1,720,962 research outputs found
Hybrid Deep Learning Models Using LSTM with Random Forest for Radio Frequency-Based Human Activity Recognition in Line-of-Sight and Non-Line-of-Sight Environments
Full text linkHuman Activity Recognition (HAR) has become an important field of study because of its wide range of applications in healthcare, security, and smart living systems. Radio Frequency (RF)-based HAR offers a non-invasive and privacy-preserving alternative to traditional vision-based systems. This study proposes a hybrid deep learning model combining Long Short-Term Memory (LSTM) networks with Random Forest classifiers for RF-based HAR, aiming to improve recognition accuracy across diverse environments. The model was evaluated using Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) features under Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions. Synthetic Minority Over-sampling Technique (SMOTE) was integrated to balance the dataset, and K-fold Cross-Validation was employed to assess robustness. The dataset included data from 8 subjects performing 10 different activities. The model achieved high classification accuracy, with 99.40% in Environment 1 (LOS), 97.58% in Environment 2 (LOS), and 98.30% in Environment 3 (NLOS), demonstrating the models adaptability and effectiveness. The results highlight the potential of the hybrid LSTM with Random Forest approach for scalable and reliable RF-based HAR systems that can be integrated into real-world Internet of Things (IoT) applications
Pemeriksaan Pola Kalimat Otomatis Pada Sebuah Karangan Menggunakan POS Tagging Bahasa Indonesia Dan LALR Parser
No full text Dalam era perkembangan teknologi yang pesat ini, berbahasa mempunyai peran penting dalam kehidupan sehari-hari seperti untuk berkomunikasi dengan sesama secara lisan maupun tulisan. Komunikasi akan berlangsung dengan baik jika bahasa yang digunakan dapat dipahami sehingga pesan dapat tersampaikan. Dalam komunikasi tulisan, keterampilan menulis diperlukan untuk menghasilkan tulisan yang dapat menyampaikan pesan dengan baik. Salah satu bentuk hasil dari keterampilan menulis adalah sebuah karangan. Penulisan karangan harus memperhatikan kaidah pemakaian bahasa yaitu fonologi, morfologi, dan sintaksis. Pentingnya kaidah tersebut khususnya sintaksis atau struktur dan pola kalimat dapat mengungkapkan ide yang dapat tersampaikan dengan baik dan mudah untuk dipahami melalui karangan. Penelitian ini bertujuan untuk membantu dalam memeriksa pola kalimat pada sebuah karangan secara otomatis. Dalam pemeriksaan ini diimplementasikan dengan bahasa pemrograman python pada jupyter notebook menggunakan library nltk untuk proses preprocessing, library flair nlp untuk proses part of speech tagging bahasa Indonesia dan penggunaan tabel lalr parser untuk pemeriksaan pola kalimat. Pola kalimat yang digunakan pada pemeriksaan ini adalah S-P, S-P-O, S-P-K, S-P-O-K, S-P-Pel-K, dan S-P-O-Pel-K. Hasil dari penelitian ini adalah berupa pemeriksaan pola kalimat otomatis pada sebuah karangan sederhana dengan batasan menggunakan kalimat tunggal dan kalimat aktif. Pemeriksaan ini dapat memeriksa 14 dari 16 kalimat pada karangan dengan nilai keberhasilan sebesar 87,5% dan nilai keakuratan sebesar 62,5%. Faktor yang mempengaruhi hasil tersebut adalah variasi komponen pola kalimat yang masih terbatas dan penggunaan flair nlp dalam proses pos tagging yang dapat menghasilkan label jenis yang berbeda pada suatu kata yang dipengaruhi oleh letak posisi kata tersebut pada sebuah kalimat
Comparative Analysis of Hybrid Intelligent Algorithms for Microsleep Detection and Prevention
Full text linkMicrosleep is a critical factor contributing to traffic accidents, posing significant risks to road safety. Research by the AAA Foundation for Traffic Safety found that 328,000 sleep-related driving accidents happen annually in the United States, underscoring the widespread and dangerous nature of drowsy driving. These incidents often occur without warning, making them especially hazardous and difficult to prevent through conventional means alone. This research aims to improve the accuracy of microsleep detection by developing a hybrid intelligent algorithms. It compares three intelligent algorithms: Fuzzy Logic (FL), representing scheme A; Fuzzy Logic combined with Artificial Neural Networks (FL-ANN), representing scheme B; and a combination of Fuzzy Logic, ANN, and Decision Trees (FL-ANN-DT), representing scheme C. These methods were evaluated using performance metrics such as MSE, MAE, RMSE, R², and response time. The results indicate that Scheme C (FL-ANN-DT) significantly outperforms the other approaches, achieving an MSE of 5.3617e-32, MAE of 4.3823e-17, R² of 1.0, and an RMSE close to zero, demonstrating near-perfect accuracy. Compared to previous models, this hybrid approach enhances prediction precision while maintaining real-time feasibility. The findings highlight the potential of FL-ANN-DT as an advanced microsleep detection system, contributing to improved road safety and real-time monitoring applications. This system can serve as a proactive safety layer in driver assistance technologies, reducing the risk of fatigue-related accidents and potentially saving lives
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
