Segmenting Lecture Videos by Topic: From Manual to Automated Methods

More and more universities and corporations are starting to provide videotaped lectures online for knowledge sharing and learning. Segmenting lecture videos into short clips by topic can extract the hidden information structure of the videos and facilitate information searching and learning. Manual segmentation has high accuracy rates but is very labor intensive. In order to develop a high performance automated segmentation method for lecture videos, we conducted a case study to learn the segmentation process of humans and the effective segmentation features used in the process. Based on the findings from the case study, we designed an automated segmentation approach with two phases: initial segmentation and segmentation refinement. The approach combines segmentation features from three information sources of video (speech text transcript, audio and video) and makes use of various knowledge sources such as world knowledge and domain knowledge. Our preliminary results show that the proposed two-phase approach is promising

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

Phosphotungstic acid intercalated Zn,Al-layered double hydroxides/ nanocellulose based 3D lightweight foam thermal insulation materials

In this study, [PW _12 O _40 ] ^3− anions have been intercalated into Zn,Al-Layered Double Hydroxides(ZnAl-NO _3 -LDHs) to synthesize ZnAl-PW _12 O _40 -LDHs by ion-exchange reaction. The chemical composition and structure were analyzed by XRD, FT-IR, ICP, and SEM. Then, the nanocellulose based 3D lightweight foam thermal insulation materials was prepared by ZnAl-PW _12 O _40 -LDHs and CNF compound with H _3 BO _3 . The TG showed that ZnAl-PW _12 O _40 - LDHs significantly reduced the maximum decomposition rate and increased the carbon residual rate at 800 °C, which indicated that ZnAl-PW _12 O _40 -LDHs can improve the oxidation resistance of CNF composite materials at high temperature.The fire resistance of different samples were evaluated by back temperature test and alcohol lamp flame test, CNF/50%ZnAl-PW _12 O _40 -LDHs /2%H _3 BO _3 showed best thermal stability and flame-retardant properties, which can be contributed to the decomposition products of ZnAl-PW _12 O _40 -LDHs, acting both as phase flame retardant and condensed phase flame retardant

Exploration of treatment technology for heavy metal wastewater

Among the current pollutants in our water bodies, the one that has the greatest degree of pollution and impact on the water environment is heavy metal wastewater. Various heavy metal ions in water bodies can seriously disrupt the ecological balance of water bodies and spread throughout the biosphere through the natural material cycle and other means. Excess heavy metal ions not only seriously endanger the health of aquatic organisms, but can also enrich in animals and even humans, posing a serious threat to human health and causing failure or damage to vital organs such as the human internal organs and brain. The common heavy metal ions in existing water bodies are Cu2+, Hg2+, Pb2+ etc. Due to their inherent difficulty in degradation, enrichment and persistence, heavy metal ions make heavy metal wastewater treatment different from other traditional pollutant treatment methods. This paper examines the two main techniques currently used to remove heavy metals from water bodies: physical, chemical and biological techniques, and summarises the advantages and disadvantages of both methods. It is proposed that future treatment methods for heavy metal wastewater should develop an environmentally friendly and efficient systematic approach based on biotechnology and synergistic multi-technologies

Planning with Spatial-Temporal Abstraction from Point Clouds for Deformable Object Manipulation

Effective planning of long-horizon deformable object manipulation requires suitable abstractions at both the spatial and temporal levels. Previous methods typically either focus on short-horizon tasks or make strong assumptions that full-state information is available, which prevents their use on deformable objects. In this paper, we propose PlAnning with Spatial-Temporal Abstraction (PASTA), which incorporates both spatial abstraction (reasoning about objects and their relations to each other) and temporal abstraction (reasoning over skills instead of low-level actions). Our framework maps high-dimension 3D observations such as point clouds into a set of latent vectors and plans over skill sequences on top of the latent set representation. We show that our method can effectively perform challenging sequential deformable object manipulation tasks in the real world, which require combining multiple tool-use skills such as cutting with a knife, pushing with a pusher, and spreading the dough with a roller.Comment: Published at the Conference on Robot Learning (CoRL 2022

Application Prospect, Development Status and Key Technologies of Shared Energy Storage toward Renewable Energy Accommodation Scenario in the Context of China

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. How to ensure the accommodation of renewable energy will also be the core issue in the future development process of renewable-dominated electric power systems. In this context, shared energy storage (SES), a novel business model combined with energy storage technologies and the sharing economy, has the potential to play an important role in renewable energy accommodation scenarios. This paper systematically organizes the application prospect, development status and key technologies of SES in the renewable energy accommodation scenario in the context of China, providing helpful references for the promotion of the business model. Firstly, a typical SES framework for renewable energy accommodation is described, and three basic forms of SES in this scenario are presented. Moreover, the application prospect of SES in the renewable energy accommodation scenario is quantitatively analyzed based on the renewable energy generation planning under the carbon peaking goal and the current guarantee mechanism of renewable energy accommodation. Furthermore, the rules for energy storage systems that provide the peak-regulation ancillary service in typical regions and provincial administrative regions in China are summarized, and the development status of SES in the renewable energy accommodation scenario is analyzed, combined with the actual market data. Finally, the key technologies to promote the further development of SES for renewable energy accommodation are presented

Flame retardancy and thermal degradation behavior of red gum wood treated with hydrate magnesium chloride

Flame retardancy and thermal degradation of wood treated with magnesium chloride (MgCl2·6H2O) were investigated. Results showed that MgCl2·6H2O decreased flame intensity and heat release rate, and reduced smoke concentration and gas yield. From ambient temperature to 250°C, MgCl2·6H2O reduced wood combustibility by gas dilution mechanism. The chemical started to decompose at 350°C and produced MgOHCl, in which -Cl and -Mg free radicals were generated and intervened the chain reactions of wood combustion. Hydrogen chloride gas generated promoted wood charring. MgCl2·6H2O gradually converted to MgOHCl and MgO compounds at higher temperatures, and MgO suppressed wood combustion by the wall effect mechanism. © 2013 The Korean Society of Industrial and Engineering Chemistry

Comparative Performance of Three Magnesium Compounds on Thermal Degradation Behavior of Red Gum Wood

The effect of basic magnesium carbonate (BMC), magnesium hydroxide (MH), and magnesium chloride hydrate (MCH) on thermal degradation of red gum wood was studied using cone calorimetry, Thermogravimetric-differential scanning calorimetry (TG-DSC) analysis, and X-ray diffraction (XRD) characterization. The results showed common fire retardation actions of the three compounds by releasing incombustible gas and/or water vapor to dilute combustible gas in the flaming zone, and by converting to MgO, which had a satisfactory protective wall effect on the wood. Individually, BMC absorbed heat from the wood at the pre-decomposition stage and, thus, slowed down wood pyrolysis process. It slightly increased the char yield by charring in both the charring stage and the char calcination stage. MH lost water at about 270 °C, close to the temperature at which wood thermally degraded. MH rendered wood char quickly, and the compact char layer impeded further carbonization and burning of inner wood. MCH promoted charring with Mg2+ as a Lewis acid, and increased wood char yield. MCH also released Cl· free radical and HCl at 167 °C, which easily coordinated with combustion reaction radical, and slowed down, even inhibited, the combustion chain reaction