The purpose of this study is increasing the usability of the user interfaces (UI) by ensuring their compliance with Gestalt principles. The developed method of evaluating the compliance of the UI with Gestalt principl...
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The problem of forecasting long sequences is important in many different domains. Proper selection of the hyperparameters when a machine learning approach is applied could make the difference between adequate and inad...
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ISBN:
(数字)9781665497770
ISBN:
(纸本)9781665497787
The problem of forecasting long sequences is important in many different domains. Proper selection of the hyperparameters when a machine learning approach is applied could make the difference between adequate and inadequate model. Several algorithms for automatic hyperparameters tuning were evaluated and compared with baseline selection. As a result, recommendations have been made. Some of the intuitive assumptions for the baseline model proved to be wrong.
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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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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As our skin is exposed to ultraviolet rays or dangerous chemicals, aberrant growth of skin cells happens which brings up undesirable conditions such as premature skin aging, transposition in skin texture, and the wors...
As our skin is exposed to ultraviolet rays or dangerous chemicals, aberrant growth of skin cells happens which brings up undesirable conditions such as premature skin aging, transposition in skin texture, and the worst-case scenario skin cancer. In the struggle to combat deadly skin cancer, machine learning can be a useful weapon to help dermatologists make better and clearer decisions while diagnosing patients. Despite promising results with numerous machine learning techniques, this field faces data inadequacy, more so the universally available datasets are subjected to data imbalances. In order to tackle the significant class imbalance present in datasets like the HAM10000 skin cancer dataset, this research introduces a class-weighted reward mechanism within the Deep Q-Learning framework that dynamically allocates higher positive rewards for the accurate classification of rare classes and imposes more substantial penalties for the incorrect classification of common classes. This strategy encourages the DQN agent to focus on underrepresented categories during the training process, thereby reducing bias towards majority classes. Quantitative assessment metrics such as Accuracy, Precision, F1-score, Specificity, and Sensitivity were used to evaluate the model. The results showed an accuracy of 97.97 %, sensitivity of 97.74 %, precision of 97.81 %, F1-Score of 97.70 %, and specificity of 97.83 % on a non-augmented dataset of HAM10000. Finally, the model performance was compared to that of already existing research work, and it had an upper hand with considerable differences over the existing ones.
Since the last few decades, the prey-predator system delivers attractive mathematical models to analyse the dynamics of prey-predator interaction. Due to the lack of precise information about the natural parameters, a...
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We consider a dynamic continuous gas production at a deposit. We set and solve the optimization control problem for maximum profit, taking into account the discount factor. The problem posed relates to some optimal co...
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A polydyne cam and knife follower system are studied. The effect of cam angular velocity and follower guides internal dimensions on Lyapunov parameter is considered. Wolf algorithm is used to quantify largest Lyapunov...
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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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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.
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