Reviewerly/exHarmony huggingface dataset:
Rock image reconstruction based on Improved Markov chain Monte Carlo

Next No AccessSEG/SPWLA 2020 Workshop: 7th Workshop on Porous Media: Structure, Flow and Dynamics, Virtual, 2–3 December 2020Rock image reconstruction based on Improved Markov chain Monte CarloAuthors: Zhili HeCong Hou*Mengqi JinZhili HeChang'an UniversitySearch for more papers by this author, Cong Hou*Chang'an UniversitySearch for more papers by this author, and Mengqi JinChang'an UniversitySearch for more papers by this authorhttps://doi.org/10.1190/prmd2020-01.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Image reconstruction is widely applied in rock physics. The imaging effect of rock section directly affects the accuracy of 3D modeling. Porous media imaging mainly considers pores and solids. In this paper, an improved two-dimensional rock image reconstruction method is proposed for the general characteristics of rock image anisotropy and the discomfort of current methods. For anisotropy, the conditional probability in the same direction as the reconstruction path is used in the imaging process, and the reconstruction results are evaluated by the fitting degree of variogram. Compared with existing methods, this method has the advantages of simple programming, high calculation accuracy, and high fitting degree between the reconstructed variogram curve and the original image. Keywords: anisotropy, rock physics, modeling, reconstruction, 3DPermalink: https://doi.org/10.1190/prmd2020-01.1FiguresReferencesRelatedDetails SEG/SPWLA 2020 Workshop: 7th Workshop on Porous Media: Structure, Flow and Dynamics, Virtual, 2–3 December 2020ISSN (online):2159-6832Copyright: 2021 Pages: 23 publication data© 2021 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 22 Jan 2021 CITATION INFORMATION Zhili He, Cong Hou*, and Mengqi Jin, (2021), "Rock image reconstruction based on Improved Markov chain Monte Carlo," SEG Global Meeting Abstracts : 1-4. https://doi.org/10.1190/prmd2020-01.1 Plain-Language Summary Keywordsanisotropyrock physicsmodelingreconstruction3DPDF DownloadLoading ...
Analysis of software vulnerabilities using Exploratory Data Analysis (EDA)

Software vulnerabilities are very crucial to organizations as it can cause severe revenue loss if exploited. Study of vulnerabilities and understanding their behavior is necessary to maintain software systems. The process of identifying and understanding vulnerabilities is the initial step in creating policies to stop them in the future. Exploratory Data Analysis is a technique to understand the data and identify the attributes and features that are requires. In this paper the authors use EDA to study the software vulnerability data collected from a company. Vulnerabilities are visualized based on CVSS scores, severity, vulnerability status, category and OS. This study is focused on understanding the features in order to prevent vulnerabilities in the future.
Steel Plate Surface Defect Image Enhancement Based on Adaptive Fractional Differentiation

During the steel plate collection process, affected by the light and shooting angle, the image of the surface defect of the steel plate will have blurred traces. In order to improve clarity, the image needs to be enhanced. Aiming at the problems of traditional image enhancement algorithms that require multiple trials to find the optimal order, based on the self-similarity of image local information, an improved adaptive fractional differential mathematical model is established, and this model is substituted into the improved 16-direction Tiansi mask. The image is enhanced in the template. Experiments show that the enhanced defect image significantly highlights the texture details of the defect image while retaining the smooth area, which is a preparation for the subsequent improvement of the accuracy of defect image classification.
Meta-Learned User Preference for Topic Participation Prediction

Predicting the potential user interest on topics in online social networks is important for many practical applications such as advertising, recommendation and malicious account identification. Previous methods on such topic prediction problem mainly focus on learning user preference from historical posting content, and/or rely on the interest of friends to infer the topics a user may be interested in. However, these methods fail to take full advantage of high-order interactions between users and topics and the implicit relations among users, which may result in limited performance. In addition, existing approaches usually require a large amount of samples to train the model and therefore have poor prediction performance for the users who have few content and/or rarely follow the topics. To overcome these limitations, we present a novel method MetaTP (Meta learning based Topic Prediction) for exploiting the complex preference of users over the topics and identify the potential topics for cold-start users. MetaTP is built on a fast graph convolutional network to estimate the user interest through extracting user posting behavior from historical posting content and recursively aggregating the interest from the social friends of a user. Moreover, MetaTP introduces a new way of training prediction model in a meta-learning manner, which not only improves the performance on topic prediction but also can effectively and efficiently adapt to users with a few records. We validate our MetaTP model on real-world datasets crawled from popular social platforms and the empirical results show that our approach significantly outperforms the state-of-the-art baselines.
An Assessment of the Risk of Service Supplier Bankruptcies as a Cybersecurity Threat

Behind technology service suppliers lie companies that are subject to the risk of business failure due to market conditions and trading risks. Such failures could suddenly stop customers accessing services or content, with potentially devastating business and personal impacts, given the rising importance of digital economies. The risk can be illustrated by reference to cloud computing insolvencies but similar issues may affect other service providers. The insolvency of a cloud service provider would be likely to present problems of access to infrastructure, platforms, services and data and insolvency laws are not always designed to enable a managed closedown of a business, which would be needed to enable replacement services to be sourced and data recovered. This cybersecurity risk has barely been touched upon in literature, since it lies at the intersection between law and computer science, both areas requiring high levels of specialist understanding, and this chapter is part of initial attempts to identify the threats presented.
FORMATION OF PROFESSIONAL COMPETENCIES SOLOISTS-VOCALISTS IN THE PROCESS OF TRAINING AT THE UNIVERSITY

Modern society is in need of a new type of specialists. These are people who have not just a set of knowledge, but such professional competencies that allow them to form new ideas and meanings. This concept applies equally to the technologies of training cultural workers. The article is devoted to the problems of professional education in the field of musical performing skills and the importance of an integrative competence approach to the university training of soloists-vocalists.
Competence of an ICT Teacher Concerning Didactic and Methodological Support in Teaching ICT at Primary School

The widely accepted rhetoric is that our industrial society has been changing to an information society that manages huge amounts of information, which can be disclosed and processed with the help of information and communication technology (ICT). This fact has been reflected in the revised school curricula, and subsequently in the growing role and importance of both, ICT implementation into non-informatics subjects, and the computer science teachers in schools of all levels. These teachers should master the new competencies related to the changes brought by the Educational Policy 2030 + in the Czech Republic, which clearly defines the implementation of computer science in non-informatics subjects. Our research aimed to find out, through a field survey, the real situation in the field of professional readiness of ICT teachers in selected primary schools - with special regard to the perception of the situation by professional teachers. The results of our survey showed that especially computer science teachers in primary schools are not sufficiently professionally or technically prepared for the implementation of ICT in the teaching of non-informatics subjects. They also encounter several problems that prevent them from successfully applying the new educational strategy. Our findings are important in terms of current developments when the COVID-19 pandemic completely paralyzed full-time teaching and underlined the importance of the educational environment to be prepared for such exceptional situations while accelerating the implementation of computer science in non-informatics subjects.
A Decentralized Hybrid Method for Goal Assignment in Multi-Robot Exploration

Many multi-robot exploration (MRE) methods generate navigation goals so that the robots can observe unknown areas. The assignment of the goals to the robots greatly affects the exploration efficiency. This paper addresses the open-path multi-depot multiple traveling salesmen problem (OP-MmTSP) derived from multi-robot goal assignment (MGA) by presenting a decentralized method: the consensus-based decentralized discrete particle swarm optimization (CD-DPSO) algorithm. CDDPSO is a fully decentralized algorithm that assigns the computational tasks of a population-based metaheuristic algorithm to individual robots and enables them to collaborate. First, a discrete particle swarm optimization (DPSO) algorithm is proposed to resolve the OP-MmTSP. Second, the velocity update formula of DPSO is revised, inspired by the idea of the discrete time consensus algorithm that the particle swarms of all robots converge to the same solution via local communication. Finally, a variable neighborhood descent (VND) method consisting of two local search heuristics designed for min-max OP-MmTSP is adopted to improve the selected particles, which makes the CDDPSO a hybrid method that benefits from global search and local search. We applied two well-known auction-based task allocation algorithms to min-max OP-MmTSP and compared them to CDDPSO via numerical experiments. CDDPSO as a hybrid approach can usually find a better solution.
New Construction of Family of MLCS Algorithms

The multiple longest common subsequence (MLCS) problem involves finding all the longest common subsequences of multiple character sequences. This problem is encountered in a variety of areas, including data mining, text processing, and bioinformatics, and is particularly important for biological sequence analysis. By taking the MLCS problem and algorithms for its solution as research domain, this study analyzes the domain of multiple longest common subsequence algorithms, extracts features that algorithms in the domain do and do not have in common, and creates a domain feature model for the MLCS problem by using generic programming, domain engineering, abstraction, and related technologies. A component library for the domain is designed based on the feature model for the MLCS problem, and the partition and recur (PAR) platform is used to ensure that highly reliable MLCS algorithms can be quickly assembled through component assembly. This study provides a valuable reference for obtaining rapid solutions to problems of biological sequence analysis and improves the reliability and assembly flexibility of assembling algorithms.
Design and Realization of Data Acquisition and Supervisory System for Electromechanical Equipment

To solve the “Isolated Data Island” problem of the detector in a certain Kaibang-Motor production workshop, a data acquisition and supervisory system based on SQL2014 database was designed, which realizes the automatic collection and recording of the test data, real-time monitoring of the production progress, data statistics, historical data query and other functions. First, build a local area network to provide the data transmission environment. Then process the acquired data based on SQL2014 database to obtain specified format data and statistical results, and upload them to the central database. Finally, two options for using Kingview software and ASP.NET platform to develop data display and query interfaces are introduced. The production practice shows that the system can display the production information, feedback and locate the problems in the production in time, and improve the production efficiency.
Automated Assertion Generation from Natural Language Specifications

We explore contemporary natural language processing (NLP) techniques for converting NL specifications found in design documents directly to an temporal logic-like intermediate representation (IR). Generally, attempts to use NLP for assertion generation have relied on restrictive sentence formats and grammars as well as being difficult to handle new sentence formats. We tackle these issues by first implementing a system that uses commonsense mappings to process input sentences into a normalized form. Then we use frame semantics to convert the normalized sentences into an IR based on the information and context contained in the Frames. Through this we are able to handle a large number of sentences from real datasheets allowing for complex formats using temporal conditions, property statements, and compound statements; all order agnostic. Our system can also be easy extended by modifying an external, rather than internal, commonsense knowledge-base to handle new sentence formats without requiring code changes or intimate knowledge of the algorithms used.
UcEF for Semantic IR

At present, keyword-based techniques allow information retrieval (IR) but are unable to capture the conceptualizations in users' information needs and contents. The response to this has been semantic search computing with commendable success. Surprisingly, it is still difficult to evaluate Semantic IR (SIR) and understand the user contexts. The absence of a standardized cognitive user-centred evaluative paradigm (CUcEP) further exacerbates these challenges. This chapter provides the state-of-the-art on IR and SIR evaluation and a systematic review of contexts. Appropriate user-centred theories and the proposed evaluative framework with its integrated-context, web analytic conception, and related data analytic technique are presented. A descriptive approach is adopted, with the conclusion that multiple contexts are essential in SIR evaluation since “searching by meaning” is a multi-dimensional cognitive conception, hence the need to consider the impact of context dynamicity. Finally, the foregrounded semantic items will be applied to standardize the CUcEP in future.
An Anonymity Preserving Framework for Associating Personally Identifying Information with a Digital Wallet

Growing adoption of cryptocurrencies by institutional investors coupled with recurring incidents of loss of access to digital wallets have resulted in emergence of custodial services for high net worth individuals and institutions.However, such services are not economically feasible for the wider community of crypto owners who are left with no recourse for recovery of lost funds.This paper proposes a framework, AFAP, for associating certain personally identifying information with a digital wallet so that a user may prove ownership of the said wallet.Thus, the owner is able to establish his/her claim over funds associated with such a wallet in case of loss of access to it.We show that the proposed scheme has no adverse effect on anonymity, privacy and forgetfulness of personal information of the wallet owner.
Applications of Hybrid Particle Swarm Optimization Algorithm: A Survey

Particle swarm optimization algorithm is based on the natural behavior of fish schooling or the birds flocking. This algorithm offers good performance in a variety of domains. PSO also offers optimal solutions to various real-life problems. In recent years, researches have been carried on to make this algorithm more efficient through hybridization with other algorithms. Such modified systems and their applications have been summarized in the paper. The purpose is to organize the literature related to past 10 years of hybridization of PSO. This paper mainly presents the amount of work done in this field, thereby indicating the amount of work which can be further done to enhance this technique and to generate more optimal solutions of a problem.
Standard and singular wavelet analysis

The paper suggests that the use of classical wavelets may be auxiliary in the analysis of a periodic signal. This is because the intuitive interpretation of the wavelet transform is not obvious. It is proposed to consider the Fourier transform as the main tool in applied research of periodic signals. An example is provided to support this point of view. To isolate the periodic component of the signal, along with wavelet analysis, it is proposed to perform spectral analysis. To do this, pre-filtering is performed using singular wavelets. This approach can significantly complement classical wavelet analysis.
Countercyclical monetary policy for overcoming COVID 19 induced recession by introducing incentive based digital currency

The objective of this this study is to examine how central bank (CB) can pursue incentive based counter cyclical monetary policy (MP) by introducing CB digital currency (CBDC) and by offering 10% purchase incentives or 10% discounts in each and every sector of the economy and as a result, aggregate expenditures of the economy will increase which will bring full employment in the economy and will eliminate COVID 19 induced recession.The study is based purely on theoretical general macroeconomic equilibrium model.The findings show that the incentive based expansionary MP will increase consumption expenditure, investment spending, government spending and net exports and as a result, aggregate expenditure line will shift up and equilibrium income and employment will increase and unemployment rate will fall and COVID 19 induced recession will disappear.Inflation rate will also fall because all the sellers in the economy will offer 10% purchase discounts and CBDC will be issued with such 10% purchase incentives.Indeed 10% discounts in all the prices of goods and services will automatically suppress inflation rate.Simultaneous decrease in unemployment rate and inflation rate will decrease misery index or discomfort index and economic performance will improve.
Zimbabwean non-uptake of protective point-of-sale behaviours

In a world which is increasingly relying on debit and credit cards to effect transactions, people are entering PINs in a wide range of situations and contexts. We all know we ought to shield PIN entry, and check for skimmers if we are using magnetic stripe cards. Yet previous studies have found that a minority of card users shield their PINs at Points of Sale (PoS). Previous studies into the incidence of PIN shielding have taken place in Europe, with stable currencies and relative wealth.
Geomorphic provinces and regolith-landform evolution of the Capricorn Orogen, Western Australia

This study characterises the variation in regolith-landform environments and associated regolith materials in the Capricorn Orogen of Western Australia. Four different geomorphic provinces were identified based on regolith-landform characteristics. The Crystalline Basement Province in the west of the region covers an area of ∼35 000 km2, thin lithosols dominate, and granitic tors are common in a dissected landscape, and the soil composition reflects the underlying substrate. The Deeply Weathered Province, which is found in the southeast of the Capricorn Orogen, covers ∼5000 km2 and is defined by thick saprolite developed over both sediments and volcanic rocks. Ferruginous nodules and pisoliths are present at the surface and weathering profiles capped by duricrust are common. Thick (up to 100 m) paleochannel sequences, found throughout the area, are represented by mottled clays and sands. The Lowland Basin and Upland Basin provinces encompass the central and northern areas of the orogen and represent an area of ∼75 000 km2. The Upland Basin Province regions are highly dissected by valleys and include several generations of ferruginous pisoliths and nodules, ferricrete, silcrete and calcrete developed in colluvium and alluvium. Paleochannel sediments are commonly located on the flanks of hills and as low mounds and hills formed after topographic inversion. The Lowland Basin Province regions are dominated by hardpan, groundwater calcrete, and colluvial and alluvial plains below low hills on which basin sediments are exposed. These provinces provide the basis for further detailed regolith mapping across the region and can assist in guiding the choice of surface sample media for geochemical exploration. The regolith present in each province can be used to evaluate the landform evolution of the region over the past approximately 250 million years and assess relative regolith ages. KEY POINTSFour different geomorphic provinces have been identified in the Capricorn Orogen, Western Australia.The evolution of regolith landforms present in the Capricorn Orogen can be used to assess relative regolith ages.The geomorphic provinces defined within the Capricorn Orogen can be used as a basis for further regolith mapping and to assist in the choice of surface geochemical samples for mineral exploration.
Semantic and Blockchain Technology

Blockchain is a distributed ledger with the ability of keeping up the uprightness of exchanges by decentralizing the record among participating clients. The key advancement is that it enables its users to exchange resources over the internet without the requirement for a centralised third party. Also, each 'block' is exceptionally associated with the past blocks by means of digital signature which implies that creation a change to a record without exasperating the previous records in the chain is beyond the realm of imagination, in this way rendering the data tamper-proof. A semantic layer based upon a blockchain framework would join the advantages of adaptable administration disclosure and approval by consensus. This chapter examines the engineering supporting the blockchain and portrays in detail how the information distribution is done, the structure of the block itself, the job of the block header, the block identifier, and the idea of the Genesis block.
GIS-based mine flood preventing and controlling assistance decision system

Abstract The author has proposed the overall structure of mine flood preventing and controlling assistance decision system by analyzing the present situation of mine flood research survey, established the mine flood assistance decision platform. We have realized the mine flood preventing and controlling informatization and intelligent by using re-development on software.