Cooperative Training Research Articles

Residual current fault type recognition based on S3VM and KNN cooperative training

Residual current fault type recognition based on S3VM and KNN cooperative training

The Impact of COVID-19 on the Clinical Practices, Working Environment, and Social Life of Intensivists in Non-COVID ICU.

Enlightening the changes in the usual clinical practices, working environment, and social life of Intensivists working in noncoronavirus disease intensive care units (non-COVID ICU) during the COVID pandemic. Observational cross-sectional study for Indian intensivists working in non-COVID ICUs conducted between July and September 2021. A 16-question online survey consisting of the work and social profile of the participating intensivists, changes in the usual clinical practices, working environment, and impact on their social life was administered. For the last three sections, intensivists were asked to compare pandemic times to prepandemic times (pre-mid-March 2020). The number of invasive interventions performed by intensivists working in the private sector with lesser clinical experience (<12 years) were significantly less as compared to the government sector (p = 0.07) and clinically experienced (p = 0.07). Intensivists without comorbidities performed significantly lesser number of patient examinations (p = 0.03). The cooperation from healthcare workers (HCWs) decreased significantly with lesser experienced intensivists (p = 0.05). Leaves were significantly reduced in case of private sector intensivists (p = 0.06). Lesser experienced intensivists (p = 0.06) and intensivists working in the private sector (p = 0.06) spent significantly lesser time with family. Coronavirus disease-2019 (COVID-19) affected the non-COVID ICUs as well. Young and private sector intensivists were affected due to less leaves and family time. HCWs need proper training for better cooperation during the pandemic time. Ghatak T, Singh RK, Kumar A, Patnaik R, Sanjeev OP, Verma A, et al. The Impact of COVID-19 on the Clinical Practices, Working Environment, and Social Life of Intensivists in Non-COVID ICU. Indian J Crit Care Med 2022;26(7):816-824.

International Professional Development Cooperation Study Tours for Environmental, Social and Sustainable Development for the Indian Mining Sector

The Key Centre for Mines International, University of New South Wales, Sydney Australia undertook professional development mining education and cooperation training study tours for overseas government fellows and groups as well as private mining companies from 1988 – 2010. During the technical environmental development short courses at the university and visits to Australian mines and government offices, the programs also covered important social and sustainable aspects as well as relevant briefings on government mining law and regulations, industry’s best practice and community engagement. Details are presented for two major successful international cooperation Indian projects, a World Bank mine environment program in 2004 for state government officials and a TATA Steel Limited coal and iron mine executives and managers training program in 2010.&#x0D; &#x0D; Received: 21 April 2022 / Accepted: 30 June 2022 / Published: 5 July 2022

Peningkatan Ekonomi Masyarakat Melalui Koperasi Serba Usaha “Ribath Darul Maslahah” Di Masjid Besar Arribath Kec. Jogoroto Kabupaten Jombang

Of the several problems based on the mapping of problems carried out at the beginning of this service activity which is the cause of the inhibition of the development of the "Ribath Darul Maslahah" Cooperative, the Great Mosque of Arribath, Jogoroto District, among others, are 1. Community Perception 2. Human Resources 3. Management Management 4. Capital. However, after socialization and training, some of these problems can be resolved, although not yet fully resolved. It is proven that from the side of the cooperative members, with the cooperative training, the members can understand the existence in depth because the cooperative is related to its main finances so that members understand the credit debit and profit calculations based on the RAT each year. And the current condition of the existence of cooperatives can increase the income of the surrounding community, with a very small percentage due to the covid-19 pandemic, which has a huge impact on the economic sector and people's income. If the people's income increases, the basic savings and voluntary savings can be increased. So that the cooperative's ability to expand the business is even wider. And finally, it can further increase the income of members and the surrounding community.

Hyperspectral anomaly detection based on score-guided cooperative autoencoders

ABSTRACT Hyperspectral anomaly detection (HAD) is an important application of hyperspectral technology and has received extensive research attention. The lack of available prior spectral information limits deep-learning-based HAD. During the model training process, background and anomaly data are input into the network indiscriminately, and the model tends to overfit, which results in a better representation of backgrounds and anomalies. Anomalies and backgrounds are highly mixed together; therefore, it is difficult to effectively separate them and measure the difference between them. To mitigate these challenges, this study proposes a HAD algorithm based on score-guided cooperative autoencoders (SGCAE). Through the cooperative training of two autoencoders, suspected ‘anomalies’ are continuously removed during the training process to purify the training data. The autoencoder’s ability to discriminate anomalies from backgrounds is enhanced using a score-guided network in the hidden layer of the autoencoder. The score-guided network encourages the model to learn from obvious-background and obvious-abnormal data, gradually distinguish highly mixed backgrounds and anomalies, and output end-to-end anomaly scores. We apply the proposed algorithm to four real hyperspectral datasets. The experimental results verified the effectiveness of the proposed SGCAE algorithm and demonstrated that it outperforms other state-of-the-art methods.

Parent Child Interaction Training (PCIT) in Zurich, Switzerland - Experiences and Results of the first two years

IntroductionParent Child Interaction Training PCIT (Zisser &amp; Eyberg, 2010; Briegel, 2016) is an evidence-based treatment of oppositional defiant disorder in preschool children. However, it is implemented in few institutions in Europe. The advantage of PCIT is the involvement of both child and parents with direct coaching of the parents.ObjectivesWe will give an overview of 20 treatment courses we have conducted since the introduction of PCIT at the Zurich University Hospital for Child and Adolescent Psychiatry. First, a descriptive analysis of our sample will be conducted. The influence of sample characteristics and intensity of training on the reduction of behavioral problems will be analyzed.MethodsParents attend the training for at least 6 months with regular sessions. The transfer into everyday life is achieved by daily homework. We use the Eyberg Child Problem Behavior Inventory as pre-post measurements. The ECBI is filled out by the parents before each session and also enables a progress analysis.ResultsThree times more boys participated than girls. Problem behavior was significantly reduced after the play training phase. There was also a significant overall pre-post effect. The effect seemed to be independent of the parental problem score before training and of the number of play-training sessions.ConclusionsParents and children clearly benefit from the play training. For the following cooperation training, the problem load experienced by the parents seems to be more relevant than the intensity of the child’s problem behavior as assessed by them. This is to be examined in the future.DisclosureNo significant relationships.

TMS-GAN: A Twofold Multi-Scale Generative Adversarial Network for Single Image Dehazing

In recent years, learning-based single image dehazing networks have been comprehensively developed. However, performance improvement is limited due to domain shift between trained synthetic hazy images and untrained real-world hazy images. To alleviate this issue, this paper proposes a real-world dehazing targeted training scheme which nearly realizes paired real-world data training. As a result, a Twofold Multi-scale Generative Adversarial Network (TMS-GAN) consisting of a Haze-generation GAN (HgGAN) and a Haze-removal GAN (HrGAN) is designed. HgGAN attributes real haze properties to synthetic images and HrGAN removes haze from both synthetic and generated fake realistic data under supervision. Thus, the proposed method can better adapt to real-world image dehazing using this cooperative training scheme. Meanwhile, several structural advances of TMS-GAN also improve dehazing performance. Specifically, a haze residual map based on atmospheric scattering model is deduced in HgGAN for fake realistic data generation. The dual-branch generator in HrGAN draws attention to detail restoration by one branch along with another color-branch. A plug-and-play Multi-attention Progressive Fusion Module (MAPFM) is proposed and inserted in both HgGAN and HrGAN. MAPFM incorporates multi-attention mechanism to guide multi-scale feature fusion in a progressive manner, in which Adjacency-attention Block (AAB) can capture contributing features of each level and Self-attention Block (SAB) can establish non-local dependency of feature fusion. Experiments on mainstream benchmarks show that the proposed framework is superior especially on real-world hazy images among single image dehazing methods.

Matching Cross-Domain Data with Cooperative Training of Triplet Networks: A Case Study on Underwater Robotics

Matching Cross-Domain Data with Cooperative Training of Triplet Networks: A Case Study on Underwater Robotics

Practices of cooperative training in the Amhara Regional State TVET colleges and companies, Ethiopia

The purpose of this study was to examine the practice of CT, companies’ involvement in CT, TVET Colleges’ and companies’ trainers’ engagement in CT from trainers’ and trainees’ perspectives and to determine whether their perspectives are significantly different. The current study also examined the influence of the involvement or engagement level of company/enterprise, company supervisors and TVET College trainers in CT program implementation. For this purpose, the convergent parallel mixed-methods design was employed. A sample of 207 trainers and 211 trainees were involved in this study. Questionnaire and semi-structured interviews were employed to collect quantitative and qualitative data, respectively. Cronbach’s alpha value for the reliability of the instrument ranged between .74 and .94. The independent-sample t-test, Pearson’s correlation, and regression methods were used to analyze quantitative data. The thematic analysis method was used to analyze qualitative data using research questions as core themes. In this study, we found that the CT practice, company, and TVET trainers’ engagement in CT-related tasks were at a medium level, but the companies’ involvement in CT implementation was low. The TVET trainers and trainees had significantly different views regarding the level of CT practice, companies’ involvement, supervisors’ and trainers’ engagement in CT activities. In conclusion, the companies’ involvement level and TVET trainers’ engagement level showed large influences on CT practice. Based on these findings, we recommended the need for devising binding rules and regulations in a way that enforces accountability amongst all stakeholders of the CT program in the TVET system.

The technology of «Learning in collaboration» in teaching world literature in higher education

This article discusses the interactive educational technology "Training in cooperation (cooperative learning)", presented in the innovative, author's method of the MHAT. The main idea of this technology is to create conditions for active joint activity of students in various educational situations, aimed at the development of critical thinking. The learning process in small academic groups relates to technologies of the humanistic direction in modern pedagogy.

Громадсько-освітнє сподвижництво Іллі Кокорудзи (1867–1933)

The article highlights the educational, enlightening and scientific activity of Illia Kokorudz, a famous Ukrainian teacher, social and cultural leader, promoter and benefactor in Galicia at the end of the 19th and the first third of the 20th century. The paper analyses the stages of his formation as a scholar and educator, the development of his worldview principles and the civic position (gymnasium education, university studies, constant improvement of his professional and scientific level, active social and educational work). For a decade starting from 1896, I. Kokorudz associated himself with the Ukrainian Academic Gymnasium in Lviv. First, as a professor, and later as a director of the educational institution for 18 years (1909–1927) he revealed his talent as an outstanding teacher, educational organizer, mentor and educator of the Ukrainian youth. In this field, he supported and developed the best traditions of his predecessors, managed to lead the gymnasium through the difficult war and post-war years, gave it the weight of the important national educational institution. The author singles out the merits of I. Kokorudz to the Ukrainian Pedagogical Association “Native School”. Having taken a well-deserved rest in 1927 after 44 years of the intense teaching work he agreed to head this public organization. In 1927–1933 the activity of the “Native School” association under the leadership of I. Kokorudz reached the highest level. Despite the extremely unfavorable social and political situation for the Ukrainians, and due to the efforts of the Main Administration, the Ukrainian national education system was actively developing – private folk schools, gymnasiums, teacherʼs seminars, preschools. New educational initiatives started (introduction of cooperation training at schools, and relatively to it the organization of special courses for the Ukrainian teachers; creation of a scientifically based system of students’ professional orientation; application of new effective forms of national-patriotic education; expansion of publishing activities; establishment of cultural and educational ties with the Ukrainian emigration to Northern America, etc.). The article focuses on the promoting activity of I. Kokorudz, his creation of a separate foundation, thanks to which new educational institutions were established for the Ukrainian youth. Keywords: Illia Kokorudz, national education, Association “Native School”, Ukrainian Academic Gymnasium, educational and enlightening initiatives, promoting, “Foundation of Illia and Ivanna Kokorudz”.

Decentralized Federated Learning for Healthcare Networks: A Case Study on Tumor Segmentation

Smart healthcare relies on artificial intelligence (AI) functions for learning and analysis of patient data. Since large and diverse datasets for training of Machine Learning (ML) models can rarely be found in individual medical centers, classical centralized AI requires moving privacy-sensitive data from medical institutions to data centers that process the fused information. Training on data centers thus requires higher communication resource/energy demands while violating privacy. This is considered today as a significant bottleneck in pursuing scientific collaboration across trans-national clinical medical research centers. Recently, federated learning (FL) has emerged as a distributed AI approach that enables the cooperative training of ML models, without the need of sharing patient data. This paper dives into the analysis of different FL methods and proposes a real-time distributed networking framework based on the Message Queuing Telemetry Transport (MQTT) protocol. In particular, we design a number of solutions for ML over networks, based on FL tools relying on a parameter server (PS) and fully decentralized paradigms driven by consensus methods. The proposed approach is validated in the context of brain tumor segmentation, using a modified version of the popular U-NET model with representative clinical datasets obtained from the daily clinical workflow. The FL process is implemented on multiple physically separated machines located in different countries and communicating over the Internet. The real-time test-bed is used to obtain measurements of training accuracy vs. latency trade-offs, and to highlight key operational conditions that affect the performance in real deployments.

Automatic Tagging by Leveraging Visual and Annotated Features in Social Media

Automatic image annotation is one of the research fields helping to extract the meaning of images, which aims at the production of a set of semantic annotations for an image to help better present the concept. Over the past few decades, researchers have developed a number of approaches for automatic image annotation. Nevertheless, previous studies have not fully accounted for visual features and annotated features. Therefore, it is still possible to achieve a better annotation performance by combining visual and annotated information. In this study, our aim is to associate multiple semantic tags with a given image. In particular, we detect how to obtain the image annotation by utilizing visual and annotated information. To take advantage of visual information, we first designed a modified neural network method to acquire the features of the image content. In addition, to obtain the annotated features, we exploit an aggregated network embedding approach that consists of annotation embedding, social embedding, profile embedding, and semantic embedding. Finally, to produce an accurate image annotation, we integrate the two aforementioned methods, that is, combining the visual and annotated information, to build a unified cooperative training framework. The experimental results on three real-world datasets clarify that our presented method is superior to the current popular image annotation approaches.

Intelligent train control for cooperative train formation: A deep reinforcement learning approach

Considering the intelligent train control problem in long-term evolution for metro system, a new train-to-train communication-based train control system is proposed, where the cooperative train formation technology is introduced for realizing a more flexible train operation mode. To break the limitation of centralized train control, a pre-exploration-based two-stage deep Q-learning algorithm is adopted in the cooperative train formation, which is one of the first intelligent approaches for urban railway formation control. In addition, a comfort-considered algorithm is given, where optimization measures are taken for providing superior passenger experience. The simulation results illustrate that the optimized algorithm has a smoother jerk curve during the train control process, and the passenger comfort can be improved. Furthermore, the proposed algorithm can effectively accomplish the train control task in the multi-train tracking scenarios, and meet the control requirements of the cooperative formation system.

Dissemination of Sharia Cooperative Research, Solutions during a Pandemic

The COVID-19 pandemic has hurt various business sectors, including Indonesian Retired Migrant Entrepreneurs (PMI), in Yogyakarta. Many of the tourism, culinary, and small trade sectors are directly affected, as PMI's business base, causing new, increasingly complex problems such as running out of capital, difficulty in marketing, and weakening enthusiasm for the business. Sharia Cooperative Training as community service, providing new enlightenment and confidence for PMI members in redeveloping their business through Sharia-based cooperatives. With an adult or participatory training approach, participants gain further understanding and enthusiasm. Through Sharia cooperatives as an economic movement based on kinship and cooperation, cooperative members can strengthen and help each other. The training results show that PMI members agree to create a Sharia Cooperative that provides capital, joint marketing of member products, and increasing business capacity. Sharia cooperatives were chosen because they are more in line with beliefs and, in principle, are more suitable for the pandemic because of the applied profit-sharing system.

Policies supporting for agricultural cooperatives in Vietnam: An experience from agricultural cooperatives in the Red River Delta

Agricultural cooperatives have been established in Vietnam since the 1950s. During its development, agricultural cooperatives have made significant contributions to the growth of agricultural sector and to the improvement of farmers' income who are members of the cooperatives. Since Vietnam implemented the "Innovation-Doi moi" in 1986, the Government has continued to issue many policies to support for agricultural cooperatives. However, the impact of these policies on the development of almost all agricultural cooperatives has not been as expected. This paper aims to analyze the implementation of several policies supporting for agricultural cooperatives; to identify advantages and disadvantages of these policies; and to propose solutions for improving policies in the furture. In addition to secondary data from the Vietnam Cooperative Alliance, this paper uses primary data collected from 60 agricultural cooperatives in the Red River Delta to analyze the implementation of policies on cooperative staffs training, cooperative finance supporting, and cooperative land supporting. Bascially, the results show that the policy on training cooperative staff is quite well implemented, it helps to improve the capacity of cooperative managers in all surveyed cooperatives. In contrast, the finance supporting policy has many regulations that make it difficult for agricultural cooperatives to access capital, only nearly 30% of surveyed cooperatives get loans for production. Similarly, the land supporting policy also has unreasonable regulations which prevent agricultural cooperatives from scaling-up production because of the lack of farm-land. Consequently, about 60% of surveyed cooperatives are supported to rent farm-land for expanding agricultural production.

HPS-Net: Multi-Task Network for Medical Image Segmentation with Predictable Performance

In recent years, medical image segmentation (MIS) has made a huge breakthrough due to the success of deep learning. However, the existing MIS algorithms still suffer from two types of uncertainties: (1) the uncertainty of the plausible segmentation hypotheses and (2) the uncertainty of segmentation performance. These two types of uncertainties affect the effectiveness of the MIS algorithm and then affect the reliability of medical diagnosis. Many studies have been done on the former but ignore the latter. Therefore, we proposed the hierarchical predictable segmentation network (HPS-Net), which consists of a new network structure, a new loss function, and a cooperative training mode. According to our knowledge, HPS-Net is the first network in the MIS area that can generate both the diverse segmentation hypotheses to avoid the uncertainty of the plausible segmentation hypotheses and the measure predictions about these hypotheses to avoid the uncertainty of segmentation performance. Extensive experiments were conducted on the LIDC-IDRI dataset and the ISIC2018 dataset. The results show that HPS-Net has the highest Dice score compared with the benchmark methods, which means it has the best segmentation performance. The results also confirmed that the proposed HPS-Net can effectively predict TNR and TPR.

Distributed Beam Training for Intelligent Reflecting Surface Enabled Multi-Hop Routing

Intelligent reflecting surface (IRS) is an emerging technology to enhance the spectral and energy efficiency of wireless communications cost-effectively. This letter considers a new multi-IRS aided wireless network where a cascaded line-of-sight (LoS) link is established between the base station (BS) and a remote user by leveraging the multi-hop signal reflection of selected IRSs. As compared to the conventional single-/double-hop IRS system, multi-hop IRS system provides more pronounced path diversity and cooperative passive beamforming gains, especially in the environment with dense obstacles. However, a more challenging joint active/passive beamforming and multi-hop beam routing problem also arises for maximizing the end-to-end channel gain. Furthermore, the number of IRS-associated channel coefficients increases drastically with the number of IRS hops. To tackle the above issues, in this letter we propose a new and efficient beam training based solution by considering the use of practical codebook-based BS/IRS active/passive beamforming without the need of explicit channel estimation. Instead of exhaustively or sequentially searching over all combinations of active and passive beam patterns for each beam route, a distributed beam training scheme is proposed to reduce the complexity, by exploiting the (nearly) time-invariant BS-IRS and inter-IRS channels and the cooperative training among the BS and IRSs’ controllers. Simulation results show that our proposed design achieves the end-to-end channel gain close to that of the sequential beam search, but at a much lower training overhead and complexity.

Pedagogical conditions for forming the project competence of future teachers in the university environment

The relevance of the problem under study is associated with an important task of the higher education system the preparation of students future teachers for project activities in an educational institution. A modern teacher should have a wide range of knowledge, skills and abilities in the field of project activities. The purpose of the paper is a theoretical substantiation of pedagogical conditions that contribute to the formation of project competence of future teachers in the university environment. As designated pedagogical conditions are named and described: organization of training in cooperation; introduction of an additional course Learning to work on a project into the educational process; the use of the project method as a form of independent work of students in the study of various disciplines of the curriculum. The scientific novelty of the research lies in the fact that pedagogical conditions have been developed and substantiated, contributing to the effective formation of the project competence of future teachers in the conditions of a university. The theoretical significance of the study lies in the fact that its results enrich the theory and methodology of vocational education in the field of forming the project competence of future teachers; complement scientific ideas about the pedagogical conditions for the effective formation of project competence, as well as about the features of its functioning; scientific approaches are systematized. The practical significance of the study lies in the fact that the revealed pedagogical conditions lead to the effective formation of the project competence of future teachers in the conditions of a university. The developed additional course can be applied in the practice of teaching universities in order to improve the quality of professional training of future teachers. The experimental base of the study was the budgetary institution of higher education Surgut State University. The methods used in the research: generalization, analysis and synthesis of information, comparison, analysis of educational and project activities of students. The effectiveness of preparing students - future teachers - for project activities with students is an urgent task in the education system, which can be ensured through the implementation of certain pedagogical conditions. It is the pedagogical conditions that increase the effectiveness of educational and cognitive activities and contribute to the most fruitful work of the teacher and students.

Belt &amp; road organ donation capacity improvement cooperation training project (BROAOD)

Belt &amp; road organ donation capacity improvement cooperation training project (BROAOD)