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9. Enterprise Resilience and Sustainability for Operations of Maritime Container Ports

Author

Kelly L. Norfleet, James H. Lambert, Rajan D. Jani, Daniel C. Hendrickson, Hollie P. Coleman, Louis G. Tanous, Daniel J. Andrews, Thomas L. Polmateer, Victoria G. Lum, Matthew R. Wajsgras, and William J. Rimer

Subjects
Strategic planning, 021110 strategic, defence & security studies, 021103 operations research, business.industry, media_common.quotation_subject, 0211 other engineering and technologies, Context (language use), 02 engineering and technology, Environmental economics, Port (computer networking), Container (abstract data type), Sustainability, Psychological resilience, business, Risk management, media_common, Liquefied natural gas
Abstract

Recent trends in markets, technologies, demographics, regulations, organizations, energy, and environments require adaptations for operations of container ports. This paper describes resilience of ports to emergent conditions in three areas: Energy and fuels, controls and automation, and logistics transformation. First, the sustainability of energy and fuels have become a priority for ports due to growing concerns of carbon emissions. Liquified natural gas (LNG) is both a cost-effective and safe alternative fuel for reducing emissions of container ships. The feasibility and several strategies for adopting LNG bunkering at ports are described. Second, ports must leverage technological development to drive greater efficiency and operative resiliency. Recent developments in industrial automation and electrification are described. Lastly, the impact of corporate development to the region of the port is discussed. An analysis of enterprise capacity expansion includes both risks and benefits to increase competitiveness. This paper uses methodology of systems and data analysis, mathematical simulation, and risk cost-benefit optimization. The key results include identifying operational and security risks for container ports and providing strategies for risk mitigation and resilience. The recommendations are discussed in context of a USD $750 million ten-year strategic plan of a major container port on the Atlantic Coast of the United States.

Published
2019
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13. An Early Detection of Asthma Using BOMLA Detector

Author

Md. Abdul Awal, Md. Shahadat Hossain, Kumar Debjit, Nafiz Ahmed, Rajan Dev Nath, G. M. Monsur Habib, Md. Salauddin Khan, Md. Akhtarul Islam, and M. A. Parvez Mahmud

Subjects
Classification, clinical and non-clinical data, asthma, ADASYN, ANOVA, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Asthma is a chronic and airway-induced disease, causing the incidence of bronchus inflammation, breathlessness, wheezing, is drastically becoming life-threatening. Even in the worst cases, it may destroy the quality to lead. Therefore, early detection of asthma is urgently needed, and machine learning can help identify asthma accurately. In this paper, a novel machine learning framework, namely BOMLA (Bayesian Optimisation-based Machine Learning framework for Asthma) detector has been proposed to detect asthma. Ten classifiers have been utilized in the BOMLA detector, where Support Vector Classifier (SVC), Random Forest (RF), Gradient Boosting Classifier (GBC), eXtreme Gradient Boosting (XGB), and Artificial Neural Network (ANN) are state-of-the-art classifiers. In contrast, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QLDA), Naive Bayes (NB), Decision Tree (DT), and K-Nearest Neighbor (KNN) are conventional popular classifiers. ADASYN algorithm has also been employed in the BOMLA detector to eradicate the issues created due to the imbalanced dataset. It has even been attempted to delineate how the ADASYN algorithm affects the classification performance. The highest accuracy (ACC) and Matthews’s correlation coefficient (MCC) for an Asthma dataset provide 94.35% and 88.97%, respectively, using BOMLA detector when SVC is adapted, and it has been increased to 96.52% and 93.04%, respectively, when ensemble technique is adapted. The one-way analysis of variance (ANOVA) has also been performed in the 10-fold cross-validation to measure the statistical significance. A decision support system has been built as a potential application of the proposed system to visualize the probable outcome of the patient. Finally, it is expected that the BOMLA detector will help patients in their early diagnosis of asthma.

Published
2021
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16. An authentication watermarking scheme with transaction tracking enabled

Author

Emmanuel, S., Achutavarrier prasad, Vinod, Rajan, D., Heng, C.K., Emmanuel, S., Achutavarrier prasad, Vinod, Rajan, D., and Heng, C.K.

Abstract

Business intelligence and customer satisfaction would be two key factors that would be used by the digital media commerce companies. For business intelligence purpose annotations for transaction tracking are required and the customers want that the digital media be authentic. In this paper, we present a novel watermarking scheme that supports authentication and transaction tracking functionalities. The watermarking scheme makes use of finite state machine principles. The proposed scheme is blind and asymmetric as it does not require the original image for watermark extraction and the watermark extraction key is different than its embedding key. The algorithm is implemented and tested for its visual quality, compression overhead, execution time overhead and pay load capacity. It is found that the algorithm has high visual quality, high payload capacity, low compression overhead and low execution time overhead. © 2007 IEEE.

Published
2007

26. An Application of Power Perturbation Method for Load Flow Analysis.

Author

Bhowmik, P. S., Rajan, D. V., Bose, S. P., Rai, P., Urvashi, and Chowdary, V. K.

Abstract

This paper presents a simple, efficient and reliable method to obtain extremely fast load flow solutions using Power Perturbation method. The proposed method shows its effectiveness with minimum number of iterations along with high accuracy on conventional load flow methods like N-R (Newton-Raphson) method. The proposed method has been applied on different IEEE 5 bus, 14 bus, 30 bus, 57 bus and 118 bus systems to show its efficacy and robustness. [ABSTRACT FROM PUBLISHER]

Published
2012
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