The Role Of Technical Know-How In Determining The Legal Nature Of A Franchise Contract

In view of the importance of a franchise contract in disseminating knowledge, and improvement, this study came to shed light on technical knowledge and its impact on determining the legal nature of a franchise contract. It also illuminated the possibility of the existence of a weak idea or a compliance problem in this type of contract. Strengthening of concession contracts was recommended, particularly relating to the industrial sector, which would inevitably lead to development and prosperity

The Intelligent Agent and Dubai Legislature Situation from Legal Action Made through Intelligent Agent

This research has come to spotlight on vital role for intelligent agent and services provided, And to found the trace out of it actions on users. Dubai e-commerce act considers i-agent as communication media, such as Telephone, Fax. Therefore they don’t give it legal personality. In addition to legislature didn’t regulate programmer liability in provisions of law

Meta Adaptation using Importance Weighted Demonstrations

Imitation learning has gained immense popularity because of its high sample-efficiency. However, in real-world scenarios, where the trajectory distribution of most of the tasks dynamically shifts, model fitting on continuously aggregated data alone would be futile. In some cases, the distribution shifts, so much, that it is difficult for an agent to infer the new task. We propose a novel algorithm to generalize on any related task by leveraging prior knowledge on a set of specific tasks, which involves assigning importance weights to each past demonstration. We show experiments where the robot is trained from a diversity of environmental tasks and is also able to adapt to an unseen environment, using few-shot learning. We also developed a prototype robot system to test our approach on the task of visual navigation, and experimental results obtained were able to confirm these suppositions

The Effects of Selling Property at Auction by Ordinary Creditor Barrier on Mortgagee Creditor Rights Analytical Study in Jordan Execution Law

The study titled The Effects of Selling Property at Auction by Ordinary Creditor Barrier on Mortgagee Creditor Rights has toke place under the provisions governing the sale of ordinary creditor barrier contained in Execution law. The study has concluded that the Jordanian legislature did not take into account in organizing the sale of real estate by auction by the ordinary creditor barrier guarantees that in law of an immovable security for debt, including minimum bidding began. So does the creditor, if the mortgagee creditor and debtor collusion only recourse to annul the sale, leading to wasted time, effort and money.  The legislature did not indicate a situation which action of contract or by auction and the impact on the debt secured by the mortgage, which affects the result on the right of the mortgagee creditor intervention or further implementation. The study concluded that a set of recommendations that wished the Jordanian legislature to be adopted

Detecting events and key actors in multi-person videos

Multi-person event recognition is a challenging task, often with many people active in the scene but only a small subset contributing to an actual event. In this paper, we propose a model which learns to detect events in such videos while automatically "attending" to the people responsible for the event. Our model does not use explicit annotations regarding who or where those people are during training and testing. In particular, we track people in videos and use a recurrent neural network (RNN) to represent the track features. We learn time-varying attention weights to combine these features at each time-instant. The attended features are then processed using another RNN for event detection/classification. Since most video datasets with multiple people are restricted to a small number of videos, we also collected a new basketball dataset comprising 257 basketball games with 14K event annotations corresponding to 11 event classes. Our model outperforms state-of-the-art methods for both event classification and detection on this new dataset. Additionally, we show that the attention mechanism is able to consistently localize the relevant players.Comment: Accepted for publication in CVPR'1