an impact on inflation, prices continue to increase. The price flexibility of buying and selling transactions makes people choose to invest in gold. This study aims to analyze the accounting system for opening accounts for gold savings products, accounting systems for product disbursement and closing accounts for gold savings products, and the application of internal control in the accounting system for gold savings products at PT Pegadaian (Persero) Pasar Mawar Branch. This research is descriptive with a qualitative analysis approach, with data collection methods using literature study techniques and documentation and observations (observations). This study concludes that the gold savings product uses an accounting system, namely the Pegadaian Application Support System Integrated Online (PASSION). The product disbursement accounting system is carried out with two methods of disbursing savings products in the form of gold and cash. The gold savings product account can be closed at any time without any conditions for depositing a nominal balance. The five components contained in internal control are Control Environment, Risk Assessment, Control Activities, Information and Communication, and Monitoring.
The Effect of Cooperative Network Dynamics of the Scientific Research Project on Project Performance: The Moderating Role of Project Leader’s Network Position

Based on the data of projects initiated from 2013 to 2015 and concluded from 2017 to 2019 supported by the Department of Management Science of the National Natural Science Foundation of China, the relevant achievements of scientific research projects are collected. This article explores the influence of the decline, expansion and stability of the cooperative network of each project team on project performance from project initiation to project closure. We also demonstrate the moderating effect of project leader&amp;rsquo;s network position in the higher-level global project cooperative network, including structural hole and degree centrality, on the relationship between project cooperative network dynamics and project performance. Results show that the decline of the project team cooperative network has a negative impact on project performance, the expansion of the project team cooperative network has an inverted U-shaped impact on project performance, and the stability of the project team cooperative network has a positive impact on project performance. At the same time, the structural hole and degree centrality of the project leaders in the higher-level global project cooperative network influence the effects of project team cooperative network dynamics on project performance. This study is of great significance to guide the construction of the project member network and improve project performance.
Abnormal behavior recognition based on feature fusion C3D network

The real-time detection and recognition ability of human action recognition in a video surveillance system is a key problem in an intelligent surveillance system. Because the behavior recognition for video surveillance systems is affected by the complexity of the scene, the classification performance of the behavior recognition models is not satisfactory. To increase the processing efficiency of the network and solve the problem of low classification accuracy of human action recognition, we designed a deep learning model based on three-dimensional (3D) convolutional network multiscale feature fusion to reduce the impact of constant appearance changes, background clutter, and pedestrian occlusion. The model alternately uses 3D convolution and 3D pooling operations to extract temporal and spatial features between consecutive frames after data preprocessing, and then uses a feature pyramid structure to select three sets of feature layers with different scales. The model performs deconvolution operations in a bottom to up order and fuses with the features of the previous layer, then downsampling and high-level feature layer fusion are performed sequentially from top to bottom. Using the newly generated the highest-level feature layer to realize abnormal behavior recognition. The C3D network algorithm based on feature fusion proposed in this paper is compared with the three most advanced methods of C3D, R3D, and R ( 2 + 1 ) D on the pedestrian abnormal action recognition (PAAR) dataset and the same parameters, and the accuracy is significantly improved.
Computational Irrelevancy: Bridging the Gap Between Pseudo- and Real Randomness in MPC Protocols

Due to the fact that classical computers cannot efficiently obtain random numbers, it is common practice to design cryptosystems in terms of real random numbers and then replace them with cryptographically secure pseudorandom ones for concrete implementations. However, as pointed out by the previous work (Nuida, PKC 2021), this technique may lead to compromise of security in secure multiparty computation (MPC) protocols, due to the property that a seed for a pseudorandom generator (PRG) is visible by an adversary in the context of MPC. Although this work suggested to use information-theoretically secure protocols (together with PRGs with high min-entropy) to alleviate the problem, yet it is preferable to base the security on computational assumptions rather than the stronger information-theoretic ones. By observing that the contrived constructions in the aforementioned work use MPC protocols and PRGs that are closely related to each other, we notice that it may help to alleviate the problem by using protocols and PRGs that are “unrelated” to each other. In this paper, we propose a notion called “computational irrelevancy” to formalise the term “unrelated” and under this condition provide a security guarantee under computational assumptions.
Integer polynomial recovery from outputs and its application to cryptanalysis of a protocol for secure sorting

Abstract We investigate the problem of recovering integer inputs (up to an affine scaling) when given only the integer monotonic polynomial outputs. Given <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>n</m:mi> </m:math> n integer outputs of a degree- <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>d</m:mi> </m:math> d integer monotonic polynomial whose coefficients and inputs are integers within known bounds and <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>n</m:mi> <m:mo>≫</m:mo> <m:mi>d</m:mi> </m:math> n\gg d , we give an algorithm to recover the polynomial and the integer inputs (up to an affine scaling). A heuristic expected time complexity analysis of our method shows that it is exponential in the size of the degree of the polynomial but polynomial in the size of the polynomial coefficients. We conduct experiments with real-world data as well as randomly chosen parameters and demonstrate the effectiveness of our algorithm over a wide range of parameters. Using only the polynomial evaluations at specific integer points, the apparent hardness of recovering the input data served as the basis of security of a recent protocol proposed by Kesarwani et al. for secure <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>k</m:mi> </m:math> k -nearest neighbor computation on encrypted data that involved secure sorting. The protocol uses the outputs of randomly chosen monotonic integer polynomial to hide its inputs except to only reveal the ordering of input data. By using our integer polynomial recovery algorithm, we show that we can recover the polynomial and the inputs within a few seconds, thereby demonstrating an attack on the protocol of Kesarwani et al.
Optimizing the Medical Resource Supply Chain During the Covid-19 Pandemic in Baghdad Hospitals using the Fuzzy Inference System (FIS)

The importance of using scientific and quantitative methods in addressing contemporary problems, including the (Covid-19) pandemic, as these challenges and problems require everyone, especially those working in educational institutions and researchers, to support international and local efforts to reduce the impact of this pandemic by achieving optimal use of medical resources, for the supply chain of medical resources that includes (therapeutic protocol and medical supplies (; Thus, providing solutions, alternatives and logistical support that would absorb the significant increases in the number of injuries in light of the limited resources in the face of this pandemic. Hence, this research came to contribute to the local and international efforts to address this problem by presenting a package of ideas and solutions for how to achieve the optimal utilization of medical resources. In light of the inaccuracy and discrepancy in the available data by distributing those resources in a quantitative and thoughtful manner to achieve the goal for which it was set, as well as evaluating alternatives on the ground and ways to improve them with an indication of the future prospects for this problem is by applying one of the artificial intelligence techniques called the fuzzy inference system (FIS).
Blockchain-Enabled Internet-Of-Vehicles on Distributed Storage

The world today is witnessing a paradigm shift attributed to expedited penetration of new technologies in the ecosystem of routine human lives. One such domain, soon to be impacted is the way traffic and transportation system is organized today. The futurity of transport will be completely different from what we have today. It is going to be based on Internet-of-Vehicles. Still in evolving times though, the envisaged growth of the Internet-of-Vehicles has thrown multiple challenges of ensuring seamless, secure, robust exchange of information between devices. These challenges majorly include large data sets storage, real-time intelligent management and information security for the entire ecosystem of these connected vehicles. The Internet-of-Vehicles being proliferated further by autonomous vehicles in the not so distant future will add to the existing challenges. Blockchain technology, majorly associated with cryptocurrencies, has recently envisaged a range of benefits vide implementation across multiple domains, by offering its inbuilt characteristics including decentralized architecture, enhanced security, immutable and transparency, etc. This paper explores the advantageous connect between smart contracts and Internet-of-Vehicles and need of distributed storage to redefine trust enhancement, security and high storage generated among devices. It proposes architecture based on smart contracts while also simulating a limited part with Internet-of-Vehicles concluding with discussion on challenges ahead.
Effectiveness of the Use of the Internet of Things (IoT) in the Agricultural Sector

The current internet architecture has been developed into the Internet of Things (IoT). The IoT idea seeks to improve effectiveness, accuracy, and financial gains. This research aims to analyse the Effectiveness of the Use of the Internet of Things (IOT) in the Agricultural Sector. This study employs qualitative methods with descriptive analysis techniques. The data collection method uses literature reviews from various reputable national and international journals. This research revealed that with the rise of the Internet of Things and the digital transformation of rural areas, using these technologies to remotely monitor agricultural development, soil moisture, and crop danger has become feasible. Automation of human intervention, particularly when leveraging the Internet of Things, can improve the efficacy of agriculture and farming processes.
Semantic Knowledge Management and Blockchain-based Privacy for Internet of Things Applications

Design of distributed complex systems raises several important challenges, such as: confidentiality, data authentication and integrity, semantic contextual knowledge sharing, as well as common and intelligible understanding of the environment. Among the many challenges are semantic heterogeneity that occurs during dynamic knowledge extraction and authorization decisions which need to be taken when a resource is Accessem in an open, dynamic environment. Blockchain offers the tools to protect sensitive personal data and solve reliability issues by providing a secure communication architecture. However, setting-up blockchain-based applications comes with many challenges, including processing and fusing heterogeneous information from various sources. The ontology model explored in this paper relies on a unified knowledge representation method and thus is the backbone of a distributed system aiming to tackle semantic heterogeneity and to model decentralized management of Access control authorizations.We intertwine the blockchain technology with an ontological model to enhance knowledge management processes for distributed systems. Therefore, rather than reling on the mediation of a third party, the approach enhances autonomous decision-making. The proposed approach collects data generated by sensors into higher-level abstraction using n-ary hierarchical structures to describe entities and actions. Moreover, the proposed semantic architecture relies on hyperledger fabric to ensure the checking and authentication of knowledge integrity while preserving privacy.
Design and Development of a Sign Language to Speech Converter for Dumb People

The Purpose of this work is to develop an interactive device to help dumb people. This is a special electronic device for the mute people which enables them to communicate with normal people by means of customized sign language system. Sign language is the medium for expressing feelings and thoughts using symbols and different patterns made by the bending of fingers. Flex sensor detects the angle of bend of each finger and sends analo signal to the processor. By processing the signal Speech synthesizer makes desired voice output. The device has been more interactive as output quality of voice is quite natural and can be customized as required.