Musawwer Khan¹, Islam Ali¹, Waqar Mehmood¹, Wasif Nisar¹, Waqar Aslam², Muhammad Shafiq³, Jin-Ghoo Choi^3,*

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 311-331, 2021, DOI:10.32604/iasc.2021.014280

Abstract Legacy systems deteriorate due to changing business practices and recurrent problems such as high maintenance cost, lack of agility, and degraded performance. Modernization is highly desired especially for those organizations where key business processes are managed by legacy systems. During modernizing, two important aspects are usually ignored, i.e., the transformation of a legacy system to an enterprise solution, and considerations of quality concerns. This overlooking leads to a modernized information system that partially achieves the expected outcome. In this paper, we propose a Capability Maturity Model Integration (CMMI) Compliant Modernization Framework (CCMF) that addresses the problems of legacy systems by… More >

Arif Iqbal^*, Abdul Basit, Imran Ali, Junaid Babar, Ihsan Ullah

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 299-309, 2021, DOI:10.32604/iasc.2021.014250

Abstract Automated meter reading has recently been adopted by utility service providers for improving the reading and billing process. Images captured during meter reading are incorporated in consumer bills to prevent reporting false reading and ensure transparency. The availability of images captured during the meter reading process presents the potential of completely automating the meter reading process. This paper proposes a convolutional network-based multi-box model for the automatic meter reading. The proposed research leverages the inception model with a single shot detector to achieve high accuracy and efficiency compared to the existing state-of-the-art machine learning methods. We tested the multi-box detector… More >

Huaning Song¹, Jiansheng Peng^1,2,*, Nianyang Tuo¹, Haiying Xia², Yiyun Peng³

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 581-592, 2021, DOI:10.32604/iasc.2021.014152

Abstract Accurate identification of sugarcane buds, as one of the key technologies in sugarcane plantation, becomes very necessary for its mechanized and intelligent advancements. In the traditional methods of sugarcane bud recognition, a significant amount of algorithms work goes into the location and recognition of sugarcane bud images. A Convolutional Neural Network (CNN) for classifying the bud conditions is proposed in this paper. Firstly, we convert the colorful sugarcane images into gray ones, unify the size of them, and make a TFRecord format data set, which contains 1100 positive samples and 1100 negative samples. Then, a CNN mode is developed to… 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 >

Ruijun Chai¹, Sujie Shao^1,*, Shaoyong Guo¹, Yuqi Wang¹, Xuesong Qiu¹, Linna Ruan²

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 471-482, 2021, DOI:10.32604/iasc.2021.013373

Abstract Long Range Radio (LoRa) has become one of the widely adopted Low-Power Wide Area Network (LPWAN) technologies in power Internet of Things (PIoT). Its major advantages include long-distance, large links and low power consumption. However, in LoRa-based PIoT, terminals are often deployed in the wild place and are easily affected by bad weather or disaster, which could easily lead to large-scale operation faults and could seriously affect the normal operation of the network. Simultaneously, the distribution characteristics of outdoor terminals with wide coverage and large links lead to a sharp increase in the difficulty and cost of fault recovery. Given… More >

S. Praveen Kumar^1,*, S. Appavu alias Balamurugan², S. Kannan³

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 333-346, 2021, DOI:10.32604/iasc.2021.013310

Abstract The establishment of multi-channel routing systems in WSNs has shown the reliability of the transmission across several channels. Meeting the service quality needs of all the applications is still a challenging task. Various surveys carried out, have suggested for the development of user-oriented Wireless Sensor Network (WSN) architectures. Throughout WSNs, the Optimized Link State Routing (OLSR) and the Adhoc On Demand Vector (AODV) are the multi-way routing systems that exhibit the reliability of the multipath delivery to fulfill the customer service quality requirements. The topology is modified only on requests, by selecting the best route based on the route weights… More >

R. Jayamala^*, A. Valarmathi

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 347-358, 2021, DOI:10.32604/iasc.2021.012401

Abstract Cloud computing is an increasingly important technology to deliver pay-as-you-go online computing services. In this study, the cloud service provider permits the cloud user to pay according to the user’s needs. Various methods have been used to reduce energy utilization in the cloud. The rapid increase of cloud users has led to increased energy consumption and higher operating costs for cloud providers. A key issue in cloud data centers is their massive energy consumption to operate and maintain computing services. Virtual machine (VM) migration is a method to reduce energy consumption. This study proposes enhanced decentralized virtual machine migration (EDVMM),… More >

Aolin Sun, Xiang Cao^*, Xu Xiao, Liwen Xu

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 551-564, 2021, DOI:10.32604/iasc.2021.01008

Abstract An essential issue in a target search is safe navigation while quickly finding targets. In order to improve the efficiency of a target search and the smoothness of AUV’s (Autonomous Underwater Vehicle) trajectory, a fuzzy-based bio-inspired neural network approach is proposed in this paper. A bio-inspired neural network is applied to a multi-AUV target search, which can effectively plan search paths. In the meantime, a fuzzy algorithm is introduced into the bio-inspired neural network to make the trajectory of AUV obstacle avoidance smoother. Unlike other algorithms that need repeated training in the parameters selection, the proposed approach obtains all the… More >

Xiang Cao^1,2,*, Ling Chen¹, Liqiang Guo³, Wei Han⁴

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 391-407, 2021, DOI:10.32604/iasc.2021.01002

Abstract As one of the classical problems in autonomous underwater vehicle (AUV) research, path planning has obtained a lot of research results. Many studies have focused on planning an optimal path for AUVs. These optimal paths are sometimes too close to obstacles. In the real environment, it is difficult for AUVs to avoid obstacles according to such an optimal path. To solve the safety problem of AUV path planning in a dynamic uncertain environment, an algorithm combining a bio-inspired neural network and potential field is proposed. Based on the environmental information, the bio-inspired neural network plans the optimal path for the… More >

Jin Wang¹, Weigang Zhang^2,*, Xiaowei Zhuang^1,*

Journal of Renewable Materials, Vol.9, No.3, pp. 557-568, 2021, DOI:10.32604/jrm.2021.013269

Abstract Using 1–8 years bamboo as materials, the content of different chemical constituent was tested, and the reactive oxygen species (ROS) free radicals produced from laccase treated bamboo were detected by electron spin-resonance (ESR) spectroscope. The wet-process particleboard was made from laccase-treated bamboo by hot pressing and board mechanical properties including internal bond strength (IB), modulus of rupture (MOR) and thickness swelling (TS) after 2-hours water absorption were tested under different conditions. Results showed that laccase mainly catalyze the bamboo components and improved the bonding strength of laccase-treated boards. By ESR measurement on each single component such as milled bamboo lignin,… More >