The cutting-edge telemedicine program presents a game-changing alternative for patients seeking ENT (ear, nose, and throat) consultations from a distant location. Utilizing the capabilities of Raspberry Pi devices, po...
详细信息
ISBN:
(数字)9798350361155
ISBN:
(纸本)9798350361162
The cutting-edge telemedicine program presents a game-changing alternative for patients seeking ENT (ear, nose, and throat) consultations from a distant location. Utilizing the capabilities of Raspberry Pi devices, powerful artificial intelligence, and cloud computing, the system allows otoscopic tests to be performed without interruption while securely transmitting data to the cloud. On a web-based platform, interactive patient-professional consultations are made possible via real-time communication, which is made possible by WebRTC. Cloud services are very important because of their ability to provide scalable storage as well as AI-driven diagnostics for accurate evaluations. The system complies with the requirements for healthcare compliance, emphasizes security and privacy, and features encryption from beginning to finish. This integrated approach promises scalability, reliability, and advanced diagnostic capabilities, and it reshapes the landscape of remote ENT care with accessible and technologically advanced healthcare solutions. With a user-friendly interface for patients and a cloud-hosted application for healthcare professionals, this integrated approach provides patients with advanced healthcare solutions.
Reluctance actuators (RA) can replace the current Lorentz actuators in the next generation of positioning and scanning motion systems, such as the wafer stage in lithography machines. However, the nonlinear output for...
详细信息
ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
Reluctance actuators (RA) can replace the current Lorentz actuators in the next generation of positioning and scanning motion systems, such as the wafer stage in lithography machines. However, the nonlinear output force characteristic and the gap dependency of the RA are the main challenges in using the RA to drive motion systems. In this paper, we design a two-loop control approach for a reluctance actuator motion system (RAMS) to achieve tracking performance for a desired motion profile. First, the current control loop linearizes the RA under different conditions. Next, the position control loop is designed using a PID control based on an extended-high gain observer to achieve a desired motion profile considering unknown dynamics in the system. The simulation results show the efficiency of the proposed current control in linearizing the dynamic behavior under different desired forces and nominal air gaps and achieving a frequency response similar to the spring-mass-damper system. Moreover, the position control can achieve different long-stroke and short-stroke motion profiles with different amplitudes and ranges of motion.
More than 2 million people have died in the world in 2019 exposed to hazard substances. In this context, it is of paramount importance to deliver effective systems to help minimizing such number of dead. The usage of ...
详细信息
Portable electronic gadgets and high-performance computing systems have increased demand for low-power, high-performance integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to mil...
详细信息
ISBN:
(数字)9798350388916
ISBN:
(纸本)9798350388923
Portable electronic gadgets and high-performance computing systems have increased demand for low-power, high-performance integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to millions of transistors on a chip, is leading these efforts. This research investigates low-power, high-performance VLSI circuit construction methods. We start with VLSI design fundamentals and power management and performance optimization concerns. The constraints of traditional VLSI design methods in satisfying current electronics' strict requirements are examined. VLSI design methodology development and evaluation are the focus of this research. Advanced power optimization methods include MTCMOS, adaptive body biasing, and power gating. We also study clock tree improvement, signal integrity enhancement, and new materials and device topologies for high performance. In addition, we study how machine learning techniques automate and optimize circuit placement, routing, and timing in VLSI design. AI handles the complexity of current VLSI designs and finds optimal design parameters for minimal power and high performance. Scaling VLSI circuits to newer technology nodes raises process variance, leakage current, and thermal management difficulties, which the research tackles. These issues can be overcome with new ways to keep VLSI circuits scaling while preserving performance and power efficiency. Finally, case studies and experimental findings show that the offered methods work in real-world applications. These findings demonstrate significant power usage and performance benefits over typical VLSI design. In conclusion, our research advances VLSI technology by developing low-power, high-performance integrated circuits. The proposed VLSI design methods and solutions could lead to more efficient and powerful electronic systems.
The combination of iot and AI technologies in the future promises to disrupt agriculture positively while trying to solve problems affecting the sector through embracing technological advances. The following paper foc...
详细信息
ISBN:
(数字)9798331540661
ISBN:
(纸本)9798331540678
The combination of iot and AI technologies in the future promises to disrupt agriculture positively while trying to solve problems affecting the sector through embracing technological advances. The following paper focuses on the development of an iot and AI framework for enhancing practices in agriculture through real-time control and smart control. Wireless iot sensors are placed in the farms to monitor important parameters of farms like moisture content, temperature, humidity etc and health of crops. Consequently, data is harvested to assist with accurate irrigation, climatic regulation, and early diagnosis of disease. From the experimental results observed it became clear that resource utilization was boosted by 25% of lesser water usage while crop yields were boosted by as much as 30%. It also early identifies crop diseases, hence cutting crop losses by 15%. Such is crucial to stress that the results obtained reveal the ability of the system to improve the sustainability and productivity of agriculture. Future work will comprise the fine-tuning of the AI model, enhancement of sensors, and their incorporation with other smart technologies besides adapting this strategy for various agricultural conditions, hence the importance of smart solutions in the promotion of eco-friendly farming.
Cloud computing (CC) platform not only offers resource sharing for users and also provide many on-demand services. business procedures can be managed to utilize the workflow technology on the cloud which signifies mos...
Cloud computing (CC) platform not only offers resource sharing for users and also provide many on-demand services. business procedures can be managed to utilize the workflow technology on the cloud which signifies most of the problems in employing the resources in an effectual approach because of the dependencies between the tasks. Task scheduling (TS) in a CC platform applies to the procedure of effectively allocating resources computing to tasks or jobs submitted to the CC environment. In a cloud platform, tasks are separated as smaller subtasks that are applied in parallel on distinct machines. There are many features to consider if the TS is in CC platform, comprising the kind of tasks like resources cost, resources required, and resources availability. Therefore, this study presents a Hybrid Competitive Swarm Optimization Algorithm based Task Scheduling (HCSOA-TS) technique in the CC platform. The presented HCSOA-TS technique schedules the tasks proficiently in such a way that maximum resource utilization and performance gets accomplished. In the design of HCSOA, Cauchy mutation operator is included in the CSO algorithm and thereby improves the overall performance. In addition, the derivation of the fitness function by the HCSOA-TS technique undergoes optimal scheduling process and decreases energy usage. The experimental result analysis of the HCSOA-TS technique is tested using a series of measures. The comprehensive comparison study highlighted the improvements of the HCSOA-TS technique over recent approaches.
AI is making labour-intensive HRM operations like hiring, performance review, and employee engagement more efficient and effective. The incorporation of AI technology in HRM could change several sectors. Through effic...
详细信息
ISBN:
(数字)9798331508456
ISBN:
(纸本)9798331508463
AI is making labour-intensive HRM operations like hiring, performance review, and employee engagement more efficient and effective. The incorporation of AI technology in HRM could change several sectors. Through efficient applicant sourcing, screening, and selection, AI-driven solutions simplify hiring processes and ensure fair and accurate picks. Performance management using AI-powered solutions provides data-driven feedback and customized development plans to align individual progress with organizational goals. Predictive analytics improve employee engagement by personalizing experiences and meeting needs. The method focuses on preprocessing and model training. Data are cleansed, ordinal and categorical variables encoded, scaling characteristics and engineering features applied, and dimensional homogeneity assured before processing. For model training, the simple and robust one-class SVM technique is used. One-class SVM model outperformed others with 95.28%. This method worked best compared to GAN and GRU models. AI could improve HRM by improving decision-making and offering data-driven solutions. The findings show that the proposed model outperforms current options, providing the framework for HRM AI applications.
Digital multimedia applications have greatly increased in recent years as a result of improvements in network technology, low-cost multimedia devices, intelligent image or video editing software, and widespread accept...
详细信息
bPNN ensemble can significantly improve the generalization ability of knowledge system by training multiple bPNNs and synthesizing their conclusions. It not only helps scientists to study machinery knowledge and neura...
bPNN ensemble can significantly improve the generalization ability of knowledge system by training multiple bPNNs and synthesizing their conclusions. It not only helps scientists to study machinery knowledge and neural computing in depth, but also helps ordinary engineers and technicians to use bPNN technology to solve real-world problems. Ensemble knowledge has become one of the hot spots in the territory of machinery knowledge in recent years, and selective integration method has become an important direction of ensemble knowledge because of its advantages in adaptability, generalization and combination. In this paper, the transcription of multi-tone piano is studied based on bPNN. The corresponding study methods are used in the research. Through the establishment of data graph and algorithm formula, the corresponding study is carried out. From the research, it can be found that the piano transcription efficiency based on bPNN is very high, up to about 90.43%. In the future, people may pay more Focus to the piano study of bPNN.
The presentation summarizes a groundbreaking cognitive training program designed specifically for those who suffer from cognitive impairments or neurodevelopmental abnormalities. The work creates a dynamic platform fo...
详细信息
ISBN:
(数字)9798350371314
ISBN:
(纸本)9798350371321
The presentation summarizes a groundbreaking cognitive training program designed specifically for those who suffer from cognitive impairments or neurodevelopmental abnormalities. The work creates a dynamic platform for immersive and adaptable cognitive training games by combining cutting-edge Convolutional Neural Networks (CNNs) with Raspberry Pi technology. Memory, focus, and ability to think creatively are all qualities directly targeted by these games. The CNN model, trained on a broad dataset, interprets real-time user inputs, delivering quick feedback and altering game complexity depending on an individual’s performance. The incorporation of Raspberry Pi guarantees a solution that is both affordable and easily accessible. The capacity of the system to redefine cognitive rehabilitation by providing a solution that is individualizable, interactive, and broadly deployable is the potential source of the system’s influence. The goal of the work is to make a substantial contribution to the field, which will eventually be to the advantage of users, caregivers, and healthcare professionals and ultimately improve the cognitive well-being of those coping with cognitive issues.
暂无评论