Fake news and its significance carried the significance of affecting diverse aspects of diverse entities,ranging from a city lifestyle to a country global relativity,various methods are available to collect and determ...
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Fake news and its significance carried the significance of affecting diverse aspects of diverse entities,ranging from a city lifestyle to a country global relativity,various methods are available to collect and determine fake *** recently developed machine learning(ML)models can be employed for the detection and classification of fake *** study designs a novel Chaotic Ant Swarm with Weighted Extreme Learning Machine(CAS-WELM)for Cybersecurity Fake News Detection and *** goal of the CAS-WELM technique is to discriminate news into fake and *** CAS-WELM technique initially pre-processes the input data and Glove technique is used for word embed-ding ***,N-gram based feature extraction technique is derived to gen-erate feature ***,WELM model is applied for the detection and classification of fake news,in which the weight value of the WELM model can be optimally adjusted by the use of CAS *** performance validation of the CAS-WELM technique is carried out using the benchmark dataset and the results are inspected under several *** experimental results reported the enhanced outcomes of the CAS-WELM technique over the recent approaches.
Modern digital technology breakthroughs include machine learning. It's used in medical, image processing, manufacturing, aviation, autonomics, and more. Our main goal is to find an automated system that can accura...
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Animal laboratory experiments have important role in the development of specialist science related to health, biology, and pharmacy. To carry out the trial of medicines, the researchers require an animal laboratory ex...
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ISBN:
(数字)9798350363432
ISBN:
(纸本)9798350363449
Animal laboratory experiments have important role in the development of specialist science related to health, biology, and pharmacy. To carry out the trial of medicines, the researchers require an animal laboratory experiment. In this case, mice and white rat which have the same basic properties, mammals as human used to find out whether the medicine reacts and suitable for curing various diseases. However, the research still experiences challenges in the process of selecting rats or mice that are suitable for experiments because it is still conducted manually, which still requires expertise from the researcher. This research proposes a system that can detect laboratory animals based on body weight, therefore it can help researchers in sorting out animal laboratory. This system is designed using load cell sensor, HX711 module, ESP32, LCD, motor servo, photodiode sensors as counter circuit. The system is linked to desktops and smartphones by utilizing IoT technology for reporting, monitoring, and manual control. The test results indicate that the accuracy of the weight measurement system still has a difference in the weight measurement range of 0.01 grams to 0.5 grams. Meanwhile, the percentage of success of the animal weight classification system reached 95% in 20 tests.
Recent achievements in the domain of computational intelligence and robotics trigger development and automation in various industry branches. One such domain is the architecture and construction, where the challenges ...
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ISBN:
(数字)9788362065486
ISBN:
(纸本)9798350373806
Recent achievements in the domain of computational intelligence and robotics trigger development and automation in various industry branches. One such domain is the architecture and construction, where the challenges related to efficient measurement, progress monitoring, maintenance, or verification of the agreement between a design and a built object, remain unsolved and may benefit from modern image and signal processing technology. Recognition of objects such as, e.g., walls, doors, or furniture in 3D scenes, allows the creation of so-called digital twins of the real-world environment. Within this study, we developed a series of deep learning models dedicated to semantic segmentation of point clouds representing interiors of buildings. Such representations are usually collected with expensive high-precision LiDAR scanners. The available neural network models, published in the literature, were, accordingly, trained using either such laser data or, alternatively, by the help of the synthetic ones. Our motivation was thus to enable semantic segmentation of RGBD point clouds acquired with a much cheaper sensor, i.e. a depth camera. In the absence of open real datasets, we propose to perform transfer learning and show that it is feasible to achieve reasonable segmentation accuracy on depth-camera data using a model pretrained on LiDAR scans.
Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such networ...
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Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely *** the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power *** optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in *** paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in *** energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient *** link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of *** simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing *** evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.
The paper provides a synoptic view of portable biomedical point-of-care devices for blood coagulation detection, emphasising the state-of-the-art technology adopted and its use in the medical industry. These devices g...
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Mycobacterium tuberculosis causes tuberculosis (TB), a bacterial illness. Although germs are most typically found in the lungs, they can affect other sections of the body as well. Tuberculosis is one of the primary ca...
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The recent advancements and a flurry of deep learning architectures in the fields of computer vision and natural language processing have greatly benefited the task of creating natural language descriptions for images...
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With the increasing popularity of live streaming platforms, there is an imperative need for robust methods for identifying individuals in real-time. The proposed system utilizes Convolutional Neural Networks (CNN) com...
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Recently,Internet of Medical Things(IoMT)has gained considerable attention to provide improved healthcare services to *** earlier diag-nosis of brain tumor(BT)using medical imaging becomes an essential task,auto-mated...
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Recently,Internet of Medical Things(IoMT)has gained considerable attention to provide improved healthcare services to *** earlier diag-nosis of brain tumor(BT)using medical imaging becomes an essential task,auto-mated IoMT and cloud enabled BT diagnosis model can be devised using recent deep learning *** this motivation,this paper introduces a novel IoMT and cloud enabled BT diagnosis model,named *** IoMTC-HDBT model comprises the data acquisition process by the use of IoMT devices which captures the magnetic resonance imaging(MRI)brain images and transmit them to the cloud ***,adaptive windowfiltering(AWF)based image preprocessing is used to remove *** addition,the cloud server executes the disease diagnosis model which includes the sparrow search algorithm(SSA)with GoogleNet(SSA-GN)*** IoMTC-HDBT model applies functional link neural network(FLNN),which has the ability to detect and classify the MRI brain images as normal or ***finds useful to generate the reports instantly for patients located in remote *** validation of the IoMTC-HDBT model takes place against BRATS2015 Challenge dataset and the experimental analysis is car-ried out interms of sensitivity,accuracy,and specifi*** experimentation out-come pointed out the betterment of the proposed model with the accuracy of 0.984.
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