Reviewerly/exHarmony huggingface dataset:
Blockchain Smart Contracts

In this computer world, digital transformation is a thoughtful and unavoidable one. The impact of this digital transformation is reflected both in government and private sectors. Amongst these, financial and business sectors must face a lot of challenges to undergo this transformation. In financial sector, transaction between two parties has become a part of their life. A transaction normally happens with the help of few centralized authorities. In the centralized system, all the transaction needs to be verified and signed by a centralized authority. But there are many issues exist in executing this methodology. Among them two important issues concerned with financial sector are, large storage space required for processing and cost of committing a transaction. Blockchain, a blooming technology has overcome this drawback by changing the execution model. Blockchain makes use of distributed ledger and crypto currencies, thus converting the centralized processing into a distributed processing system. Here, all the ledgers needed for the transaction are maintained as distributed database. Block chain also minimizes the process by executing all the rules with the help of software. The software that acts as the execution unit of the blockchain is known as smart contract. Smart contracts facilitate the implementation of user-defined operations of uninformed complexity which are not probably plain cryptocurrency protocols. It facilitates user to realize the constraints, instructions, and policies of the domain applications. To explore the feature of the smart contracts, it should be properly designed and coded. Smart contracts work in the application layer of the blockchain. All the rules for the applications can be realized using smart contract. Data for the verification can also be obtained from external sources. i.e., usually, the data for the contract execution is supplied through the transactions. But it can also be obtained from external sources. Each smart contract in the blockchain is assigned a unique address of size 20 bytes. To run a contract, the transaction must be sent to the contract's address. The smart contract performs the necessary operation and when all the protocols are satisfied, the smart contract by itself executes the transaction. This transaction will be run by different miners whose output will be validated and the block of the miner who wins it will be added to the chain. Smart contracts run on Ethereum virtual machine and solidity is the programming language used for writing smart contracts. Ethereum smart contracts need gas to run. When the required gas is not found, then the requested transactions cannot be executed. In this chapter, the detailed explanation of the smart contract along with its architecture is discussed. Also, designing of the smart contract using the programming language solidity is discussed.
ERROR ANALYSIS IN THE SPEECH TEXT OF THE SECOND SEMESTER STUDENTS AT IKIP PGRI BOJONEGOROIN THE ACADEMIC YEAR OF 2019/2020

Abstract This research is an attempt to understand errors in the text made by the second semester students at IKIP PGRI Bojonegoro. Statement of the problem in this study is Analysis in The Speech Text of The Second Semester Students at IKIP PGRI Bojonegoro. To analyze the data, the authors used a qualitative descriptive method and used an error analysis procedure to make a clear explanation. The study participants consisted of 32 second semester students at IKIP PGRI Bojonegoro. The data was taken only 5 manuscripts of the second semester student speech to find out the errors of the word order made by students. The author found errors as follows: errors using grammar (39%), and errors using vocabulary (13%). Based on the research findings and discussion, the researcher concludes that students still face difficulties in using grammar and vocabulary. Because of the results of this study, students must learn more word order, especially in the use of grammar. They must learn more about grammar to increase their knowledge and reduce their mistakes. Then, the lecturer as a facilitator must be able to facilitate the needs of students in any material.Keyword: Speech Texts, Error Analysis
Graph Theory-based Fast Linear Iterative Clustering Multi-feature Fusion Model for Art Image Segmentation

ABSTRACTImage segmentation is the pre-processing stage of image analysis. It divides the image into different re-gions for the subsequent image analysis. The traditional segmentation algorithms can not deal with the images with complex background and uneven gray level effectively. Especially, for the art images seg-mentation with high resolution, the distinguishment degree between foreground of the object to be seg-mented and the background is small, which can lead to the incomplete segmentation effect. Therefore, this paper proposes a graph theorybased Fast Linear Iterative Clustering (FLIC) multi-feature fusion model for art image segmentation. First, the FLIC segmentation algorithm is used to pre-segment the su-perpixel of raw image. Second, the HOG feature, Lab color feature and spatial location feature are ex-tracted. Third, A multi-feature fusion strategy based on superpixel is designed. Four, the fast image seg-mentation based on multi-feature fusion is realized by using the graph theory. The graph theory is opti-mized by time domain convolution. Finally, the comparison experiments with other state-of-the-art methods are conducted on the public datasets: Berkeley Segmentation Dataset and Culture Gene Online . The results show that the proposed algorithm has better effect in terms of evaluation indexes (USE, BR, ASA and Time).
Return, Volatility and Shock Spillovers of Bitcoin with Energy Commodities

Purpose:The purpose of this paper is to examine empirically the spillover impacts between Bitcoin and the major energy commodities.Design/methodology/approach: To do so, we employ an asymmetric multivariate VAR-BEKK-AGARCH model to study spillover effects between Bitcoin and three energy commodities during the period from July 18, 2010 to June 30, 2018.Findings: The empirical findings show return spillovers from energy stock indices to Bitcoin.We find unilateral return and volatility spillovers and bidirectional shock influences and demonstrate portfolio management implications of dynamic conditional correlation.The little correlation of Bitcoin with the stock indices offers portfolio benefits.Our findings imply the importance of Bitcoin in portfolio construction and reflects the importance of diversification of portfolio between energy commodities and the crypto-currencies, mainly Bitcoin.Practical Implications: Bitcoin has qualified a fast development while across a time and several shareholders and investors are demonstrating importance in its possibility as a consolidative component of portfolio variation.Originality/value: The significant extension is the using of a recently established multivariate econometric method, VAR-BEKK-AGARCH, which is utilized to study the degree of incorporation in rapports of instability and return among Bitcoin and energy commodities.
RESEARCH ON APPLICATION OF NEURAL NETWORKS FOR RESTORING DAMAGED VIDEO FILES OF AVI AND MP4 FORMATS

In the modern world, video files play a special role. The development of video compression algorithms and the growth of the Internet’s capabilities make it possible to transfer video files. Damage inevitably occurs when transferring video files. Accordingly, the question arises about restoring a damaged file and obtaining information from it. The article discusses the most commonly used video file extensions AVI, MP4. As a result of the study, it was revealed that the most common damage is in the headers, which leads to errors when opening files by players, data is damaged less often. Data corruption leads to the fact that a certain fragment of the video file is either played with errors, distortions, or is skipped. The article discusses the possibility of recovering damaged video file using the removal of undistorted data and proposes an algorithm for analyzing frames using a neural network. As part of the algorithm, a neural network is used to identify damaged frames in video data. The algorithm was implemented as a software product. For the first stage of checking the efficiency of the algorithm, deliberate distortions of one frame were made for each video file under study. As a result of experimental verification of the developed algorithm, it was revealed that it provides high accuracy in detecting distorted frame sequences.
Discussion on Teaching Reform of Basic Course of Engineering Chemistry

The teaching purpose and idea of modern chemistry basic course in China is to take students as the education center, pay attention to the actual needs of students, and promote the reform of modern education classroom by evaluating the training objectives. The basic course of engineering chemistry is a comprehensive basic theory course of chemistry, which pays attention to the cultivation of students' ability to solve practical problems. As the reform and exploration of education classroom, we can effectively evaluate and reflect students' learning by establishing a complete teaching evaluation system, combine various multimedia means, and enhance students' learning interest, as well as innovate classroom teaching means, in order to improve the level of classroom teaching technology, make the basic engineering chemistry teaching recognized by all sectors of society, and improve students' autonomous learning ability and inquiry and innovation literacy.
The Contractual Cryptoeconomy: An Arrow of Time for Economics

We consider the potential blockchains have for building a framework for all manner of contracts that can characterize an economy using the unifying idea of control over their duration. Such a contractual cryptoeconomy (CCE) would accommodate a broader variety of contracts than smart contracts, which are suitable for a relatively small portion of the set of all feasible contracts. We proceed by examining the idea of a contract’s natural life as a common feature shared across all contracts, be they incomplete or complete. This simplifying idea suggests why providing flexibility over a contract’s duration on a blockchain -- through innovations such as HTLCs -- is necessary to increasing the variety of contracts that can be feasibly represented. We also assess participation in a CCE that features blockchains with differing degrees of security. We do so by focusing on how the value of a contract is related directly to its natural life for both its immediate participants and, through externalities across the CCE, to a wider set of users. A key idea provides the overall impetus: When contracts rely on third-party intermediation, at least some contractual surplus is dissipated in arbiter rent, making the quality of third-party arbitration as important as its scale. By contrast, blockchains create contractual mechanisms that act as Coasian exchanges that can internalize this arbiter rent. However, crucially, the degree to which their use requires forgoing contractual complexity and absorbing the cost of externalities can determine the relative benefits provided by a CCE.
Flexible Refinement Proofs in Separation Logic

Refinement transforms an abstract system model into a concrete, executable program, such that properties established for the abstract model carry over to the concrete implementation. Refinement has been used successfully in the development of substantial verified systems. Nevertheless, existing refinement techniques have limitations that impede their practical usefulness. Some techniques generate executable code automatically, which generally leads to implementations with sub-optimal performance. Others employ bottom-up program verification to reason about efficient implementations, but impose strict requirements on the structure of the code, the structure of the refinement proofs, as well as the employed verification logic and tools. In this paper, we present a novel refinement technique that removes these limitations. Our technique uses separation logic to reason about efficient concurrent implementations. It prescribes only a loose coupling between an abstract model and the concrete implementation. It thereby supports a wide range of program structures, data representations, and proof structures. We make only minimal assumptions about the underlying program logic, which allows our technique to be used in combination with a wide range of logics and to be automated using off-the-shelf separation logic verifiers. We formalize the technique, prove the central trace inclusion property, and demonstrate its usefulness on several case studies.
RESEARCH ON THE CURRENT SITUATION AND COUNTERMEASURES OF RURAL PHYSICAL EDUCATION IN CHINA

Physical education as a compulsory course to promote the all-round development of students, at the same time, with the continuous promotion of quality education, physical education has been significantly improved. However, compared with cities with better economic conditions, the current situation of rural physical education is not satisfactory. By using the methods of literature investigation and analysis, this paper discusses the current situation of rural physical education in China and puts forward some measures to promote the development of rural physical education in China.
A Photonic Neural Network Using &lt; 1 Photon per Scalar Multiplication

New Frontiers in Optical Technology The proliferation of optical sensors and user interfaces offers opportunities for deeper integration of sensing, processing, and data transmission.
Quantum Computing with Atoms

The Next Technological Revolution is Quantum Quantum Computers are poised to take over where conventional computers and Moore’s Law leave off. This quantum revolution will touch every sector of the economy.
&lt;&lt;Tesseract&gt;&gt;, the card game

Article describes new card game for 4 players, that requires from its participants decisions, made in presence of information asymmetry arising from secret component of players' every move. Significance for outcome of information asymmetry is demonstrated, and overview of potential lines of research in game analysis is given.
IMPROVING STUDENTS’ ABILITY TO WRITE ENGLISH DISCOURSE BY MASTERING ITS GLOSSARY IN GRADE XI.MIPA 1 SMAN 1 CIGUGUR

The study aims to determine the extent to which students' ability to write English discourse is increased through mastery of the glossary. Glossary mastery is mastery of vocabularies or terms used in the material to be studied. This is one way for the author to make it easier for students to write an English discourse. This is carried out in hybrid learning during the Covid-19 pandemic. This study uses a classroom action research method with a quantitative approach to 32 students of Class XI.MIPA1 SMAN 1 Cigugur which is carried out in 2 cycles in the odd semester of the 2021-2022 academic year. The results showed that 89% of students were able to write English discourse well. In addition, there was an increase in their writing ability by 27% from their previous ability.
The Increasing Role of Urban Geoscience at the End of the Twentieth Century

Urban geoscience is assuming an ever increasing importance. Unfortunately there is a tendency to spurn the potential of scientific solutions to the present problems of escalating urbanisation and to rather concentrate on sociological problems. The International Working Group on Urban Geology (sponsored by COGEOENVIRONMENT, a commission of IUGS, IAH and IAEG) has recently prepared and had published a multiauthor definitive volume treating the subject in a broad manner. This contribution to the Symposium B4 on Urban Geology at the 30th IGC in Beijing expresses the philosophy behind this volume. The topic has been treated from a realistic viewpoint, acknowledging the equal importance of resource aspects and environmental constraints. Some consideration has been given to the reasons for the increasing incidence of urban geohazards: among them are the increasing size of urban developments and conurbations, the extension of urban development onto unsuitable ground, the lack of urban planning with early input of geoscience data and evaluation, the decay of old cities and towns and the too rapid and uncontrolled growth of new cities and towns. Much of the increase is real, though it may in part be an artifact of increased public and media awareness. The global effects on the environment of urbanisation are briefly considered and the global escalation of population.
The Construction and Application of An English-Chinese Corpus of Academic Formulaic language

Formulaic language plays an indispensable role in academic English writing and translation. To provide a convenient environment for Chinese learners to acquire the English formulaic language, an English-Chinese bilingual parallel corpus of academic formulaic language with 1643 sentence pairs is constructed. This paper introduces the construction method of the corpus, discusses the teaching application scenarios matching with its functions, designs a cross-contrast experiment, and verifies the convenience and effectiveness of the system. Using various retrieval channels and abundant corpus provided by the system, learners could master a large number of academic formulaic languages imperceptibly in their daily study. At the same time, the system can also provide data sources for computer-aided translation and other research on formulaic language.
Estimating Mutual Information via Geodesic <i>k</i>NN

Previous chapter Next chapter Full AccessProceedings Proceedings of the 2022 SIAM International Conference on Data Mining (SDM)Estimating Mutual Information via Geodesic kNNAlexander Marx and Jonas FischerAlexander Marx and Jonas Fischerpp.415 - 423Chapter DOI:https://doi.org/10.1137/1.9781611977172.47PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract Estimating mutual information (MI) between two continuous random variables X and Y allows to capture non-linear dependencies between them, non-parametrically. As such, MI estimation lies at the core of many data science applications. Yet, robustly estimating MI for high-dimensional X and Y is still an open research question. In this paper, we formulate this problem through the lens of manifold learning. That is, we leverage the common assumption that the information of X and Y is captured by a low-dimensional manifold embedded in the observed high-dimensional space and transfer it to MI estimation. As an extension to state-of-the-art kNN estimators, we propose to determine the k-nearest neighbors via geodesic distances on this manifold rather than from the ambient space, which allows us to estimate MI even in the high-dimensional setting. An empirical evaluation of our method, G-KSG, against the state-of-the-art shows that it yields good estimations of MI in classical benchmark and manifold tasks, even for high dimensional datasets, which none of the existing methods can provide. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-717-2 https://doi.org/10.1137/1.9781611977172Book Series Name:ProceedingsBook Code:PRDT22Book Pages:1-737
Volatile memory forensics of privacy-aware operating systems

Along with the use of the internet, awareness regarding the privacy of the user data is also increasing slowly and gradually but at a comparatively slower rate than that of cybercrime. At present in the market, there are many such operating systems available that are secured and leave the minimum number of traces which makes it difficult to retrieve or obtain any kind of data from that system after carrying out the forensics of that machine. In this research, acquisition, and analysis of random access memory (RAM), of such secured operating systems, is performed and potential artefacts related to the activities are identified, that the operating systems leave in the memory of the system which can be further submitted in the court of law as evidence in case of a crime being committed using such security providing technology.
Psychological, Pedagogical and Drganizational Peculiarities of the Development of Students’ Volitional Qualities as a Factor of Success in Learning

The article reports the results of the empirical study of the impact of volitional qualities development on the level of academic achievements of higher education institution students. The article gives a theoretical analysis of the main types of volitional qualities that affect the assimilation of educational material by students. There was established the level of their development and the relationship with academic achievements. The article also identifies the main psycho-pedagogical and organizational peculiarities that affect the success of mastering the knowledge by university students. The psychological and pedagogical recommendations for forming, developing and supporting the volitional sphere of students are developed.
Research on Information Visualization Based on User Experience (UX)

With the vigorous development of digital information technology, more and more products and mobile applications have become more and more diversified in our daily life and product interaction. In the digital age and new media, most information transmission is done through images rather than text messages. Since images are expressed through visual symbols and expressions, the simplicity of information visualization is essential for effective information transmission. The main purpose of this research is to study the types of information acceptance through the basic research of user experience (UX) visualization theory, analyse how text information can be effectively visualized output, propose a visualization framework based on user experience, and transform text information visually through various interactive methods, bring new thinking and reference to visual design based on user experience.
Modeling and Control of Large Scale Neural Systems

Author(s): Mitchell, Brian August | Advisor(s): Petzold, Linda R | Abstract: The control of large scale neural systems promises to usher in a new era of technologies for use in treating disease, answering scientific questions, and improving human performance. Unlike other systems amenable to modern control and reinforcement learning (e.g. robots), we have many examples of high-functioning brains being used by healthy individuals. Combined with the fact that exploratory perturbations of the brain are extremely expensive relative to observation of healthy brains, this suggests that an appropriate workflow for constructing a controller should begin with inverse methods. We present a number of results showing how inverse schemes can be used to both model human behavior and neural dynamics. We show how these methods can be used to facilitate interactions between human beings and artificial agents. We conclude by suggesting that with further refinement, such schemes can be used to directly guide perturbation of the brain.
Design and Effect Evaluation of Personalized English Teaching System in Colleges and Universities

Under the background of the new curriculum reform, personalized English teaching in colleges and universities has become an important measure of the current teaching reform. We should build a personalized teaching model, learning methods and evaluation mechanism, and scientifically and carefully design the teaching system and classroom tasks, so as to enable students to independently identify with the existing English teaching objectives, guide students to form scientific and effective autonomous learning methods, and improve the overall quality and effect of English teaching.