Reviewerly/exHarmony huggingface dataset:
Migration patterns of earthquake clusters

&amp;lt;p&amp;gt;Earthquake hypocenter migration is the most characteristic pattern which indicates aseismic processes triggering the observed seismicity. These processes can involve creep, fluid migration or similar. While interactions among earthquakes can also lead to some expansion of seismic clouds, these expansions are rather small and not comparable to migration patterns related to pore-pressure diffusion, slow slip events, or growing hydraulic fractures. Thus, identification and modeling of migration patterns, which has not been studied in detail, is important for the characterization of fault dynamics.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Advance of the triggering front is usually analyzed using distance-time plots that show the time dependence of the distance of individual events from the origin. If event order is used instead of time as the argument on the horizontal axis, event migration is analyzed in dependence on the seismic activity itself, which brings a new view to the running seismicity. We applied this approach to the relocated earthquake swarm catalogs from West Bohemia, California and Iceland and found a striking linear growth of the triggering front. This indicates that the advance of the front is likely to be driven by the rupture of individual earthquakes rather than by the running time. It also turned out that the growth velocity measured in meters per event increases with the magnitude of the data set.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Using the basic concepts of earthquake physics, we propose the relation of the growth velocity on earthquake magnitudes and compare it with measurements on the analyzed swarm catalogues. We show that the spreading velocity of the triggering front is closely related to source parameters, which gives hints to the understanding of the background mechanism.&amp;lt;/p&amp;gt;
Evaluating the performance of an internal control system to enhance the quality of auditing Applied research in Al-Muthanna Governorate

The research aims to evaluate the internal control system's performance to enhance the quality of auditing in economic units. Accordingly, the province of Muthanna was chosen as a sample for the research and the period (2014, 2015. 2016, 2017). The researcher relied on a group of published sources, books, and research on the theoretical side. As for the applied side, a group of methods was relied upon, such as collecting data required from the provincial office and the Financial Supervision Bureau's reports for the years of study. Field observations and visits. As well as personal interviews. The research concluded that no plans had been prepared to draw up the general policy of the governorate and define its priorities in all areas in a way that does not contradict the national development plans, as well as the absence of plans in the field of supervision and control over the functioning of public facilities in the governorate and inspecting them.Consequently, it is necessary to prepare plans to draw up the governorate's general policy and define its priorities in all fields and object to the local council decisions that violate the constitution and laws.
Can Digitalization Help Deter Corruption in Africa

This paper studies the effect of digitalization on the perception of corruption and trust in tax officials in Africa. Using individual-level data from Afrobarometer surveys and several indices of digitalization, we find that an increase in digital adoption is associated with a reduction in the perception of corruption and an increase in trust in tax officials. Exploiting the exogeneous deployment of submarine cables at the local level, the paper provides evidence of a negative impact of the use of Internet on the perception of corruption. Yet, the paper shows that the dampening effect of digitalization on corruption is hindered in countries where the government has a pattern of intentionally shutting down the Internet, while countries that successfully promote information and communication technology (ICT) enjoy a more amplified effect.
KEY CONDITIONS OF DEVELOPMENT OF PSYCHOLOGICAL-PEDAGOGICAL COMPETENCE OF TEACHERS OF SPECIAL DISCIPLINES OF TECHNICAL COLLEGE

The article analyzes conditions of development of psychological and pedagogical competence of teachers of special disciplines of technical colleges as a determining factor in the preparation of a highly qualified graduate. An author's scheme of scientific and methodological work of a technical college is proposed, which combines components, principles and functions of the system and conditions of its effective functioning, in which all structural components of the system (goals and objectives, content, forms and methods) are aimed at realizing the result of work and associated with the conditions, principles and functions, and the integrity and systematic use of all the components identified in the complex will contribute to the end result. It is emphasized that an important factor for becoming a beginning teacher is the moral and financial support of a pedagogical employee by the administration of an educational institution. The priority goal of improving the teachers training system is the principle of accessibility of methodological-educational services and orientation to the individual needs of each teacher, and among the ways of solving the set tasks - full-scale introduction of modern computer technologies of teaching. The key conditions for the development of psychological and pedagogical competence of teachers of special disciplines of technical colleges have been formulated, namely: the creation of a system of scientific and methodological work in the educational establishment, which allows to develop the psychological and pedagogical competence of teachers of special disciplines of technical colleges, the formation of internal and external disciplines of teaching professional activity in a technical college, providing scientific and methodological system of educational establishment with information, in particular clouds technology. It is concluded that the implementation of the above-mentioned organizational and pedagogical conditions into the scientific and methodological process of the technical college will become the foundation for the further formation and development of the psychological and pedagogical competence of teachers of special disciplines.
GENESIS OF FORMATION OF VALUE ORIENTATIONS OF STUDENT YOUTH IN THE HISTORY OF DOMESTIC PEDAGOGICAL THOUGHT (XX – BEGINNING OF XXI CENTURY)

The article deals with the historical and pedagogical aspect of the genesis of the formation of value orientations of student youth in the institutions of higher education of Ukraine from the XXth to the beginning of the XXI century. The preconditions for strengthening tendencies in the development of ideas and accumulation of the experience of formation of value orientations in higher education institutions of Ukraine in the XX - the beginning of the XXI century are characterized. The essence of the definition of "value orientation" is revealed. The changes that took place in the value orientations of youth in Ukraine are considered. The theoretical ideas are systematized and the experience of formation of value orientations of student youth in institutions of higher education of Ukraine (XX – the beginning of the ХХІ-st century) is generalized. the prospects of further formation of value orientations of student youth in institutions of higher education of Ukraine are substantiated. "Professional values" are considered as a complex multilevel education, a system of coordinates and relevant regulations of the process of professional activity of a specialist. It is established that the professional values of student youth embody professional responsibility, substantive saturation of pedagogical work, its moral aspect, principles and professional relations. The functions of value orientations and peculiarities of their formation in the professional training of future specialists of the institution of higher education of Ukraine are determined. It is established that the mechanism of formation of value orientations in student youth of the institution of higher education covers the stages: perception; response (subordinate, voluntary, response pleasure); assimilation of professional values acceptance of values, prevalence of professional values, conviction); organization of professional values conceptualization of professional values, organization of the system of professional values); use of professional values internalization of professional values, use of professional values in activity).
OSS PESTO: An Open Source Software Project Evaluation and Selection TOol

Open source software (OSS), playing an increasingly critical role nowadays, has been commonly adopted and integrated in various software products. For many practitioners, selecting and adopting suitable OSS can help them greatly. Though many studies have been conducted on proposing OSS evaluation and selection models, a limited number are followed and used in the industry. Meanwhile, many existing OSS evaluation tools, though providing valuable details, fall short on offering intuitive suggestions in terms of framework-supported evaluation factors. Towards filling the gap, we propose an Open Source Software Project Evaluation and Selection TOol (OSS PESTO). Targeting OSS on Github, the largest OSS source code host, it facilitates the evaluation practice by enabling practitioners to compare candidates therein in terms of selected OSS evaluation models. It also allows in-time Github data collection and customized evaluation that enriches its effectiveness and ease of use.
STRUKTUR DAN CIRI KEBAHASAAN TEKS LAPORAN HASIL OBSERVASI SISWA KELAS VII SMP NEGERI 12 SOLOK SELATAN

ABSTRACT This study aims to (1) describe the structure of the report text observation of the work of class VII SMP Negeri 12 Solok Selatan (2) illustrates the linguistic characteristics of the observation report text by class VII SMP Negeri 12 Solok Selatan. The results of this study are as follows. First, in writing the report text of observations of Grade VII students of class VII SMP Negeri 12 Solok Selatan, they have used the three text structures of the observation report results. The structure of the report's observational text is a general definition, section description, and description of benefits. This is evident from the 20 observational report texts that have been analyzed throughout the observation report text of class VII SMP Negeri 12 Solok Selatan complete using general definitions, section descriptions, and benefits descriptions. Second, in writing the report text of observations generally in class VII SMP Negeri 12 Solok Selatan have used the four text structures of the observation report. The Fourth linguistic characteristics of the text of the observation report are repetition, pronoun, conjunction, and description sentences. This is evident from the 20 text reports on observations that have been analyzed, there are 16 text reports on observations that are complete using the linguistic characteristics of repetition, pronouns, conjunctions, and sentence definitions. Kata Kunci: Struktur Teks, Ciri Kebahasaan, dan Teks Laporan Hasil Observasi
Deep Learning Based Depth Estimation and Reconstruction of Light Field Images

Light field imaging is one of the most promising methods to capture realistic 3D scenes. In this paper, we propose a deep learning network composed of two sub-networks performing depth estimation and light field image reconstruction, respectively. We simultaneously train the two sub-networks by employing a loss function combining the reconstruction loss of the reconstruction network and the estimation loss of the depth estimation network. Experimental results demonstrate that the proposed method accurately estimates the disparity maps of light field images and also faithfully reconstructs light field images.
Research on Lidar Data Error Correction Method Based on Bayesian Network

Data quality analysis is the first and key step of remote sensing mechanism/application research (especially quantitative remote sensing), which directly affects the accuracy of remote sensing inversion and the effect of remote sensing applications. Lidar (light detection and ranging, referred to as lidar) is a new active remote sensing technology. The research on hardware system development and data post-processing algorithm needs to be further strengthened, especially for the quality analysis of lidar data. After initializing the Bayesian network and checking the error, a correction mathematical model is established. Experiments have proved that after correction, the angle error of the radar is significantly improved, which verifies the feasibility and reliability of the precision orbit star calibration method.
Goods Transportation Problem Solving via Routing Algorithm

This paper outlines the ideas behind developing a graph-based heuristic-driven routing algorithm designed for a particular instance of a goods transportation problem with a single good type. The proposed algorithm solves the optimization problem of satisfying the demand of goods on a given undirected transportation graph with minimizing the estimated cost for each traversed segment of the delivery path. The operation of the routing algorithm is discussed and overall evaluation of the proposed problem solving technique is given.
Design of Intelligent Retrieval System for Visibility Animation Material Based on Data Mining

Due to the lack of information viscosity, the semantic consistency of the traditional visual animation material intelligent retrieval system is poor. A visual animation material intelligent retrieval system based on data mining is designed. In hardware design, SED1335 liquid crystal display and resistive touch screen are used to design AD7843 pin function to realize human-computer interaction; in software design, visual animation material data is clustered through data mining technology to obtain a class-centric material data set, Create an index for each data set, and use Lucene to realize intelligent retrieval. The test results show that: the designed visual animation material intelligent retrieval system based on data mining has strong correlation between the material data and the retrieval semantics are basically consistent, which is better than the traditional intelligent retrieval system.
Domain Knowledge in Exploration Noise in AlphaZero

The AlphaZero algorithm has achieved remarkable success in a variety of sequential, perfect information games including Go, Shogi and Chess. In the original paper the only hyperparameter that is changed from game to game is the α parameter governing a search prior. In this paper we investigate the properties of this hyperparameter. First, we build a formal intuition for its behavior on a toy example meant to isolate the influence of α. Then, by comparing performance of AlphaZero agents with different α values on Connect 4, we show that the performance of AlphaZero improves considerably with a good choice of α. This all highlights the importance of α as an interpretable hyperparameter which allows for cross-game tuning that more opaque hyperparameters like model architecture may not.
A proposed technique for improving run length encoding

Image compression, is used to reduce the quantity of pixels used in image representation without excessively change image visualization. Reducing image size  enhance images sharing, transmitting and storing. Data compression has become more important than ever, due to the increasing demand for internet use and exchange of a huge amount of images, videos, audio and documents as well as growing demand for electronic archiving by government departments that produce thousands of documents per day. In this paper, a proposed technique for improving run length encoding results will be presented.       The proposed technique is a lossless and completed technique, it is consisting of two parts the compression part and decompression part. The compression part contains some basic stages such as: pre-processing, run length encoding, replace maximum values by unused values, minimize levels, delta encoding, while the decompression part is the revers of compression part.        This technique is applied on twenty documents and compared with RLE. The experimental results showed that the proposed technique gives a higher compression ratio than the RLE
E-Commerce Human Capital Value Prediction Method based on Fuzzy Comprehensive Evaluation

The evaluation of human capital is a very complex task. How to confirm human capital in the corporate system, accurately measure the value of human capital, and consider the income rights of human capital has become a focus of academic research, and thus a design based on fuzzy Comprehensive evaluation method of e-commerce human capital value prediction. Through the first fuzzy comprehensive evaluation, the evaluation index system and evaluation standard set are established. Through the second fuzzy comprehensive evaluation, the human capital value prediction of e-commerce based on fuzzy comprehensive evaluation is completed. Experiments have proved that the e-commerce human capital value prediction method based on fuzzy comprehensive evaluation in this study is more accurate than traditional prediction methods, and the e-commerce human capital value prediction time is shorter, which has practical application significance.
Research on stability control method of mechanical driving device based on Data Mining

The stability of the mechanical drive device affects the performance of the device. The control performance of the existing mechanical drive device stability control methods is low. Therefore, this paper designs a stability control method of mechanical drive device based on data mining. First analyze the configuration of the mechanical drive device, and obtain the working data of the mechanical drive device based on this, and then use the data mining algorithm to extract the feature data of the mechanical drive device, and build the vibration equation of the mechanical drive device based on the extracted feature data to analyze the mechanical drive device The stability state. On this basis, direct torque control technology is used to control the stability of mechanical drive device. The simulation experiment results show that the average displacement error of the mechanical drive device of the method in this paper is less than 0.1 under various working conditions, which fully shows that the method in this paper has a better control effect.
Domain Adaptive Learning Based on Sample-Dependent and Learnable Kernels

Reproducing Kernel Hilbert Space (RKHS) is the common mathematical platform for various kernel methods in machine learning. The purpose of kernel learning is to learn an appropriate RKHS according to different machine learning scenarios and training samples. Because RKHS is uniquely generated by the kernel function, kernel learning can be regarded as kernel function learning. This paper proposes a Domain Adaptive Learning method based on Sample-Dependent and Learnable Kernels (SDLK-DAL). The first contribution of our work is to propose a sample-dependent and learnable Positive Definite Quadratic Kernel function (PDQK) framework. Unlike learning the exponential parameter of Gaussian kernel function or the coefficient of kernel combinations, the proposed PDQK is a positive definite quadratic function, in which the symmetric positive semi-definite matrix is the learnable part in machine learning applications. The second contribution lies on that we apply PDQK to Domain Adaptive Learning (DAL). Our approach learns the PDQK through minimizing the mean discrepancy between the data of source domain and target domain and then transforms the data into an optimized RKHS generated by PDQK. We conduct a series of experiments that the RKHS determined by PDQK replaces those in several state-of-the-art DAL algorithms, and our approach achieves better performance.
Attitudes of Early Education Teachers Towards Pedagogical Innovation

The subject of the research considerations are the attitudes of early education teachers towards pedagogical innovation, being a response to the permanently changing reality and the related necessity to introduce changes to education. The conducted surveys and their analysis prove that the majority of teachers share the view that application of innovation in pedagogical practice is necessary, noticing both its impact on their professional activity and pointing to significant obstacles in the field of deployment and implementation of innovations at school.
APLIKASI CORELDRAW DALAM PEMBUATAN KALENDER SEBAGAI MEDIA PROMOSI PADA GERAI SENTRAL ONE MALANG

Calendars are of promotional media that can be used to show the information about the company. Through calendar, the company can deliver information which can attract customer’s attention This research was of an action research. The Corel Draw X7 aplication was applied to design the calendar It is concluded that the calendar is very worth using and can be used as a promotional tool. It is suggested that the Sentral One make calendars as promotional media regularly with other promotion.
RANCANG BANGUN SISTEM INFORMASI PELAYANAN PADA KELURAHAN BALOI PERMAI

Technology and information are very important in every agency. E-service is an electronic-based service that uses certain processes to provide better service. Baloi Indah Kelurahan is a community headquarters by providing services, one of which is managing population documents. In this study, the authors conducted a sistem design using the SDLC method with the Waterfall model. The process of designing and coding applications using the PHP and MySQL languages
Improvement in Accuracy and Speed of Image Semantic Segmentation via Convolution Neural Network Encoder-Decoder

Recent researches on pixel-wise semantic segmentation use deep neural networks to improve accuracy and speed of these networks in order to increase the efficiency in practical applications such as automatic driving. These approaches have used deep architecture to predict pixel tags, but the obtained results seem to be undesirable. The reason for these unacceptable results is mainly due to the existence of max pooling operators, which reduces the resolution of the feature maps. In this paper, we present a convolutional neural network composed of encoder-decoder segments based on successful SegNet network. The encoder section has a depth of 2, which in the first part has 5 convolutional layers, in which each layer has 64 filters with dimensions of 3×3. In the decoding section, the dimensions of the decoding filters are adjusted according to the convolutions used at each step of the encoding. So, at each step, 64 filters with the size of 3×3 are used for coding where the weights of these filters are adjusted by network training and adapted to the educational data. Due to having the low depth of 2, and the low number of parameters in proposed network, the speed and the accuracy improve compared to the popular networks such as SegNet and DeepLab. For the CamVid dataset, after a total of 60,000 iterations, we obtain the 91% for global accuracy, which indicates improvements in the efficiency of proposed method.
Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models

Reinforcement learning is a promising paradigm for solving sequential decision-making problems, but low data efficiency and weak generalization across tasks are bottlenecks in real-world applications. Model-based meta reinforcement learning addresses these issues by learning dynamics and leveraging knowledge from prior experience. In this paper, we take a closer look at this framework, and propose a new Thompson-sampling based approach that consists of a new model to identify task dynamics together with an amortized policy optimization step. We show that our model, called a graph structured surrogate model (GSSM), outperforms state-of-the-art methods in predicting environment dynamics. Additionally, our approach is able to obtain high returns, while allowing fast execution during deployment by avoiding test time policy gradient optimization.