Sudan Prasad Uprety, Seung Ryul Jeong^*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 1-11, 2022, DOI:10.32604/iasc.2022.018757

Abstract Natural Language Understanding and Speech Understanding systems are now a global trend, and with the advancement of artificial intelligence and machine learning techniques, have drawn attention from both the academic and business communities. Domain prediction, intent detection and entity extraction or slot fillings are the most important parts for such intelligent systems. Various traditional machine learning algorithms such as Bayesian algorithm, Support Vector Machine, and Artificial Neural Network, along with recent Deep Neural Network techniques, are used to predict domain, intent, and entity. Most language understanding systems process user input in a sequential order: domain is first predicted, then intent… More >

Jing Sun^1,3,*, Youting Lin², Yangyang Fan⁴, Samantha Ferguson³, Nicholas Buys³, Minyan Sun²

International Journal of Mental Health Promotion, Vol.23, No.3, pp. 417-427, 2021, DOI:10.32604/IJMHP.2021.013098

Abstract Knee instability as a symptom of ligament injury usually only receives attention when it causes pain or impacts patients’ mobility in China. In this study both the physical and psychosocial impact of an innovative approach to treatment, Half-cut Wood Training, was examined. Twenty individuals with knee instability who received Halfcut Wood Training (Intervention group) and twenty two individuals with knee instability who did not receive Half-cut Wood Training (as Control group) participated in the study. The electric WIFI based HBF-306 was used to collect the anthropometry and biomedical data. Symptom severity was assessed by a doctor and through response to… More >

Qingyang Zhou¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 159-174, 2021, DOI:10.32604/cmc.2021.017480

Abstract The existing safety helmet detection methods are mainly based on one-stage object detection algorithms with high detection speed to reach the real-time detection requirements, but they can’t accurately detect small objects and objects with obstructions. Therefore, we propose a helmet detection algorithm based on the attention mechanism (AT-YOLO). First of all, a channel attention module is added to the YOLOv3 backbone network, which can adaptively calibrate the channel features of the direction to improve the feature utilization, and a spatial attention module is added to the neck of the YOLOv3 network to capture the correlation between any positions in the… More >

Shengjie Li, Chaosheng Tang^*

Journal on Artificial Intelligence, Vol.3, No.2, pp. 55-62, 2021, DOI:10.32604/jai.2021.017408

Abstract On the basis of studying the influencing factors of training effect evaluation, this paper constructs an AHP-fuzzy comprehensive evaluation model for farmers’ vocational training activities in Hainan Province to evaluate farmers’ training effect, which overcomes the limitations of traditional methods. Firstly, the content and index system of farmer training effect evaluation are established by analytic hierarchy process, and the weight value of each index is determined. Then, the fuzzy comprehensive evaluation (FCE) of farmer training effect is carried out by using multi-level FCE. The joint use of AHP and FCE improves the reliability and effectiveness of the evaluation process and… More >

Shakeel Ahmed¹, Munazza Ambreen¹, Muneer Ahmad², Abdulellah A. Alaboudi³, Roobaea Alroobaea⁴, NZ Jhanjhi^5,*

Computer Systems Science and Engineering, Vol.38, No.2, pp. 131-140, 2021, DOI:10.32604/csse.2021.016504

Abstract The COVID-19 outbreak severely affected formal face-to-face classroom teaching and learning. ICT-based online education and training can be a useful measure during the pandemic. In the Pakistani educational context, the use of ICT-based online training is generally sporadic and often unavailable, especially for developing English-language instructors’ listening comprehension skills. The major factors affecting availability include insufficient IT resources and infrastructure, a lack of proper online training for speech and listening, instructors with inadequate academic backgrounds, and an unfavorable environment for ICT-based training for listening comprehension. This study evaluated the effectiveness of ICT-based training for developing secondary-level English-language instructors’ listening comprehension… More >

Chung Le Van¹, Trinh Hiep Hoa¹, Nguyen Minh Duc¹, Vikram Puri¹, Tung Sanh Nguyen², Dac-Nhuong Le^3,4,*

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 853-871, 2021, DOI:10.32604/iasc.2021.013732

Abstract Background: Augmented Reality (AR) incorporates both real and virtual objects in real-time environments and allows single and multi-users to interact with 3D models. It is often tricky to adopt multi-users in the same environment because of the devices’ latency and model position accuracy in displaying the models simultaneously. Method: To address this concern, we present a multi-user sharing technique in the AR of the human anatomy that increases learning with high quality, high stability, and low latency in multiple devices. Besides, the multi-user interactive display (HoloLens) merges with the human body anatomy application (AnatomyNow) to teach and train students, academic… More >

Xiaorui Zhang^1,2,*, Hailun Wu¹, Wei Sun¹, Aiguo Song³, Sunil Kumar Jha⁴

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 873-889, 2021, DOI:10.32604/iasc.2021.013541

Abstract Virtual surgery simulation is indispensable for virtual vascular interventional training system, which provides the doctor with visual scene between catheter and vascular. Soft tissue deformation, as the most significant part, determines the success or failure of the virtual surgery simulation. However, most soft tissue deformation model cannot simultaneously meet the requirement of high deformation accuracy and real-time interaction. To solve the challenge mentioned above, this paper proposes a fast and accurate vascular tissue simulation model based on point primitive method. Firstly, the proposed model simulates a deformation of the internal structure of the vascular tissue by adopting a point primitive… More >

Adel Saad Assiri^*

Computer Systems Science and Engineering, Vol.36, No.3, pp. 435-450, 2021, DOI:10.32604/csse.2021.014894

Abstract Artificial neural networks (ANNs) are one of the hottest topics in computer science and artificial intelligence due to their potential and advantages in analyzing real-world problems in various disciplines, including but not limited to physics, biology, chemistry, and engineering. However, ANNs lack several key characteristics of biological neural networks, such as sparsity, scale-freeness, and small-worldness. The concept of sparse and scale-free neural networks has been introduced to fill this gap. Network sparsity is implemented by removing weak weights between neurons during the learning process and replacing them with random weights. When the network is initialized, the neural network is fully… More >

Yajun Zhang^1,*, Jianjun Yi¹, Jiahao Zhang¹, Yuanhao Chen¹, Liang He²

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 425-439, 2021, DOI:10.32604/iasc.2021.013795

Abstract Image recognition algorithms based on deep learning have been widely developed in recent years owing to their capability of automatically capturing recognition features from image datasets and constantly improving the accuracy and efficiency of the image recognition process. However, the task of training deep learning networks is time-consuming and expensive because large training datasets are generally required, and extensive manpower is needed to annotate each of the images in the training dataset to support the supervised learning process. This task is particularly arduous when the image scenes involve randomly stacked objects. The present work addresses this issue by developing a… More >

Prisca Eser^1,*, Thomas Gruber¹, Thimo Marcin¹, Claudia Boeni^1,2, Kerstin Wustmann³, Christina DeLuigi¹, Matthias Greutmann⁴, Daniel Tobler⁵, Markus Schwerzmann³, Matthias Wilhelm¹

Congenital Heart Disease, Vol.16, No.1, pp. 73-84, 2021, DOI:10.32604/CHD.2021.013051

Abstract Background: The purpose of this study was to investigate whether patients with adult congenital heart disease (ACHD) benefit from exercise-based cardiac rehabilitation (CR) short- and long-term with regard to improvement of cardiorespiratory fitness. Methods: Cardiopulmonary exercise tests (CPET) completed by ACHD patients between January 2000 and October 2019 were analysed retrospectively. Linear mixed models were performed for peak oxygen consumption (VO₂) with patients as random effect and age, sex, disease classification, preceding surgery (≤3 months) and preceding CR (≤4 weeks for short term and >4 weeks for long term) as fixed effects. Results: 1056 CPETs of 311 ACHD patients with… More >