1,720,960 research outputs found
Sistem Deteksi Orang Jatuh Dengan Menggunakan Sensor Kamera Kinect Dengan Metode AdaBoost
Full text linkFall cases of elderly people aged 65 or above put their health at risk because it could lead to hip bone fracture, concussion, even death. Immediate help is needed if fall happened which is why an automatic and unobtrusive fall detection system is needed. There are three approaches in fall detection system; wearable, ambience, and vision-based. Wearable approach has the drawback of its obtrusive nature while ambience approach is prone to high false positive value. Vision-based approach is chosen because its unobtrusive nature and low false positive value. This study uses Kinect camera because of its ability on extracting skeletal data. The methods that are used in the fall detection system are AdaBoost method and joint velocity thresholding method. Thresholding method is used as a comparison to AdaBoost method. Both methods use skeletal data from the subject recorded by the Kinect camera. AdaBoost method compares the skeletal data with model that was made before while thresholding method compares the joint velocity value with the threshold value. System test is done using training data, test data, and real-time data. The average accuracy obtained from the system test with AdaBoost method is 91.75% and with thresholding method is 68.22%
Peningkatan Akurasi Deteksi Jatuh Menggunakan Sensor Akselerometer dan Giroskop pada Smartphone
Full text linkThe aging population is a global concern, partly because as the body ages, physical conditions weaken, increasing the likelihood of falls. Falls are particularly dangerous for the elderly as they can lead to serious problems and even death. Detecting falls quickly and accurately is crucial to implement preventive measures and timely intervention when a fall occurs.This research focuses on designing a human physical activity classification system, primarily used for fall detection. Seven model architectures are proposed using a novel approach involving the variant of recurrent neural network (RNN) methods, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Simple Recurrent Neural Network (SimpleRNN). Additionally, variations with Convolutional Neural Network (CNN) are explored, specifically 1D Convolutional Neural Network (1D CNN).Validation results of the classification show that the experimented methods for the classes of sitting, standing, and falling achieved perfect scores, while the falling class showed varying scores for each designed model architecture. For the overall classes, the lowest performance is observed in the combination of 1D CNN and SimpleRNN architecture with an accuracy of 95.6%, whereas the highest performance is attributed to the SimpleRNN architecture and the combined CNN and GRU architecture with an accuracy reaching 99.0%
Pengembangan Kemampuan Model Autonomous Car Terhadap Aspek Keselamatan Berkendara Saat Kondisi Ekstrem Menggunakan Carla Simulator
Full text linkThe advancement of automation technology, particularly in autonomous vehicles, has rapidly progressed with the integration of machine learning. However, these systems still face challenges in environments with dense traffic and dynamic conditions, making safety a primary concern. Traffic accident data indicate that the implementation of autonomous vehicles remains far from optimal, especially under extreme conditions such as severe weather and unpredictable traffic congestion. This study aims to develop an autonomous vehicle system model that can operate not only under normal conditions but also adapt to extreme situations. The model is developed using the CARLA Simulator, which enables testing in various realistic environmental scenarios. Simulations involving severe weather and high traffic density are conducted to evaluate the model’s resilience and responsiveness across different scenarios. The results show that the developed model enhances driving safety under extreme conditions with high effectiveness in obstacle avoidance and dynamic decision-making. Thus, this approach is expected to contribute to the development of more adaptive and safer autonomous vehicles for real-world application
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
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