Recent transmission of large volumes of data through mobile ad hoc networks (MANETs) has resulted in degraded Quality of Service (QoS) due to factors such as packet loss, delay, and packet drop in multipath routing. To address this issue, a traffic-aware Enhanced QoS-Aware Multipath Routing Protocol (EQMRP) has been proposed for real-time IoT applications in MANETs. EQMRP efficiently switches between multiple paths and monitors traffic conditions to maintain an optimal data transmission rate. The proposed method considers different delay sensitivity levels and link expiration time (LTE) to maintain QoS in each path. Through IoT application data analysis, EQMRP maintains QoS in each path more efficiently than conventional methods. The proposed method has been simulated and validated using MATLAB, and the performance analysis shows that EQMRP achieves a higher packet delivery ratio, lower delay, and reduced packet drop compared to conventional methods. In conclusion, the traffic-aware EQMRP protocol offers a significant improvement in QoS for real-time IoT applications in MANETs.
The purpose of this study was to devise a more efficient system for data storage and exchange in the Computer System and Network (CSN) Laboratory at Ibn Khaldun Bogor University. Open Media Vault (OMV) software and Raspberry Pi 3B+ were employed to establish a Network Attached Storage (NAS) system. The performance and file transfer speeds of the Raspberry Pi were evaluated in the context of this implementation. The implementation of the NAS system was intended to offer students of the CSN laboratory swifter and more efficient access to data, thereby reducing dependence on USB media. The findings of this study could hold substantial implications for enhancing the efficiency and effectiveness of data storage and exchange in educational environments.
Cervical cancer is the second most common cancer among women globally. Colposcopy plays a vital role in assessing cervical intraepithelial neoplasia (CIN) and screening for cervical cancer. However, existing colposcopy methods mainly rely on physician experience, leading to misdiagnosis and limited medical resources. This study proposes a cervical lesion recognition method based on ShuffleNetV2-CA. A dataset of 6,996 cervical images was created from Hebei University Affiliated Hospital, including normal, cervical cancer, low-grade squamous intraepithelial lesions (LSIL, CIN 1), high-grade squamous intraepithelial lesions (HSIL, CIN 2/CIN 3), and cervical tumor data. Images were preprocessed using data augmentation, and the dataset was divided into training and validation sets at a 9:1 ratio during the training phase. This study introduces a coordinate attention mechanism (CA) to the original ShuffleNetV2 model, enabling the model to focus on larger areas during the image feature extraction process. Experimental results show that compared to other classic networks, the ShuffleNetV2-CA network achieves higher recognition accuracy with smaller model parameters and computation, making it suitable for resource-limited embedded devices such as mobile terminals and offering high clinical applicability.
Physical impairments affect a significant proportion of the global populace, emphasizing the need for assistive technologies to increase the ability of these individuals to perform daily activities autonomously. This study discusses the development and implementation of a multimodal home control system, designed to afford physically challenged individuals greater control over their home environments. This system utilizes the Internet of Things (IoT) for its functionality. The system is primarily based on the utilization of the Amazon Alexa Echo Dot, which facilitates speech-based control, and a sequential clap recognition system, both made possible through an internet connection. These methods are further supplemented by an additional manual switching option, thereby ensuring a diverse range of control methods. The processing core of this system consists of an Arduino Uno and an ESP32 Devkit module. In conjunction with these, a sound detector is employed to discern and process a variety of clap patterns, which is set to function at a predefined threshold. The Amazon Alexa Echo Dot serves as the primary interface for voice commands and real-time information retrieval. Furthermore, an Android smartphone, equipped with the Alexa application, provides alternate interfaces for appliance control, through both soft buttons and voice commands. Based on an analysis of this system, it is suggested that it is not only viable but also effective. Key attributes of the system include rapid response times, aesthetic appeal, secure operation, low energy consumption, and most importantly, increased accessibility for physically disabled individuals.
Social media, particularly Twitter, has emerged as a vital platform for understanding public opinion on contemporary issues. This study investigates public attitudes towards UK rail strikes by analyzing Twitter data and provides a framework to assist policymakers in the RMT Union and the government in managing social media information. A dataset comprising tweets related to rail strikes from 25 June 2022 to 7 October 2022 was collected and multidimensional scaling and sentiment analysis techniques were employed to examine public opinions and sentiments. The analysis revealed that the predominant trends in tweets were dissatisfaction and negativity, with users expressing inconvenience caused by the rail strikes. Interestingly, the public also questioned the government's capabilities, with some suggesting that rail strikes were politically motivated events orchestrated by the government. Sentiment analysis results indicated that approximately 85% of tweets displayed negative sentiment towards the rail strikes. This research contributes to the understanding of public attitudes derived from tweet mining and offers valuable insights for academics and policymakers in interpreting public reactions to current events. Based on the findings, recommendations for the RMT Union are proposed through the lenses of stakeholder orientation theory and signaling theory. For instance, fostering public engagement can help reduce information asymmetry between the RMT Union and the public, enabling the union to better comprehend public sentiment towards rail strikes. The approach amalgamates these two theories, presenting a novel theoretical perspective for such investigations and extending their applicability, while also providing clear and in-depth recommendations for the RMT Union.
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