TIME-BASED ANTI-REPLAY CHECK

Techniques are provided herein for a time-based anti-replay check. These techniques may address the 64-bit sequence number recovery issue and the replay check issue in multi-sender security engine and multi-receiver security engine applications

Revisiting Classifier: Transferring Vision-Language Models for Video Recognition

Transferring knowledge from task-agnostic pre-trained deep models for downstream tasks is an important topic in computer vision research. Along with the growth of computational capacity, we now have open-source vision-language pre-trained models in large scales of the model architecture and amount of data. In this study, we focus on transferring knowledge for video classification tasks. Conventional methods randomly initialize the linear classifier head for vision classification, but they leave the usage of the text encoder for downstream visual recognition tasks undiscovered. In this paper, we revise the role of the linear classifier and replace the classifier with the different knowledge from pre-trained model. We utilize the well-pretrained language model to generate good semantic target for efficient transferring learning. The empirical study shows that our method improves both the performance and the training speed of video classification, with a negligible change in the model. Our simple yet effective tuning paradigm achieves state-of-the-art performance and efficient training on various video recognition scenarios, i.e., zero-shot, few-shot, general recognition. In particular, our paradigm achieves the state-of-the-art accuracy of 87.8% on Kinetics-400, and also surpasses previous methods by 20~50% absolute top-1 accuracy under zero-shot, few-shot settings on five popular video datasets. Code and models can be found at https://github.com/whwu95/Text4Vis .Comment: Accepted by AAAI-2023. Camera Ready Versio

Dynamic Furnace Temperature Setting Research on Combustion System of Rolling Mill Reheating Furnace

AbstractThe setting of furnace temperature in combustion system of reheating furnace at rolling mill is an important parameter in the production process. Variety of some factors such as furnace heating capacity, steel thermal stress, production rhythm etc. directly affects the setting of furnace temperature, it is an industry problem. This article analysis about how the above mentioned factors affect the furnace temperature setting, and mainly focus on dynamic setting strategy of furnace temperature so as to fit fluctuation of production rhythm through theoretical analysis on the energy balance of billet heat transfer in the furnace. This strategy has been verified by production and experiment, and matches with the related data

Reversible Anionic Redox Activities in Conventional LiNi1/3 Co1/3 Mn1/3 O2 Cathodes.

Redox reactions of oxygen have been considered critical in controlling the electrochemical properties of lithium-excessive layered-oxide electrodes. However, conventional electrode materials without overlithiation remain the most practical. Typically, cationic redox reactions are believed to dominate the electrochemical processes in conventional electrodes. Herein, we show unambiguous evidence of reversible anionic redox reactions in LiNi1/3 Co1/3 Mn1/3 O2 . The typical involvement of oxygen through hybridization with transition metals is discussed, as well as the intrinsic oxygen redox process at high potentials, which is 75 % reversible during initial cycling and 63 % retained after 10 cycles. Our results clarify the reaction mechanism at high potentials in conventional layered electrodes involving both cationic and anionic reactions and indicate the potential of utilizing reversible oxygen redox reactions in conventional layered oxides for high-capacity lithium-ion batteries

Short O-O separation in layered oxide Na0.67CoO2 enables an ultrafast oxygen evolution reaction.

The layered oxide Na0.67CoO2 with Na+ occupying trigonal prismatic sites between CoO2 layers exhibits a remarkably high room temperature oxygen evolution reaction (OER) activity in alkaline solution. The high activity is attributed to an unusually short O-O separation that favors formation of peroxide ions by O--O- interactions followed by O2 evolution in preference to the conventional route through surface O-OH- species. The dependence of the onset potential on the pH of the alkaline solution was found to be consistent with the loss of H+ ions from the surface oxygen to provide surface O- that may either be attacked by solution OH- or react with another O-; a short O-O separation favors the latter route. The role of a strong hybridization of the O-2p and low-spin CoIII/CoIV π-bonding d states is also important; the OER on other CoIII/CoIV oxides is compared with that on Na0.67CoO2 as well as that on IrO2

DetToolChain: a new prompting paradigm to unleash detection ability of MLLM

We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object detection ability of multimodal large language models (MLLMs), such as GPT-4V and Gemini. Our approach consists of a detection prompting toolkit inspired by high-precision detection priors and a new Chain-of-Thought to implement these prompts. Specifically, the prompts in the toolkit are designed to guide the MLLM to focus on regional information (e.g., zooming in), read coordinates according to measure standards (e.g., overlaying rulers and compasses), and infer from the contextual information (e.g., overlaying scene graphs). Building upon these tools, the new detection chain-of-thought can automatically decompose the task into simple subtasks, diagnose the predictions, and plan for progressive box refinements. The effectiveness of our framework is demonstrated across a spectrum of detection tasks, especially hard cases. Compared to existing state-of-the-art methods, GPT4V with our DetToolChain improves state-of-the-art object detectors by +21.5% AP50 on MS COCO Novel class set for open-vocabulary detection, +24.23% Acc on RefCOCO val set for zero-shot referring expression comprehension, +14.5% AP on D-cube describe object detection FULL setting