Video Desnowing and Deraining via Saliency and Dual Adaptive Spatiotemporal Filtering

Outdoor vision sensing systems often struggle with poor weather conditions, such as snow and rain, which poses a great challenge to existing video desnowing and deraining methods. In this paper, we propose a novel video desnowing and deraining model that utilizes the salience information of moving objects to address this problem. First, we remove the snow and rain from the video by low-rank tensor decomposition, which makes full use of the spatial location information and the correlation between the three channels of the color video. Second, because existing algorithms often regard sparse snowflakes and rain streaks as moving objects, this paper injects salience information into moving object detection, which reduces the false alarms and missed alarms of moving objects. At the same time, feature point matching is used to mine the redundant information of moving objects in continuous frames, and a dual adaptive minimum filtering algorithm in the spatiotemporal domain is proposed by us to remove snow and rain in front of moving objects. Both qualitative and quantitative experimental results show that the proposed algorithm is more competitive than other state-of-the-art snow and rain removal methods

Embeddable Soil Moisture Content Sensor based on Open–end Microwave Coaxial Cable Resonator

In This Paper, We Propose and Demonstrate a Novel Corrosion-Resistant, Embeddable Open-End Coaxial Cable Soil Moisture Sensor. This Microwave Resonator is Constructed using Two Reflectors Along the Coaxial Line. the First Reflector is a Metal Post at the Signal Input End, Short-Circuiting the Inner Conductor to the Outer Conductor. the Second Reflector Comprises a Welded Metal Plate Parallel to the Open-End of the Coaxial Line, Maintaining a Fixed Gap. a Moisture-Sensitive Polyvinyl Alcohol (PVA) Film is Inserted into This Gap. the Resonance Frequency of the Open-End Coaxial Cable Resonator is Highly Dependent on the Fringe Capacitance, Which Varies with Soil Moisture Levels. as Such, Tracking Resonance Frequency Changes Allows for Correlation with Soil Moisture Fluctuations. We Provide a Detailed Discussion of the Embeddable Open-End Microwave Coaxial Cable Resonator (EOE-MCCR) Mathematical Model and a Proof of Concept for Soil Moisture Measurement. the Demonstration Experiments Investigate Soil Moisture Content Ranging from 4% to 24%. the Prototype Device Exhibits a Soil Moisture Measurement Sensitivity of 0.76MHz% for Soil Moisture between 4% and 10%, and 1.44MHz% for Soil Moisture between 10% and 24%. the Soil Moisture Sensor Presented Here is Robust, Easy to Manufacture, Chemically Resistant, Low-Cost, and Suitable for Long-Term Applications and Potential Industrial Uses. This Innovative Sensor is Ideal for Sensing Applications in Harsh Environments, Advancing the Field of Chemical Trace Sensing

Punica: Multi-Tenant LoRA Serving

Low-rank adaptation (LoRA) has become an important and popular method to adapt pre-trained models to specific domains. We present Punica, a system to serve multiple LoRA models in a shared GPU cluster. Punica contains a new CUDA kernel design that allows batching of GPU operations for different LoRA models. This allows a GPU to hold only a single copy of the underlying pre-trained model when serving multiple, different LoRA models, significantly enhancing GPU efficiency in terms of both memory and computation. Our scheduler consolidates multi-tenant LoRA serving workloads in a shared GPU cluster. With a fixed-sized GPU cluster, our evaluations show that Punica achieves 12x higher throughput in serving multiple LoRA models compared to state-of-the-art LLM serving systems while only adding 2ms latency per token. Punica is open source at https://github.com/punica-ai/punica

Private-Library-Oriented Code Generation with Large Language Models

Large language models (LLMs), such as Codex and GPT-4, have recently showcased their remarkable code generation abilities, facilitating a significant boost in coding efficiency. This paper will delve into utilizing LLMs for code generation in private libraries, as they are widely employed in everyday programming. Despite their remarkable capabilities, generating such private APIs poses a formidable conundrum for LLMs, as they inherently lack exposure to these private libraries during pre-training. To address this challenge, we propose a novel framework that emulates the process of programmers writing private code. This framework comprises two modules: APIFinder first retrieves potentially useful APIs from API documentation; and APICoder then leverages these retrieved APIs to generate private code. Specifically, APIFinder employs vector retrieval techniques and allows user involvement in the retrieval process. For APICoder, it can directly utilize off-the-shelf code generation models. To further cultivate explicit proficiency in invoking APIs from prompts, we continuously pre-train a reinforced version of APICoder, named CodeGenAPI. Our goal is to train the above two modules on vast public libraries, enabling generalization to private ones. Meanwhile, we create four private library benchmarks, including TorchDataEval, TorchDataComplexEval, MonkeyEval, and BeatNumEval, and meticulously handcraft test cases for each benchmark to support comprehensive evaluations. Numerous experiments on the four benchmarks consistently affirm the effectiveness of our approach. Furthermore, deeper analysis is also conducted to glean additional insights

Research on the influence of team psychological capital on team members’ work performance

Team psychological capital is the positive psychological state of a team and has a positive impact on the human resource management and performance management of the team. Team members’ work performance, as a component of team performance, has an important impact on improving team performance. However, there is less cross-level impact analysis between the two. The purpose of this paper is to explore the mechanisms of the cross-level effects of team psychological capital on members’ performance. A paired questionnaire survey was administered to 387 human resource management team members from 86 human resource management teams across China, and SPSS 22.0, AMOS 23.0, and HLM 6.08 software were used to analyze the questionnaire data at the same level and across levels. The test shows that the cross-level positive effect of team psychological capital on team members’ work performance is established, and the cross-level mediating role of team members’ psychological capital and team support between the two is established. It enriches the cross-level research from team to individual, refines and enriches the research on the impact of team psychological capital on individual behavior, and provides new ideas for team management in companies. Therefore, when conducting team management, enterprises can enhance team members’ psychological capital by improving team psychological capital, thereby improving team members’ work performance and team efficiency

Characterization, Genomic Organization, Abundance, and Chromosomal Distribution of Ty1-copia Retrotransposons in Erianthus arundinaceus

Erianthus arundinaceus is an important wild species of the genus Saccharum with many valuable traits. However, the composition and structure of its genome are largely unknown, which have hindered its utilization in sugarcane breeding and evolutionary research. Retrotransposons constitute an appreciable fraction of plant genomes and may have played a significant role in the evolution and sequence organization of genomes. In the current study, we investigate the phylogenetic diversity and genomic abundance of Ty1-copia retrotransposons for the first time and inspect their chromosomal distribution patterns in E. arundinaceus. In total, 70 Ty1-copia reverse transcriptase (RT) sequences with significant levels of heterogeneity were obtained. The phylogenetic analysis revealed these Ty1-copia retrotransposons were classified into four distinct evolutionary lineages (Tork/TAR, Tork/Angela, Retrofit/Ale, and Sire/Maximus). Dot-blot analysis showed estimated the total copy number of Ty1-copia retrotransposons to be about 4.5 × 103 in the E. arundinaceus genome, indicating they were a significant component. Fluorescence in situ hybridization revealed that Ty1-copia retrotransposons from the four lineages had strikingly similar patterns of chromosomal enrichment, being exclusively enriched in the subterminal heterochromatic regions of most E. arundinaceus chromosomes. This is the first clear evidence of the presence of Ty1-copia retrotransposons in the subterminal heterochromatin of E. arundinaceus. Altogether, these results promote the understanding of the diversification of Ty1-copia retrotransposons and shed light on their chromosomal distribution patterns in E. arundinaceus