Open Access
ARTICLE
K. Yuvaraj*, U. S. Ragupathy
Computer Systems Science and Engineering, Vol.40, No.3, pp. 823-834, 2022, DOI:10.32604/csse.2022.018837
Abstract This research implements a novel segmentation of mammographic mass. Three methods are proposed, namely, segmentation of mass based on iterative active contour, automatic region growing, and fully automatic mask selection-based active contour techniques. In the first method, iterative threshold is performed for manual cropped preprocessed image, and active contour is applied thereafter. To overcome manual cropping in the second method, an automatic seed selection followed by region growing is performed. Given that the result is only a few images owing to over segmentation, the third method uses a fully automatic active contour. Results of the segmentation techniques are compared with… More >
Open Access
ARTICLE
Sadia Husain1, Fouad A. Abolaban2, Ali Ahmad1, Muhammad Ahsan Asim1, Yasir Ahmad1
Computer Systems Science and Engineering, Vol.40, No.3, pp. 835-850, 2022, DOI:10.32604/csse.2022.018534
Abstract Due to the combinatorial nature of graphs they are used easily in pure sciences and social sciences. The dynamical arrangement of vertices and their associated edges make them flexible (like liquid) to attain the shape of any physical structure or phenomenon easily. In the field of ICT they are used to reflect distributed component and communication among them. Mathematical chemistry is another interesting domain of applied mathematics that endeavors to display the structure of compounds that are formed in result of chemical reactions. This area attracts the researchers due to its applications in theoretical and organic chemistry. It also inspires… More >
Open Access
ARTICLE
M. Govindarajan1,*, V. Chandrasekaran2, S. Anitha3
Computer Systems Science and Engineering, Vol.40, No.3, pp. 851-863, 2022, DOI:10.32604/csse.2022.019298
Abstract Accurate cellular network traffic prediction is a crucial task to access Internet services for various devices at any time. With the use of mobile devices, communication services generate numerous data for every moment. Given the increasing dense population of data, traffic learning and prediction are the main components to substantially enhance the effectiveness of demand-aware resource allocation. A novel deep learning technique called radial kernelized LSTM-based connectionist Tversky multilayer deep structure learning (RKLSTM-CTMDSL) model is introduced for traffic prediction with superior accuracy and minimal time consumption. The RKLSTM-CTMDSL model performs attribute selection and classification processes for cellular traffic prediction. In… More >
Open Access
ARTICLE
Vasaki Ponnusamy1, Aun Yichiet1, NZ Jhanjhi2,*, Mamoona humayun3, Maram Fahhad Almufareh3
Computer Systems Science and Engineering, Vol.40, No.3, pp. 865-879, 2022, DOI:10.32604/csse.2022.018801
Abstract Enhancement in wireless networks had given users the ability to use the Internet without a physical connection to the router. Almost every Internet of Things (IoT) devices such as smartphones, drones, and cameras use wireless technology (Infrared, Bluetooth, IrDA, IEEE 802.11, etc.) to establish multiple inter-device connections simultaneously. With the flexibility of the wireless network, one can set up numerous ad-hoc networks on-demand, connecting hundreds to thousands of users, increasing productivity and profitability significantly. However, the number of network attacks in wireless networks that exploit such flexibilities in setting and tearing down networks has become very alarming. Perpetrators can launch… More >
Open Access
ARTICLE
M. A. El Safty1,*, Samirah Al Zahrani1, Ansari Saleh Ahmar2, M. El Sayed3
Computer Systems Science and Engineering, Vol.40, No.3, pp. 881-894, 2022, DOI:10.32604/csse.2022.019549
（This article belongs to this Special Issue: Impact of Industry 4.0 on Supply Chain Management and Optimization)
Abstract Real world applications are dealing now with a huge amount of data, especially in the area of high dimensional features. In this article, we depict the simply*upper, the simply*lower continuous, we get several characteristics and other properties with respect to upper and lower simply*-continuous soft multi-functions. We also investigate the relationship between soft-continuous, simply*continuous multifunction. We also implement fuzzy soft multifunction between fuzzy soft topological spaces which is Akdag’s generation of the notion. We are introducing a new class of soft open sets, namely soft simply*open set deduce from soft topology, and we are using it to implement the new… More >
Open Access
ARTICLE
Tsung-Yin Ou1, Chen-Yang Cheng2, Chun Hsiung Lai3, Hsin-Pin Fu1,*
Computer Systems Science and Engineering, Vol.40, No.3, pp. 895-911, 2022, DOI:10.32604/csse.2022.018432
Abstract This paper proposes a solution to the open vehicle routing problem with time windows (OVRPTW) considering third-party logistics (3PL). For the typical OVRPTW problem, most researchers consider time windows, capacity, routing limitations, vehicle destination, etc. Most researchers who previously investigated this problem assumed the vehicle would not return to the depot, but did not consider its final destination. However, by considering 3PL in the B2B e-commerce, the vehicle is required back to the nearest 3PL location with available space. This paper formulates the problem as a mixed integer linear programming (MILP) model with the objective of minimizing the total travel… More >
Open Access
ARTICLE
Norjihan Binti Abdul Ghani1,*, Suraya Hamid1, Muneer Ahmad1, Younes Saadi1, N.Z. Jhanjhi2, Mohammed A. Alzain3, Mehedi Masud4
Computer Systems Science and Engineering, Vol.40, No.3, pp. 913-926, 2022, DOI:10.32604/csse.2022.018467
Abstract The world health organization (WHO) terms dengue as a serious illness that impacts almost half of the world’s population and carries no specific treatment. Early and accurate detection of spread in affected regions can save precious lives. Despite the severity of the disease, a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text streams. However, the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data, as reliable mechanisms to gather the data and suitable techniques to extract meaningful insights… More >
Open Access
ARTICLE
Azza Abdullah Alnssayan, Mohammad Mahdi Hassan*, Suliman A. Alsuhibany
Computer Systems Science and Engineering, Vol.40, No.3, pp. 927-945, 2022, DOI:10.32604/csse.2022.016734
Abstract The digitalization of healthcare-related information service systems has become a trend across the world. However, several crucial services are still provided manually due to a lack of trust in digital solutions. One such service is keeping records of children’s vaccination, which still relies on a paper-based file system in most parts of the world. This approach causes serious data integrity problems. Recently, healthcare has become a potential application area of the blockchain, as it can preserve and protect highly sensitive private medical records while sharing these records in a decentralized manner without losing personal ownership. Therefore, we propose a new… More >
Open Access
ARTICLE
Mamoona Humayun1,*, Ahmed Alsayat2
Computer Systems Science and Engineering, Vol.40, No.3, pp. 947-961, 2022, DOI:10.32604/csse.2022.019288
Abstract The recent global outbreak of COVID-19 damaged the world health systems, human health, economy, and daily life badly. None of the countries was ready to face this emerging health challenge. Health professionals were not able to predict its rise and next move, as well as the future curve and impact on lives in case of a similar pandemic situation happened. This created huge chaos globally, for longer and the world is still struggling to come up with any suitable solution. Here the better use of advanced technologies, such as artificial intelligence and deep learning, may aid healthcare practitioners in making… More >
Open Access
ARTICLE
G. Maria Jones1,*, S. Godfrey Winster2, P. Valarmathie3
Computer Systems Science and Engineering, Vol.40, No.3, pp. 963-978, 2022, DOI:10.32604/csse.2022.019483
Abstract Mobile devices and social networks provide communication opportunities among the young generation, which increases vulnerability and cybercrimes activities. A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters. This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit. We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection. We use forensics techniques, Machine Learning (ML), and Deep Learning (DL) algorithms to exploit suspicious… More >
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