Bayesian multinomial logistic-normal (MLN) models are popular for the analysis of sequence count data (e.g., microbiome or gene expression data) due to their ability to model multivariate count data with complex covar...
详细信息
Bayesian multinomial logistic-normal (MLN) models are popular for the analysis of sequence count data (e.g., microbiome or gene expression data) due to their ability to model multivariate count data with complex covariance structure. However, existing implementations of MLN models are limited to small datasets due to the non-conjugacy of the multinomial and logistic-normal distributions. Motivated by the need to develop efficient inference for Bayesian MLN models, we develop two key ideas. First, we develop the class of Marginally Latent Matrix-T Process (Marginally LTP) models. We demonstrate that many popular MLN models, including those with latent linear, non-linear, and dynamic linear structure are special cases of this class. Second, we develop an efficient inference scheme for Marginally LTP models with specific accelerations for the MLN subclass. Through application to MLN models, we demonstrate that our inference scheme are both highly accurate and often 4-5 orders of magnitude faster than MCMC.
Semi-supervised learning algorithms make use of both labelled training data and unlabelled data. However, the visual domain gap between these sets poses a challenge which prevents deep learning models from obtaining t...
详细信息
Trusting others and reciprocating the received trust with trustworthy actions are fundaments of economic and social interactions. The trust game (TG) is widely used for studying trust and trustworthiness and entails a...
详细信息
In recent years, research in human counting from CCTV (Closed Circuit Television) images have found an increasing demand to be deployed in real-world applications. The applications have been implemented in various set...
详细信息
In recent years, research in human counting from CCTV (Closed Circuit Television) images have found an increasing demand to be deployed in real-world applications. The applications have been implemented in various settings, both indoor and outdoor. In the case of indoor setting, we found a type of room setting that conveys a problem to human counting model if we need to count only humans inside a room. With this respect, we present RHC (Room Human Counting) dataset, which images are captured in the aforementioned setting. The dataset can be used to develop a robust model that can differentiate between humans inside and outside a room. The dataset is publicly available at https://***/datasets/vt5c8h6kmh/1.
Score-based generative models can effectively learn the distribution of data by estimating the gradient of the distribution. Due to the multi-step denoising characteristic, researchers have recently considered combini...
详细信息
Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the materials involved. To advance this field, this paper models computa...
详细信息
ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the materials involved. To advance this field, this paper models computationally three types of soft elastomeric actuators designed to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. The analysis focuses on the interaction between a phantom representing transversely isotropic muscle and homogeneous skin, with a soft robotic device comprised of a hyperelastic actuator and a rigid support. Results from deformation, stress-strain and surface pressure analysis demonstrate efficient actuation, suggesting deep and focused stimulation on the muscle, while actuators exhibit reliable safety factors and load distribution, implying longer operational life. This lightweight and compact soft robotic device is suitable for integration into a wearable suit for targeted muscle groups stimulation in the lower limbs. Furthermore, this computational approach represents a significant advance in the biomechanical study of soft robot-human tissues interaction, with potential for generalization in similar biomedical device applications. Keywords—Soft Robotics, Mechanotherapy, Transversely Isotropic Muscle, Human-Robot interaction.
Treatments of disuse-induced muscle atrophy entail unmet clinical needs due to the lack of medical devices capable of mimicking physicians manual therapies. Therefore, in this paper we develop and model a wearable sof...
详细信息
ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
Treatments of disuse-induced muscle atrophy entail unmet clinical needs due to the lack of medical devices capable of mimicking physicians manual therapies. Therefore, in this paper we develop and model a wearable soft pneumatic elastomeric actuator to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. Static and dynamic characterization of the prototype demonstrate a 2.5 mm active deformation at 100 kPa with 600 mm
3
/s and a 5 Hz bandwidth. We estimate the transfer function of the experimentally acquired pressure, flow and deformation signals, processed by a Gaussian kernel-based approach. Our mathematical model accurately describes the actuator behavior and enables to extract its mechanical parameters. Then, through computational simulations, we illustrate its efficacy in emulating multiple complex bio-inspired movements. Our proposed methodology aims to improve the control efficiency in wearable soft robotics for muscle atrophy treatment.
The rapid proliferation of Artificial Intelligence (AI) applications in various domains of our lives has prompted a need for a shift towards a human-centered and trustworthy approach to AI. In this study we employ the...
详细信息
The rapid proliferation of Artificial Intelligence (AI) applications in various domains of our lives has prompted a need for a shift towards a human-centered and trustworthy approach to AI. In this study we employ the Assessment List for Trustworthy Artificial Intelligence (ALTAI) checklist to evaluate the trustworthiness of Artificial Intelligence for Student Performance Prediction (AI4SPP), an AI-powered system designed to detect students at risk of school failure. We strongly support the ethical and legal development of AI and propose an implementation design where the user can choose to have access to each level of a three-tier outcome bundle: the AI prediction alone, the prediction along with its confidence level, and, lastly, local explanations for each grade prediction together with the previous two information. AI4SPP aims to raise awareness among educators and students regarding the factors contributing to low school performance, thereby facilitating the implementation of interventions not only to help students, but also to address biases within the school community. However, we also emphasize the ethical and legal concerns that could arise from a misuse of the AI4SPP tool. First of all, the collection and analysis of data, which is essential for the development of AI models, may lead to breaches of privacy, thus causing particularly adverse consequences in the case of vulnerable individuals. Furthermore, the system’s predictions may be influenced by unacceptable discrimination based on gender, ethnicity, or socio-economic background, leading to unfair actions. The ALTAI checklist serves as a valuable self-assessment tool during the design phase of AI systems, by means of which commonly overlooked weaknesses can be highlighted and addressed. We argue that adopting a critical approach to AI development is essential for societal progress, believing that it can evolve and accelerate over time without impeding openness to new technologies. By aligning with ethi
A novel elastic time distance for sparse multivariate functional data is proposed and used to develop a robust distance-based two-layer partition clustering method. With this proposed distance, the new approach not on...
详细信息
Access to healthcare facilities is crucial in the present day. Healthcare facilities must be proportional to the population in a given area. Therefore, it is important to increase the number of healthcare facilities i...
详细信息
暂无评论