No abstract

No abstract

The new era of technology has brought us to the point where it is convenient for people to share their opinions over an abundance of platforms. These platforms have a provision for the users to express themselves in multiple forms of representations, including text, images, videos, and audio. This, however, makes it difficult for users to obtain all the key information about a topic, making the task of automatic multi-modal summarization (MMS) essential. In this paper, we present a comprehensive survey of the existing research in the area of MMS, covering various modalities like text, image, audio, and video. Apart from highlighting the different evaluation metrics and datasets used for the MMS task, our work also discusses the current challenges and future directions in this field.

A novel grasp optimization algorithm for minimizing the net energy utilized by a five-fingered humanoid robotic hand with twenty degrees of freedom for securing a precise grasp is presented in this study. The algorithm utilizes a compliant contact model with a nonlinear spring and damper system to compute the performance measure, called ‘Grasp Energy’. The measure, subject to constraints, has been minimized to obtain locally optimal cartesian trajectories for securing a grasp. A case study is taken to compare the analytical (applying the optimization algorithm) and the simulated data in MSC.Adams $^{^{\circledR}}$ , to prove the efficacy of the proposed formulation.

No abstract