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  • Open Access

    ARTICLE

    An Enhanced Re-Ranking Model for Person Re-Identification

    Jayavarthini Chockalingam*, Malathy Chidambaranathan

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 697-710, 2022, DOI:10.32604/iasc.2022.024142

    Abstract Presently, Person Re-IDentification (PRe-ID) acts as a vital part of real time video surveillance to ensure the rising need for public safety. Resolving the PRe-ID problem includes the process of matching observations of persons among distinct camera views. Earlier models consider PRe-ID as a unique object retrieval issue and determine the retrieval results mainly based on the unidirectional matching among the probe and gallery images. But the accurate matching might not be present in the top-k ranking results owing to the appearance modifications caused by the difference in illumination, pose, viewpoint, and occlusion. For addressing these issues, a new Hyper-parameter… More >

  • Open Access

    ARTICLE

    An Improved DeepNN with Feature Ranking for Covid-19 Detection

    Noha E. El-Attar1,*, Sahar F. Sabbeh1,2, Heba Fasihuddin2, Wael A. Awad3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2249-2269, 2022, DOI:10.32604/cmc.2022.022673

    Abstract The outbreak of Covid-19 has taken the lives of many patients so far. The symptoms of COVID-19 include muscle pains, loss of taste and smell, coughs, fever, and sore throat, which can lead to severe cases of breathing difficulties, organ failure, and death. Thus, the early detection of the virus is very crucial. COVID-19 can be detected using clinical tests, making us need to know the most important symptoms/features that can enhance the decision process. In this work, we propose a modified multilayer perceptron (MLP) with feature selection (MLPFS) to predict the positive COVID-19 cases based on symptoms and features… More >

  • Open Access

    ARTICLE

    SmartCrawler: A Three-Stage Ranking Based Web Crawler for Harvesting Hidden Web Sources

    Sawroop Kaur1, Aman Singh1,*, G. Geetha2, Mehedi Masud3, Mohammed A. Alzain4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2933-2948, 2021, DOI:10.32604/cmc.2021.019030

    Abstract Web crawlers have evolved from performing a meagre task of collecting statistics, security testing, web indexing and numerous other examples. The size and dynamism of the web are making crawling an interesting and challenging task. Researchers have tackled various issues and challenges related to web crawling. One such issue is efficiently discovering hidden web data. Web crawler’s inability to work with form-based data, lack of benchmarks and standards for both performance measures and datasets for evaluation of the web crawlers make it still an immature research domain. The applications like vertical portals and data integration require hidden web crawling. Most… More >

  • Open Access

    ARTICLE

    Ensemble Based Temporal Weighting and Pareto Ranking (ETP) Model for Effective Root Cause Analysis

    Naveen Kumar Seerangan1,*, S. Vijayaragavan Shanmugam2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 819-830, 2021, DOI:10.32604/cmc.2021.012135

    Abstract Root-cause identification plays a vital role in business decision making by providing effective future directions for the organizations. Aspect extraction and sentiment extraction plays a vital role in identifying the root-causes. This paper proposes the Ensemble based temporal weighting and pareto ranking (ETP) model for Root-cause identification. Aspect extraction is performed based on rules and is followed by opinion identification using the proposed boosted ensemble model. The obtained aspects are validated and ranked using the proposed aspect weighing scheme. Pareto-rule based aspect selection is performed as the final selection mechanism and the results are presented for business decision making. Experiments… More >

  • Open Access

    ARTICLE

    Evaluating and Ranking Mobile Learning Factors Using a Multi-criterion Decision-making (MCDM) Approach

    Quadri Noorulhasan Naveed1, Ali M. Aseere1, AbdulHafeez Muhammad2, Saiful Islam3, Mohamed Rafik N. Qureshi3, Ansar Siddique4,*, Mohammad Rashid Hussain1, Samreen Shahwar5

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 111-129, 2021, DOI:10.32604/iasc.2021.015009

    Abstract The escalating growth in digital technology is setting the stage for changes in university education, as E-learning brings students and faculties outside the contained classroom environment. While mobile learning is considered an emerging technology, there is comprehensive literature on mobile learning and its applications. However, there has been relatively little research on mobile learning recognition and readiness compared to mobile learning studies and implementations. The advent of mobile learning (M-learning) provides additional flexibility in terms of time and location. M-learning lacks an established place in university education. The influence of its critical success factors (CSFs) on the university education system… More >

  • Open Access

    ARTICLE

    An Improved Jellyfish Algorithm for Multilevel Thresholding of Magnetic Resonance Brain Image Segmentations

    Mohamed Abdel-Basset1, Reda Mohamed1, Mohamed Abouhawwash2,3, Ripon K. Chakrabortty4, Michael J. Ryan4, Yunyoung Nam5,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2961-2977, 2021, DOI:10.32604/cmc.2021.016956

    Abstract Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is achieved by applying two novel… More >

  • Open Access

    ARTICLE

    A Link Analysis Algorithm for Identification of Key Hidden Services

    Abdullah Alharbi1, Mohd Faizan2, Wael Alosaimi1, Hashem Alyami3, Mohd Nadeem2, Suhel Ahmad Khan4, Alka Agrawal2, Raees Ahmad Khan2,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 877-886, 2021, DOI:10.32604/cmc.2021.016887

    Abstract The Tor dark web network has been reported to provide a breeding ground for criminals and fraudsters who are exploiting the vulnerabilities in the network to carry out illicit and unethical activities. The network has unfortunately become a means to perpetuate crimes like illegal drugs and firearm trafficking, violence and terrorist activities among others. The government and law enforcement agencies are working relentlessly to control the misuse of Tor network. This is a study in the similar league, with an attempt to suggest a link-based ranking technique to rank and identify the influential hidden services in the Tor dark web.… More >

  • Open Access

    ARTICLE

    Optimal Solution of Fuzzy Transportation Problem Using Octagonal Fuzzy Numbers

    D. Gurukumaresan1,*, C. Duraisamy1, R. Srinivasan2

    Computer Systems Science and Engineering, Vol.37, No.3, pp. 415-421, 2021, DOI:10.32604/csse.2021.014130

    Abstract In this paper a fuzzy transportation problem under a fuzzy environment is solved using octagonal fuzzy numbers. The transportation problem is significant and has been widely studied in the field of applied mathematics to solve a system of linear equations in many applications in science. Systems of concurrent linear equations play a vital major role in operational research. The main perspective of this research paper is to find out the minimum amount of transportation cost of some supplies through a capacitated network formerly the availability and the demand notes are octagonal fuzzy numbers. Octagonal fuzzy numbers are used and showed… More >

  • Open Access

    ARTICLE

    Prediction of Cloud Ranking in a Hyperconverged Cloud Ecosystem Using Machine Learning

    Nadia Tabassum1, Allah Ditta2, Tahir Alyas3, Sagheer Abbas4, Hani Alquhayz5, Natash Ali Mian6, Muhammad Adnan Khan7,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3129-3141, 2021, DOI:10.32604/cmc.2021.014729

    Abstract Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the Internet. The design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter metric. In a hyperconverged cloud ecosystem environment, building high-reliability cloud applications is a challenging job. The selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud rankings. The emergence of cloud computing is significantly reshaping the digital ecosystem, and the numerous services offered by cloud service providers are playing a vital role in this transformation. Hyperconverged… More >

  • Open Access

    ARTICLE

    New Improved Ranked Set Sampling Designs with an Application to Real Data

    Amer Ibrahim Al-Omari1, Ibrahim M. Almanjahie2,3,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1503-1522, 2021, DOI:10.32604/cmc.2021.015047

    Abstract This article proposes two new Ranked Set Sampling (RSS) designs for estimating the population parameters: Simple Z Ranked Set Sampling (SZRSS) and Generalized Z Ranked Set Sampling (GZRSS). These designs provide unbiased estimators for the mean of symmetric distributions. It is shown that for non-uniform symmetric distributions, the estimators of the mean under the suggested designs are more efficient than those obtained by RSS, Simple Random Sampling (SRS), extreme RSS and truncation based RSS designs. Also, the proposed RSS schemes outperform other RSS schemes and provide more efficient estimates than their competitors under imperfect rankings. The suggested mean estimators under… More >

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