Weiwu Ren^1,*, Xiaoqiang Di¹, Zhanwei Du², Jianping Zhao¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2057-2073, 2021, DOI:10.32604/cmc.2021.016678 - 13 April 2021

Abstract CFSFDP (Clustering by fast search and find of density peak) is a simple and crisp density clustering algorithm. It does not only have the advantages of density clustering algorithm, but also can find the peak of cluster automatically. However, the lack of adaptability makes it difficult to apply in intrusion detection. The new input cannot be updated in time to the existing profiles, and rebuilding profiles would waste a lot of time and computation. Therefore, an adaptive anomaly detection algorithm based on CFSFDP is proposed in this paper. By analyzing the influence of new input… More >

Saleem Ibraheem Saleem^1,*, Adnan Mohsin Abdulazeez¹, Zeynep Orman²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2727-2754, 2021, DOI:10.32604/cmc.2021.016447 - 13 April 2021

Abstract The writer identification (WI) of handwritten Arabic text is now of great concern to intelligence agencies following the recent attacks perpetrated by known Middle East terrorist organizations. It is also a useful instrument for the digitalization and attribution of old text to other authors of historic studies, including old national and religious archives. In this study, we proposed a new affective segmentation model by modifying an artificial neural network model and making it suitable for the binarization stage based on blocks. This modified method is combined with a new effective rotation model to achieve an… More >

Miguel-Angel Sicilia^1,*, Elena García-Barriocanal¹, Marçal Mora-Cantallops¹, Salvador Sánchez-Alonso¹, Lino González²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1661-1672, 2021, DOI:10.32604/cmc.2021.015874 - 13 April 2021

Abstract Existing studies have challenged the current definition of named bacterial species, especially in the case of highly recombinogenic bacteria. This has led to considering the use of computational procedures to examine potential bacterial clusters that are not identified by species naming. This paper describes the use of sequence data obtained from MLST databases as input for a k-means algorithm extended to deal with housekeeping gene sequences as a metric of similarity for the clustering process. An implementation of the k-means algorithm has been developed based on an existing source code implementation, and it has been More >

Sung-Jung Hsiao¹, Wen-Tsai Sung^2,*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1899-1918, 2021, DOI:10.32604/cmc.2021.015762 - 13 April 2021

Abstract This paper proposes a method for improving the data security of wireless sensor networks based on blockchain technology. Blockchain technology is applied to data transfer to build a highly secure wireless sensor network. In this network, the relay stations use microcontrollers and embedded devices, and the microcontrollers, such as Raspberry Pi and Arduino Yun, represents mobile databases. The proposed system uses microcontrollers to facilitate the connection of various sensor devices. By adopting blockchain encryption, the security of sensing data can be effectively improved. A blockchain is a concatenated transaction record that is protected by cryptography.… More >

Moatasem M. Draz¹, Marwa S. Farhan^2,3,*, Sarah N. Abdulkader^4,5, M. G. Gafar^6,7

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1919-1935, 2021, DOI:10.32604/cmc.2021.015586 - 13 April 2021

Abstract Software systems have been employed in many fields as a means to reduce human efforts; consequently, stakeholders are interested in more updates of their capabilities. Code smells arise as one of the obstacles in the software industry. They are characteristics of software source code that indicate a deeper problem in design. These smells appear not only in the design but also in software implementation. Code smells introduce bugs, affect software maintainability, and lead to higher maintenance costs. Uncovering code smells can be formulated as an optimization problem of finding the best detection rules. Although researchers… More >

Debajit Datta¹, Pramod Kumar Maurya¹, Kathiravan Srinivasan², Chuan-Yu Chang^3,*, Rishav Agarwal¹, Ishita Tuteja¹, V. Bhavyashri Vedula¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2545-2561, 2021, DOI:10.32604/cmc.2021.015478 - 13 April 2021

Abstract The pandemic situation in 2020 brought about a ‘digitized new normal’ and created various issues within the current education systems. One of the issues is the monitoring of students during online examination situations. A system to determine the student’s eye gazes during an examination can help to eradicate malpractices. In this work, we track the users’ eye gazes by incorporating twelve facial landmarks around both eyes in conjunction with computer vision and the HAAR classifier. We aim to implement eye gaze detection by considering facial landmarks with two different Convolutional Neural Network (CNN) models, namely More >

Rajesh Kumar Dhanaraj¹, Lalitha Krishnasamy², Oana Geman^3,*, Diana Roxana Izdrui⁴

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1949-1965, 2021, DOI:10.32604/cmc.2021.015363 - 13 April 2021

Abstract In Wireless Body Area Networks (WBANs) with respect to health care, sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically. The great challenges posed to healthcare WBANs are the black hole and sink hole attacks. Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path. Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness. This work proposes a hybrid detection framework for attacks by applying… More >

Ornela Bardhi^1,2,*, Begonya Garcia Zapirain¹

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326 - 13 April 2021

Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178… More >

Amena Mahmoud^1,*, Mahmoud Y. Shams², O. M. Elzeki³, Nancy Awadallah Awad⁴

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2711-2726, 2021, DOI:10.32604/cmc.2021.015293 - 13 April 2021

Abstract Semantic Web (SW) provides new opportunities for the study and application of big data, massive ranges of data sets in varied formats from multiple sources. Related studies focus on potential SW technologies for resolving big data problems, such as structurally and semantically heterogeneous data that result from the variety of data formats (structured, semi-structured, numeric, unstructured text data, email, video, audio, stock ticker). SW offers information semantically both for people and machines to retain the vast volume of data and provide a meaningful output of unstructured data. In the current research, we implement a new… More >

Sidharth Samanta¹, Mrutyunjaya Panda¹, Somula Ramasubbareddy², S. Sankar³, Daniel Burgos^4,*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1937-1948, 2021, DOI:10.32604/cmc.2021.014406 - 13 April 2021

Abstract Earth surveillance through aerial images allows more accurate identification and characterization of objects present on the surface from space and airborne platforms. The progression of deep learning and computer vision methods and the availability of heterogeneous multispectral remote sensing data make the field more fertile for research. With the evolution of optical sensors, aerial images are becoming more precise and larger, which leads to a new kind of problem for object detection algorithms. This paper proposes the “Sliding Region-based Convolutional Neural Network (SRCNN),” which is an extension of the Faster Region-based Convolutional Neural Network (RCNN) More >