Checking Method Research Articles

A Seismic Checking Method of Engineering Structures Based on the Stochastic Semi-Physical Model of Seismic Ground Motions

A seismic checking method of engineering structures based on the stochastic semi-physical model of seismic ground motions is developed. Four groups of stochastic ground motions are generated using the stochastic semi-physical model of seismic ground motions. In conjunction with the probability density evolution method (PDEM) and the idea of the equivalent extreme-value event, the dynamic reliabilities of an engineering structure are evaluated. The dynamic reliability of the structure is taken as an index for seismic checking. A five-story reinforced concrete frame structure is analyzed using both the response spectrum method and the proposed method. Some features of the instantaneous probability density function (PDF) and its evolution, the extreme value distribution, and the dynamic reliability are discussed and compared with the results of the response spectrum method in the Chinese seismic code. The seismic checking results of the response spectrum method show that the structure is safe, while the results of the proposed method reveal a failure probability as high as 35.39%. Moreover, the structure has such different reliabilities when it is excited by different groups of simulated seismic ground motions. It reveals that a structure designed according to the seismic code may carry a high risk of failure. The proposed method provides a more accurate way for the evaluation of the reliabilities of engineering structures.

Binary Graph Descriptor for Robust Relocalization on Heterogeneous Data

In this letter, we propose a novelbinary graph descriptor to improve loop detection for visual SLAM systems. Our contribution is twofold: i) a graph embedding technique for generating binary descriptors which conserve both spatial and histogram information extracted from images; ii) a generic mean of combining multiple layers of heterogeneous data into the proposed binary graph descriptor, coupled with a matching and geometric checking method. We also introduce an implementation of our descriptor into an incremental Bag-of-Words (iBoW) structure that improves efficiency and scalability, and propose a method to interpret Deep Neural Network (DNN) results. We evaluate our system on synthetic and real datasets across different lighting and seasonal conditions. The proposed method outperforms state-of-the-art loop detection frameworks in terms of relocalization precision and computational performance, as well as displays high robustness against cross-condition datasets.

Automatic verification method of progressive image model matching information based on machine learning

In order to solve the problems of large error and low performance of traditional progressive image model matching information checking methods, an automatic progressive image model matching information checking method based on machine learning is proposed. The generation method of progressive image is analyzed, and the target image sample is obtained. On this basis, machine learning algorithm is used to segment progressive image samples. In each image segmentation part, crawler technology is used to automatically collect progressive image model matching information, and under the constraint of image model matching information checking standard, automatic checking of progressive image model matching information is realized from geometric structure, image content and other aspects. Experimental results show that the verification error of the design method is reduced by 0.687 Mb, and the quality of progressive image is improved.

Improving modified policy iteration for probabilistic model checking

Value iteration, policy iteration and their modified versions are well-known algorithms for probabilistic model checking of Markov Decision Processes. One the challenge of these methods is that they are time-consuming in most cases. Several techniques have been proposed to improve the performance of iterative methods for probabilistic model checking. However, the running time of these techniques depends on the graphical structure of the model and in some cases their performance is worse than the performance of the standard methods. In this paper, we propose two new heuristics to accelerate the modified policy iteration method. We first define a criterion for the usefulness of the computations of each iteration of this method. The first contribution of our work is to develop and use a criterion to reduce the number of iterations in modified policy iteration. As the second contribution, we propose a new approach to identify useless updates in each iteration. This method reduces the running time of computations by avoiding useless updates of states. The proposed heuristics have been implemented in the PRISM model checker and applied on several standard case studies. We compare the running time of our heuristics with the running time of previous standard and improved methods. Experimental results show that our techniques yields a significant speed-up.

Saddle Point Method for Transient Processes in Waveguides

A modification of the saddle point method is proposed for computation of nonstationary wave processes (pulses) in waveguides. The dispersion diagram of the waveguide is continued analytically. A set of possible saddle points on the dispersion diagram is introduced. A method of checking whether the particular saddle points contribute terms to the field decomposition is proposed. A classification of the waveguides based on the topology of the set of possible saddle points is outlined.

Compliance checking of software processes: A systematic literature review

AbstractThe processes used to develop software need to comply with normative requirements (e.g., standards and regulations) to align with the market and the law. Manual compliance checking is challenging because there are numerous requirements with changing nature and different purposes. Despite the importance of automated techniques, there is not any systematic study in this field. This lack may hinder organizations from moving toward automated compliance checking practices. In this paper, we characterize the methods for automatic compliance checking of software processes, including used techniques, potential impacts, and challenges. For this, we undertake a systematic literature review (SLR) of studies reporting methods in this field. As a result, we identify solutions that use different techniques (e.g., anthologies and metamodels) to represent processes and their artifacts (e.g., tasks and roles). Various languages, which have diverse capabilities for managing competing and changing norms, and agile strategies, are also used to represent normative requirements. Most solutions require tool‐support concretization and enhanced capabilities to handle processes and normative diversity. Our findings outline compelling areas for future research. In particular, there is a need to select suitable languages for consolidating a generic and normative‐agnostic solution, increase automation levels, tool support, and boost the application in practice by improving usability aspects.

Challenges Faced by School Heads in Maintaining Students’ Academic Performance in Private Secondary Schools in Tanga and Korogwe Districts, Tanga Region Tanzania

The study investigated challenges faced by school heads in maintaining students’ academic performance in Tanga and Korogwe districts. Three specific objectives were formulated to guide the study. The study was guided by Administrative Management and Scientific Management Theory founded by Henry Fayol and Fredrick Taylor, respectively. A mixed research approach and convergent parallel research design were adopted. A sample size of 39 was obtained using proportionate purposive and simple random sampling techniques; questionnaires and interview guides were used in data collection. The validity ensured through member checking methods and through research expertise and supervisor check as well as the reliability ensured through the split half method. Quantitative data were analysed through SPSS software version 20 and presented through frequencies, percentages, figures, and tables, while qualitative data were analysed through thematic analysis and presented through quotation and narration. The findings revealed that major roles of school heads were planning, supervising, coordinating, and monitoring, while challenges they faced were inadequate funds, competition, low enrolment, fee-free policy, and high taxation by TRA, while strategies they used to overcome challenges were; motivation of teachers and students, marketing schools and monitoring discipline. The study concluded that challenges school heads face are: inadequate funds, lack of motivation and low enrolment of students. It is recommended for school owners to find other sources of funds and put clear policies which would guide private secondary schools as well as reduce the high taxes.

A Hybrid Method for Equivalence Checking Between System Level and RTL

Deep State Sequence-based (DSS) equivalence checking and path-based equivalence checking have been successfully applied for verification of digital designs between System Level Model (SLM) and Register Transfer Level (RTL). The DSS-based equivalence checking method can validate designs without mapping information, but the query size for each DSS is large compared with path-based verification. The query size for path-based methods is small, but the number of comparisons is large. In this work, we combine the advantages of DSS-based methods and path-based methods. We use DSS-based methods to find the corresponding paths and use cut-points like in path-based methods to split the DSS to reduce the query size. Finite State Machine with Datapath (FSMD) is used to represent the SLM and RTL models. Experimental results demonstrate that our method can effectively validate the designs and reduce the query size for DSS-based equivalence checking method.

Artificial Intelligence based Student Absenteeism Detector

Abstract: The whole procedure of marking attendance in a classroom full of students can be a burdensome as well as timeconsuming task at times. Presence of students in a substantial amount during the lecture increases the chances of botching the attendance. Moreover, after the pandemic hit of covid-19, all the safety measures and concerns will prove previously existing conventional methods of attendance marking to be very inefficient and unmethodical. On these grounds, marking of attendance with standard approaches has been a region of dispute. Demand of effective and automated methods to produce a8n attendance management system has been expanding recently. Recently, the trouble of automated attendance marking has been a wide concern using basic biometric info like fingerprint and RFID Tags (Radio Frequency Identification) etc. Conventional attendance checking methods for example pen and paper or attendance sheet signing are not difficult to sidestep and deceive as giving proxies or fake signature is a typical and common practice among students these days, students pull an unfair advantage mostly due to this. However, in any case, a facial recognition framework is unassailable and cannot be tricked as every individual has a set of exclusive and individual features restricted to that individual only and cannot be simulated or altered, everything boils down to one basic rule that is, except if you are actually present in the lecture your participation won't get acknowledged.

"Changed our lives": Psychosocial issues experienced by families of early adolescents with leukemia.

This research aimed to explore psychosocial problems experienced by families of early adolescents with leukemia. This phenomenology research was done during December 2019-August 2020 and involved eighteen families (47 family members) of early adolescents (10-14 years old) with leukemia. Participants were recruited by using purposive sampling and snowball techniques. Data were collected by using in-depth interviews and non-participatory observations until data saturation. Content analysis was used for data analysis. Member checking and triangulation methods were confirmed for trustworthiness. The families' perception on psychosocial problem experiences included three themes and nine sub-themes. The first theme was dealing with adolescent' emotional changes with sub-themes, namely, emotional responses to the illness, compensation for the suffering, and self-showing. The second theme was parents' social isolation with sub-themes, namely, cancer-stigma, burden of care, and jealousy to non-cancer families. The last theme was emotional distress struggles with sub-themes, namely, feeling worried, guilty, and depressed. Leukemia diagnosis in early adolescents causes psychosocial problems affecting the family lives. Health care providers need to concern and support the families and the adolescents so that they can pass through the difficulties with positive adjustments.

Representaciones sociales de la identidad y los roles de género en adolescentes de una escuela secundaria de México

Gender identity and roles are two of the most complex and important aspects of sexuality, as they define how people should think, feel and behave within society according to the gender they identify with. They are formed from the experiences, beliefs and evaluations that each person makes from childhood about what it means to be a man or woman in a society, which is influenced by both the socio-historical context and the biological factors of sexuality. Adolescence is the critical period of development when great bodily and psychological changes are faced, which forces people to behave according to their sexual nature and the acceptance (or non-acceptance) of the gender culturally associated to their genitals. Social representations (SR), in turn, allow us to understand how collective thought is formed around a specific phenomenon and how the social context influences the construction of beliefs. Thus, this study has set out to describe the SR of gender identity and roles in a group of adolescents in a secondary school in Mexico. To achieve this goal, the research has been framed within the qualitative paradigm, working under the phenomenological design from the process approach of SR. A projective technique of incomplete sentences was used to access the beliefs of the adolescents who participated in the study. The instrument used was the Incomplete Sentences on Sexuality of the Colombian Institute of Family Welfare, which is composed of 10 reagents that explore gender identity and the behaviors related to it. The sample consisted of 73 students aged 12 to 16 years from a secondary school in the city of Santiago de Querétaro in Mexico. A thematic analysis was carried out to identify the codes, categories and subcategories present in the students’ responses, and finally the method of consistency checking was applied based on the review and analysis made by another coder of the results obtained in order to guarantee the objectivity of the study. In this way, the categories of gender identity and cultural gender roles were obtained, within which subcategories emerged that encompass the concepts of masculinity and femininity for the participants, as well as the disadvantages associated with these two genders for the first and the second categories (roles, professions and behaviors that are prohibited for men and women). Among the results, it is evident that the SR of most adolescents around gender identity and roles have been constructed under the sex/gender system and have been influenced by what they have seen or heard from their parents at home. Therefore, the behaviors they believe they can perform are linked to the gender stereotypes they have included within their belief systems and values. This shows that for most participants sex and gender are synonymous, implying that people’s behavior, roles, attitudes and characteristics are defined by the sex they are born with, in which men are superior and women are inferior. According to this analysis of the narratives expressed by the participants, it was found that a small group are included within what has been called the “new masculinities”. Finally, it is worth mentioning that the novelty of the research is represented by the instrument and technique used, which allowed the participants to know how everything they have seen and heard in their homes has influenced their definition of what it is to be male, female and the roles of people in society according to their gender. It is recommended that more studies be done in the future on the construction of gender in adolescents, since it continues to be an issue of social tension and inequality in Latin America and throughout the world. https://doi.org/10.16888/interd.2022.39.2.10

The evolving role of printed publications in the digital age and relevance for their continued development

PurposeThe purpose of this article is to adhere to the construction of foreign print books. Of course, when the funds are limited or reduced, we can adjust the collection structure according to the utilization situation and reduce the subjects or languages that readers use poorly. Provide data support for library collection development plan.Design/methodology/approachThis paper analyzes the development and utilization of printed foreign language books based on the case of the National Library of China (NLC).The quality of library collection is analyzed by list checking method, and the utilization of library collection is analyzed by comparative analysis method and the statistical analysis method is used for language and subject areas, the questionnaire analysis method is used for users in NLC.FindingsForeign printed books plays a certain role in supporting domestic social users. The construction advantages of these print books need to be adhered to and developed. They should not be interrupted or cut down sharply because of many libraries are developing towards digital library or smart library nowadays. Libraries need to balance printed and digital resources in their collection and optimize their printed collection composition in terms of subject areas and unique resources to keep up with evolving needs of their patrons.Research limitations/implicationsIt is not compared with the utilization of e-books.Practical implicationsIn the transition period from traditional library to digital library, quantitative analysis of the construction and utilization of printed book resources can provide research support for the formulation of collection development planning, better service to users and better use of funds.Social implicationsIn the period of library transformation and development, it is of great practical significance to study the construction and utilization of printed books in NLC for resource transformation and service transformation. This paper gives the corresponding analysis and discussion on whether printed books should adhere to and whether they can be optimized.Originality/valueIn the period of Library Transformation and development, it is of great practical significance to study the construction and utilization of foreign language printed books in NLC. The printed book resources can provide research support for the formulation of collection development plan, better service to users and better use of funds.

Bayesian Estimation of Presidential Elections in Ghana: A Validation Approach

Elections are one of the barometers through which electorates measure the performance of governments and decide whether to renew their mandate or not. The success of every election goes a long way to strengthen the frontiers of a country's democracy and provide legitimacy for those who hold political power. However, the electoral process of many African countries has been challenged in courts or allegations of fraud and vote rigging are leveled against the winning party or candidate. Therefore, there is the need for a statistical method for checking and validating election results to ascertain fraud and vote rigging claims. Existing validation methods include the Parallel Vote Tabulation methodology. However, some significant disadvantages of this approach are issues of cost, sampling techniques and sample size determination. To overcome these, this study resorts to using the Dirichlet multinomial Bayesian model to compute posterior probabilities of valid votes cast and Bayesian credible intervals to ascertain the legitimacy of the votes cast. Using the Ghana general elections in 2020, the fitted Bayesian model accurately predicted approximately 99% of the proportion of votes obtained by New Patriotic Party, National Democratic Congress and all Other Political Parties. Also, the valid votes received by all the political parties fall within the Bayesian credible intervals indicating that the credibility of the 2020 presidential elections held in Ghana may not be in doubt.

Reviewing Methods for Controlling Spatial Data Quality from Multiple Perspectives

Spatial data is the core and operation object of geographic information system (GIS). The quality of spatial data determines the application of GIS and the effectiveness of decision-making to a great extent. This article introduces two important types of spatial data, vector data and raster data. Then, this paper discusses the uncertainty and sources of errors in spatial data, and discusses the methods of checking and preventing uncertainty and errors from the aspects and processes of digitization, so as to ensure the quality of spatial data. Finally, this paper explores cutting-edge approaches to improving spatial data quality, including the Area preserving method for improved categorical raster resampling, and using hierarchical grid index to detect and correct errors in vector elevation data. By studying effective data quality control methods, the quality of spatial data in GIS can be guaranteed, and the basic guarantee for the wide application and development of geographic information science can be provided.

Counterexample-guided Spatial Flow Model Checking Methods for C Code

Software verification has always been a popular research topic to ensure the correctness and security of software. However, due to the complex semantics and syntax of programming languages, the formal methods for verifying the correctness of programs have the problems of low accuracy and low efficiency. In particular, the state change in address space caused by pointer operations makes it difficult to guarantee the verification accuracy of existing model checking methods. By combining model checking and sparse value-flow analysis, this paper designs a spatial flow model to effectively describe the state behavior of C code at the symbolic-variable level and address-space level and proposes a model checking algorithm of CounterExample-Guided Abstraction refinement and Sparse value-flow strong update (CEGAS), which enables points-to-sensitive formal verification for C code. This paper establishes a C-code benchmark containing a variety of pointer operations and conducts comparative experiments on the basis of this benchmark. These experiments indicate that in the task of analyzing multi-class C code features, the model checking algorithm CEGAS proposed in this paper can achieve outstanding results compared with the existing model checking tools. The verification accuracy of CEGAS is 92.9%, and the average verification time of each line of code is 2.58 ms, both of which are better than those of existing verification tools.

A Conformance Checking-based Approach for Sudden Drift Detection in Business Processes

Real life business processes change over time, in both planned and unexpected ways. The detection of these changes is crucial for organizations to ensure that the expected and the real behavior are as similar as possible. These changes over time are called concept drift and its detection is a big challenge in process mining since the inherent complexity of the data makes difficult distinguishing between a change and an anomalous execution. In this paper, we present C2D2 (Conformance Checking-based Drift Detection), a new approach to detect sudden control-flow changes in the process models from event traces. C2D2 combines discovery techniques with conformance checking methods to perform an offline detection. Our approach has been validated with a synthetic benchmarking dataset formed by 68 logs, showing an improvement in the accuracy while maintaining a minimum delay in the drift detection.

Towards Modeling and Verification of Eurobalise Telegram Encoding Algorithm

A eurobalise is designed to broadcast the current state of the railway to a passing train. Such a transmitter is activated with an approaching train and its goal is to dispatch messages called telegrams. In this article, we consider the encoding process of such telegrams. Since the CRC checksum building method is based on operations with polynomials over the Galois field modulo 2, we describe a proven library to work with polynomials. Next, we present the implementation of the encoder in a modeling language according to the open specification and then discuss its verification strategies using the Model Checking method.

The Problem of Reference Rot in Spatial Metadata Catalogues

The content at the end of any hyperlink is subject to two phenomena: the link may break (Link Rot) or the content at the end of the link may no longer be the same as it was when it was created (Content Drift). Reference Rot denotes the combination of both effects. Spatial metadata records rely on hyperlinks for indicating the location of the resources they describe. Therefore, they are also subject to Reference Rot. This paper evaluates the presence of Reference Rot and its impact on the 22,738 distribution URIs of 18,054 metadata records from 26 European INSPIRE spatial data catalogues. Our Link Rot checking method detects broken links while considering the specific requirements of spatial data services. Our Content Drift checking method uses the data format as an indicator. It compares the data formats declared in the metadata with the actual data types returned by the hyperlinks. Findings show that 10.41% of the distribution URIs suffer from Link Rot and at least 6.21% of records suffer from Content Drift (do not declare its distribution types correctly). Additionally, 14.94% of metadata records only contain intermediate HTML web pages as distribution URIs and 31.37% contain at least one HTML web page; thus, they cannot be accessed or checked directly.

AUDIT OF CALCULATIONS FOR PAYMENTS TO EMPLOYEES AT THE ENTERPRISE

The purpose of the article is to study the organization and methodology of audit of payments to employees at the enterprise. The methodology consists in the use of the following methods: method of observation, methods of analysis and synthesis, monographic method, method of generalization. The scientific novelty of the work is to improve the organization and methodology of audit of payments to employees, which will objectively evaluate the level of these payments in the total costs of the enterprise, to verify the correctness of the formation of employee benefits under current legislation at enterprises. Conclusions. In modern business conditions, accounting of payments to employees of constant control and improvement. Any incorrect entry, error in calculations, lack of documentation, incorrect approach to the formation of wages, other payments can cause not only problems with the calculation of wages and other payments to employees, but also lead to incorrect reflection of other economic indicators of the enterprise. Audit of employee benefits usually takes up a significant portion of the audit, as this area of accounting is quite specific and requires the auditor to pay more attention and concentration. However, it should be noted that there is no single approach to the organization and methodology of the audit, namely: experts suggest considering the audit of payments as a list of issues to be investigated. The lack of a systematic approach to the audit of payment settlements makes it impossible to consider this process comprehensively, in accordance with a clearly defined purpose and objectives of the audit. Payments, as the object of the audit, need special attention because it is a time-consuming and voluminous stage, during which it is impossible to conduct a continuous audit. At the enterprises with a significant number of employees, it is almost impossible to verify salary transactions in a continuous manner in the short period of time allotted for the for the conduction of audit. That is why the audit mainly uses a selective method of checking documents and transactions on salary, which is justified and appropriate, although not sufficiently developed. That is why audit the calculations of payments to employees at the enterprise is important. Keywords: audit, payments to employees, salary, audit of payment settlements.

Knowledge structure driven prototype learning and verification for fact checking

To inhibit the spread of rumorous information, fact checking aims at retrieving relevant evidence to verify the veracity of a given claim. Previous work on fact checking typically uses knowledge graphs (KGs) as external repositories and develop reasoning methods to retrieve evidence from KGs. Domain knowledge structure, including category hierarchy and attribute relationships, can be utilized as discriminative information to facilitate KG based learning and verification. However, in previous fact checking research, category hierarchy and attribute information was often scattered in a KG and treated as the ordinary triple facts in the learning process like other types of information, or was utilized in a limited way without the consideration of category hierarchy or the combination of category hierarchy with the learning process. Thus to better utilize category hierarchy and attribute relationships, in this paper, we propose an end-to-end knowledge structure driven prototype learning and verification method for fact checking. For improving intra-category compactness and inter-category separation, we develop a hierarchical prototype learning technique that jointly learns a prototype for each sub-category to enhance entity embeddings and optimize embedding representations using high-level category. For further enhancing embedding learning, we propose a graph attention network to aggregate information from neighboring attribute nodes. We construct a real-world dataset on food domain, and experimental results on the benchmark datasets and our domain dataset show the effectiveness of our method compared to both previous fact checking methods and representative KG reasoning methods.