This paper proposes a new hybrid preference structure combining strength of preference and probabilistic preference within the Graph Model for Conflict Resolution (GMCR) for two Decision-Makers (DMs). This novel prefe...
详细信息
The worldwide need for sustainable energy solutions has continued to attract the attention of researchers. One vital means for such provision is the harvesting of energy using various methods. This study therefore rev...
详细信息
Green Hydrogen (GH) has emerged as a very promising medium for transporting environmentally friendly energy. The integration of H2-based energy capacity frameworks and fuel cells with other sustainable energy sources ...
详细信息
This study works on scalable formation control of general linear system agents which based on self-loop Laplacian method. Self-loop Laplacian method for scalable formation is used when it is desired that the initial s...
详细信息
ISBN:
(数字)9798331508616
ISBN:
(纸本)9798331508623
This study works on scalable formation control of general linear system agents which based on self-loop Laplacian method. Self-loop Laplacian method for scalable formation is used when it is desired that the initial states of agents and communication topology of agents affects the formation size directly. Proof is provided demonstrating that the self-loop Laplacian matrix shares spectral properties with the standard Laplacian matrix, and the two can be related through a transformation matrix. Existing works on scalable formation mostly focused on single and double integrator agents, particularly where the control input algorithm uses self-loop Laplacian matrix. Extending the work on self-loop Laplacian matrix, this study proposes a control input algorithm for agents in linear system dynamics. The algorithm uses both self-loop Laplacian formulation and general linear system consensus methods, and the stability of the whole system is proven using Lyapunov direct method. Two numerical examples with 4 and 5 agents are shown to verify the result.
This paper deals with the direct kinematic analysis of a hip exoskeleton with 3 Degrees of Freedom (DoF), to assist users in walking. A methodology based on the Denavit Hartenberg (D-H) convention is presented, in the...
详细信息
Every human being has the basic need for clean drinking water, however 1.1 billion people worldwide do not have access to it. While there are other methods for purifying water, including filtration, reverse osmosis, U...
详细信息
This paper presents the dynamic modelling and end effector position control of a soft endoscope. Soft endoscope system under study consists mainly of a pneumatic driven soft actuator (PDSA) with four independently cha...
详细信息
ISBN:
(数字)9798350394245
ISBN:
(纸本)9798350394252
This paper presents the dynamic modelling and end effector position control of a soft endoscope. Soft endoscope system under study consists mainly of a pneumatic driven soft actuator (PDSA) with four independently chambers. Recurrent neural network (RNN) and dynamic back propagation (DBP) training algorithm are used to obtain PDSA dynamic model. PDSA position controller is based on a feedforward neural network (FNN) and it is trained using PDSA closed loop system (CLS) and DBP training algorithm. CLS stability analysis concludes that it is not possible control PDSA end effector position using one position controller for different end effector initial and desired positions. Fuzzy logic methodology is used to integrate several positions controllers in a one controller valid for all operation range. The controller implementation and close loop system simulation are performed in MATLAB for different end effector desired position to validate system performance in all range of operation.
There are many problems faced by people who stand for hours at billing counter after shopping, even though crowds are avoided everywhere, shopping mall billing queue isn't reducing since ages. Since the world reli...
详细信息
ISBN:
(数字)9798331540661
ISBN:
(纸本)9798331540678
There are many problems faced by people who stand for hours at billing counter after shopping, even though crowds are avoided everywhere, shopping mall billing queue isn't reducing since ages. Since the world relies on automation today, everyone has to automate processes which consumes time, money and efforts wherever possible. The technique related with the use of Raspberry Pi, LCD display and Webcam helps the people to bill the groceries within the shopping cart. It reduces consumption of time and their energy can be conserved which can't happen when they stand in a queue for billing process. User have to scan the object in front of webcam and LCD display allows them to add purchased items along with their price and quantity. They can also remove the product fromthe cart and it will be automatically removed. At the end of process, payment can be made online using a QR code or UPI. The Bill will be generated to their respective mail or it will be sent as SMS. User have to register or Log in when they start shopping. Automatic detection is possible without any inspection behind. The model is much portable and does not face any problem in its operation. When compared with the existing methods the processor, display along with its webcam accuracy is much better, it does not require complete continuous guidance and maintenance upon its usage. The need to push the cart has been eliminated as the cart can move along/follow the user autonomously.
This paper introduces an experimental method to detect the motion of an electrostatic Micro-Electro-Mechanical Systems (MEMS) resonator in aqueous media. The resonator comprises a micro cantilever beam subject to elec...
This paper introduces an experimental method to detect the motion of an electrostatic Micro-Electro-Mechanical Systems (MEMS) resonator in aqueous media. The resonator comprises a micro cantilever beam subject to electrostatic actuation through a side electrode. A Finite Element Method (FEM) model of the resonator is developed to determine the in-plane mode shapes and their natural frequencies in order to facilitate the experimental study. The motion of the resonator lead to variations in its capacitance and induce a current. The developed experiments demonstrate that motion-induced current can be measured and analyzed to detect the motion of the resonator's higher-order modes and can be used in chemical sensing.
Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as...
详细信息
ISBN:
(数字)9798350368918
ISBN:
(纸本)9798350368925
Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as it can accurately estimate the distance to the detected objects. In current developments technologies such as stereo cameras are more popular for a more accurate depth estimation. The process for object detection consists of a combination of classification, localization, and segmentation. Deep convolutional neural networks are the basis of object detection. The methods for object detection are divided into two categories namely the Region Proposal-based method such as RCNN, and the Classification-based method which provides for methods such as YOLO and MobileNet. As a part of the research conducted by the National Research and Innovation Agency (BRIN) on Automatic Micro Electric Vehicles or MEVi, this paper analyzed and compared the performance of several CNN models for object detection as well as the performance of depth sensing using ZED stereo camera which was used for the autonomous system in MEVi. Among several models that had been compared, YOLO v8 model demonstrates high accuracy and moderate speed as indicated by its high mAP (0.50) and FPS (38.46). Based on depth sensing results, the accuracy of distance measurement also depended on brightness and environment with the average of accuracy achieved indoors was 98.2% and outdoors was 96.3%.
暂无评论