Ling Wang¹, Shan Ji², Zhaokang Wang³, Xiaowan Wang^4,*, Ghulam Mohiuddin⁵, Yongjun Ren¹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 221-234, 2022, DOI:10.32604/iasc.2022.027536

Abstract As the data scale exceeds the petabyte level, more and more users outsource their local databases to third-party service providers to save local storage costs and avoid cumbersome local data management. However, because third-party service providers are not fully trusted, they may leak outsourced data and bring security risks to the personal privacy of data users. The service provider may also return incorrect or incomplete query results to the data user. Therefore, in this paper, we propose a Lightweight and Verifiable Multi-keyword Query Scheme for the integrity verification of multi-keyword query of outsourced data. This scheme supports multi-keyword query integrity… More >

Yintong Wang^1,2,*, Yingjie Yang², Haiyan Chen³, Hao Zheng¹, Heyou Chang¹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 371-388, 2022, DOI:10.32604/iasc.2022.027146

Abstract Handwritten Chinese recognition which involves variant writing style, thousands of character categories and monotonous data mark process is a long-term focus in the field of pattern recognition research. The existing methods are facing huge challenges including the complex structure of character/line-touching, the discriminate ability of similar characters and the labeling of training datasets. To deal with these challenges, an end-to-end residual attention handwritten Chinese paragraph text recognition method is proposed, which uses fully convolutional neural networks as the main structure of feature extraction and employs connectionist temporal classification as a loss function. The novel residual attention gate block is more… More >

Wei Fang^1,2,*, Yu Sha¹, Meihan Qi¹, Victor S. Sheng³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 609-622, 2022, DOI:10.32604/iasc.2022.027067

Abstract With the rapid development of personalized services, major websites have launched a recommendation module in recent years. This module will recommend information you are interested in based on your viewing history and other information, thereby improving the economic benefits of the website and increasing the number of users. This paper has introduced content-based recommendation algorithm, K-Nearest Neighbor (KNN)-based collaborative filtering (CF) algorithm and singular value decomposition-based (SVD) collaborative filtering algorithm. However, the mentioned recommendation algorithms all recommend for a certain aspect, and do not realize the recommendation of specific movies input by specific users which will cause the recommended content… More >

Rongrong Ni¹, Xiaofeng Liu^1,*, Yizhou Chen¹, Xu Zhou¹, Huili Cai¹, Loo Chu Kiong²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 149-164, 2022, DOI:10.32604/iasc.2022.026813

Abstract Lonely older adults and persons restricted in movements are apt to cause negative emotions, which is harmful to their mental health. A humanoid robot with audiovisual interactions is presented, which can correspondingly output positive facial expressions to relieve human's negative facial expressions. The negative emotions are identified through an attention-enhanced facial expression recognition (FER) network. The network is firstly trained on MMEW macro-and micro-expression databases to discover expression-related features. Then, macro-expression recognition tasks are performed by fine-tuning the trained models on several benchmarking FER databases, including CK+ and Oulu-CASIA. A transformer network is introduced to process the sequential features engineered… More >

K. Naveen Durai^*, R. Subha, Anandakumar Haldorai

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 467-483, 2022, DOI:10.32604/iasc.2022.026020

Abstract In cloud computing, the processes of load balancing and task scheduling are major concerns as they are the primary mechanisms responsible for executing tasks by allocating and utilizing the resources of Virtual Machines (VMs) in a more optimal way. This problem of balancing loads and scheduling tasks in the cloud computing scenario can be categorized as an NP-hard problem. This problem of load balancing needs to be efficiently allocated tasks to VMs and sustain the trade-off among the complete set of VMs. It also needs to maintain equilibrium among VMs with the objective of maximizing throughput with a minimized time… More >

K. Prathibanandhi^1,*, R. Ramesh², C. Yaashuwanth³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 543-557, 2022, DOI:10.32604/iasc.2022.025860

Abstract The delivery of combined benefits of Alternating Current (AC) motor and Direct Current (DC) Motor makes the Brushless Direct Current (BLDC) motors as a unique feature in numerous industrial applications. The possibilities of running the motor at very high speed with extensive operating life span of BLDC with miniature and its compact design make it an un-ignorable option for Electrical Engineers. With many advantages, till managing as well as controlling the speed of BLDC is complicated. This work is intended to come up with an effective control of speed of the motor through Torque Ripple Minimization Route and an Enhanced-Fractional… More >

M. L. Ramamoorthy¹, S. Selvaperumal^2,*, G. Prabhakar³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 485-497, 2022, DOI:10.32604/iasc.2022.025824

Abstract The scope of this research is to design and fuse the sensors used in the self-balancing vehicle through Adaptive Neuro-Fuzzy Inference systems (ANFIS) algorithm to optimize the output. The self-balancing vehicle is a wheeled inverted pendulum, which is extremely complex, nonlinear and unstable. Homogeneous and Heterogeneous sensors are involved in this sensor fusion research to identify the best feasible value among them. The data fusion algorithm present inside the controller of the self-balancing vehicle makes the inputs of the homogeneous sensors and heterogeneous sensors separately for ameliorate surrounding perception. Simulation is performed by modeling the sensors in Simulink. The outcomes… More >

Divya Sharma^1,*, Sanjay Jain², Vivek Maik³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 357-370, 2022, DOI:10.32604/iasc.2022.025637

Abstract In recent years, the use of Internet of Things (IoT) devices has increased exponentially due to the advancement of information and communication technologies. Wireless sensor networks (WSNs) are vital in the development of IoT and include low-cost smart devices for data collection. However, such smart devices hold some restrictions in terms of calculation, processing, storage, and energy resources. With such constraints, one of the primary difficulties for the WSN is to achieve the lowest possible energy consumption across the network. This article aims to develop an Energy-Efficient cluster-based Lightweight On-Demand Ad hoc Distance Vector Routing Protocol–Next Generation (LOADng) routing protocol… More >

S. Deivanayagi^1,*, P. S. Periasamy²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 639-653, 2022, DOI:10.32604/iasc.2022.025632

Abstract Coronary artery disease (CAD) remains a major reason for increased mortality over the globe, comprising myocardial infarction and ischemic cardiomyopathy. The CAD is highly linked to coronary stenosis owing to the encumbrance of atherosclerotic plaques. Particularly, diversified atherosclerotic plaques are highly responsible for major cardiac adverse events over the calcified and non-calcified plaques. There, the recognition and classification of atherosclerotic plaques play a vital role to prevent and intervene in CAD. The process of detecting various class labels of the atherosclerotic plaques is significant to identify the disease at the earlier stages. Since several automated coronary plaque recognition models are… More >

D. Banumathy^1,*, Osamah Ibrahim Khalaf², Carlos Andrés Tavera Romero³, J. Indra⁴, Dilip Kumar Sharma⁵

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 667-685, 2022, DOI:10.32604/iasc.2022.025609

Abstract Lump in the breast, discharge of blood from the nipple, and deformation of the nipple/breast and its texture are the symptoms of breast cancer. Though breast cancer is very common in women, men can also get breast cancer. In the early stages, BCD makes use of Thermal Mammograms Breast Images (TMBI). The cost of treatment can be severely reduced in the early stages of detection. Based on the techniques of segmentation, the Breast Cancer Detection (BCD) works. Moreover, by providing a balanced, reliable and appropriate second opinion, a tremendous role has been played by ML in medical practices due to… More >