The details of future failures of systems that are serially produced are important for the remanufacturing departments to frame an optimal strategy for the post series supply. The existing one-dimensional and two-dime...
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Remanufacturing, a popular term in the automotive industry, helps to reduce the need for raw materials, increase profitability, is an effective solution to the challenges of postal items and also benefits the environm...
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To remanufacture automobile systems, it is important to understand the future failure rate of the serially produced systems. In addition, remanufacturing departments need the information about the number of cores to r...
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Nowadays the information of future rates of systems produced in series appears to be crucial to the production plan, especially for remanufacturing departments. Several questions need to be answered: the number of cor...
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Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pai...
Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pain may manifest suddenly in some cases, it often develops gradually and persists for weeks, and in untreated cases, it can linger for years. Hence, the utilization of assistive devices such as wearable posture-monitoring vests can offer valuable assistance and guidance to users. This research paper is dedicated to the development of a system for detecting, diagnosing, and correcting poor posture, specifically leaning posture. The vest is designed to provide users with visual, auditory, and tactile cues to help them address this issue, thereby reducing the risk associated with leaning. Additionally, an integrated electrical box has been designed to consolidate all components directly onto the main board in a secure enclosure. This box also displays the daily count of instances where the user has leaned. This system is characterized by its electrical safety, portability, compactness, comfort, and affordability. A comprehensive analysis of the system's performance has been conducted with a meticulous evaluation of accuracy. Each component of the system has undergone successful testing, and the system as a whole is currently in the testing phase. The results of these tests have indicated a lack of faulty errors and have demonstrated outstanding accuracy and detection rates. Over 100 individuals of varying ages, genders, and BMI categories were involved in testing, with each person wearing the device for an average of six hours. The accuracy rate achieved was 98.85%, with an average of 54.35 instances of poor posture detected per participant.
This research focuses on hyperparameter optimization for LSTM to forecast SARS-CoV-2 infection cases in the Russian Federation, aiming to determine the best combination of parameters for a well-fitting model. Using L...
This research focuses on hyperparameter optimization for LSTM to forecast SARS-CoV-2 infection cases in the Russian Federation, aiming to determine the best combination of parameters for a well-fitting model. Using LSTM’s capability to analyze relationships within time series data, a bidirectional LSTM-based method is introduced for predicting daily infection cases. The study evaluates nearly 10 unique forecasting models and conducts a comprehensive analysis and comparison of their results. The Bidirectional LSTM model proves to be a reliable approach for forecasting daily SARS-CoV-2 infection cases in Russia, displaying the highest prediction accuracy among the tested models.
In recent decades, global climate change has become one of the most critical environmental issues, leading to increased environmental and social concerns about the sustainability of logistics networks. This study prop...
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time series Due to better algorithms, more accessible data, and higher computing power over the past ten years, forecasting has become more popular. It is used in a variety of industries, including as financial time s...
time series Due to better algorithms, more accessible data, and higher computing power over the past ten years, forecasting has become more popular. It is used in a variety of industries, including as financial time series, weather forecasting, and medical diagnostics. In this study, we provide a model of the mechanism governing attention, which enables attended input to be provided to the model in place of actual input. In order for the model to produce more precise predictions, it seeks to demonstrate a fresh perspective on the data. The experiments were conducted with the (encoder-decoder) LSTM model as well to demonstrate the usefulness and superiority of the suggested strategy. The obtained results demonstrate that, when compared to the (encoder-decoder) LSTM base model, the proposed approach could reduce the mean square error (RMSE=9819.05), relative root mean square error (RRMSE=99.09), and coefficient of determination (R Square=0.96). The obtained results support the suggested approach’s efficacy, superiority, and importance in predicting SARS-CoV-2 infection cases.
An article presents an approach for cyberattack detection based on genetic algorithms is presented. The method allows detecting both known and unknown cyberattacks. The method has the heuristic nature and is based on ...
ISBN:
(数字)9781728199573
ISBN:
(纸本)9781728199580
An article presents an approach for cyberattack detection based on genetic algorithms is presented. The method allows detecting both known and unknown cyberattacks. The method has the heuristic nature and is based on the collected data about the cyberattacks. It makes it possible to give an answer about the cyberattacks' existence in the computer networks and its hosts. Developed attack detection approach consists of training and detection stages. The mechanism of attack detection system is based on the cyberattacks' features gathering from network or hosts, extracting the subset of acquired set and generation the attacks' detection rules. Genetic algorithms are used for the minimization of the feature set, which allows effective using of the system resources for attacks detection. In order to detect the attacks, the proposed technique involves the rule generation. The attacks' features are described by the set of sub-rules. It is suggested to use the feature with the smallest domain for generating the minimal set for rules. It is possible to select the optimal feature after all selected features which were discovered while applying the genetic algorithm. The sub-rule set is used with the aim to reduce false positive rate.
In this paper, we introduce an approach via regularization and Homotopy way for resolving the inverse Cauchy problem of the Laplace of system partial differential equation which appears in the wave propagation for com...
In this paper, we introduce an approach via regularization and Homotopy way for resolving the inverse Cauchy problem of the Laplace of system partial differential equation which appears in the wave propagation for communication networks. We considered the method of Homotopy Perturbation Metheod (HPM) for solving the integral equations of the first kind named Fredholm. In order to formulate the Laplace equation into the first-kind integral equation (Fredholm) the Fourier series used. Then the discretization method used to reduce the integral equation into a linear operator equation for the first kind. It is clear that this kind of problem is callsified as an ill-posed and the direct way to solve it unacceptably. Tikhonov’s regularization method with Homotopy Perturbation algorithm used for obtaing the approximation solution for the Laplace differential equation. Finally, the numerical example is proposed.
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