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  • Open Access

    ARTICLE

    Novel Multimodal Biometric Feature Extraction for Precise Human Identification

    J. Vasavi1, M. S. Abirami2,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1349-1363, 2023, DOI:10.32604/iasc.2023.032604

    Abstract In recent years, biometric sensors are applicable for identifying important individual information and accessing the control using various identifiers by including the characteristics like a fingerprint, palm print, iris recognition, and so on. However, the precise identification of human features is still physically challenging in humans during their lifetime resulting in a variance in their appearance or features. In response to these challenges, a novel Multimodal Biometric Feature Extraction (MBFE) model is proposed to extract the features from the noisy sensor data using a modified Ranking-based Deep Convolution Neural Network (RDCNN). The proposed MBFE model enables the feature extraction from… More >

  • Open Access

    ARTICLE

    Graph Ranked Clustering Based Biomedical Text Summarization Using Top k Similarity

    Supriya Gupta*, Aakanksha Sharaff, Naresh Kumar Nagwani

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2333-2349, 2023, DOI:10.32604/csse.2023.030385

    Abstract Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and effort. Evaluating and selecting the most informative sentences from biomedical articles is always challenging. This study aims to develop a dual-mode biomedical text summarization model to achieve enhanced coverage and information. The research also includes checking the fitment of appropriate graph ranking techniques for improved performance of the summarization model. The input biomedical text is mapped as a graph where meaningful sentences are evaluated as the central node and the critical associations between them. The proposed framework utilizes the top… More >

  • Open Access

    ARTICLE

    Ensemble Classifier-Based Features Ranking on Employee Attrition

    Yok-Yen Nguwi*

    Journal on Artificial Intelligence, Vol.4, No.3, pp. 189-199, 2022, DOI:10.32604/jai.2022.034064

    Abstract The departure of good employee incurs direct and indirect cost and impacts for an organization. The direct cost arises from hiring to training of the relevant employee. The replacement time and lost productivity affect the running of business processes. This work presents the use of ensemble classifier to identify important attributes that affects attrition significantly. The data consists of attributes related to job function, education level, satisfaction towards work and working relationship, compensation, and frequency of business travel. Both bagging and boosting classifiers were used for testing. The results show that the selected features (nine selected features) achieve the same… More >

  • Open Access

    ARTICLE

    Ranked-Set Sampling Based Distribution Free Control Chart with Application in CSTR Process

    Ibrahim M. Almanjahie1,2, Zahid Rasheed3,4,*, Majid Khan5, Syed Masroor Anwar6, Ammara Nawaz Cheema7

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2091-2118, 2023, DOI:10.32604/cmes.2023.022201

    Abstract Nonparametric (distribution-free) control charts have been introduced in recent years when quality characteristics do not follow a specific distribution. When the sample selection is prohibitively expensive, we prefer ranked-set sampling over simple random sampling because ranked set sampling-based control charts outperform simple random sampling-based control charts. In this study, we proposed a nonparametric homogeneously weighted moving average based on the Wilcoxon signed-rank test with ranked set sampling () control chart for detecting shifts in the process location of a continuous and symmetric distribution. Monte Carlo simulations are used to obtain the run length characteristics to evaluate the performance of the… More >

  • Open Access

    ARTICLE

    Life Cycle Assessment Introduced by Using Nanorefrigerant of Organic Rankine Cycle System for Waste Heat Recovery

    Yuchen Yang1,2, Lin Ma1,2,*, Jie Yu1,2, Zewen Zhao1,2, Pengfei You1,2

    Journal of Renewable Materials, Vol.11, No.3, pp. 1153-1179, 2023, DOI:10.32604/jrm.2022.022719

    Abstract The use of nanorefrigerants in Organic Rankine Cycle (ORC) units is believed to affect the cycle environment performance, but backed with very few relevant studies. For this purpose, a life cycle assessment (LCA) has been performed for the ORC system using nanorefrigerant, the material and energy input, characteristic indicators and comprehensive index of environmental impact, total energy consumption and energy payback time (BPBT) of the whole life cycle of ORC system using Al2O3/R141b nanorefrigerant were calculated. Total environmental comprehensive indexes reveal that ECER-135 index decrease by 1.5% after adding 0.2% Al2O3 nanoparticles to R141b. Based on the contribution analysis and… More >

  • Open Access

    ARTICLE

    Multi Criteria Decision Making for Evaluation and Ranking of Cancer Information

    Shahid Mahmood1,*, Muhammad Amin2, Mubashir Baig Mirza1, Salem Abu-Ghumsan1, Muhammad Akram3, Zahid Mahmood Janjua4, Arslan Shahid5, Usman Shahid6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4469-4481, 2023, DOI:10.32604/cmc.2023.030728

    Abstract Cancer is a disease that is rapidly expanding in prevalence all over the world. Cancer cells can metastasize, or spread, across the body and impact several different cell types. Additionally, the incidence rates of several subtypes of cancer have been on the rise in India. The countermeasures for the cancer disease can be taken by determining the specific expansion rate of each type. To rank the various forms of cancer’s rate of progression, we used some of the available data. Numerous studies are available in the literature which show the growth rate of cancer by different techniques. The accuracy of… More >

  • Open Access

    ARTICLE

    Computational Modeling of Reaction-Diffusion COVID-19 Model Having Isolated Compartment

    Muhammad Shoaib Arif1,2,*, Kamaleldin Abodayeh1, Asad Ejaz2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1719-1743, 2023, DOI:10.32604/cmes.2022.022235

    Abstract Cases of COVID-19 and its variant omicron are raised all across the world. The most lethal form and effect of COVID-19 are the omicron version, which has been reported in tens of thousands of cases daily in numerous nations. Following WHO (World health organization) records on 30 December 2021, the cases of COVID-19 were found to be maximum for which boarding individuals were found 1,524,266, active, recovered, and discharge were found to be 82,402 and 34,258,778, respectively. While there were 160,989 active cases, 33,614,434 cured cases, 456,386 total deaths, and 605,885,769 total samples tested. So far, 1,438,322,742 individuals have been… More >

  • Open Access

    ARTICLE

    Exergy Analysis of Organic Rankine Cycles with Zeotropic Working Fluids

    Antonio Mariani, Davide Laiso, Biagio Morrone*, Andrea Unich

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.3, pp. 593-601, 2023, DOI:10.32604/fdmp.2022.022524

    Abstract Waste heat recovery is one of the possible solutions to improve the efficiency of internal combustion engines. Instead of wasting the exhaust stream of an energy conversion system into the environment, its residual energy content can be usefully recovered, for example in Organic Rankine Cycles (ORC). This technology has been largely consolidated in stationary power plants but not yet for mobile applications, such as road transport, due to the limitations in the layout and to the constraints on the size and weight of the ORC system. An ORC system installed on the exhaust line of a bus powered by a… More > Graphic Abstract

    Exergy Analysis of Organic Rankine Cycles with Zeotropic Working Fluids

  • Open Access

    ARTICLE

    Weighted PageRank Algorithm Search Engine Ranking Model for Web Pages

    S. Samsudeen Shaffi1,*, I. Muthulakshmi2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 183-192, 2023, DOI:10.32604/iasc.2023.031494

    Abstract As data grows in size, search engines face new challenges in extracting more relevant content for users’ searches. As a result, a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements. Unfortunately, most existing indexes and ranking algorithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations, making it impossible to deliver exceptionally accurate results. As a result, this study investigates and analyses how search engines work, as well as the elements that contribute to higher ranks. This paper addresses the… More >

  • Open Access

    ARTICLE

    Improved Key Node Recognition Method of Social Network Based on PageRank Algorithm

    Lei Hong1, Yiji Qian1,*, Chaofan Gong2, Yurui Zhang1, Xin Zhou3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1887-1903, 2023, DOI:10.32604/cmc.2023.029180

    Abstract The types and functions of social networking sites are becoming more abundant with the prevalence of self-media culture, and the number of daily active users of social networking sites represented by Weibo and Zhihu continues to expand. There are key node users in social networks. Compared with ordinary users, their influence is greater, their radiation range is wider, and their information transmission capabilities are better. The key node users playimportant roles in public opinion monitoring and hot event prediction when evaluating the criticality of nodes in social networking sites. In order to solve the problems of incomplete evaluation factors, poor… More >

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