In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

Soils that cause effective damages to engineer structures (such as pavement and foundation) are called problematic or difficult soils (include collapsible soil, expansive soil, etc.). These damages occur due to poor or unfavorited engineering properties, such as low shear strength, high compressibility, high volume changes, etc. In the case of expansive soil, the problem of the shrink-swell phenomenon, when the soil reacts with water, is more pronounced. To overcome such problems, soils can be treated or stabilized with many stabilization ways (mechanical, chemical, etc.). Such ways can amend the unfavorited soil properties. In this review, the pozzolanic materials have been selected to be presented and discussed as chem

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The adsorption process of 5-Fluorouracil (5FU) drugs on Aluminum nitride nanotubes surface (AlNNTs) have been evaluated through density functional theory (DFT). The DFT results show that the interaction of AlNNTs with the F atoms of 5FU drugs is strong due to the fact that the amount of adsorption energy was about − 29.65 kcal.mol−1. Conversely, the interaction of the 5FU through O atoms with the AlNNTs was weaker due to the lower value of adsorption energy. Also, based on the values of Gibbs free energy, the 5FU adsorption on the surfaces of AlNNTs was spontaneous. In addition, based on natural bond orbital (NBO) analysis, the direction of charge transfer was from fluorine’s σ orbitals of the drug to nitrogen’s and aluminum’s n*

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a