bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recognition of character information for automation of production processes
Authors: Panishchev V. S. , Trufanov M. I. , Dobroserdov O. G. , Khomyakov O. O. 
Published: May 2021

Purpose of research.Nowadays optical character recognition systems have a high level of dependence on the specific type of marking that is to be recognized, and therefore, the creation of a universal solution is an important and difficult task. The paper considers the issue of creating a system for recognizing symbolic information that can be used at various stages of production to automate processes in control systems, in particular, to analyze the labeling of circuit breakers.Methods.Binarization, filtering, and boundary detection are digital image processing techniques. Line search method, baseline search method, word splitting algorithms, image enhancement methods by segmentation, damaged characters recognition method, an algorithm for increasing the final recognition quality are character recognition methods.Results.The analysis of algorithms used for preprocessing and subsequent recognition of images containing marking of circuit breakers is carried out. The mathematical model of image processing for subsequent recognition has been created. We have described methods used to define marking symbols. Illustrative examples of the operation of the algorithms on which the system is built are given. The obtained solution was tested. The ways of system development are described here, they can lead to improved results, for particular use cases.Conclusion.It is proposed a solution that recognizes symbolic information on the labeling of circuit breakers, which can be the basis for the development and description of systems serving for the automation of production, by transferring information read from the product during the production process. This system, by its example, describes the components of character recognition systems, and for direct use, it needs to be refined in accordance with the technical requirements and the specifics of the conditions in which it will be used.
Automated Leadership Selection Educational Projects Based on Genetic Algorithms
Authors: Kovshov E. E. , Kuvshinnikov V. S. , Osipenko L. E. 
Published: May 2021

Purpose or research.The purpose of the study is to conduct a research of the possibility to use automated methods of finding a solution for the task of forming a selection of candidates in solving a wide range of business problems with the possibility of the influence of such factors as: requirements for the quality of business processes, restrictions on the competence of candidates, the employment of candidates in other processes of the company, planned urgency of fulfilling tasks, the amount of tasks in the pool and expected tasks, tasks characteristics, private policy of the company when selecting candidates, company's policy on risks.Methods.A typology of innovative business tasks is given by the subject area, the range of target results, the duration of execution, etc. External and internal factors are considered to ensure the effective operation of the project team and the success of the project. There are offered sets of attributive characteristics for assessment of projects quality and potential projects. The structure of the algorithm for solving the problem of creating a selection of candidates for solving a set of problems is considered. Prerequisites for using principles of genetic programming in solving the problem under consideration are given. Search algorithm implementation parameters, criteria and constraints are defined. Algorithm was implemented as well as modeling in the Jupyter Lab v2 environment. The results are described in the text. A relative analysis of practical effectiveness of the algorithm was carried out depending on the modeling parameters to justify the selection of their values.Results.The task of creating a selection of candidates for the implementation of projects pool considering a number of factors was described during the study. An approach to solving the problem based on a genetic heuristic search algorithm has been developed. A numerical simulation was performed in Jupyter Lab v2. Simulation results were analyzed, and algorithm parameters were selected.Conclusion.The proposed approach allows not only automatize the selection of managers based on the accumulated data history, but also to adjust the established process to change the vector of organization development. The interaction of education and informatics (information technology) can enrich and expand the field of both sciences in the field of recruitment of innovative project teams. Their object analysis, supplemented by genetic programming capabilities, together allows you to achieve specified qualities of the head of innovative project teams that help maximize business benefits while minimizing material costs. As a result of computational experiments using mathematical apparatus and genetic algorithm technologies, it is necessary to emphasize the possibility of extrapolating such approaches to any level of implementation of innovative projects.
Investigation of the Degree of Augmentation of the Mass Transfer Coefficient of the Heat Transfer Medium in a Vortex Heat Exchanger of a Gas Pressure Regulating and Metering Station Heating System
Authors: Grigorova N. P. , Monastyrev P. V. , Pakhomova E. G. , Semicheva N. Ye. 
Published: May 2021

Purpose of research.is to investigate the degree of augmentation of the mass transfer coefficient of a heat transfer medium in contact with a "spot" of liquid on the surface of the vortex blade when it is bombarded with dispersed contaminants in a vortex heat exchanger in order to identify a pattern that allows obtaining design values of the heat transfer coefficient of the heat transfer medium that have the best agreement with the experimental values provided in previously published articles [4, 6, 7].Methods.A complex analysis of the degree of augmentation of the mass transfer coefficient of the heat transfer medium on the surface of the vortex blade in a vortex heat exchanger based on the known theoretical positions and equations of heat and mass transfer processes.Results.The dependence of the augmentation of the mass transfer coefficient of the heat transfer medium in contact with the "spot" of liquid on the surface of the vortex blade when it is bombarded with dispersed contaminants was obtained, which allows obtaining the best agreement of the design and experimental values of the heat transfer coefficient in the vortex heat exchanger of a gas pressure regulating and metering station.Conclusion.The values of the heat transfer coefficient of the heat transfer medium calculated using the obtained dependence of the augmentation of the mass transfer coefficient of the heat transfer medium have a satisfactory convergence with the experimental data, which allows us to use this dependence in engineering calculations of the design parameters of the vortex heat exchanger used as a heat exchanger for the heating system of the working area of the gas pressure regulating and metering station. This technical solution allows not only saving natural gas as a source of heat generation, but also reducing the negative impact on the environment, since there is no need to burn natural gas. In this case, the production of thermal energy is carried out due to a regulated pressure drop of natural gas coming from the main line to consumers.
Applying Multitask Deep Learning to Emotion Recognition in Speech
Authors: Ryabinov A. V. , Uzdiaev M. Yu. , Vatamaniuk I. V. 
Published: May 2021

Purpose of research.Emotions play one of the key roles in the regulation of human behaviour. Solving the problem of automatic recognition of emotions makes it possible to increase the effectiveness of operation of a whole range of digital systems such as security systems, human-machine interfaces, e-commerce systems, etc. At the same time, the low efficiency of modern approaches to recognizing emotions in speech can be noted. This work studies automatic recognition of emotions in speech applying machine learning methods.Methods.The article describes and tests an approach to automatic recognition of emotions in speech based on multitask learning of deep convolution neural networks of AlexNet and VGG architectures using automatic selection of the weight coefficients for each task when calculating the final loss value during learning. All the models were trained on a sample of the IEMOCAP dataset with four emotional categories of ‘anger’, ‘happiness’, ‘neutral emotion’, ‘sadness’. The log-mel spectrograms of statements processed by a specialized algorithm are used as input data.Results.The considered models were tested on the basis of numerical metrics: the share of correctly recognized instances, accuracy, completeness, f-measure. For all of the above metrics, an improvement in the quality of emotion recognition by the proposed model was obtained in comparison with the two basic single-task models as well as with known solutions. This result is achieved through the use of automatic weighting of the values of the loss functions from individual tasks when forming the final value of the error in the learning process.Conclusion.The resulting improvement in the quality of emotion recognition in comparison with the known solutions confirms the feasibility of applying multitask learning to increase the accuracy of emotion recognition models. The developed approach makes it possible to achieve a uniform and simultaneous reduction of errors of individual tasks, and is used in the field of emotions recognition in speech for the first time.
Redesigning a Web-Based Stakeholder Consensus Meeting About Core Outcomes for Clinical Trials: Formative Feedback Study
Authors: Katiri Roulla , Hall Deborah A , Hoare Derek J , Fackrell Kathryn , Horobin Adele , Buggy Nóra , Hogan Nicholas , Kitterick Pádraig T ,   Core Rehabilitation Outcome Set For Single-Sided Deafness (CROSSSD) Initiative
Published: May 2021

Background
Clinical trials that assess the benefits and harms of an intervention do so by measuring and reporting outcomes. Inconsistent selection and diversity in the choice of outcomes make it challenging to directly compare interventions. To achieve an agreed core set of outcomes, a consensus methodology is recommended, comprising a web-based Delphi survey and a face-to-face consensus meeting. However, UK government regulations to control the pandemic prohibited plans for a face-to-face consensus meeting as part of the Core Rehabilitation Outcome Set for Single-Sided Deafness (CROSSSD) study.

Objective
This study aims to evaluate the modifications made by the CROSSSD study team to achieve consensus using web-based methods, but with minimal deviation from the original study protocol.

Methods
The study team worked with health care users and professionals to translate the planned face-to-face consensus meeting in a web-based format, preserving the key elements of the nominal group technique. A follow-up survey gathered evaluation feedback on the experiences of the 22 participating members. Feedback covered premeeting preparation, the process of facilitated discussions and voting, ability to contribute, and perceived fairness of the outcome.

Results
Overall, 98% (53/54) of feedback responses agreed or strongly agreed with the statements given, indicating that the web-based meeting achieved its original goals of open discussion, debate, and voting to agree with a core outcome set for single-sided deafness. Hearing-impaired participants were fully engaged, but there were some methodological challenges. For the participants, challenges included building rapport, understanding, and delivering the tasks in hand. For the study team, challenges included the need for thorough preparation and management of the unpredictability of tasks on the day.

Conclusions
Sharing our experiences and lessons learned can benefit future core outcome set developers. Overcoming the challenges of delivering a web-based consensus exercise in the face of the pandemic can be applied more generally to maximize inclusiveness, enhance geographical access, and reduce research costs.
The Use of Social Media in Detecting Drug Safety–Related New Black Box Warnings, Labeling Changes, or Withdrawals: Scoping Review
Authors: Lee Jae-Young , Lee Yae-Seul , Kim Dong Hyun , Lee Han Sol , Yang Bo Ram , Kim Myeong Gyu 
Published: May 2021

Background
Social media has become a new source for obtaining real-world data on adverse drug reactions. Many studies have investigated the use of social media to detect early signals of adverse drug reactions. However, the trustworthiness of signals derived from social media is questionable. To confirm this, a confirmatory study with a positive control (eg, new black box warnings, labeling changes, or withdrawals) is required.

Objective
This study aimed to evaluate the use of social media in detecting new black box warnings, labeling changes, or withdrawals in advance.

Methods
This scoping review adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. A researcher searched PubMed and EMBASE in January 2021. Original studies analyzing black box warnings, labeling changes, or withdrawals from social media were selected, and the results of the studies were summarized.

Results
A total of 14 studies were included in this scoping review. Most studies (8/14, 57.1%%) collected data from a single source, and 10 (71.4%) used specialized health care social networks and forums. The analytical methods used in these studies varied considerably. Three studies (21.4%) manually annotated posts, while 5 (35.7%) adopted machine learning algorithms. Nine studies (64.2%) concluded that social media could detect signals 3 months to 9 years before action from regulatory authorities. Most of these studies (8/9, 88.9%) were conducted on specialized health care social networks and forums. On the contrary, 5 (35.7%) studies yielded modest or negative results. Of these, 2 (40%) used generic social networking sites, 2 (40%) used specialized health care networks and forums, and 1 (20%) used both generic social networking sites and specialized health care social networks and forums. The most recently published study recommends not using social media for pharmacovigilance. Several challenges remain in using social media for pharmacovigilance regarding coverage, data quality, and analytic processing.

Conclusions
Social media, along with conventional pharmacovigilance measures, can be used to detect signals associated with new black box warnings, labeling changes, or withdrawals. Several challenges remain; however, social media will be useful for signal detection of frequently mentioned drugs in specialized health care social networks and forums. Further studies are required to advance natural language processing and mine real-world data on social media.
The Impact of Conditional Cash Transfer (CCT) to Socio-Economic of Poor Families; A Case Study
Authors: Dulkiah Moh. , Sari Avid Leonardo , Irwandi Irwandi 
Published: June 2021

Poverty is a multidimensional problem such as political dimension, social dimension, environmental dimension, economic dimension and asset dimension. Indonesian government creates program to alleviate poverty. Program Keluarga Harapan (PKH) is one of Indonesian government program. Program Keluarga Harapan (PKH) is a social protection program through the provision of conditional cash transfers to very poor families. This program focuses on improving the quality of life to achieve social welfare through behavioral changes to education and health. The article aims to explore the impact of Conditional Cash Transfer (CCT) on the socio-economic of poor families in Linggo Sari Baganti district, Pesisir Selatan regency. Data were collected from interviews, observations, and documentation by referring to descriptive research method with a qualitative approach. Research findings evaluate the provision of Conditional Cash Transfers. It has not been effective in improving the socio-economic life of poor families in Linggo Sari Baganti district, Pesisir Selatan regency.
Competencia digital: análisis en personal docente de la Escuela Ciencias de la Administración de la UNED de Costa Rica
Authors: Barboza-Robles Yansin Rebeca 
Published: May 2021

Este estudio analiza la competencia digital docente (CDD) de 29 personas tutoras pertenecientes a dos cátedras de la Escuela Ciencias de la Administración de la UNED de Costa Rica. El enfoque fue cuantitativo descriptivo. Se estudió toda población y los datos se recolectaron a través de un instrumento.
Como resultados, se logró clasificar los 22 indicadores de la CDD en tres grupos (grave, moderado y satisfactorio). Se identificaron 5 indicadores graves, 13 moderados y 14 satisfactorios. Los primeros conciernen a retroalimentación, trabajo colaborativo, sesiones sincrónicas y seguimiento del aprendizaje y la participación en los entornos virtuales de aprendizaje, lo cual preocupa por el papel que juegan dichos aspectos en el éxito del estudiantado y su permanencia en el proceso educativo. Se determinó que la mayoría de la población tiene un nivel general medio de la CDD y está anuente a capacitarse sobre el tema.
Para futuras investigaciones, se recomienda aprovechar el instrumento utilizado en esta pesquisa y construir otros con la misma metodología, uno sobre las competencias requeridas antes de ofrecer la asignatura y otro sobre las que se requieren después para evaluar la experiencia y tomar decisiones para mejorar la oferta académica virtual de la universidad.
Reacreditación de carreras de la Universidad de Costa Rica: lo cumplido y lo pendiente.
Authors: Guido-Guido Elsiana 
Published: May 2021

En este artículo se analiza el contenido de quince compromisos de mejoramiento (CM) presentados por carreras de la Universidad de Costa Rica (UCR) que se han reacreditado por primera vez, con la Agencia Sistema Nacional de Acreditación de la Educación Superior (SINAES) utilizando el Manual de acreditación oficial de carreras de grado vigente, que corresponde al año 2009. Estos CM corresponden a carreras reacreditadas entre los años 2011 y el primer semestre del 2020. Los hallazgos obtenidos en este estudio se presentan de acuerdo con las cuatro dimensiones y los veintiún componentes del modelo de acreditación, de manera que se detallan los criterios y componentes que, con mayor frecuencia, presentan debilidades en los CM analizados. Según esto, los CM presentan debilidades en todas las dimensiones del modelo; asimismo, contienen criterios con debilidades en todos los componentes. Los componentes con mayor cantidad de criterios asociados a una debilidad son correspondencia con el contexto, plan de estudios, personal académico, infraestructura, gestión de la carrera, investigación, vida estudiantil y graduados. Más de una cuarta parte de los criterios no están contemplados como debilidades. A partir de los hallazgos, se presentan características que comparten las carreras reacreditadas, considerando las dimensiones del modelo, así como los asuntos atendidos y pendientes a nivel institucional.
Komparasi Luas Tutupan Lahan di Kota Bandar Lampung Berdasarkan Algoritma NDVI (Normalized Difference Vegetation Index) dan EVI (Enhanced Vegetation Index)
Authors: Luvi Luvi Roma Doni , Yuliantina Aisah , Dewi Rafika , Pahlevi M Zaki , Kusumawardhani Nur Aysha 
Published: May 2021

Lahan adalah salah satu sumber daya alam penting yang sangat dibutuhkan oleh makhluk hidup baik hewan, tumbuhan, dan manusia untuk berpijak, sebagai tempat hidup serta melakukan kegiatan kehidupan serta untuk memenuhi kebutuhannya. Ibukota Provinsi Lampung menjadi lokasi penelitian ini yaitu Kota Bandar Lampung. Untuk menentukan luasan wilayah tutupan lahan salah satunya yaitu dengan cara mengidentifikasi kumpulan vegetasi. Vegetasi yang bervariatif bisa disebabkan karena bermacam-macam faktor, yaitu penyebaran tumbuhan, iklim dan jenis tanah. Vegetasi yang merupakan penyusunan lahan memiliki jenis yang beraneka ragam sehingga akan memiliki kelas kerapatan vegetasi berbeda untuk setiap daerah. Beberapa metode citra satelit telah dikembangkan untuk mengestimasi wilayah tutupan lahan di suatu daerah, antara lain metode Algoritma NDVI dan EVI yang dipakai pada penelitian kali ini. Penelitian menunjukkan perbedaan hasil antara NDVI dan EVI, di mana metode EVI lebih baik dalam mengidentifikasi sebuah vegetasi. Hasil klasifikasi atau kerapatan vegetasi Kota Bandar Lampung bahwa vegetasinya sudah kurang yang baik dikarenakan untuk wilayah non vegetasi yang sudah tinggi dibandingkan dengan daerah vegetasi tinggi. Dengan begitu daerah yang bukan vegetasi atau non vegetasi mungkin dapat diciptakan vertical garden (taman vertikal) untuk menjaga vegetasi tumbuhan.
The Involvement of Local Community in Mangrove Forest Conservation in West Kalimantan
Authors: Roslinda Emi , Listiyawati Lilis , Ayyub Ayyub , Fikri Farih Al 
Published: May 2021

Mangrove forest conservation on the coast of West Kalimantanhas been successfully carried out and saved the environment from coastal abrasion (ecological benefit) and provided economic benefits for the community. This study aims to describe the role of the community in mangrove conservation activities in the coastal areas of West Kalimantan. Survey methods were used in this research. The data was collected through interviews based on questionnaires and in-depth interviews. Data processing was conducted by calculating the percentage and then analyzed by tabulation. Mangrove conservation activities are based on community experiences in saving the environment, boosting economic activities, and obtaining benefits from conservation results. The involvement of the local community uses the bottom-up approach, starting from planning activities, implementation, utilization, and evaluation. In general, the local community’s level of involvement is still at the information and consultation stage. The involvement of the local community as an individual varies greatly, from those who are only involved as part of formality to the level of being actively involved, having decision-making authority, and being able to negotiate and deal directly with capital sources. It occurs due to the varying capacity of each individual. Keywords: forest conservation, local community, mangrove
Utilization of Wood Vinegar as a Natural Preservative for Sengon Wood (Falcataria moluccana Miq.) against Fungal Attack (Schizophyllum commune Fries)
Authors: Anggraini Riana , Khabibi Jauhar , Ridho Muhammad Rasyidur 
Published: May 2021

Most wood supplied from forests currently has a low level of durability and vulnerable to wood-destroying organisms attacks. Sengon wood (Falcataria moluccana Miq.) is classified as low durable class wood (class IV-V); hence wood preservation is needed to protect from the attacks of wood-destroying organisms. One of the eco-friendly materials that can be used for wood preservation is wood vinegar. This study aims to analyze the influence of wood vinegar from tembesu (Fagraea fragrans) and rengas (Gluta renghas) on the durability of sengon wood against Schizophyllum commune Fries fungus. The results showed that wood parts and types of wood vinegar significantly affected preservative retention, absorption, penetration, and weight loss. Some of the chemical compounds contained in tembesu and rengas wood vinegar can inhibit the growth of fungi: (1) acetic acid (CAS) ethylic acid, (2) 2-propanone, 1-hydroxy- (CAS) acetol, (3) phenol, 2-methoxy- (CAS) guaiacol, and (4) phenol (CAS) izal. Preservation of wood using tembesu and rengas wood vinegar with a concentration of 70% could increase the resistance of sengon wood and improve sengon wood’s durability into very resistant (durability class I) against S. commune fungus attacks.Keywords: Falcataria moluccana, wood durability, wood parts, wood vinegar