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This database is from a family of studies about the user-perceived quality and functional suitability of DEMO's Process and Fact Models. It includes three different samples. Sample 1 consists of the results from a group of professionals within the urban appraisal area. Sample 2 consists of the results from a group of health professionals. Finally, Sample 3 includes the results from a group of students trained in the DEMO standard.
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Recently, contactless hand biometrics authentication has become increasingly popular among biometric researchers. These systems offer several advantages over traditional hand identification systems, including ease of capture and affordability, as they do not require the user’s hand to make direct contact with the sensor.
The Mobile Hand Biometrics (MHB) dataset includes images of fingerprint, palmprint, and hand geometry. These images are captured with a mobile camera without any physical contact, with no lighting conditions, and in free positions.
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The SH_traffic dataset presents comprehensive traffic speed data for the Shanghai urban area, collected over a period from January 25, 2022, to February 9, 2022. The dataset encompasses a square area of 900 km² and consists of 4,500 graph nodes representing road intersections across the city. The dataset includes traffic speed information recorded at regular intervals, along with related data such as geographical entity attributes and relationships between entities within the road network.
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Bangladesh's aquaculture industry provides employment and food security. However, water quality management, disease control, and environmental monitoring continue to hinder aquaculture productivity and sustainability. This research uses IoT devices to create a comprehensive aqua fisheries dataset to solve these issues.The project uses IoT sensors and data collection methods to monitor water temperature, pH, dissolved oxygen, and turbidity in Bangladeshi aquaculture ponds.
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The sudden shift from physical office location to a fully remote or hybrid work model accelerated by the COVID-19 pandemic is a phenomenon that changed how organizations traditionally operated and thereby introduced new vulnerabilities and consequently changed the cyber threat landscape. This has led organizations around the globe to seek new approaches to protect their enterprise network. One such approach is the adoption of the Zero Trust security approach due to its many advantages over the traditional/perimeter security approach.
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The dataset involves two sets of participants: a group of twenty skilled drivers aged between 40 and 68, each having a minimum of ten years of driving experience (class 1), and another group consisting of ten novice drivers aged between 18 and 46, who were currently undergoing driving lessons at a driving school (class 2).
The data was recorded using JINS MEME ES_R smart glasses by JINS, Inc. (Tokyo, Japan).
Each file consists of a signals from one sigle ride.
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Achieving robust path tracking is essential for efficiently operating autonomous driving systems, particularly in unpredictable environments. This paper introduces a novel path-tracking control methodology utilizing a variable second-order Sliding Mode Control (SMC) approach. The proposed control strategy addresses the challenges posed by uncertainties and disturbances by reconfiguring and expanding the state-space matrix of a kinematic bicycle model guaranteeing Lyapunov stability and convergence of the system.
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Publicly available dataset weibo_senti_100k, which consists of Weibo comments, verify the validity of the model. We have assigned the label of 0 to negative semantics, 1 to neutral statements, and 2 to positive semantics in the dataset,comments data is divided into a training set, a test set and a validation set, distributed in a ratio of 3:1:1 to facilitate the training and evaluation of our machine learning model.
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