Understanding the oviposition behaviour of mosquitoes is crucial for developing a vector surveillance program and a control strategy. To study this behaviour, in situ observation is one of the ways to determine the de...
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ISBN:
(数字)9798331528553
ISBN:
(纸本)9798331528560
Understanding the oviposition behaviour of mosquitoes is crucial for developing a vector surveillance program and a control strategy. To study this behaviour, in situ observation is one of the ways to determine the details of oviposition preference. However, this method of data collection is time-consuming and labour-intensive, and the presence of human observers often causes odour nuisance, which can lead to bias. We demonstrated a novel method that able to study this behaviour, which we named Automatic Mosquito Oviposition Study System (AMOSS) that automatically detects and measures mosquito oviposition activity and collects data without human intervention. the system consists of a microcomputer with an infrared camera that records time-lapse video in a dark environment, and a post-record processing component for detecting the activity by using a deep learning algorithm. We used the system to study the oviposition activity of Aedes mosquitoes on a disposable mask and the result was consistent withthe standard oviposition testing - egg counting bioassay. this technology could be an additional tool to determine mosquito preference for a particular substrate, which is very helpful in developing a push-and-pull strategy for mosquito control.
this study focuses on a stabilizing control for the electrically-assisted bicycle equipping a power-steering system. We have developed the power-steering system for the bicycle on whose front seat a child sits. the po...
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ISBN:
(纸本)9781479952007
this study focuses on a stabilizing control for the electrically-assisted bicycle equipping a power-steering system. We have developed the power-steering system for the bicycle on whose front seat a child sits. the power-steering system has the ability to recover the maneuverability of handlebars compromised by a child sitting on the front seat. the power-steering system has also capability to realize automatic stabilization. Hence, in this paper, 1) a simple inverted pendulum model is introduced to simulate the behavior of the bicycle, and 2) a stabilizing control is designed based on the simple model.
In the modern world there is an intensive increasing of global mobile data traffic in multi-service mobile networks, in particular networks based on LTE technology. In 5th generation (5G) wireless network some of the ...
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In the modern world there is an intensive increasing of global mobile data traffic in multi-service mobile networks, in particular networks based on LTE technology. In 5th generation (5G) wireless network some of the key drivers of data traffic growth are machine type communications (MTC) or machine-to-machine (M2M) services. Various MTC devices such as smart meters and sensors form the basis of smart cites and homes. Expanding the range of services provided through the mobile networks leads to increasing of quality of service (QoS) requirements by the mobile operators. It is necessary to use the frequency spectrum as efficiently as possible, to provide the services withthe required QoS level. therefore, in this paper we investigate the question how to more efficiently transmit the information in particular from MTC devices via a wireless network, which is primarily used for human-to-human (H2H) communications. the efficiency of data transmission is affected by the applied radio resource management (RRM) mechanism and the selected RRM scheduler. Also, the transfer of information depends on such secondary parameters as the MTC devices positons within a cell, the uniqueness of the terrain, etc. these characteristics have a significant effect on the reduction in power density (attenuation) or so-called path loss (PL). We propose an approach for analyzing the performance measures of one of the 3GPP wireless network models by implementing different PL scenarios. For more eDcient usage of frequency spectrum we consider scheme model within licensed shared access (LSA) framework.
this paper demonstrates the design and fabrication of an autonomous agricultural drone for sowing seeds in the crop fields. In order to reduce the seeds sowing time, a seed sowing device has been specially developed a...
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this paper demonstrates the design and fabrication of an autonomous agricultural drone for sowing seeds in the crop fields. In order to reduce the seeds sowing time, a seed sowing device has been specially developed and integrated withthe quad-copter agricultural drone. the drone consists of a global positioning system (GPS) and an auto-pilot device, the flight path of which is controllable from the ground control station. the flying path can be programmed in the Mission-Planner software before the drone flight starts and can be altered if required. In addition, the agricultural drone is manually controllable using a long-range remote controller. It can fly under variable altitude where the maximum altitude is - 500 meter. the drone can fly at a maximum speed of 14.76 km/hour. the maximum seeds sowing rate of 498 m~2/min is achieved for an altitude of 5 meter. At this seeds sowing rate, the mode value of seeds' distance is ～2.5cm. We can controlthe seeds sowing rate by controlling various operational modes of the seeds sowing device. the proposed agricultural drone will reduce the seeds sowing time significantly and contribute towards the automation of the agricultural sector.
Cognitive robots are intelligent systems that learn from their environment, adapt to dynamic changes, and make decisions without a human's direct intervention. this research studies the integration of Reinforcemen...
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ISBN:
(数字)9798350389609
ISBN:
(纸本)9798350389616
Cognitive robots are intelligent systems that learn from their environment, adapt to dynamic changes, and make decisions without a human's direct intervention. this research studies the integration of Reinforcement Learning in cognitive robots with Q-Learning for autonomous path planning. the study addresses the most critical issues in traditional A* and Dynamic Programming algorithms by devising path-planning techniques, mainly the lack of adaptability and computational efficiency in real-time and unpredictable environments. Our approach is based on Q-Learning, which is a model-free RL algorithm allowing the robots to find paths autonomously by optimizing their paths and avoiding obstacles. the Q-Learning algorithm provides the possibility of learning optimal policies for the robot through iterative interaction with its environment balanced between exploration and exploitation of the decision process. A reward system is utilized by the proposed model, encouraging the robot to explore shorter, collision-free paths and adjust based on feedback in real time from its surroundings. the model was found to be significantly better than its counterparts. In this context, as indicated, the Q-Learning model runs at 11.5 seconds, faster than A* at 18.3 seconds and Dynamic Programming at 16.7 seconds, yet with an accuracy of 94% and was found to have the highest collision avoidance rate at 98%. Additionally, the adaptability of the model about the environment presents a marked difference in terms of path length optimization, having done so with a mean path length of 12.3, compared to approaches or models. the robustness and scalability of the Q-Learning model make it highly applicable in real-world applications.
Considering constantly increasing demand for shift from mass production to mass customization and the need to maintain high level of automation despite permanent changes in manufacturing technologies and tools new app...
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ISBN:
(纸本)9781479966509
Considering constantly increasing demand for shift from mass production to mass customization and the need to maintain high level of automation despite permanent changes in manufacturing technologies and tools new approaches and solutions have to be provided in manufacturing. Cyber-Physical Systems and Industrial Internet of things are enabling smart manufacturing to tackle the challenge of data processing, integration and interpretation, but beyond uniformed data collection and visualization. the cognitive approach is argued to introduce brain and biologically-inspired algorithms capable to better adapt industrial systems for unforeseen conditions. Such approach should provide flexible and robust solution for manufacturing systems, enabling new level of adaptability and re-configurability in the system by self-X capabilities. In this paper contemporary solutions applicable for introduction of cognitive capabilities in manufacturing systems are studied and the architecture for cognitive manufacturing system employing benefits of Industrial Internet and Cognitive control is proposed.
the purpose of this study was to adapt a multipurpose robotic arm for gait rehabilitation. An advantage of this approach is versatility: a robotic arm can be attached to almost any point on the body to assist with low...
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ISBN:
(纸本)9781424492695
the purpose of this study was to adapt a multipurpose robotic arm for gait rehabilitation. An advantage of this approach is versatility: a robotic arm can be attached to almost any point on the body to assist with lower- and upper-extremity rehabilitation. this may be more cost-effective than purchasing and training rehabilitation staff to use several specialized rehabilitation robots. Robotic arms also have a more human-like morphology, which may make them less intimidating or alien to patients. In this study a mechanical interface was developed that allows a fast, secure, and safe attachment between a robotic arm and a human limb. the effectiveness of this interface was assessed by having two healthy subjects walk on a treadmill with and without a robotic arm attached to their legs. the robot's ability to follow the subjects' swinging legs was evaluated at slow and fast walking speeds. Two different control schemes were evaluated: one using the standard manufacturer-provided control algorithm, and another using a custom algorithm that actively compensated for robot-human interaction forces. the results showed that both robot control schemes performed well for slow walking. there were negligible differences between subjects' gait kinematics with and without the robot. During fast walking withthe robot, similar results were obtained for one subject;however, the second subject demonstrated noticeable gait modifications. Together, these results show the feasibility of adapting a multipurpose robotic arm for gait rehabilitation.
A In-depth mining and analysis of traffic big data can help the government better manage urban traffic problems. However, most of the current transportation systems are based on big data prediction and control of tran...
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ISBN:
(数字)9781728185750
ISBN:
(纸本)9781728185767
A In-depth mining and analysis of traffic big data can help the government better manage urban traffic problems. However, most of the current transportation systems are based on big data prediction and control of transportation facilities, and lack of mechanism research integrating multi-humanities fields, which is not conducive to fundamentally solving urban transportation problems. Based on virtual geographic environments (VGEs), this paper proposes an urban traffic decision-making analysis (UTDA) platform, which supports the storage of multi-source heterogeneous data, the integration of multi-disciplinary models, the display of multi-form visual analysis results and the collaborative work among multiple users. then, a platform framework based on hybrid cloud was built and the collaboration mechanism within the platform was described in detail. then, taking Beijing's multi-source traffic big data as an example, a prototype system was implemented to verify the feasibility of the coordination mechanism and system framework, and the ability of the system to solve urban traffic problems. Finally, this paper discusses the impact of emerging technology on the development of urban traffic decision analysis platform.
this paper proposes an unsupervised learning framework based on the Point-Move network to address the issue of converting point cloud data to high-quality surface meshes in the field of 3D reconstruction. By utilizing...
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ISBN:
(数字)9798350386943
ISBN:
(纸本)9798350386950
this paper proposes an unsupervised learning framework based on the Point-Move network to address the issue of converting point cloud data to high-quality surface meshes in the field of 3D reconstruction. By utilizing an end-to-end unsupervised learning approach, the network directly learns the signed distance function (SDF) of 3D shapes from the original point cloud data, enabling a direct conversion from point cloud data to high-quality surface meshes. Experimental validation was conducted using high-quality samples from the ShapeNet and ModelNet datasets, and the accuracy was evaluated using the average distance between the point cloud and the mesh as an evaluation metric. the experimental results demonstrate that the proposed method achieves excellent performance with high precision, providing new ideas and methods for the development of 3D reconstruction technology.
By the year 2030, there is expected an increase in hip arthroplasties between 43% and 70% compared to 2014. For this reason, a novel investigation was conducted in 2023 under the supervision of the Professional School...
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ISBN:
(数字)9798350351378
ISBN:
(纸本)9798350351385
By the year 2030, there is expected an increase in hip arthroplasties between 43% and 70% compared to 2014. For this reason, a novel investigation was conducted in 2023 under the supervision of the Professional School of Mechatronic Engineering at Ricardo Palma University, focusing on a proof of concept for the design of a hip prosthesis using mechanics of materials analysis and finite element method. the mechanical design of the implant indicated that to withstand a weight load of Q=2300 N and achieve resulting displacements (URES) less than 0.008 mm, the minimum safety factor required is 3.93, as a result of the finite element analysis (FEA). the electronic design, consisting of an Arduino Mega 2560, two potentiometers, two MG996R servo motors, a MPU6050 accelerometer, and an OLED display, resulted in a voltage consumption of 5V separately for the control board and the others sensors and actuators. SolidWorks was used for stress studies, URES, and safety factor analysis in this design. Von Mises stress analysis revealed a maximum of 87.8 MPa at the stem-joint junction, while URES analysis determined a maximum displacement of 0.008 mm. In conclusion, favorable results were achieved. For future research, it is proposed to consider other geometries for the cross-section, optimizing the design, and conducting experimental studies of the loads.
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