Properties of composite of closure operations and choice functions

The equivalence of the family of FDs is among many hottest topics that get a lot of attention and consideration currently. There are many equivalent descriptions of the family of FDs. The closure operation and choice function are two of them. Major results of this paper are the properties of the composite function of the choice functions and closure operations. The first parts of this paper address the theories of the composite function of two choice functions and the sufficient and necessary condition of a composite function of two choice functions to be a choice function. Rest of the paper addresses the sufficient and necessary condition of a composite function of more than two choice functions to be a choice function and a composite function of more than two closure operations to be a closure operation

Learning to Generate Better Than Your LLM

Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning Large Language Models (LLMs) for text generation. In particular, recent LLMs such as ChatGPT and GPT-4 can engage in fluent conversations with users after finetuning with RL. Capitalizing on key properties of text generation, we seek to investigate RL algorithms beyond general purpose algorithms like Proximal Policy Optimization (PPO). In particular, we extend RL algorithms to allow them to interact with a dynamic black-box guide LLM and propose RL with guided feedback (RLGF), a suite of RL algorithms for LLM fine-tuning. We provide two ways for the guide LLM to interact with the LLM to be optimized for maximizing rewards. The guide LLM can generate text which serves as additional starting states for the RL optimization procedure. The guide LLM can also be used to complete the partial sentences generated by the LLM that is being optimized, treating the guide LLM as an expert to imitate and surpass eventually. We experiment on the IMDB positive sentiment, CommonGen, and TL;DR summarization tasks. We show that our RL algorithms achieve higher performance than supervised learning (SL) and the RL baseline PPO, demonstrating the benefit of interaction with the guide LLM. On both CommonGen and TL;DR, we not only outperform our SL baselines but also improve upon PPO across a variety of metrics beyond the one we optimized for. Our code can be found at https://github.com/Cornell-RL/tril.Comment: 23 pages, 5 figures, 7 tables, 4 algorithm

On an unusual swarming of the planktonic blue-green algae Trichodesmium Spp., off Mangalore

Instances of discoloured water phenomenon in the Indian waters have been reported earlier.This is caused by a variety of organisms such as blue-green algae, cystoflagellates and dinoflagellates, and is sometimes associated with adverse effects on the marine fauna including fish

Investigation on the rate of uptake of vegetable tannins with respect to time and concentration

This article does not have an abstract

A note on the occurrence of post larvae of Penaeus penicillatus Alcock near Bombay

A collection of postlarvae belonging to the genus Penaeus that are closely resembling Penaeus indicus on one hand and P. merguiensis on the other in most of the characters, but differing from them in certain other, obtained from near Bombay are assigned to P. penicillatus, a closely allied species, on the strength of the distinctive characters and as the adults of this species occur considerably throughout the year in the area of collection

To Achieve An Optimal Tradeoff Between P2p Overlay Maintenance And Video Sharing Efficiency In Osn’s

Video sharing has been a gradually more popular application in OSNs facilitating users to share their personal videos or interesting videos they found with their friends. However OSN’s additional progress is strictly caught up by the inherent limits of the conventional client/server architecture of its video sharing system which is not only costly in terms of server storage and bandwidth but also not scalable with the high amount of users and video content in OSNs. The efforts have been dedicated to perk up the client/server architecture for video sharing with the peer-to-peer (P2P) architecture being the most promising. P2P-based video sharing has been used in on demand video streaming.The dimension reveals that mainly of the viewers of a user’s videos are the user’s close friends, most video views are driven by social relationships and the rest are driven by interests and viewers of the same video tend to live in the same location. Based on our observations we propose Social Tube a system that discover the social relationship interest resemblance and location to improve the presentation of video sharing in OSNs. Specifically an OSN has a social network (SN)-based P2P overlay construction algorithm that come together peers based on their social relationships and interests.

Design and Comparison of Immersive Interactive Learning and Instructional Techniques for 3D Virtual Laboratories

This work presents the design, development, and testing of 3D virtual laboratories for practice, specifically in undergraduate mechanical engineering laboratories. The 3D virtual laboratories, implemented under two virtual environments3DTV and Computer Automated Virtual Environment (CAVE)serve as pre-lab sessions performed before the actual physical laboratory experiment. The current study compares the influence of two instructional methods (conventional lecture-based and inquiry-based) under two virtual environments, and the results are compared with the pre-lab sessions using a traditional paper-based lab manual. Subsequently, the evaluation is done by conducting performance and quantitative assessments from students pre-and post-laboratory performances. The research results demonstrate that students in the virtual modules (3DTV and CAVE) performed significantly better in the actual physical experiment than the students in the control group in terms of the overall experiment familiarity and procedure and the conceptual knowledge associated with the experiment. 2015 by the Massachusetts Institute of Technology

The impact of monsoon intraseasonal variability on renewable power generation in India

India is increasingly investing in renewable technology to meet rising energy demands, with hydropower and other renewables comprising one-third of current installed capacity. Installed wind-power is projected to increase 5-fold by 2035 (to nearly 100GW) under the International Energy Agency’s New Policies scenario. However, renewable electricity generation is dependent upon the prevailing meteorology, which is strongly influenced by monsoon variability. Prosperity and widespread electrification are increasing the demand for air conditioning, especially during the warm summer. This study uses multi-decadal observations and meteorological reanalysis data to assess the impact of intraseasonal monsoon variability on the balance of electricity supply from wind-power and temperature-related demand in India. Active monsoon phases are characterised by vigorous convection and heavy rainfall over central India. This results in lower temperatures giving lower cooling energy demand, while strong westerly winds yield high wind-power output. In contrast, monsoon breaks are characterised by suppressed precipitation, with higher temperatures and hence greater demand for cooling, and lower wind-power output across much of India. The opposing relationship between wind-power supply and cooling demand during active phases (low demand, high supply) and breaks (high demand, low supply) suggests that monsoon variability will tend to exacerbate fluctuations in the so-called demand-net-wind (i.e., electrical demand that must be supplied from non-wind sources). This study may have important implications for the design of power systems and for investment decisions in conventional schedulable generation facilities (such as coal and gas) that are used to maintain the supply/demand balance. In particular, if it is assumed (as is common) that the generated wind-power operates as a price-taker (i.e., wind farm operators always wish to sell their power, irrespective of price) then investors in conventional facilities will face additional weather-volatility through the monsoonal impact on the length and frequency of production periods (i.e. their load-duration curves)