Distance Learning and Character Building in Rural Area During the Covid-19 Pandemic

The COVID-19 pandemic has brought a number of obstacles and challenges in learning. The bigger obstacle is found for schools in rural areas. Starting from the problem of the availability of supporting facilities, parental support, to the problem of teacher readiness in carrying out learning and character education during the COVID-19 pandemic. Therefore this study aims to describe the teacher's strategy in carrying out distance learning and character education in rural area during the Covid-19 pandemic. This research was a qualitative research, involving 13 teachers. The data were collected through observation, interview, and questionnaire. The data analysis was carried out in by using a qualitative descriptive analysis. The data were analyzed through three stages, namely data reduction, data presentation, and data verification. The data were validated through source, method, and theory triangulations. The results of this study indicate that the teachers’ strategies in implementing distance learning include: Whatsapp-based online distance learning, offline distance learning, and mixed distance learning. There were 3 strategies to carry out character education during the Covid-19 pandemic, namely direct feedback through examples or narrative in the text. Examples given were also in the form of pictures; and through a checklist of daily and weekly activities. Various obstacles occured in distance learning and character education. Parents also felt stressed because of the increased burden during the pandemic. Therefore, collaboration between various components is needed to design the most effective learning strategies in rural areas.

Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterogeneous Wireless Sensor Network

One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.

Distributed Event-Triggered Approach for Multi-Agent Formation Based on Cooperative Localization with Mixed Measurements

This paper concentrates on multi-agent formation control problems under mixed measurements of distance and bearing. Towards this objective, a distributed event-triggered estimation-based control framework is developed such that only at necessary time instants, the event for estimation (namely, cooperative localization among a subgroup of agents) is triggered to recover relative position information by utilizing a mixed distance and bearing measurements from different agents. Firstly, it is shown by using the stiffness theory that a subgroup of agents are capable of recovering relative position information if a sufficient number of independent distance and range measurements are available. Secondly, a distributed event-triggered mechanism is presented for achieving an affine formation control, which can be implemented in an asynchronous manner and also ensures Zeno-free behavior. Simulation studies are provided to demonstrate the effective performance of the proposed approach.