Liquid crystal elastomers (LCEs) offer potentially programmable actuation through precise molecular alignment, making them ideal for microactuators in soft robotics and optical systems. However, achieving precise micr...
详细信息
The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application ***,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)technology...
详细信息
The correction of Light Detection and Ranging(LiDAR)intensity data is of great significance for enhancing its application ***,traditional intensity correction methods based on Terrestrial Laser Scanning(TLS)technology rely on manual site setup to collect intensity training data at different distances and incidence angles,which is noisy and limited in sample quantity,restricting the improvement of model *** overcome this limitation,this study proposes a fine-grained intensity correction modeling method based on Mobile Laser Scanning(MLS)*** method utilizes the continuous scanning characteristics of MLS technology to obtain dense point cloud intensity data at various distances and incidence ***,a fine-grained screening strategy is employed to accurately select distance-intensity and incidence angle-intensity modeling ***,based on these samples,a high-precision intensity correction model is established through polynomial fitting *** verify the effectiveness of the proposed method,comparative experiments were designed,and the MLS modeling method was validated against the traditional TLS modeling method on the same test *** results show that on Test Set 1,where the distance values vary widely(i.e.,0.1–3 m),the intensity consistency after correction using the MLS modeling method reached 7.692 times the original intensity,while the traditional TLS modeling method only increased to 4.630 times the original *** Test Set 2,where the incidence angle values vary widely(i.e.,0○–80○),the MLS modeling method,although with a relatively smaller advantage,still improved the intensity consistency to 3.937 times the original intensity,slightly better than the TLS modeling method’s 3.413 *** results demonstrate the significant advantage of the modeling method proposed in this study in enhancing the accuracy of intensity correction models.
Autism spectrum disorder(ASD)is a multifaceted neurological developmental condition that manifests in several *** all autistic children remain undiagnosed before the age of *** problems affecting face features are oft...
详细信息
Autism spectrum disorder(ASD)is a multifaceted neurological developmental condition that manifests in several *** all autistic children remain undiagnosed before the age of *** problems affecting face features are often associated with fundamental brain *** facial evolution of newborns with ASD is quite different from that of typically developing *** recognition is very significant to aid families and parents in superstition and *** facial features from typically developing children is an evident manner to detect children analyzed with ***,artificial intelligence(AI)significantly contributes to the emerging computer-aided diagnosis(CAD)of autism and to the evolving interactivemethods that aid in the treatment and reintegration of autistic *** study introduces an Ensemble of deep learning models based on the autism spectrum disorder detection in facial images(EDLM-ASDDFI)*** overarching goal of the EDLM-ASDDFI model is to recognize the difference between facial images of individuals with ASD and normal *** the EDLM-ASDDFI method,the primary level of data pre-processing is involved by Gabor filtering(GF).Besides,the EDLM-ASDDFI technique applies the MobileNetV2 model to learn complex features from the pre-processed *** the ASD detection process,the EDLM-ASDDFI method uses ensemble techniques for classification procedure that encompasses long short-term memory(LSTM),deep belief network(DBN),and hybrid kernel extreme learning machine(HKELM).Finally,the hyperparameter selection of the three deep learning(DL)models can be implemented by the design of the crested porcupine optimizer(CPO)*** extensive experiment was conducted to emphasize the improved ASD detection performance of the EDLM-ASDDFI *** simulation outcomes indicated that the EDLM-ASDDFI technique highlighted betterment over other existing models in terms of numerous performance measures.
Delay-sensitive applications are becoming more and more in demand as a result of the development of information systems and the expansion of communication in cloud computing technologies. Some of these requests will b...
详细信息
Chronic renal disease is the term used to describe kidney function that gradually declines. The kidneys’ final byproduct of eliminating waste and surplus fluid from the bloodstream is urine. Abnormal accumulations of...
详细信息
In today's era, the convergence of modern technology and healthcare has paved the path for novel diseases prediction and prevention technologies. Brain strokes, a major public health concern around the world, nece...
详细信息
The Internet Of Things (IoT) is a network of heterogeneous nodes that exchange data and critical information amongst themselves with minimum human intervention. The utility of this technology is large, thus it is used...
详细信息
Sleep is an essential time for body recovery and healthy living. Therefore, sleep monitoring for health management is important. The gold-standard method for evaluating sleep is polysomnography (PSG), and physicians s...
详细信息
Recently, there has been interest in classifying emotions using audio inputs and machine learning methods. Because a single statement might be delivered in a variety of emotional circumstances, textual data alone is i...
详细信息
This research work explores the effects of dry, liquid N2-based cryogenic cooling and cryogenic plus MQL hybrid strategy on surface roughness, rake surface temperature, principal cutting-edge temperature, auxiliary cu...
详细信息
暂无评论