Reviewerly/exHarmony huggingface dataset:
Backpropagation artificial neural network learning algorithm process impact based on hyperparameters

&lt;p&gt;The problem of computing machine passing the maze is one of theoretical computer science key tasks. This task was partially considered by the classics of computer science, e.g. A. Turing, C. Shannon, L. Budach and Z. Pawlak. Labyrinth problem solving includes fundamental knowledges in the main three branches, namely environment (labyrinth) knowledge, computing machines features knowledge and behavior of computing machines in labyrinth knowledge. These three components are built on the fundamental basis of the theoretical computer science. Nowadays the labyrinth passing task is complemented by intellectuality as an additional criterion. That is, computing machines must acquire intelligent functions, and this task gets a new component and a new statement, which is briefly formulated as the search for a way out of the labyrinth by intelligent computing machines. The main concept of this article is to develop artificial neural networks based intelligent functions for calculating machine to pass the maze. Besides this visual aspect is emphasized, i.e. the computational machine includes a maze viewing function. Authors accentuate fundamental principles of artificial neural networks technologies building and engage backpropagation algorithm, which is used in a artificial neural network learning process. The article discusses maze, dataset construction, artificial neural network training, maze recognition computational experiment and analysis of the hyperparameters effect on artificial neural network training.&lt;/p&gt; &lt;p&gt;The aim of the article is to build mathematical model based on backpropagation algorithm and to identify how hyperparameters affect the learning process of artificial neural networks. Thus the research is based on the methods of computational experiment and step-by-step detailing to implement the algorithm. The results of the research include theoretical basis of computing machines intellectualization for the maze and computing machine ability to recognize the maze. These results may be useful to theorists for a detailed description of the process and to practitioners for ability to test this algorithm and approach while solving a problem of maze passing by intelligent agents.&lt;/p&gt;
ANALISIS PENGARUH PENERAPAN SISTEM INFORMASI AKUNTANSI, PENGENDALIAN INTERNAL, MOTIVASI KERJA DAN BUDAYA ORGANISASI TERHADAP KINERJA KARYAWAN DENGAN INTEGRITAS KARYAWAN SEBAGAI VARIABEL INTERVENING

The success of an organization is strongly influenced by employee performance. Every company always improves employee performance to achieve the goals it wants. This study aims to determine the effect of applying accounting information systems, internal control, work motivation and organizational culture on employee performance with employee integrity as an intervening variable. The method used in this study is a quantitative approach and uses a purposive sampling method. The data in this study are primary data obtained from distributing questionnaires directly to accounting students in the Pamulang University employee class, especially students in the accounting study program. The number of samples used is 100 respondents. Data were analyzed by Structural Equation Modeling (SEM). Exogenous latent variables are the application of accounting information systems, internal control, work motivation and organizational culture. While employee performance as an endogenous latent variable with employee integrity as an intervening variable. The results showed that internal control variables formed employee integrity variables (loading factor = 0.69) and employee integrity variables were proven to influence employee performance variables (loading factor = 0.97). This provides an overview in the form of recommendations for improving internal control from the employee side which will have an impact on improving organizational performance.
Agriculture Financing for Output Growth: A Focus on Livestock Production in Nigeria

In this study, the effect of agriculture financing such as the agricultural credit guarantee scheme fund, bank loans and advances to agriculture, and foreign aid to agriculture on livestock production was examined in Nigeria from 1981 to 2021. Annual time series data for each of the variables were obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin and the Organisation for Economic Cooperation and Development (OECD) Statistics. The method of data analysis includes descriptive statistics, a parsimonious error correction model (ECM), and diagnostic tests. Evidence of the first difference stationary processes was established from the unit root test results. This indicates that the variables are all integrated of order one, I(1). The Johansen cointegration test results show that the variables in the model have a long-run relationship. The parsimonious ECM shows that the agriculture credit guarantee scheme fund has a positive and significant effect on livestock output. The estimated parameters show that a 1% increase in the current value of the agriculture credit guarantee scheme fund leads to a 0.0244% increase in livestock output. Similarly, it was found that livestock output increased by 0.0183% following a 1% increase in the first-lag agriculture credit guarantee scheme fund. The findings highlight the importance of agriculture financing in boosting the growth of livestock production in Nigeria. The results further show that bank loans and advances, as well as foreign aid to agriculture, negatively and significantly affected livestock production. The error correction coefficient (-0.297) is negative and significant at the 5% level. This indicates that about 29.7% of
La preparación del docente para favorecer el autocontrol en escolares con rasgos de agresividad. Un estudio de revisión

The need for the constant preparation of teachers in accordance with the demands of the rapid scientic and technological development that contemporary times impose, constitutes for the education sector an unavoidable need in which researchers and teachers as a challenge are dedicated, to develop the teaching-educational process contextualized and with quality. The following review seeks to identify theteacher's competencies for handling situations of aggression among peers. It is concluded the importance of knowing the different cognitive, procedural and attitudinal actions to promote behaviors that allow the formation of attitudes and personal and social values in students.
Recognition of sectional line loss anomaly in low-voltage substations based on multidimensional feature constrained clustering

The line loss in low-voltage substation area is difficult to identify and the identification accuracy is low. In order to improve the accuracy of line loss judgment, a method based on multi-dimensional feature constrained clustering is proposed to identify sectional line loss anomalies in low-voltage substations. First of all, use LOF algorithm to collect electricity information, judge abnormal information of line loss data, and eliminate irrelevant data. Secondly, Hasusdorff distance formula is improved to calculate the multi-dimensional feature similarity of line loss data in power grid substation area, and the similarity matrix between line loss data is obtained. Finally, the multidimensional Hasusdorff distance is applied to the hierarchical clustering algorithm to identify the anomalies in the line loss data of power grid substation areas. The experimental results show that the proposed method has a good effect on identifying the line loss of low-voltage stations.
Fast Multifrequency Phase Unwrapping Method Based on 3D Printing Object Appearance Acquisition

3D printing is an indispensable technology in modern life and is widely used in aerospace, exoskeleton, and architecture. The increasing accuracy requirements of 3D printed objects in these fields require high-precision measurement methods to obtain accurate data. Based on the precision measurement requirements, in this study, a fast multifrequency phase unwrapping method based on 3D printing object appearance acquisition is proposed. By performing standard image acquisition of 3D printed objects that are not limited to materials and sampling locations, the surface shape and texture details of the objects can be accurately reconstructed using this method, independent of ambient light, with high robustness. Compared with the conventional multifrequency method, the required projection pattern is reduced from 12 to 9 and the overall measurement efficiency is improved by 25%, while maintaining the advantages of the independent pixel calculation method of the multifrequency method. In addition, the effectiveness of the method is experimentally verified by complex surface reconstruction experiments and plaster model experiments, which provide accurate measurement accuracy with high efficiency and precision. Therefore, the method can provide accurate measurements for 3D printed objects.
Ontologies and Physical Analogues of Two-Particle Intrasystem Interactions Based on Doublets Models

Open systems (natural, social, anthropogenic, cyber-physic, and technical ones) are initially given in actual states by their empirical descriptions, obtained from huge amount of retrospective multimodal heterogeneous empirical data. At the level of fact, the empirical descriptions contain hundreds and thousands of indicators and represent such systems at their natural scales and real complexity. Furthermore, knowledge about systems’ ontology is represented at the level of sense, knowledge whose fullness and completeness are investigated and proven. At the level of ontological knowledge, the system’s reconstructions are obtained «in parts» (in eigen qualities). And, to build reconstruction of system’s states as a whole, such system reconstructions «in parts» need to be complemented by models of two-particle, three-particle, and multi-particle interactions between eigen system qualities. Ontologies of all kinds of doublets (models of two-particle interactions named SIM, SWI, MIX, SEP, ABS, DIV) are obtained and investigated in this paper. Each such kind of model possesses discovered types and forms. And, for them, such states are revealed whose attributes of orientation, tension, and “charge” level are agreed upon values. These doublets states attributed in such a way possess analogues represented by states of physical science objects exhibiting effects of deformation field as well as electric and magnetic fields that cause «multispecies» variability of open systems.
Enhancing Cybersecurity Defense of IoT Ecosystem Using Blockchain

The expansion of IoT devices over the past years has led to the development of smart ecosystems susceptible to cyberattacks. These ecosystems include smart industries and smart home security systems. However, when these devices are widely deployed and generate significant amounts of data, this data must be securely stored on the cloud to prevent it from being compromised by serious cyber attacks. Although traditional security methods partly meet the need to protect the privacy and security of smart IoT ecosystems, their centralized structure and limited computing power make them inefficient. However, recent advancements in blockchain technology have made it possible to employ decentralized architectures to enhance the cybersecurity defense mechanisms of IoT ecosystems. The utilization of blockchain-enabled methodologies is considered one of the most auspicious advancements in the domain of the IoT. These techniques offer a secure and decentralized mode of communication among internet-connected devices.&#x0D; This study presents a blockchain-based novel framework to enhance the cybersecurity measures of smart IoT ecosystem installations. The proposed framework prioritizes the immutability of devices and users present in such environments and incorporates smart contracts to ensure their overall security. Furthermore, the system includes a module for regularly verifying the firmware of connected devices by comparing them to the valid firmware hashes present in the smart contract's storage. The proposed approach has also come up with the idea of blacklisting the malicious IP addresses trying to connect with IoT ecosystems network.
Developing the performance of artificial intelligence units to ensure sustainability and enhance spending efficiency in some Saudi universities

The study aimed to measure the degree of performance of artificial intelligence units to ensure the raising and development of spending efficiency in some Saudi universities. The researcher used a descriptive analytical methodology. The researcher used a questionnaire as a tool for collecting information. The study community consisted of all faculty members in King Abdul Aziz University, King Saud University), in the Kingdom of Saudi Arabia, from the academic year 1443-1444 AH, and the study sample amounted to (371) faculty members from the study community. The study reached several results, including: The degree of performance of the leaders of artificial intelligence units in raising the efficiency of spending was medium, at a rate of 77.75%. %, and that the degree of performance of the leaders of artificial intelligence units in the field of implementing plans to raise the efficiency of spending was medium, at a rate of 78.00%. The study recommended: the need to build a system that works within the standards of quality and the cost of spending to determine the best scenario that maintains the quality of work while controlling spending, and establishing partnerships with external parties to build the system for spending, the optimal investment of resources, and building an accountability system that works to control spending according to determinants and standards determined by the system artificial intelligence and others.
AGILE ESTIMATIONS: EMPIRICAL STUDY USING WEIGHTED COMPLEXITY FACTORS

Software time and cost estimates are always challenging due to the quickly changing software process. Especially Agile project estimations are complex, and the story points differ from person to person. Due to the person-to-person variations, project managers have difficulty arriving at the project cost for development projects with different sizes or complexity of systems/software. This paper proposes a new estimation model named the WEighted COmplexity Factor Estimation (WECOFE) Model to reduce the complexities of Agile story point estimations. Weighted complexities factors identify Low, Moderate, and High Project Level Factors and Story Level Factors. For each level, multiple factors were defined. Derived Weighted complexity based on Project, Requirement, and Resource Level factors. Each story's point estimation is explained based on weighted complexity defined and assigned factors values. Conducted study on various industry projects, showing that the WECOFE approach is promising by observing the Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE). Also, performed a t-test for one sprint project with 51 stories, and paired sample means are equal for WECOFE with actual story points spent by the team.
DEVELOPMENT OF AN ELECTRONIC TEACHING AID ON THE DISCIPLINE «OLYMPIAD TASKS IN MATHEMATICS»

The paper describes the process of implementing the electronic textbook «Differential and Integral Calculus», using the designer of electronic courses ISpring Suite. The compliance with the state standard of information and communication technologies in the field of education, structure and content of the electronic textbook. With the help of the set cover problem, optimal tests are formed, consisting of practical tasks and covering a set of knowledge elements.
Associative Games with Virtual Agents: unexpectedness increases willingness to continue dialog

Abstract In the field of human-agent interaction, increasing agents' trustworthiness, inelligence perceived and users' motivation to continue interacting are important issues.Prior research has attempted to solve this problem by having "agents meet user expectations".In this paper, we attempted to show that, on the contrary, "agents contradicting user expectations" can increase agents' trustworthiness and users' motivation to continue dialogue.In this study, we conducted an experiment using an "association game" task.In this task, participants were given three hints and answered what those hints have in common.The correct answer is then given, along with a fourth hint.In the first condition, the "expected" condition, the correct answer was the one that the majority of participants associate with.In the second condition, the "unexpected" condition, the correct answer is different from the answer that the majority of participants associate with.After this task, participants answered the question about the extent to which they felt the agents' trustworthiness, intelligence and motivation to continue the interaction using a 7-point Likert scale.The experiment was conducted on the web.The results of the experiment showed that agents' trustworthiness and users' motivation to continue the interaction were significantly higher in the "unexpected" condition than in the "expected" condition.This result indicates that "the agent contradicts the user's expectations" can increase the agent's intelligence perceived and the user's motivation to continue the interaction.The results show the effectiveness of a new method in human-agent interaction that has not received much attention.
Reducing knowledge synthesis workload time using a text-mining algorithm for research location and subtopic extraction from geographically dependent research publications

Abstract The use of text-mining for knowledge synthesis, including literature reviews, has been gaining traction as modern Natural Language Processing tools have progressed. However, there is a trade off between accuracy and precision with workload times. The largest workload times for data extraction typically have better validation metrics. Manual data extraction is an example of this. Currently, there are a limited number of text-mining tools that have shown data extraction from research texts within minutes while maintaining acceptable validation metrics. By using a previously demonstrated generalized approach to determine research production with modern text-mining tools for extracting research locations and subtopics, a methodology with higher than average validation metrics and significantly improved workload times is shown. It was shown that coupling two reliable Named Entity Recognition tool kits for research location extraction, a Latent Dirichlet Allocation model for unsupervised subtopic detection, and a Large Language Model for subtopic clustering can extract research locations, from more than 1,000 public health research articles, and cluster their subtopics, in less than 5 minutes. Validation metrics return F1 Measures of 92% for research location extraction and 71% for subtopic clustering. Additionally, applying these results to a previously constructed spatiotemporal generalization process reproduces the generalized results with a correlation coefficient of 97%, which significantly varies from random chance (p &lt; 0.001). The mapped fitted values are reliably close with the validation model’s fitted values.
Students’ Ability in Writing Opinion Essay Using Writing Process Method and a Story Based on Adab Education

A Good writing is determined by some things, one of which is its process. This study aimed at finding out the influence of the writing process method and a story based on Adab education on the student’s ability to write an opinion essay. The design of this research is mixed method research. The research population was eight classes of undergraduate students in semester 3 of the English Education Department of Teacher Training and Education Faculty in the academic year 2019/2020. The research sample was 37 students that were purposively chosen. The instruments used were a pretest and a posttest. The findings showed that the average posttest score for the experimental class (71.0) was two points higher than the score for the control class (69.0). The results of calculating the difference between the experimental class's posttest and pretest values, a value of 24, were obtained. In contrast, in the control class, a value of 26 was obtained as the result of calculating the difference between the posttest and pretest values. The difference between the two results was -2. Based on that, the conclusion was that the influence of the writing process method and a story based on Adab's education was insignificant. In other words, the writing process method and a story based on Adab education were similarly good in improving students' competence in writing an opinion essay. The findings suggest the necessity of doing or implementing the writing process and a story based on Adab’s education if students hope to have good English writing particularly an opinion essay.
The Impact of SAVI Learning Model on Students' Speaking Skills for Elementary Levels

The field of education in modern times has advanced quickly. Learning is made easier by educators and school infrastructure. Every student's potential is still being maximized through ongoing design improvements in the teaching and learning process. This research investigates the effectiveness of the SAVI (Somatic, Auditory, Visual, Intellectual) model on the students' speaking skills. The research employs true experimental with a pretest-posttest control group design, which gives a test before and after the treatment using the SAVI model. The sample of this study is two classes, namely class VA as the experimental class, totaling 30 students, and class VB as the control class, totaling 34 students. The data collection techniques used in this study are observation, test, and documentation, which are analyzed with descriptive statistics. The data is analyzed using the inferential test formula (t-test). The results showed that the SAVI model was effectively used in learning students' speaking skills. It can be seen from the results of the hypothesis, namely the value of t_count 2.47 and 2.00 so that the results are accepted and rejected. Thus, it can be concluded that there is a positive impact of the SAVI learning model on students' speaking skills. The teacher can apply this model in teaching the students whose grades are below the class average so that this method can be used in learning students' speaking skills in Indonesian subjects.
Supplemental Material: Reconciling complex stratigraphic frameworks reveals temporally and geographically variable depositional patterns of the Campanian Ignimbrite

&lt;p&gt;File S1 includes an elaboration of our methods, a figure portraying our geochemical data in greater detail, and a figure showing some trends in quantitative shard shape parameters. File S2 is a catalog of all the samples used in our study with an image of the exposure. File S3 is a series of Excel documents containing all data sets. &lt;/p&gt;