Reviewerly/exHarmony huggingface dataset:
A Multi-Target Detection Method on Distribution Cabinet Based on Improved Faster R-CNN

It is an inevitable trend to detect and recognize the states of different component on distribution cabinet panel more effectively and accurately by using inspection robots instead of manpower. Aiming at the problems of multiple recognition targets and large size difference in image recognition of distribution cabinet panel, an improved Faster R-CNN multi-target detection method is designed. Automatically detect and recognize of different targets on required cabinet panel is achieved by this method. In this paper, Resnet50 is used instead of VGG16 as the feature extraction network in Faster R-CNN, Adam Optimizer is used instead of Momentum, and anchor box size is changed to adapt target size difference on cabinet panel. Experiments show that the improved model has higher accuracy and less computational cost on the required distribution cabinet panel dataset.
Software Maintenance Process Towards Cloud Environment: A Review Study

Software maintenance is the irreplaceable stage in the Software Development Life Cycle (SDLC) and is the most extended, more complex, and costly one. The maintenance phase starts when the software is delivered to the end user and ends after the software goes out of service. In this paper, we review the essential software maintenance models. Also, we propose a model for performing maintenance in the Cloud Computing environment due to the characteristics of the Cloud that would facilitate this process.
Progress in Interdisciplinarity: Bibliometric Analysis of the Diversity of Researchers’ Fields of Specialization Over a 20-Year Period

Background.To support the development of interdisciplinary research effectively, it is essential to provide research funding that takes into account the interdisciplinary characteristics of the field.Objectives.We investigated the progress of interdisciplinarity between 1997 and 2017 for 12 selected target fields, from two points of view, focusing on the diversity of researchers' specializations: (1) the number of researchers' fields of specialization, and (2) the dispersion of the number of researchers among the fields of specialization.Methods.For (1), we investigated different specialization fields, not only the target field as a whole but also for each researcher (author) and each article.For (2), we calculated the Gini coefficient and the coefficient of variation.Results.Different characteristics were observed depending on the viewpoint and the index.The increase rate of (1) was especially high in Materials Science, Biomaterials.The rate of decline of (2) was particularly significant in Information Science & Library Science, Environmental Sciences and Anthropology.It was found that the interdisciplinarity of a field cannot be judged simply as high or low.Interdisciplinarity has gradually grown: not always increasing but also sometimes decreasing or stagnating at times.Contributions.This study has offered a different perspective of interdisciplinarity, and also charted how it has strengthened over the past 20 years.
Machine Learning on Spatiotemporal Data in Football: A Survey of Methods and Problems

Machine learning is growing exponentially, and its applications are gaining more traction in the sports analysis community in recent years.The application of machine learning methods on spatiotemporal data in sports like football is getting attention from football clubs, academics, and amateur analysts and is the focus of this survey.This survey analyses and identifies current trends in research papers and literature to determine current and future applications in football analytics using spatiotemporal data.
“Human – Social Robot” Interaction: Through Overcoming Barriers to Hybrid Communication

Introduction. The article analyzes the problems that arise during communication between a person and a social robot. Barriers that prevent a person from adapting to the specifics of communication tools embedded in the software of devices with artificial intelligence are revealed. Human reactions to the behavior of humanoid robots in various conditions of their use are analyzed. The presence of a person's desire to adapt to the behavior pattern of the device is checked. The authors also test the hypothesis of the emergence of hybrid communication as a way to overcome the barriers of human communication with smart devices. Methodology and sources. The approach implemented in the article interprets the communication of a person and a social robot as a similar subject-subject interaction of performers of social roles by heterogeneous communication participants who implement a model of mutual adaptation to the reactions of the Other. As the key methods there was used the method of observation, mediated by digital recordings of human communication situations with various types of devices. A nonobtrusive (unobtrusive) research method was applied, which excludes the contact of the researcher with the object of study. The sources were audiovisual documents containing recordings of a demonstration of human communication with a social robot. Results and discussion. A weak orientation of a person to adjust his reactions to actions on the part of a social robot with simultaneous attempts to modify his behavior with a focus on imitation of the robot was revealed. The development of hybrid reactions is affected by an increase in the duration of human communication with the device. To a greater extent, hybrid forms of communication continue to be present in the software embedded in social robots of its communication with a person. Conclusion. In the process of reproducing the stable nature of communication in the peculiarities of the behavior of each of the parties, there were ways of responding to overcome the blockade, not foreseen either by the developers of the algorithms or by a person entering into communication with a robot with the expectation of programmed “machine behavior”. Such a process remains predominantly one-sided and is not supplemented by the activity of the other party – a person, their participation in the synthesis of natural and artificial languages, which is impossible without modification of the language of the person oneself, and their cultural and bodily modifications.
New Teaching Approaches in Conditions of Globalisation in Digitized Higher Engineering Education

The study was intended to explore the potential of new teaching approaches in digitized higher engineering education for conducting professional communication as it serves a significant competitive advantage for many specialties, and in a number of companies it is a mandatory item of the professionogram in the conditions of globalisation.This research aims to fill this void in its exploration of the effects of training engineering specialists in learning foreign languages in order to make them possess the knowledge, skills and abilities to successfully participate in foreign language professional communication.They also should be able to present the results of their professional and scientific activities in digital context, as well as possess the skills of academic writing.The conducted research shows that the main principles of teaching second foreign language for engineering specialities in the digitized context are consciousness and the principle of taking into account interference and transference.The frequency of occurrence of interference and transference phenomena depends on three factors, which are investigated in the research.The article serves the interest for those who research digital trends in education as well as those who are interested in introducing new teaching approaches into the educational process of engineers.
Peningkatan Hasil Belajar Melalui Model Pembelajaran Window Shopping pada Materi Alat Pernapasan Manusia dan Hewan Kelas V di MI Giwangretno Tahun Ajaran 2021/2022

This study aims to find out how the application of the window shopping learning model improves learning outcomes in class V human and animal respiratory material at MI Giwangretno for the 2021/2022 academic year and to find out the increase in learning outcomes in class V human and animal respiratory material at MI Giwangretno 2021/2022. This research is a Classroom Action Research (CAR) through qualitative methods which was carried out in class V MI Giwangretno with a total of 26 students consisting of 15 boys and 11 girls. Researchers used data analysis in the form of quantitative and qualitative data analysis. The data analysis technique used is data reduction, data presentation, and drawing conclusions. The results of the study found that the application of the window shopping learning model to material on human and animal breathing apparatus in class V MI Giwangretno was carried out according to the scenario through the pre-cycle, cycle I, and cycle II stages and the window shopping learning model was proven to be able to improve student learning outcomes in the cognitive domain. affective, and psychomotor. This can be seen from the learning outcomes in the cognitive domain, namely the average class value which was previously 69.03 increased to 73.37 in cycle I, and in cycle II it increased to 86.26 and the percentage of completeness of learning outcomes increased from 53.85% to 69.23% in cycle I, and increased to 92.31% in cycle II. Learning outcomes in the affective domain, namely an increase in students in the good category, initially 9 students became 14 students in cycle I, and in cycle II it became 20 students, while learning outcomes in the psychomotor domain can be seen from the number of students who are able to make works that are displayed creatively and interesting and can be completed on time, namely in the first cycle there are 16 students increased to 26 students in the second cycle.
Upaya Meningkatkan Hasil Belajar Peserta Didik pada Tema Makanan Sehat Melalui Metode Genius Learning di Kelas V SDN 215/X Sungai Toman Semester Ganjil Tahun Ajaran 2022/2023

This research is motivated by the students' thematic learning outcomes which are still low and there is a need for corrective action. The purpose of this study is to obtain information and discuss efforts to improve student learning outcomes on the theme of healthy food through the genius learning method in class V SDN 215/X Sungai Toman odd semester of the 2022/2023 academic year. This research is a classroom action research which consists of two cycles and each cycle has two meetings. Each cycle follows four stages, namely planning, implementing, observing, and reflecting. This research was carried out at SDN 215/X Sungai Toman in the odd semester of the 2022/2023 school year with a total of 20 class V students as subjects. Data collection techniques using tests, observations, field notes and documentation. Data were analyzed using percentages and data reduction. Based on the results of the research and discussion, it can be concluded that the genius learning method can improve student learning outcomes on the theme of healthy food in class V SDN 215/X Sungai Toman in the odd semester of the 2022/2023 school year by giving bonus points to students. The increase in learning outcomes can be seen in the percentage of students' mastery learning in cycle I by 65% ​​and increased in cycle II by 85%
A Method for Scientific Cultivation Analysis Based on Knowledge Graphs

The development of big data and artificial intelligence has improved the intelligence and informatization of scientific planting. A scientific cultivation analysis method based on knowledge graphs is proposed in this paper. First, the logical representation and the ontological representation are combined to realize the access of static cultivation information and dynamic cultivation experience, as well as their representation with graphs. Second, according to the characteristics of plant cultivation information, knowledge extraction is realized via relational computing. A relationship determination method based on the first derivative and a multi-level classification retrieval method based on a tree structure are proposed to extract cultivation experience from the experimental data. Then, multimedia technology is embedded in the RDF framework and implemented, which further realizes the display of decision suggestions after scientific cultivation information analysis. Finally, taking perennial flowers as an example, the realization and application performance of cultivation knowledge graphs are demonstrated.
Peningkatan Hasil Belajar dan Motivasi Belajar Siswa dalam Pembelajaran PAI Melalui Pendekatan Behavior Modification di SDIT VIP Al-Huda Candiwulan

The purpose of this study was to improve student learning outcomes and learning motivation through a behavior modification approach in class IV of SDIT VIP Al-Huda Candiwulan Kebumen, Central Java. This research was carried out using the classroom action research method. This research was conducted in two cycles. Data collection techniques used in this study were tests and observations. The data were analyzed by descriptive statistics, namely calculating the mean and standard deviation. Furthermore, using the standard formula formula, the data is compiled with a frequency distribution table. Data analysis is by comparing the scores obtained from Cycle I and Cycle II (data on learning outcomes and student motivation). The data analysis was the analysis of variance of the paired-samples t-test formula with the help of SPSS PASW Statistics 18. The results of the study were: (1) the level of student learning outcomes through the behavior modification approach was included in the fairly good category; (2) the level of students' learning motivation through the behavior modification approach is included in the fairly high category; and (3) there is an increase in student learning outcomes and motivation through a behavior modification approach in Class IV SDIT VIP Al-Huda Candiwulan.&#x0D;
Penggunaan Model Pembelajaran Snowball Throwing untuk Meningkatkan Hasil Belajar Peserta Didik Tema Benda di Sekitarku Kelas III SD Negeri 02/X Parit Culum II Semester Ganjil Tahun Ajaran 2022/2023

The purpose of this study was to obtain information and discuss the use of the snowball throwing learning model to improve student learning outcomes on the theme of objects around me in class III SD Negeri 02/X Parit Culum II odd semester of the 2022/2023 academic year. This research is a classroom action research which consists of two cycles. This research was conducted at SDN 02/X Parit Culum for the academic year 2022/2023 odd semester with 18 class III students as research subjects. Data collection techniques using tests, observations, field notes and documentation. Data were analyzed using percentages and data reduction. From the results of the research and discussion it can be concluded that through the snowball throwing type cooperative learning model it can improve student learning outcomes on the theme of objects around me in class III SD Negeri 02/X Parit Culum II even semester of the 2022/2023 school year by giving rewards
A General Neural Network Deployment Framework for Edge Devices

As the expansion of edge devices, such as local edge servers or even IoT (Internet of Things) devices, edge computing reforms data processing flow, engendering improvement in faster insights, improved response times and better bandwidth availability. However, industry encounters computational resource constraints of machine learning on edge devices, e.g., limitation of memory and processing power. To tackle this situation, we attempt to enhance flexibility of neural network models for variable hardware constraints. In this paper, we propose a paradigm of neural network combination implementation as a primitive solution; further more, we manage to build up a general neural network deployment framework for edge devices.
A Preliminary Study on Auditors’ Performance Attributes – Perceptions from Accounting Firm Practitioners

Research aim: Recent occurrences of accounting failures have raised concerns over the quality of auditors’ performance. While there have been numerous studies on audit quality, there are limited research on what attributes constitute proper auditors’ performance. Thus, the objective of this study is to examine auditors’ performance attributes perceived to be important to achieve audit quality by auditors in practice. Design/ Methodology/ Approach: Data were obtained from 307 survey questionnaires received from auditors of large firms, small and medium-sized firms, and sole proprietors. Research finding: The study respondents perceived auditors’ performance related to competencies to perform the audit effectively and performing the audit in accordance with standards and regulations as the most significant attributes. These two key attributes were significant regardless of the types of audits performed (i.e. PLC or SME) and the position of the auditor (management or staff levels). On the other hand, attribute relating to providing individualised attention to clients was perceived to be of the lowest importance to the respondents. Theoretical contribution/ Originality: This study examined various behavioural and individual attributes for proper auditors’ performance, which enhances the literature on audit quality. Practitioner/ Policy implication: Key attributes and behaviours for auditors’ performance can be used by researchers and audit practitioners to set their performance benchmark and also used to assess any shortcomings. Research limitation: The respondents were mainly auditors of small and medium-sized firms and sole proprietors.
Big Transformers for Code Generation

IT industry has been thriving over the past decades. Numerous new programming languages have emerged, new architectural patterns and software development techniques. Tools involved in the process ought to evolve as well. One of the key principles of new generation of instruments for software development would be the ability of the tools to learn using neural networks. First of all, it is necessary for the tools to learn how to write code. In this work we study the ability of Transformers to generate competition level code. The main goal is to discover whether open-source Big Transformers are “naturally” good coders.
Requirements and architecture design for cloud PaaS orchestrator

Cloud technologies provide abilities for simple and reliable scaling of resources, due to which they have become widespread. The task of managing distributed services in a cloud environment is especially relevant today. Special programs are used for that purpose named “orchestrators” which implement the functions of lifecycle management for applications. However, the existing solutions have many limitations and are not applicable in the general case. Also there is no single standard or protocol for interaction with such tools which requires adaptation of programs for each particular case. The main objectives of this paper are to identify the requirements for a platform-level cloud computing (PaaS) orchestrator, as well as to propose flexible architecture patterns for such tools.
Methods and techniques to automatic entity linking in Russian

Nowadays, there is a growing interest in solving NLP tasks using external knowledge storage, for example, in information retrieval, question-answering systems, dialogue systems, etc. Thus it is important to establish relations between entities in the processed text and a knowledge base. This article is devoted to entity linking, where Wikidata is used as an external knowledge base. We consider scientific terms in Russian as entities. Traditional entity linking system has three stages: entity recognition, candidates (from knowledge base) generation, and candidate ranking. Our system takes raw text with the defined terms in it as input. To generate candidates we use string match between terms in the input text and entities from Wikidata. The candidate ranking stage is the most complicated one because it requires semantic information. Several experiments for the candidate ranking stage with different models were conducted, including the approach based on cosine similarity, classical machine learning algorithms, and neural networks. Also, we extended the RUSERRC dataset, adding manually annotated data for model training. The results showed that the approach based on cosine similarity leads to better results compared to others and doesn’t require manually annotated data. The dataset and system are open-sourced and available for other researchers.
JIT-aware DBMS planner configuration

Dynamic compilation of certain operator compositions might have a drastic impact on overall query performance, but not be considered during optimal query plan selection by DBMS planner due to lack of knowledge. To tackle this problem, we propose to extend cost model with criteria that make dynamic compilation overhead relevant. The necessity to set up the optimizer criteria is due to the fact that the properties of various execution models impose restrictions on the efficiency of query plan execution using certain operator nodes. For example, the push-model used in the dynamic compiler is advantageous when executing queries using sequential scan. So, dynamic compilation makes sequential scan more efficient than index scan. Using index nodes in such a plan makes the value of the dynamic compilation method diminishing. To overcome these problems, it is proposed to configure the DBMS optimizer, so that it evaluates and takes into account the efficiency of using certain types of nodes when building a query plan with its subsequent dynamic compilation. This paper discusses the modification of the PostgreSQL planner to select the most efficient query execution plan based on hardware characteristics and the execution model of operator nodes with interpretation or compilation.
ESTIMATION OF RICE PRODUCTIVITY USING THE NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) ALGORITHM (CASE STUDY OF GUNUNG TALANG DISTRICT, SOLOK REGENCY)

Rice productivity is closely related to rice harvested area and cropping intensity. Remote sensing technology using MODIS MOD13A1 v006 image produces NDVI values that can be interpreted in analyzing the value of rice productivity. Gunung Talang District has a rice field area of 3,369 m2, which is one of the central rice areas in West Sumatra Province. This study aimed to determine the regression equation to estimate rice productivity in Gunung Talang District, Solok Regency using the NDVI (Normalized Difference Vegetation Index) algorithm. The NDVI data used to generate the regression equation was taken in the generative phase. From the results of data analysis, the regression equation for estimating rice productivity in Talang District, Solok Regency is y = 250.33x4 - 1493.3x3 + 2293.6x2 - 1353.9x + 281.13, where x is the NDVI value and y is the productivity value ( tons/ha). The test results of the model's validity are expressed in the value of NSE (Nash-Sutcliffe Efficiency) is 0.66, which is categorized as adequate.
Reduction of false negatives in multi-class sentiment analysis

Sentiment analysis classifications are done as positive, negative, as well as neutral ones. The increased usage of social media and its effects on society call for a more thorough, fine-grained explanation than that. In this study, classification is done in five classes-strongly positive, weakly positive, neutral, weakly negative, and strongly negative-in a more precise manner. Instead of using the typical ways of measuring accuracy alone, a novel method to eliminate false negatives (FN) is focused together with a fine-grained categorization. A bigger risk in sentiment analysis is a false negative. FN classification occurs when the context's polarity is identified as True when it is actually false. A complex dataset is used in this research for the experimental study, and the entire dataset is separated into five classes. Each class's FN are assessed using the suggested methodology. Comparing the proposed strategy to other, it was found to achieve about 53% more reduction in FN cases than rule based models and better predictions than compared machine learning models.