Models of Effective Writing Methods in Teacher Preparation

To shed some light on how writing methods are currently taught in a variety of programs across the United States and continue examining high-quality writing educators, the present chapter presents five distinct models for teacher preparation. These models are the result of meeting state-level standards; national standards through the International Literacy Association (ILA); and core competencies from research, theory, and practice. The course models represent the Pacific Northwest, Midwest, Southeast, and Northeast, showing diversity across the United States. Specifically in the present chapter, the researchers (1) present effective models of writing instruction; (2) provide examples of integrated approaches to research, theory, and practice for writing instruction; and (3) examine limitations and opportunities within each model. The goal of the present chapter is to outline these models in the hopes that other programs can modify and replicate the models that best fit their unique demographics, needs, and literacy standards.

Behavioral Models of Isolated Individuals and Entities

The article describes the possibilities of using simulation in various fields, whether in aviation, education or in many other sectors. Modeling and simulation in computer training to increase civil security are becoming particularly important for the development of today's society. Many simulator programs today allow the simulation of the influence of individual human factors and it is possible to apply this into model situations, which for safety reasons is difficult to test in real life. However, accurate and effective models of human behavior also indicate great potential in military and crisis management. At present, these methods can be used to simulate the behavior of isolated individuals and entities that have a major impact, for example, on the spread of various viral diseases, depending on several factors. These factors include population, geographical location, age group of the isolated and also social and cultural aspects, to which special space is devoted in this article. These factors can be used as inputs to the model for predicting the behavior of isolated groups of the population, on the basis of which it is possible to estimate in advance the spread of a possible epidemic, through various simulations.

Effective Models of Reintegration for De-occupied Territories

The article aims to reveal the essence of the reintegration process of the occupied and de-occupied territories, determining the current state and characterizing the conflict in the East of Ukraine. Its components and implementation tools are analyzed, and foreign models of reintegration of the occupied and de-occupied territories are presented and evaluated; there is also determined the degree of their conformity for Ukraine. In this research, there was made an attempt to find the most effective model for the reintegration of Donbas, which would not only contribute to the demilitarization and restoration of state control in these territories, but also prevent the emergence of separatist movements, stimulate the process of returning, and integration of citizens to the social, cultural, economic and political life of their country of origin. It was stressed that the Ukrainian model for restoring the territorial integrity and reintegration of Donbas should be based on compromise and key issues that have a positive international grounding for which the government has a public support, combined with a strong national, international, and military one. There is a greater chance for working out a mutual standpoint of Ukraine and its international partners which would allow the conflict with Russia to be solved. It is noted that the problem remains since there is no consensus among citizens on the optimal way of restoring the territorial integrity of Ukraine. That is why there is an urgent need to create a comprehensive strategy to restore the territorial integrity and reintegration of Donbas. It will have a necessary impact on all the parties of the conflict, and result in a publicly supported compromise. This can be achieved despite the current domestic and international peculiarities of the process; help can be expected from international experience in restoring peace as well as from the government’s approach to the process of reintegration and shaping up a unified state.

Data Augmentation for EEG-Based Emotion Recognition Using Generative Adversarial Networks

One of the greatest limitations in the field of EEG-based emotion recognition is the lack of training samples, which makes it difficult to establish effective models for emotion recognition. Inspired by the excellent achievements of generative models in image processing, we propose a data augmentation model named VAE-D2GAN for EEG-based emotion recognition using a generative adversarial network. EEG features representing different emotions are extracted as topological maps of differential entropy (DE) under five classical frequency bands. The proposed model is designed to learn the distributions of these features for real EEG signals and generate artificial samples for training. The variational auto-encoder (VAE) architecture can learn the spatial distribution of the actual data through a latent vector, and is introduced into the dual discriminator GAN to improve the diversity of the generated artificial samples. To evaluate the performance of this model, we conduct a systematic test on two public emotion EEG datasets, the SEED and the SEED-IV. The obtained recognition accuracy of the method using data augmentation shows as 92.5 and 82.3%, respectively, on the SEED and SEED-IV datasets, which is 1.5 and 3.5% higher than that of methods without using data augmentation. The experimental results show that the artificial samples generated by our model can effectively enhance the performance of the EEG-based emotion recognition.

The Supervised Learning Model for Analyzing the Sportsperson Training Efficiency

The driving concept of students’ sports training involves a unique activity that is often tightly correlated to students’ efficiency and varies with the momentum of sports training. Supervised learning is one of the smart methods with positive results in the fields of classification techniques. Due to the excessive currency unit associated with sports, sports forecasting is a growing area that must be well predicted. Therefore, in this paper, sports training based on the supervised learning (STSLM) model has been proposed to evaluate and predict student sports efficiency. STSLM models are based on various variables, such as traditional student ratings, performance, and efficiency. The emphasis is on the efficiency of students predicting sports outcomes. STSLM defines evaluation methods, information sources, effective models for testing students’ sports training, and unique challenges to forecast sports outcomes. The experimental results have been performed. The suggested STSLM model enhances the efficiency ratio of 96.3%, injury prevention level of 98.2%, fitness level of 95.5%, evaluation ratio of 98.8%, and training optimization ratio of 97.2% compared to other existing approaches.

DIGITALISASI TATA KELOLA KORBAN KEKERASAN TERHADAP PEREMPUAN BERBASIS STAKEHOLDERS DI PROVINSI JAWA TIMUR

The phenomenon of violence against women is a pandemic. There are many studies on violence but studies focusing on governance are rare. Governance involves various stakeholders with different roles so that they often face problems of coordination, integration, and synchronization. This problem also occurs in East Java. As a leading sector in handling victims of violence against women and children, the Office of Women's Empowerment and Child Protection and Population (DP3AK) of East Java Province faces challenges in the form of effective models in handling victims of violence. Meanwhile, cases of violence against women and children are very high. DP3AK requires a digital governance model in handling victims of violence more effectively on a stakeholder basis. This study offers a solution in the form of a digital platform that is able to connect victims with stakeholders.Keywords: digitalization, governance, violence against women and children, stakeholdersAbstrakFenomena kekerasan terhadap perempuan bersifat pandemik. Kajian terhadap kekerasan sangat banyak namun studi berfokus pada tata kelola jarang dilakukan. Tata kelola melibatkan berbagai stakeholders dengan peran berbeda sehingga sering menghadapi masalah koordinasi, integrasi dan sinkronisasi. Problematika tersebut juga terjadi di Jawa Timur. Sebagai leading sector penanganan korban kekerasan terhadap perempuan dan anak, Dinas Pemberdayaan Perempuan dan Perlindungan Anak dan Kependudukan (DP3AK) Provinsi Jawa Timur menghadapi tantangan berupa model efektif dalam penanganan korban kekerasan. Sementara itu, kasus kekerasan terhadap perempuan dan anak sangat tinggi. DP3AK membutuhkan model tata kelola digital dalam penanganan korban kekerasan yang lebih efektif dengan berbasis stakeholder. Kajian ini menawarkan solusi berupa platform digital yang mampu menghubungkan korban dengan para stakeholder.Kata kunci: digitalisasi, tata kelola, kekerasan perempuan dan anak, stakeholders

A review of model-based scenario analysis of poverty for informing sustainability

Ending poverty in all its forms everywhere is the first goal being targeted by the United Nations 2030 Agenda for Sustainable Development. Poverty eradication is a long-term process that faces the challenges of many uncertainties and complex interactions with other Sustainable Development Goals (SDGs). In order to better understand poverty and contribute to addressing poverty in a sustainable manner, this paper aims to conduct a systematic review of model-based analysis for poverty scenario in the context of SDGs. We first review 144 studies from the perspectives of bibliometric information (i.e., publication types, research topics for poverty, research objects, research scales and geographic locations) and models information for poverty scenario analysis (i.e., model types, purposes, states, temporal and spatial range, sectors considered, poverty and other SDGs indicators). Second, we discuss the pros and cons of different types of models and identify seven representative models. We also discuss the synergies and trade-offs between poverty and other SDGs. Finally, we identify four potential research gaps in model-based poverty scenario analysis and provide suggestions for future research. The review shows that poverty scenario analysis was carried out mainly from a single perspective, such as economic, ecological, and agricultural. Few studies used effective models to analyze poverty under an integrated interactions analysis of multiple sectors. Comprehensive multi-sector models are needed for global and regional poverty scenario analysis over the medium- or long-term to enhance the ability of analyzing the combined effects, synergies, and trade-offs between poverty and a variety of other SDGs.