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Using grey-quality function deployment to construct an aesthetic product design matrix Concurr. Eng. (IF 2.118) Pub Date : 2023-02-06 Nanyi Wang, Xinhui Kang, Qian Wang, Chang Shi
Quality function deployment (QFD) is a systematic approach to transform customer requirements (CRs) into product engineering characteristics (ECs). Traditional QFD relies on market research or cust...
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Research on uncertain integrated production planning and scheduling with risk management based on improved collaborative optimization Concurr. Eng. (IF 2.118) Pub Date : 2022-11-10 Song Zheng, Jun Liu, Di Wu
The optimization of production planning and scheduling is important for modern process industry. Due to different time dimensions of them, it is easy to create conflicts between the optimization re...
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A structured approach for functional analysis of context-aware systems Concurr. Eng. (IF 2.118) Pub Date : 2022-11-04 Fajun Gui, Yong Chen, Haomin Li, Chao Tang
With the popularity of IoT (Internet of Things) technology, more and more engineering systems are integrated with context-aware functionalities. It is self-evident that functional analysis is a cri...
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A hybrid model to develop aesthetic product design of customer satisfaction Concurr. Eng. (IF 2.118) Pub Date : 2022-11-03 Xinhui Kang, Nanyi Wang
With the improvement of manufacturing technology, the performance gap between different products has been gradually narrowed, and customers pay more and more attention to psychological feelings and...
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Variation architecture for reducing unnecessary variants in modular product family design by domain mapping and variant-level planning Concurr. Eng. (IF 2.118) Pub Date : 2022-10-31 Kwansuk Oh, Jongwook Lim, Yoo Suk Hong
One of the major challenges in variety management of modular product families is to prevent continuously generated variants of design elements. This paper aims to provide guidance on how manufactur...
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Compressing project to minimize the increased risk and cost Concurr. Eng. (IF 2.118) Pub Date : 2022-10-25 Qinglan Chen, Liu Chen, Xiang-Ting Zeng, Chiu-Chi Wei
In a highly competitive market environment, organizations must improve their productivity, reduce production costs and improve management methods, in order to maintain a favorable competitive posit...
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An optimal strategy for sustainable IoT device placements for agriculture Concurr. Eng. (IF 2.118) Pub Date : 2022-10-13 Puppala Tirupathi, Polala Niranjan
In recent years, there has been a significant increase in the adaptation of current computer methodologies to tackle issues from different fields. Education, medical research, and agriculture are j...
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Evaluation of biometric communication and authenticate recognition using ANN with PSO algorithm Concurr. Eng. (IF 2.118) Pub Date : 2022-09-30 N Umasankari, B Muthukumar
This research investigates the novel techniques which provide the detailed information on the biometric images used along with the methods applied for biometric image pre-processing. It also descri...
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Performance analysis of machine learning algorithms in heart disease prediction Concurr. Eng. (IF 2.118) Pub Date : 2022-09-14 Dhasaradhan K, Jaichandran R
This work presents performance analysis of machine learning algorithms such as logistic regression, naive bayes, decision tree, k nearest neighbour, random forest, support vector machine, and extre...
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Game-relationship-based remanufacturing scheduling model with sequence-dependent setup times using improved discrete particle swarm optimization algorithm Concurr. Eng. (IF 2.118) Pub Date : 2022-08-23 Shuai Zhang, Huifen Xu, Hua Zhang, Sihan Yang
Remanufacturing has become a Frontier technology in sustainable manufacturing and enables end-of-life products to be restored to their new conditions. Although remanufacturing scheduling has been w...
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Concurrent product-process-supply chain strategy formulation for small medium enterprises Concurr. Eng. (IF 2.118) Pub Date : 2022-08-23 Fitri Trapsilawati, Subagyo, Dimas Ardy Firmansyah, Nur Aini Masruroh, I Gusti Bagus Budi Dharma, Budhi Sholeh Wibowo
Small-medium enterprises (SMEs) have the potentials to translate ideas into innovative products in a quick and efficient manner. Therefore, they should be supported to transform into well-establish...
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A framework for an effective virtual commissioning of agent-based cyber-physical production systems integrated into manufacturing facilities Concurr. Eng. (IF 2.118) Pub Date : 2022-08-22 Abdelhamid Bendjelloul, Bachir Mihoubi, Mehdi Gaham, Mansour Moufid, Brahim Bouzouia
The rise of the fourth industrial revolution and the interest in autonomous production led to increased adoption of Cyber-Physical Production Systems (CPPS) in the industry. Due to the significant ...
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A new remanufacturing system scheduling model with diversified reprocessing routes using a hybrid meta-heuristic algorithm Concurr. Eng. (IF 2.118) Pub Date : 2022-08-18 Jun Wang, Xiangqi Liu, Wenyu Zhang, Junliang Xu
With the increasingly serious problem of environmental pollution and resource scarcity, remanufacturing has become one of the popular research fields to solve these issues. However, the practical i...
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Selecting and balancing market portfolio using artificial intelligence and fuzzy multiobjective decision-making model Concurr. Eng. (IF 2.118) Pub Date : 2022-08-17 Wen-Lung Shih, Chiu-Chi Wei, Hsien-Hong Lin, Pin-Hsiang Chang
Most enterprises focus on product portfolio management (PPM) and exclude market portfolio management, and individual markets are selected solely based on financial performance which may not be appr...
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Customer’s opinion mining from online reviews using intelligent rules with machine learning techniques Concurr. Eng. (IF 2.118) Pub Date : 2022-08-12 Sadhana SA, Sabena S, SaiRamesh L, Kannan A
In the field of marketing, many surveys were conducted to analyze the customer satisfaction on products in their online purchases. But the real view of customers about the product is mirrored in th...
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Cuckoo Search Optimization based PI Controller Tuning for Hopper Tank System Concurr. Eng. (IF 2.118) Pub Date : 2022-08-09 Vinothkumar C, Esakkiappan C
The paper work focuses on soft computing and Conventional controller tuning approach to design of PI controller, for a nonlinear hopper tank liquid level control system process Industries. The auto...
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Modeling and optimization of concurrent execution process of coupled design-construction tasks under design-build mode Concurr. Eng. (IF 2.118) Pub Date : 2022-08-06 Ting Wang, Jingchun Feng
Concurrent execution of design and construction tasks is an important way to realize the integration of them in design-build (DB) mode, but it may bring about period risk due to multiple rework and frequent information transfer in local scope. To solve this problem, this study constructs a concurrent execution strategy model from the perspective of quantitative analysis with the decision goal of minimizing
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Integrated fuzzy linguistic preference relations approach and fuzzy Quality Function Deployment to the sustainable design of hybrid electric vehicles Concurr. Eng. (IF 2.118) Pub Date : 2022-08-04 Xinhui Kang, Qi Zhu
Through the prevalence of sustainable ideas, automobiles are increasingly pursuing environmental protection strategies for green design, the non-traditional hybrid electric vehicles (HEV) are promoted continuously. If the company can add emotional value to the modeling of HEV, it will be helpful to its sustainable design and sales promotion of it. Therefore, an innovative model combining fuzzy linguistic
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Special issue on intelligent computing and communication in industrial internet of things Concurr. Eng. (IF 2.118) Pub Date : 2022-08-08 K Vijayakumar
The proposed special issue focuses on collecting the research articles on recent advancements in the research domains, like intelligent computing, communication and IIoT applications. The selected ...
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Robust product line pricing under the multinomial logit choice model Concurr. Eng. (IF 2.118) Pub Date : 2022-06-16 Wei Qi, Xinggang Luo, Xuwang Liu, Zhong-Liang Zhang
Incorporating consumer choice behavior into a product line design optimization model enhances the understanding of consumer choices and improves the opportunities to increase profit. Most product line optimization problems assume that parameters are precisely known in consumer choice model. However, the decision maker does not precisely know the model parameters because of insufficient sample data
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Machine Learning and Automation in Concurrent Engineering Concurr. Eng. (IF 2.118) Pub Date : 2022-06-14 K Vijayakumar
In the past few years, Science has played an impressive role in providing solutions to various real-life problems. The current growth in the domain of science, technology and computing has helped the human community to live life with a better ambience. The enhanced occupation helps humans, access a wide variety of recent facilities, which further helps to enhance their lifestyle and their work atmosphere
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Modeling and solving the two-sided U-type assembly line balance based on a heuristic algorithm of a multi-priority rule Concurr. Eng. (IF 2.118) Pub Date : 2022-06-07 Yu-ling Jiao, Xue Deng, Lin Li, Xin-ran Liu, Nan Cao
In order to improve the efficiency of assembly line and optimize the layout, this paper presents a collaborative optimization model for a two-sided U-type assembly line and a novel design with p-l partition layout is proposed to minimize number of workstations without increasing the length of the assembly line. Considering the task orientation and time sequencing in cross-workstation, the mathematical
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Detection of Pneumonia from Chest X-Ray images using Machine Learning Concurr. Eng. (IF 2.118) Pub Date : 2022-06-05 SureshKumar M, Varalakshmi Perumal, Gowtham Yuvaraj, Sakthi Jaya Sundar Rajasekar
The survival percentage of lung patients can be improved if pneumonia is detected early. Images of the chest X-ray (CXR) are the most common way of identifying and diagnosing pneumonia. A competent radiologist faces a difficult problem in detecting pneumonia from CXR images. Many people are at danger of contracting pneumonia, especially in developing countries where billions of people live in energy
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Federation payment tree: An improved payment channel for scaling and efficient ZK-hash time lock commitment framework in blockchain technology Concurr. Eng. (IF 2.118) Pub Date : 2022-05-26 P Shamili, B Muruganantham
Federation Payment Tree, a new Off-chain with zero-knowledge hash time lock commitment setup is proposed in this paper. The security of blockchain is based on consensus protocols that delay when number of concurrent transactions processed in given throughput framework. The scalability of blockchain is the ability to perform support increasing workload transaction. The FP-Tree provides zero knowledge
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Fusion-based advanced encryption algorithm for enhancing the security of Big Data in Cloud Concurr. Eng. (IF 2.118) Pub Date : 2022-05-19 A Vidhya, P Mohan Kumar
Every organization in this digital age is expected to exponentially increase its digital data due to generations from machines. The advanced computations of Big Data are now showing various opportunities for the researchers who work on security enhancements to ensure the efficient accessibility of the data stores. Our research work aims to derive a Fusion-based Advanced Encryption Algorithm (FAEA)
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Detection and classification of epilepsy using hybrid convolutional neural network Concurr. Eng. (IF 2.118) Pub Date : 2022-05-19 A Sabarivani, R Ramadevi
In recent years, more than 50 million people have been affected by the epilepsy, neurological disorder diseases. To monitor the situation of the epilepsy patient requires experienced and skilled person. In order to overcome these issues, autonomous detection of electroencephalogram (EEG) signal by deep learning model has evolved. Convolutional neural network (CNN) is one of the sub-category of neural
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Petite term traffic flow prediction using deep learning for augmented flow of vehicles Concurr. Eng. (IF 2.118) Pub Date : 2022-05-19 J Indumathi, V Kaliraj
An Intelligent Transport System (ITS) model that is contingent on the compulsion and expertise of the Traffic Prediction System in the contemporary urban context is proposed in this paper. Deep Learning (DL) is computationally becoming comfortable to train and set as many hyperparameters automatically as possible. The researchers and practitioners crave to set as many hyperparameters inevitably as
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A secured biomedical image processing scheme to detect pneumonia disease using dynamic learning principles Concurr. Eng. (IF 2.118) Pub Date : 2022-05-09 Venkata Samy Raja Nanammal, Venu Gopalakrishnan Jayagopalan
Now-a-days, the medical industry is growing a lot with the adaptation of latest technologies as well as the logical evaluation and security norms provides a robust platform to enhance the effectiveness of the industry at a drastic level. In this paper, a digital bio-medical image processing based Pneumonia disease identification system is introduced with enhanced security features. Due to improving
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Optimal feature reduction for biometric authentication using intelligent computing techniques Concurr. Eng. (IF 2.118) Pub Date : 2022-04-23 N Umasankari, B Muthukumar
The Intelligent Computing area such as Automatic Biometric authentication is an emerging and high priority research work where the researchers invent several biometric applications which result in the revolutionary development in the recent era. In this approach, a novel algorithm is known as Modified AntLion Optimization (MALO) with Multi Kernel Support Vector Machine (MKSVM) was used to classify
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The role of industry 4.0 technologies in overcoming pandemic challenges for the manufacturing sector Concurr. Eng. (IF 2.118) Pub Date : 2022-04-23 Parham Dadash Pour, Mohammad A Nazzal, Basil M Darras
Industry 4.0 aims to revolutionize the manufacturing sector to achieve sustainable and efficient production. The novel coronavirus pandemic has brought many challenges in different industries globally. Shortage in supply of raw material, changes in product demand, and factories closures due to general lockdown are all examples of such challenges. The adaption of Industry 4.0 technologies can address
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Sports highlight recognition and event detection using rule inference system Concurr. Eng. (IF 2.118) Pub Date : 2022-04-15 Kanimozhi Soundararajan, Mala T
Computer vision in sport is a very interesting application. People spend a lot of time watching sports videos because this is one of the best field of entertainment. Sports video broadcasts generally take a lot of time, ranging from two to four hours. However, the interesting part happens for just a few minutes. Detecting the highlighted event in a sport will be useful for people who like to watch
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Computer-aided diagnosis for breast cancer detection and classification using optimal region growing segmentation with MobileNet model Concurr. Eng. (IF 2.118) Pub Date : 2022-04-14 J Dafni Rose, K VijayaKumar, Laxman Singh, Sudhir Kumar Sharma
Globally, breast cancer is considered a major reason for women’s morality. Earlier and accurate identification of breast cancer is essential to increase survival rates. Therefore, computer-aided diagnosis (CAD) models are developed to help radiologists in the detection of mammographic lesions. Presently, machine-learning (ML) and deep-learning (DL) models are widely employed in the disease diagnostic
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Editorial Concurr. Eng. (IF 2.118) Pub Date : 2022-03-08 DR. K. Vijayakumar
In recent years, concurrent engineering (CE) has played an essential role in providing relevant and optimal solutions for multi-disciplinary problems. These are closely associated with various vital tasks, such as product design, manmachine interface for product automation, and in achieving the overall performance of the product integrated with cognitive ergonomics. Concurrent Engineering aids in the
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Special issue on “intelligent computing and communication in concurrent engineering” Concurr. Eng. (IF 2.118) Pub Date : 2022-03-07 K Vijayakumar,V Rajinikanth
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Phased array ultrasonic test signal enhancement and classification using Empirical Wavelet Transform and Deep Convolution Neural Network Concurr. Eng. (IF 2.118) Pub Date : 2022-02-22 Jayasudha JC, Lalithakumari S
In the recent past, Non-Destructive Testing (NDT) has become the most popular technique due to its efficiency and accuracy without destroying the object and maintaining its original structure and gathering while examining external and internal welding defects. Generally, the NDT environment is harmful which is distinguished by huge volatile fields of electromagnetic, elevated radiation emission instability
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Identifying modular candidates in engineer-to-order companies Concurr. Eng. (IF 2.118) Pub Date : 2022-02-05 Carsten Keinicke Fjord Christensen, Niels Henrik Mortensen
The purpose of this paper is to address a gap of missing modularization methods for engineer-to-order (ETO) companies. The research project was initiated by clarifying the challenges facing ETO companies, based on these challenges synthesis of existing methods was done to conceptualize a method. This article presents the modular candidate identification (MCI) method aimed at identifying modular candidates
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A cost-effective computer vision-based vehicle detection system Concurr. Eng. (IF 2.118) Pub Date : 2022-02-02 Altaf Alam, Zainul Abdin Jaffery, Himanshu Sharma
Vehicle detection plays an important role in the development of an autonomous driving system. Fast processing and accurate detection are two major aspects of generating the autonomous vehicle detection system. This paper proposes a novel computer vision-based cost-effective vehicle detection system. Here, a Gentle Adaptive Boosting algorithm is trained with Haar-like features to generate the hypothesis
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Embedded mobile computational framework for multidimensional diabetic retinopathy extraction and detection technique using recursive neural network approach for unstructured tomography datasets Concurr. Eng. (IF 2.118) Pub Date : 2022-01-31 K.T. Ilayarajaa, E. Logashanmugam
Diabetic Retinopathy (DR) is considered to be the leading cause for preventive blindness in humans, the DR is sighted with a diabetic stage of progression and hence the patient is required to undergo regular health checkups on DR formation and detection. In this paper, the objective is to extract and detect the patterns of DR with respect to the propagation stages using Recursive Neural Network (RNN)
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Balancing of parallel U-shaped assembly lines with a heuristic algorithm based on bidirectional priority values Concurr. Eng. (IF 2.118) Pub Date : 2021-12-22 Yuling Jiao, Xue Deng, Mingjuan Li, Xiaocui Xing, Binjie Xu
Aiming at improving assembly line efficiency and flexibility, a balancing method of parallel U-shaped assembly line system is proposed. Based on the improved product priority diagram, the bidirectional priority value formula is obtained. Then, assembly lines are partitioned into z-q partitions and workstations are defined. After that, the mathematical model of the parallel U-shaped assembly line balancing
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Conducting product comparative analysis to outperform competitor’s product using Teardown JST Model Concurr. Eng. (IF 2.118) Pub Date : 2021-12-12 Cuiqing Jiang, Abdullah Alqadhi, Mahmood Almesbahi
Due to the massive number of products being produced every year in every industry, firms have witnessed a tremendous growth in innovation of methods to create a sustainable competitive advantage. For the past decade and with the availability of online consumer reviews, companies and researchers have developed many approaches utilizing electronic Word-of-Mouth to improve and develop products and services
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Knowledge capitalization in mechatronic collaborative design Concurr. Eng. (IF 2.118) Pub Date : 2021-12-09 Mouna Fradi, Raoudha Gaha, Faïda Mhenni, Abdelfattah Mlika, Jean-Yves Choley
In mechatronic collaborative design, there is a synergic integration of several expert domains, where heterogeneous knowledge needs to be shared. To address this challenge, ontology-based approaches are proposed as a solution to overtake this heterogeneity. However, dynamic exchange between design teams is overlooked. Consequently, parametric-based approaches are developed to use constraints and parameters
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Applications of affordance and cognitive ergonomics in virtual design: A digital camera as an illustrative case Concurr. Eng. (IF 2.118) Pub Date : 2021-12-09 Mo Chen, Georges Fadel, Ivan Mata
Affordance-based design (ABD) plays an important role in identifying interactions, especially effortless ones, between users and artifacts. Cognitive ergonomics extends our understanding of this effortless interaction. This study combines the two design methodologies together in order to reduce cognitive friction in using digital products. The design process of a compact digital camera is selected
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Connector-link-part-based disassembly sequence planning Concurr. Eng. (IF 2.118) Pub Date : 2021-12-08 Hwai-En Tseng, Chien-Cheng Chang, Shih-Chen Lee, Cih-Chi Chen
Under the trend of concurrent engineering, the correspondence between functions and physical structures in product design is gaining importance. Between the functions and parts, connectors are the basic unit for engineers to consider. Moreover, the relationship between connector-liaison-part will help accomplish the integration of information. Such efforts will help the development of the Knowledge
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Bayesian approach to incremental batch learning on forest cover sensor data for multiclass classification Concurr. Eng. (IF 2.118) Pub Date : 2021-11-05 Venkata Vara Prasad D, Lokeswari Y Venkataramana, Saraswathi S, Sarah Mathew, Snigdha V
Deep neural networks can be used to perform nonlinear operations at multiple levels, such as a neural network that is composed of many hidden layers. Although deep learning approaches show good results, they have a drawback called catastrophic forgetting, which is a reduction in performance when a new class is added. Incremental learning is a learning method where existing knowledge should be retained
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Artificial intelligence techniques for industrial automation and smart systems Concurr. Eng. (IF 2.118) Pub Date : 2021-08-30 Sheldon Williamson,K Vijayakumar
Artificial intelligence (AI) has navigated away from public skepticism, back into the limelight in an impactful way. From an application perspective, it is largely accepted that the industrial implications of AI will be significant, even if the broader societal implications are still under question. AI has the power to drive competitiveness in the industrial sphere in a manner that has not been seen
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Resource utilization prediction technique in cloud using knowledge based ensemble random forest with LSTM model Concurr. Eng. (IF 2.118) Pub Date : 2021-08-12 K Valarmathi, S Kanaga Suba Raja
Future computation of cloud datacenter resource usage is a provoking task due to dynamic and Business Critic workloads. Accurate prediction of cloud resource utilization through historical observation facilitates, effectively aligning the task with resources, estimating the capacity of a cloud server, applying intensive auto-scaling and controlling resource usage. As imprecise prediction of resources
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A discrete manufacturing SCOS framework based on functional interval parameters and fuzzy QoS attributes using moving window FPA Concurr. Eng. (IF 2.118) Pub Date : 2021-08-06 Jie Gao, Xianguo Yan, Hong Guo
Manufacturing service composition and optimal selection (SCOS) is a key technology that improves resource utilization and reduces the cost in discrete manufacturing. However, the lack of evaluation of the service composition function and the unconformity of the actual composition vague characteristics, resulting in the incomplete evaluation of the service composition. Additionally, various optimization
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Scene construction of nano particle system based on virtual technology Concurr. Eng. (IF 2.118) Pub Date : 2021-07-23 Han Yang, Chongzhong Jia, Jifeng Xie, Kun Wang, Xiaoling Hao
In view of the problems in traditional 3D scene simulation, such as the poor simulation effect and the inability to really feel the scene, this paper proposes the research of nano particle system scene construction based on virtual technology. By analyzing the advantages of virtual reality technology, the role of virtual reality in three-dimensional scene is determined; the method of three-dimensional
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An automated learning model for sentiment analysis and data classification of Twitter data using balanced CA-SVM Concurr. Eng. (IF 2.118) Pub Date : 2021-07-20 C Pretty Diana Cyril, J Rene Beulah, Neelakandan Subramani, Prakash Mohan, A Harshavardhan, D Sivabalaselvamani
The modern society runs over the social media for their most time of every day. The web users spend their most time in social media and they share many details with their friends. Such information obtained from their chat has been used in several applications. The sentiment analysis is the one which has been applied with Twitter data set toward identifying the emotion of any user and based on those
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Automated glaucoma detection from fundus images using wavelet-based denoising and machine learning Concurr. Eng. (IF 2.118) Pub Date : 2021-07-09 Sibghatullah I. Khan, Shruti Bhargava Choubey, Abhishek Choubey, Abhishek Bhatt, Pandya Vyomal Naishadhkumar, Mohammed Mahaboob Basha
Glaucoma is a domineering and irretrievable neurodegenerative eye disease produced by the optical nerve head owed to extended intra-ocular stress inside the eye. Recognition of glaucoma is an essential job for ophthalmologists. In this paper, we propose a methodology to classify fundus images into normal and glaucoma categories. The proposed approach makes use of image denoising of digital fundus images
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Integrity and memory consumption aware electronic health record handling in cloud Concurr. Eng. (IF 2.118) Pub Date : 2021-07-02 Kakunuri Sreelatha, Vuyyuru Krishna Reddy
Cloud environment greatly necessitates two key factors namely integrity and memory consumption. In the proposed work, an efficient integrity check system (EICS) is presented for electronic health record (EHR) classification. The existing system does not concentrate on storage concerns such as storing and retrieving files in cloud and memory storage overheads. De-duplication is one of the solution,
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Breast cancer diagnosis using multiple activation deep neural network Concurr. Eng. (IF 2.118) Pub Date : 2021-06-25 K Vijayakumar, Vinod J Kadam, Sudhir Kumar Sharma
Deep Neural Network (DNN) stands for multilayered Neural Network (NN) that is capable of progressively learn the more abstract and composite representations of the raw features of the input data received, with no need for any feature engineering. They are advanced NNs having repetitious hidden layers between the initial input and the final layer. The working principle of such a standard deep classifier
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Deep learning based fusion model for COVID-19 diagnosis and classification using computed tomography images Concurr. Eng. (IF 2.118) Pub Date : 2021-06-09 RT Subhalakshmi, S Appavu alias Balamurugan, S Sasikala
Recently, the COVID-19 pandemic becomes increased in a drastic way, with the availability of a limited quantity of rapid testing kits. Therefore, automated COVID-19 diagnosis models are essential to identify the existence of disease from radiological images. Earlier studies have focused on the development of Artificial Intelligence (AI) techniques using X-ray images on COVID-19 diagnosis. This paper
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Batch-based agile program management approach for coordinating IT multi-project concurrent development Concurr. Eng. (IF 2.118) Pub Date : 2021-06-08 Qing Yang, Yingxin Bi, Qinru Wang, Tao Yao
Software development projects have undergone remarkable changes with the arrival of agile development approaches. Many firms are facing a need to use these approaches to manage entities consisting of multiple projects (i.e. programs) simultaneously and efficiently. New technologies such as big data provide a huge power and rich demand for the IT application system of the commercial bank which has the
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Time-aware cloud manufacturing service selection using unknown QoS prediction and uncertain user preferences Concurr. Eng. (IF 2.118) Pub Date : 2021-06-03 Ying Yu, Shan Li, Jing Ma
Selecting the most efficient from several functionally equivalent services remains an ongoing challenge. Most manufacturing service selection methods regard static quality of service (QoS) as a major competitiveness factor. However, adaptations are difficult to achieve when variable network environment has significant impact on QoS performance stabilization in complex task processes. Therefore, dynamic
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Design of novel multi filter union feature selection framework for breast cancer dataset Concurr. Eng. (IF 2.118) Pub Date : 2021-05-31 Dinesh Morkonda Gunasekaran, Prabha Dhandayudam
Nowadays women are commonly diagnosed with breast cancer. Feature based Selection method plays an important step while constructing a classification based framework. We have proposed Multi filter union (MFU) feature selection method for breast cancer data set. The feature selection process based on random forest algorithm and Logistic regression (LG) algorithm based union model is used for selecting
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Prioritizing failure risks of components based on information axiom for product redesign considering fuzzy and random uncertainties Concurr. Eng. (IF 2.118) Pub Date : 2021-05-27 Zhenhua Liu, Xuening Chu, Hongzhan Ma, Mengting Zhang
The prioritization of the failure risks of the components in an existing product is critical for product redesign decision-making considering various uncertainties. Two issues need to be addressed in the failure risk prioritization process. One is the evaluation of the failure risk considering each failure mode for each component. Currently, many failure mode effects and analysis (FMEA) methods based
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Assembly line balance research methods, literature and development review Concurr. Eng. (IF 2.118) Pub Date : 2021-05-03 Yu-ling Jiao, Han-qi Jin, Xiao-cui Xing, Ming-juan Li, Xin-ran Liu
With the continuous upgrading of the manufacturing system, the assembly line balancing problem (ALBP) is gradually complicated, and the researches are constantly deepened in the application theory and solution methods. In order to clarify the research direction and development status of assembly line balancing, 89 articles are read and studied. We classify ALBPs to construct the network structure of
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An efficient approach for brain tumor detection and segmentation in MR brain images using random forest classifier Concurr. Eng. (IF 2.118) Pub Date : 2021-04-27 Meenal Thayumanavan, Asokan Ramasamy
Nowadays, the most demanding and time consuming task in medical image processing is Brain tumor segmentation and detection. Magnetic Resonance Imaging (MRI) is employed for creating a picture of any part in a body. MRI provides a competent quick manner for analyzing tumor in the brain. This proposed framework contains different stages for classifying tumor like Preprocessing, Feature extraction, Classification
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Color perception and recognition method for Guangdong embroidery image based on discrete mathematical model Concurr. Eng. (IF 2.118) Pub Date : 2021-04-20 Ya Zhang, Qiang Xiong
Aiming at the problem that the traditional color perception and recognition method for Guangdong embroidery image has poor color stereo restoring ability, a color perception, and recognition method for Guangdong embroidery image based on discrete mathematical model is proposed. Through histogram equalization, the input image with centralized gray distribution is transformed into the output image with