Digital transformation plays a big role in many industries, including construction. One of the obstacles to manage large-scale and complex construction projects is inefficient communication between involving personnel...
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Background: Juvenile Idiopathic Arthritis (JIA) and Familial Mediterranean Fever (FMF) are among the most common pediatric rheumatic diseases, often resulting in reduced physical fitness and activity levels in affecte...
Background: Juvenile Idiopathic Arthritis (JIA) and Familial Mediterranean Fever (FMF) are among the most common pediatric rheumatic diseases, often resulting in reduced physical fitness and activity levels in affected adolescents. Addressing these issues through personalized, technology-supported interventions has the potential to significantly improve outcomes. Objectives: The objectives of this study were to: 1 Develop the Pediatric Physical Activity Tracking Platform (Pedi@ctivity) including two core components—a mobile application and a web-based interface—enabled real-time tracking 2 Monitor physical activity and health parameters in healthy adolescents and those with pediatric rheumatic diseases using smartwatch data. 3 Assess the impact of AI-driven personalized exercise programs on physical fitness. 4 Compare fitness outcomes between healthy adolescents and those with chronic rheumatic diseases. Methods: The Pedi@ctivity platform was comprehensively developed as part of an extensive R&D project undertaken by our team and was recognized as a multidisciplinary initiative. The Pedi@ctivity comprises a mobile application and a web-based interface, developed to monitor and improve physical fitness in adolescents. The mobile application includes two main modules: the User Module, which collects data from smartwatches and delivers AI-driven personalized exercise plans, and the Supervisor Module, which tracks participants' progress and manages fitness metrics. It enables real-time health monitoring, smartwatch synchronization, and continuous feedback. The web platform serves as a comprehensive decision-support tool for physiotherapists. The study included 362 adolescents aged 12-18 years, with 304 healthy participants and 58 diagnosed with chronic rheumatic diseases, including JIA and FMF. Over a six-month period, physical activity metrics such as steps, distance, and heart rate were tracked with Pedi@ctivity supervisor app and smartwatches, including a three-month
The Opportunistic Spectrum Access (OSA) model has been developed for the secondary users (SUs) to exploit the stochastic dynamics of licensed channels for file transfer in an opportunistic manner. Common approaches to...
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Adversarial attacks have become one of the most serious security issues in widely used deep neural networks. Even though real-world datasets usually have large intra-variations or multiple modes, most adversarial defe...
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The Flying Robot Trial League (FRTL), from RoboCup Brazil, is a competition that stimulates the development of autonomous and intelligent flying robots for inspection and operation in pipeline lanes and oil installati...
The Flying Robot Trial League (FRTL), from RoboCup Brazil, is a competition that stimulates the development of autonomous and intelligent flying robots for inspection and operation in pipeline lanes and oil installations. In this context, this work presents the system developed by the BDP-UaiFly Team for the 2022 competition, using the off-the-shelf Parrot Bebop 2 to execute the Equipment Transport phase. This paper presents in detail the system platform and the navigation and sensing strategies implemented for autonomous navigation and image processing. In particular, the strategy adopted for cargo transportation based on servo-visual control is presented. Practical experiments validate the proposed solutions for the phases of the challenge.
Unmanned aerial vehicles (UAVs) have attracted a lot of research attention because of their high mobility and low cost in serving as temporary aerial base stations (BSs) and providing high data rates for next-generati...
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The occurrence of leaks in the transport of fluids in the oil and gas industry is a recurring problem. Compounds subject to reactions with the environment flowing under high pressure and temperature, through long pipe...
The occurrence of leaks in the transport of fluids in the oil and gas industry is a recurring problem. Compounds subject to reactions with the environment flowing under high pressure and temperature, through long pipes in places of difficult access exposed to the weather create several conditions for leaks. Distributed Acoustic Sensing (DAS) technology perfectly addresses those challenges as it provides long-range remote sensing through a dense network of sensors with high sensitivity and wide frequency response. In this work, we demonstrate the use of a DAS system simultaneously operating in acoustic and temperature gradient modes to detect a 1 mm diameter hole leak in a 1 inch-pipeline under water-air slug flow. The measurement data demonstrate the effects of the leakage in both acoustic and thermal perspectives. The results determine the system's ability to identify the integrity of the pipeline, as well as the exact moment the leak started, its location, characteristics in both time and frequency domain, and thermal effects as well. This research contributes to advance DAS technology as a sensing tool capable of detecting mm-sized leak hole in fluid transport pipelines.
We theoretically propose and experimentally demonstrate nonlocal metasurfaces rationally designed using symmetry-breaking principles to manipulate the optical wavefront with a geometric phase selective to custom ellip...
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ISBN:
(纸本)9781957171258
We theoretically propose and experimentally demonstrate nonlocal metasurfaces rationally designed using symmetry-breaking principles to manipulate the optical wavefront with a geometric phase selective to custom elliptical polarizations.
Our research introduces a novel method for safe hydrogen detection. We've developed an advanced nano-candle sensor, combining Pd with nano-candles, enabling accurate detection of low-concentration hydrogen (<3%...
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ISBN:
(数字)9798350372076
ISBN:
(纸本)9798350372083
Our research introduces a novel method for safe hydrogen detection. We've developed an advanced nano-candle sensor, combining Pd with nano-candles, enabling accurate detection of low-concentration hydrogen (<3%) and intuitive leakage identification, demonstrating its potential.
Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022...
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ISBN:
(纸本)9798350345728
Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned.
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