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Investigation of a PDMS based micromixer for heterogeneous immunoassays of insulin

Investigation of a PDMS based micromixer for heterogeneous i...

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IEEE international conference on Nano/Micro Engineered and Molecular Systems (NEMS)

作者： Zhikun Zhan Yanli Qu Shuai Wang Zaili Dong Balaji Srinivasan Steve Tung Wen J. Li State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China Chinese Academy of Sciences Beijing China Department of Mechanical Engineering University of Arkansas Fayetteville USA Centre for Micro and Nano Systems Chinese University of Hong Kong Hong Kong China

An experimental study was carried out to evaluate the performance of a polydimethylsiloxane (PDMS) based micromixer for heterogeneous immunoassays of insulin. the detection method is based on coupling the highly specific double-antibody sandwich immunoassay with the sensitive chemiluminescence of the Luminol-Hydrogen Peroxide reaction. Both the immune and chemiluminescence reactions are conducted in the micromixer, and the resultant light emission is detected by a highly sensitive photometer. the behavior of the luminol based chemiluminescence is parabolic with respect to time, and the maximum light intensity is used here to represent the output of the reaction. the current results indicate that at an actuation pressure of 15 psi, an actuation frequency of 30 Hz leads to the best reaction result. At these operating conditions, the detection limit of insulin is about 10 -14 mol/L while the total reaction time of the insulin immunoassay in the micromixer is less than 5 minutes.

关键词： Insulin Immune system Microfluidics Sensors Sugar Mixers Diabetes

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Comparative Analysis of Smart Pesticide Recommendation System sing ML/AI

Comparative Analysis of Smart Pesticide Recommendation Syste...

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international conference on Contemporary Computing and informatics (IC3I)

作者： K.G. Harsha Kakoli Banerjee P Vinooth Shruti Varshney Shreya Gupta Smily Jasrotia JSS Academy of Technical Education Noida India

the agriculture sector is crucial in meeting societal requirements in a world where there is food insecurity and malnutrition. One of the biggest issues that crops confront is pests. Pests are creatures that live in undesirable places and harm humans, animals, plants, etc. Pests have the potential to harm plants and impede growth. the quantity and quality of the crops are directly impacted. Pre-and post-harvest pests and illnesses are thought to be responsible for at least 30 to 40% of the world’s agricultural output being lost. In an effort to manage or control diseases and pests, humans also devote a lot of time and resources to developing and applying new pesticides. these pesticides may have negative effects on the environment and people’s health when used improperly. Given that pest infestations significantly reduce crop quality and cause major crop damage, farmers have a tough time recognizing agricultural insects. the disadvantage of traditional insect identification is that it requires qualified taxonomists to rightly recognize insects on the basis of physical traits. this article gives a comparative analysis of various methods for picture classification and pest identification. the article chooses the most effective method for classifying pest images and utilizes machine learning to suggest pesticides that are accessible in India that adhere to ISO criteria.

关键词： Machine learning algorithms Insects ISO Crops Machine learning Object recognition informatics

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Virtual Multi-Interaction for Rehabilitation robotics

Virtual Multi-Interaction for Rehabilitation Robotics

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international conference on Advanced robotics and Mechatronics (ICARM)

作者： Wenjie Li Alberto Rovetta Xilun Ding Lei Chen Yifei Han Beijing Microelectronics Technology Institute Beijing BJ P.R.China School of Mechanical Engineering and Automation Beihang University Beijing BJ P.R.China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

this article is to develop an intelligent exoskeleton to support the wearable, interactive and customizable path on the rehabilitation needs of falling foot. In collaboration with engineers and doctors from Milan and Beijing, it is to realize an active device that performs function adapting perfectly to the anatomical characteristics of each subject, and it would supply greater possibilities and flexibility. Traditional devices are passive rigid orthoses (AFO) and active peroneal stimulation systems (FES). Although simple and cheap, AFO system can bring about phenomena of adaptation at the central level that gradually decrease muscle activity over time. More is the stiffness in the path. FES devices ensure a more natural movement of the foot but without control autonomy. Moreover, the efficiency is always limited with high costs. According analysis of the path, anatomy and biomechanics of the calf, considering combination of sensing and interaction technologies and devices, it focuses on using MEMS inertial sensors and force sensors to make a fusion and measure state of the calf's motion and attitude. It also uses 3D printing to construct lightweight and customable structures. the mobile device is used as local center to transfer data and feedback with Bluetooth and Internet, to give instruction and detect emotion with voice. Virtual Reality is used to build training scenes combined with rehabilitation plan, connections and feedbacks are also built between vision and motion states to form closed loop control. It expounds system construction, virtual scene construction, control method design, system tests, etc. according rehabilitation application, and preliminary application data indicates that the whole system works well with low cost and high efficiency.

关键词： Exoskeletons Cloud computing Servers Robots Software Training control systems

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Pedestrian Target Detection Model Based on Improved Yolov8

Pedestrian Target Detection Model Based on Improved Yolov8

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Artificial Intelligence and Electromechanical automation (AIEA), international conference on

作者： Jinglun Huang Jianan Liang Yongjun Cao School of Electronics and Information Engineering Wuyi University Jiangmen Guangdong China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing GDAS Guangzhou Guangdong China South China Robotics innovation Research Institute Foshan Guangdong China School of Mechanical & Automotive Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (数字)9798350366174

ISBN: (纸本)9798350366181

Dense pedestrian detection is a key technology in public intelligent surveillance. It identifies the location and number of pedestrians in videos through object detection methods, thereby achieving intelligent surveillance of crowds. However, in crowded scenes, due to occlusion and small pedestrian targets, it is easy to miss pedestrians. To solve this problem, this paper proposes an improved YOLOv8 detection algorithm, YOLOv-8FastTCD. Firstly, the FasterNet module is used to replace the backbone network. Secondly, a task collaborative dynamic detection head (TCDDH) is introduced after the neck network. the performance of this model on the CrowdHuman dense pedestrian detection dataset has been improved, with mAP 50 and $\mathrm{mAP}_{50-95}$ reaching $\mathbf{7 8. 4 \%}$ and 51.5% respectively, which are 2.1% and 2.0% higher than the original YOLOv8n model.

关键词： Performance evaluation Pedestrians Shape Computational modeling Surveillance Object detection Real-time systems Neck Computational efficiency Videos

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Decentralized Adaptive Digital control for Multi-machine Excitation Systems with Static Var Compensator

Decentralized Adaptive Digital Control for Multi-machine Exc...

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international conference on Advanced robotics and Mechatronics (ICARM)

作者： Guoqiang Zhu Mengyun Wang Cheng Zhong Yong Mu Yan Li Xiuyu Zhang Jilin Province International Research Center of Precision Drive and Intelligent Control Tangshan Power Supply Company State Grid Jibei Electric Power Company College of Electrical Engineering Chongqing Electric Power College

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

In this paper, a decentralized discrete adaptive quantized control (DDQC) method has been proposed for multi-machine excitation system (MES) with static var compensator (SVC). the mathematical model of the power system is studied in discrete-time form, the digital control scheme is realized by using the improved hysteresis quantizer, which can discretize the control signals in amplitude and time scale. then, by using the discrete first-order low-pass filter (FLF), the complexity of discrete backstepping control method is reduced. Finally, the stability analysis proves that the trace error converges to the compact set and the simulation results illustrate the effectiveness of the control method.

关键词： Power system stability Static VAr compensators Mathematical model Robots Mechatronics Stability analysis

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A systems design approach to manage mechatronics R&D

A systems design approach to manage mechatronics R&D

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IEEE conference on Cybernetics and Intelligent Systems

作者： Chee Khiang Pang Tsan Sheng Ng Frank L. Lewis Tong Heng Lee Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Industrial and Systems Engineering National University of Singapore Singapore Automation and Robotics Research Institute University of Texas Arlington Fort Worth TX USA

We propose a systems design procedure to integrate mechanical design, structural prototyping, and servo evaluation through careful comprehension of the servo-mechanical-prototype production cycle commonly employed in mechatronic industries. Our approach focuses on the Modal Parametric Identification (MPI) of key feedback parameters for fast exchange of design specifications and information to enable efficient conduct of product design evaluations and support schedule compression of the R&D project life cycle. Using the commercial Hard Disk Drive (HDD) as a case example, we demonstrate how our approach allows inter-disciplinary specifications to be communicated amongst engineers from different backgrounds to speed up the R&D process for the next generation of intelligent manufacturing. this provides the project management team with powerful decision-making tools for project strategy formulation, and improvements in project outcome are potentially massive because of the low costs of change.

关键词： Mechatronics Prototypes System analysis and design Servomotors Production Damping Poles and zeros

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A robotic needle guide for prostate brachytherapy

A robotic needle guide for prostate brachytherapy

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IEEE international conference on robotics and automation (ICRA)

作者： Septimiu E. Salcudean thomas D. Prananta William J. Morris Ingrid Spadinger Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada Department of Radiation Oncology Vancouver Cancer Centre British Columbia Cancer Agency 600 West 10th Avenue V5Z-4E6 Canada Department of Medical Physics Vancouver Cancer Centre British Columbia Cancer Agency BC Canada

Low dose rate prostate brachytherapy involves the permanent implant of radioactive sources into the prostate region using needles. We present a four-degree-of-freedom robot for prostate brachytherapy. the robot can translate a needle guide in the X-Y plane allowing for precise needle insertion along the Z direction. It can also rotate the guide about the X and Y axes, providing thus fine control over the needle insertion point and angle. the robot is light and mountable on a standard brachytherapy stepper. It is non- back-drivable providing a stable needle insertion direction when the power is off. It allows for manual control of each of the motor axes for fine positioning and has a quick-release mechanism for gross translation of the needle guide. We present the robot design and the performance characteristics of the prototype we built. the robot has an interface that allows the guide to be stepped through a complete treatment plan. A radiation oncologist implanted a phantom according to a treatment plan. Only 32 minutes were required for the complete implant that had 26 needles with 136 seeds. this demonstrates that, in spite of its increased flexibility of use, the robotic guide does not add to the procedure time.

关键词： Robots Needles Brachytherapy Ultrasonic imaging robotics and automation Implants Cancer Imaging phantoms Neoplasms Interference

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On the Importance of the DCT Phase for Image Steganography Schemes

On the Importance of the DCT Phase for Image Steganography S...

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international conference on Computing, Communication & automation (ICCCA)

作者： Mohammed Baziyad Mohammad S. Obaidat Research Institute of Sciences & Engineering (RISE) University of Sharjah Sharjah United Arab Emirates College of Computing & Informatics University of Sharjah UAE with KASIT University of Jordan Amman Jordan and with University of Science & Technology Beijing Beijing China

ISBN: (数字)9781728163246

ISBN: (纸本)9781728163253

there is a well-known theory in the literature that as long as the Fourier phase of an image is maintained intact, the overall appearance of an image remains specious if the Fourier magnitude of the image is slightly modified. However, the Discrete Cosine Transform (DCT) is the real number transformation version of the Fourier transform. therefore, there is no phase spectrum in the DCT transform. However, it is noticeable that several state-of-the-art DCT hiding schemes treat the DCT signs as phase signals, and hide only in the DCT magnitude spectrum. However, there is no solid study on the importance of the DCT signs (phase) on image steganography schemes. thus, this paper aims to highlight the impact of the DCT phase on hiding schemes, and to discover the degree of improvement achieved by simply keeping the DCT signs intact while hiding the secret message.

关键词： Fourier transforms automation conferences Solids Discrete cosine transforms Separation processes

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Recent Management Trends Involved With the Internet of things in Indian Automotive Components Manufacturing Industries

Recent Management Trends Involved With the Internet of Thing...

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international conference on Contemporary Computing and informatics (IC3I)

作者： Farhat Ali Syed N Bargavi Abhishek Sharma Abhishek Mishra Pooja Nagpal Aparna Srivastava Department of Management (HR) Prestige Institute Of Management And Research Indore Madhya Pradesh Demartment of Management Studies Bharat Institute of Higher Education And Research Chennai Tamilnadu India Mittal School of Business Lovely Professional University Phagwara Punjab India Department of Management Studies Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Management Studies International School of Business Excellence ISME Bangalore Karnataka India Department of MCA Lloyd Institute of Engineering and Technology Greater Noida Uttar Pradesh India

the development of smart manufacturing systems is being driven by a variety of diverse needs for the dependability of equipment and the prediction of quality. In order to accomplish this objective through the use of machine learning, a wide range of approaches are being investigated. the management and protection of one’s company’s data presents yet another challenging aspect of doing business. In order to cope with fraudulent datasets, machine learning and internet of things technologies were utilized. these technologies were used to protect system transactions and manage a dataset. Because of this, we were able to find solutions to the problems that we had previously discussed. the gathered information was organized and examined with the help of big data techniques. the Internet of things system was constructed using the Hyperledger Fabric platform, which is a private computer network. In addition, a hybrid prediction strategy was utilized for the defect diagnostic as well as the defect forecasting. the latest machine learning techniques were utilized in order to model the complexity of the environment and estimate the genuine positive ratio of the quality control system. the quality control of the system was evaluated using these pieces of data.

关键词： Manufacturing industries Computational modeling Machine learning Quality control Market research Fabrics Internet of things

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Grape leaf disease detection from color imagery using hybrid intelligent system

Grape leaf disease detection from color imagery using hybrid...

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5th international conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2008), vol.1

作者： A. MEUNKAEWJINDA P. KUMSAWAT K. ATTAKITMONGCOL A. SRIKAEW Robotics & Automation Research Unit for Real-World APplications Suranaree University of Technology Nakhon Ratchasima THAILAND

Vegetables and fruits are the most important export agricultural products of thailand. In order to obtain more value-added products, a product quality control is essentially required. Many studies show that quality of agricultural products may be reduced from many causes. One of the most important factors of such quality is plant diseases. Consequently, minimizing plant diseases allows substantially improving quality of the products. this work presents automatic plant disease diagnosis using multiple artificial intelligent techniques. the system can diagnose plant leaf disease without maintaining any expertise once the system is trained. Mainly, the grape leaf disease is focused in this work. the proposed system consists of three main parts: (i) grape leaf color segmentation, (ii) grape leaf disease segmentation, and (iii) analysis & classification of diseases. the grape leaf color segmentation is pre-processing module which segments out any irrelevant background information. A self-organizing feature map together with a back-propagation neural network is deployed to recognize colors of grape leaf. this information is used to segment grape leaf pixels within the image. then the grape leaf disease segmentation is performed using modified self-organizing feature map with genetic algorithms for optimization and support vector machines for classification. Finally, the resulting segmented image is filtered by Gabor wavelet which allows the system to analyze leaf disease color features more efficient. the support vector machines are then again applied to classify types of grape leaf diseases. the system can be able to categorize the image of grape leaf into three classes: scab disease, rust disease and no disease. the proposed system shows desirable results which can be further developed for any agricultural product analysis/inspection system.

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