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YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source Detection

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arXiv

arXiv 2024年

作者： Tang, Xiaoyu Chen, Xingming Cheng, Jintao Wu, Jin Fan, Rui Zhang, Chengxi Zhou, Zebo The School of Electronic and Information Engineering Faculty of Engineering South China Normal University Guangdong Foshan528225 China The School of Physics South China Normal University Guangdong Guangzhou510000 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The School of Internet of Things Engineering Jiangnan University Wuxi214122 China The School of Aeronautics Astronautics University of Electronic Science and Technology of China and Aircraft swarm intelligent sensing and cooperative control Key Laboratory of Sichuan Province Chengdu610097 China The National Laboratory on Adaptive Optics Chengdu610209 China

In the era of 5G communication, removing interference sources that affect communication is a resource-intensive task. The rapid development of computer vision has enabled unmanned aerial vehicles to perform various high-altitude detection tasks. Because the field of object detection for antenna interference sources has not been fully explored, this industry lacks dedicated learning samples and detection models for this specific task. In this article, an antenna dataset is created to address important antenna interference source detection issues and serves as the basis for subsequent research. We introduce YOLO-Ant, a lightweight CNN and transformer hybrid detector specifically designed for antenna interference source detection. Specifically, we initially formulated a lightweight design for the network depth and width, ensuring that subsequent investigations were conducted within a lightweight framework. Then, we propose a DSLK-Block module based on depthwise separable convolution and large convolution kernels to enhance the network’s feature extraction ability, effectively improving small object detection. To address challenges such as complex backgrounds and large interclass differences in antenna detection, we construct DSLKVit-Block, a powerful feature extraction module that combines DSLK-Block and transformer structures. Considering both its lightweight design and accuracy, our method not only achieves optimal performance on the antenna dataset but also yields competitive results on public datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Antennas

Recursive Time-Sensor Domain Data Decomposition: A Novel Method for Time-Varying Process Monitoring

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SSRN 2024年

作者： Gui, Yufei Lang, Zi-Qiang Liu, Zepeng Laalej, Hatim Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS10 2TN United Kingdom School of Engineering Newcastle University Newcastle upon TyneNE1 7RU United Kingdom Advanced Manufacturing Research Centre University of Sheffield SheffieldS10 2TN United Kingdom

Process monitoring aims to timely detect faults or abnormal conditions, ensuring safety and achieving satisfactory product quality. Time-varying processes are common in various industries, including chemical, semiconductor, and advanced manufacturing. A key challenge in time-varying process monitoring is how to accommodate deterministic but unknown time-varying trends in process responses. Existing multivariate statistical process monitoring (MSPM) approaches designed for time-varying processes face challenges including intensive computation and worse adaption to unknown process changes. In this study, a new process monitoring approach is proposed based on a novel idea referred to as recursive time-sensor decomposition (RTSD). The multi-sensor data are compressed into dominant time and sensor domain components. In the time domain, the feature vectors are extracted to represent process states. In the sensor domain, the process information distributed across different sensors is used to accommodate the normal time-varying trend and determine the control limit. The proposed approach is validated first by analysing a simulated time-varying process and then by an application of monitoring tool wear states in a real milling experiment. The results demonstrate that the proposed approach is highly effective, has higher fault detection rates and lower false alarm rates when compared to existing methods, and is applicable in a real time-varying industrial process. © 2024, The Authors. All rights reserved.

关键词： Process monitoring

Low-Temperature Co Oxidation on Cuo-Ceo2 Catalyst Prepared by Facile One-Step Solvothermal Synthesis: Improved Activity and Moisture Resistance Via Optimizing the Activation Temperature

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SSRN 2022年

作者： Liu, Yanmin Mao, Dongsen Yu, Jun Guo, Xiaoming Ma, Zhen School of Chemical and Environmental Engineering Shanghai Institute of Technology Shanghai201418 China Department of Environmental Science and Engineering Fudan University Shanghai200433 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

Development of a highly efficient Cu-based catalyst for low-temperature CO oxidation under moisture condition remains a grand challenge. In this paper, effect of activation temperature (350-800 oC) on catalytic performance of CuO-CeO2, prepared by facile one-step solvothermal synthesis, in CO oxidation was investigated, and the catalysts’ physicochemical properties were studied by TG-DSC, ICP-AES, N2 sorption, XRD, TEM, Raman spectroscopy, XPS, in-situ DRIFTS, H2-TPR, CO-TPD, and O2-TPD. It was found that activation at 550 oC is beneficial for the interaction between CuO and CeO2, leading to the formation of more Cu+ species and oxygen vacancies advantageous for improving the catalytic activity. Activation at 800 oC, nevertheless, would weaken the interaction between CuO and CeO2 due to the sintering of CuO and CeO2, thus decreasing the catalytic activity and moisture resistance. Interestingly, no deactivation was observed over the optimal catalyst (activated at 550 oC) after 50 h testing at a low temperature of 87 oC (at which 90% CO conversion was obtained), even when 4.2% water vapor was added into the feed gas. © 2022, The Authors. All rights reserved.

关键词： Cerium oxide

Characterization and analysis of petrochemical wastewater through particle size distribution, biodegradability, and chemical composition

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Chinese Journal of chemical engineering 2019年第2期27卷 444-451页

作者： Xiaoqiang Jia Dayao Jin Chen Li Wenyu Lu Department of Biochemical Engineering School of Chemical Engineering and Technology Tianjin University Key Laboratory of Systems Bioengineering Tianjin University Synthetic Biology Platform Collaborative Innovation Center of Chemical Science and Engineering(Tianjin)

The centralized treatment method is a widely used form of wastewater treatment that tends to be less effective at removing toxic substances. Therefore, a detailed analysis of the composition of wastewater can provide important information for the design of an effective wastewater treatment process. The objective of this paper was to investigate particle size distribution(PSD), biodegradability, and the chemical composition of the petrochemical wastewater discharges. For this purpose, this project selected the petrochemical wastewater and treated wastewater of China National Offshore Oil Corporation Zhongjie Petrochemical Co, Ltd. as the analysis *** step-by-step filtration method, along with a molecular weight classification method, was selected to build the chemical oxygen demand(COD) and biochemical oxygen demand(BOD) fingerprints of petrochemical wastewater and treated wastewater. The results showed that the main pollutants were settleable particles in petrochemical wastewater, which contributed to over 54.85% of the total COD. The colloidal particles with particle sizes in the range of 450–1000 nm had the highest COD value in the treated wastewater, which contributed34.17% of the total COD of treated wastewater. The results of the BOD analysis showed that the soluble fractions were the main reason that treated wastewaters did not meet the treatment standards. Tests on the organic compounds in petrochemical wastewater found that there were mainly linear paraffins, branched paraffins, benzene series compounds, and some plasticizers in the influent of the petrochemical wastewater. The most abundant pollutants in treated petrochemical wastewater were the adjacent diisobutyl phthalate and the linear *** transform infrared(FTIR) transmission spectroscopy analysis showed that the settleable particles of petrochemical wastewater and membrane bioreactor(MBR)-treated wastewater contained multiple types of organic substances. The results also indicated

关键词： Petrochemical wastewater Gradient membrane separation chemical oxygen demand Biochemical oxygen demand

High Sensitivity Submicron Scale Temperature Sensor Based on Perovskite Nanoplatelet Lasers

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SSRN 2024年

作者： Zhao, Ruofan Tao, Jianxun Xi, Yuying Chen, Jiangzhao Ji, Ting Wang, Wenyan Wen, Rong Cui, Yanxia Chen, Junsheng Lia, Guohui College of Physics and Optoelectronics Key Laboratory of Interface Science and Engineering in Advanced Materials Key lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology Taiyuan030024 China School of Materials Science and Engineering Kunming University of Science and Technology Kunming650093 China Shanxi-Zheda institute of advanced materials and chemical engineering China Nano-Science Center Department of Chemistry University of Copenhagen Universitetsparken 5 CopenhagenDK-2100 Denmark

Submicron scale temperature sensors are crucial for a range of applications, particularly in micro and nanoscale environments. One promising solution involves the use of active whispering gallery mode (WGM) microresonators. These resonators can be remotely excited and read out using free-space structures, simplifying the process of sensing. In this study, we present a submicron-scale temperature sensor with a remarkable sensitivity up to 190 pm/℃ based on a triangular CH3NH3PbI3 nanoplatelet (NPL) laser. Notably, as temperature changes, the peak wavelength of the laser line shifts linearly. This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser. The optical modes are confined within the perovskite NPL, which measures just 85 nanometers in height, due to total internal reflection. Our NPL laser boasts several key features, including a high Q-factor of ~ 2610 and a low laser threshold of about 19.8 µJ cm−2. The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors. This advancement paves the way for significant progress in the development of ultrasmall temperature sensors, opening new possibilities across various fields. © 2024, The Authors. All rights reserved.

关键词： Perovskite

Competition and Cooperation Mechanism Between Agency Selling and Wholesale: An Application of the Emerging E-commerce Model

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Competition and Cooperation Mechanism Between Agency Selling...

IEEE International Conference on Industrial engineering and engineering Management

作者： Haonan Wang C. K. M. Lee Ping Ji Gang Li Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong China Laboratory for Artificial Intelligence in Design Hong Kong Science Park New Territories Hong Kong SAR China School of Intelligent Finance and Business XJTLU Entrepreneur College (Taicang) Xi'an Jiaotong - Liverpool University China School of Management Xi'an Jiaotong University The State Key Lab for Manufacturing Systems Engineering The Key Lab of the Ministry of Education for Process Control and Efficiency Engineering Xi'an China

Recently, the platform economy allows enterprises to collaborate with business partners and provide additional channels for various parties. E-commerce platforms have become integral channels for connecting suppliers with consumers. In the platform economy, agency selling and reselling are two predominant sales models that often coexist for the same product types, resulting in a competitive relationship. This study analyzes transaction data for 30,000 Stock Keeping Units (SKUs) provided by the Chinese e-commerce platforms over one month. We employ three models to compare the sales quantity and profits of manufacturers and online platforms and to identify the most efficient mode for stakeholders based on the model establishment and empirical evidence. Our findings suggest that apart from the existing channel to provide products to customers, manufacturers enter the platform which will increase the profit of platform operators. On the other hand, platform operators may also affect the profit of the manufacturers.

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Development of an Aloe Vera and Cellulose Based Bead to Aid the Growth of Edible Crops on Mars Regolith

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Development of an Aloe Vera and Cellulose Based Bead to Aid ...

IAF/IAA Space Life Sciences Symposium 2021 at the 72nd International Astronautical Congress, IAC 2021

作者： Garcia, Axel Jimenez, Gilberto Roman, Juan Department of Life Support Systems PRatian LLC San Juan00757 Puerto Rico The Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Chemical Engineering University of Puerto Rico Mayaguez 00882 Puerto Rico Department of Computer Engineering University of Puerto Rico Mayaguez 00882 Puerto Rico

Our goal is to develop an efficient water and nutrient supplement for soil, targeting controlled plant growth settings in greenhouses. In an effort to support sustainable agricultural supplement that maximizes resource use and improves agricultural productivity while remediating potential occupational burdens in farming, PRatian (our team) designed and developed a prototype for the biodegradable polymer called Nutrient-Containing Porous Biodegradable Bead (NCPB), a cost-effective, self-contained, hydration and nutrient bead capable of supporting the growth of an individual plant. As we optimize our NCPB-based technology, our goal is to mitigate water losses associated with farming irrigation systems while increasing plant growth performance, leading to a more sustainable use of water, soil, and nutrients. This paper focuses explaining the overall design, plant growth performance and provide insight in how to use similar technologies for in-house agriculture on Mars. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved

关键词： Sodium alginate

Recursive Time-Sensor Domain Data Decomposition: A Novel Method for Time-Varying Process Monitoring

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SSRN 2024年

关键词： Process monitoring

Jseun: Joint Semantic-Instance Segmentation of Point Cloud Via Neighbor Features for Indoor Scenes

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SSRN 2023年

作者： Chen, Hui Jiang, Jinlong Chen, Wanlou Liu, Wanquan Liu, Peter Xiaoping College of Automation Engineering Shanghai University of Electric Power Shanghai200090 China Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Nanovision Medical Technology Co. Ltd Shanghai200000 China School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada

Efficient and accurate segmentation of the point cloud for indoor scenes is an important task for 3D scene understanding. Due to the complexity of indoor environments. It is difficult to fully extract the details of point cloud, resulting in poor recognizability in existing models. In this paper, a novel framework called joint semantic-instance segmentation via enhancedutilization of neighbor features is proposed to achieve semantic and instance segmentation of indoor scenes. This framework mines point cloud information from a local scale, but it is different from other models in that it focuses on the full mining of point cloud neighbor information. In this regard, a new neighbor feature extraction module is developed to enrich the expression of neighborhood information and enlarge the construction of the neighborhood neighbor scope. Besides, semantic and instance segmentations take advantages of each other by constructing a mutual promotion model of semantic and instance, which can obtain more accurate semantic and instance predictions for indoor scenes. The proposed scheme is evaluated on the S3DIS dataset and compared with existing methods. Experimental results demonstrate that this method is more effective and efficient than previous approaches in joint 3D semantic and instance segmentation. © 2023, The Authors. All rights reserved.

关键词： Semantics