Samih M. Mostafa^1,2,*

Journal on Artificial Intelligence, Vol.2, No.4, pp. 189-215, 2020, DOI:10.32604/jai.2020.014944

Abstract Because of the abundance of clustering methods, comparing between methods and determining which method is proper for a given dataset is crucial. Especially, the availability of huge experimental datasets and transactional and the emerging requirements for data mining and the like needs badly for clustering algorithms that can be applied in various domains. This paper presents essential notions of clustering and offers an overview of the significant features of the most common representative clustering algorithms of clustering categories presented in a comparative way. More specifically the study is based on the numerical type of the data that the algorithm supports,… More >

Weipeng Cao¹, Zhongwu Xie¹, Xiaofei Zhou², Zhiwu Xu¹, Cong Zhou¹, Georgios Theodoropoulos³, Qiang Wang^3,*

Journal on Artificial Intelligence, Vol.2, No.4, pp. 177-187, 2020, DOI:10.32604/jai.2020.014829

Abstract Software verification is a key technique to ensure the correctness of software. Although numerous verification algorithms and tools have been developed in the past decades, it is still a great challenge for engineers to accurately and quickly choose the appropriate verification techniques for the software at hand. In this work, we propose a general learning framework for the intelligent selection of software verification algorithms, and instantiate the framework with two state-of-the-art learning algorithms: Broad learning (BL) and deep learning (DL). The experimental evaluation shows that the training efficiency of the BL-based model is much higher than the DL-based models and… More >

Ze Chen, Leiming Yan^*, Siran Yin, Yuanmin Shi

Journal on Artificial Intelligence, Vol.2, No.4, pp. 167-175, 2020, DOI:10.32604/jai.2020.012716

Abstract With the popularity of intelligent transportation system, license plate recognition system has been widely used in the management of vehicles in and out of closed communities. But in the natural environment such as video monitoring, the performance and accuracy of recognition are not ideal. In this paper, the improved Alex net convolution neural network is used to remove the false license plate in a large range of suspected license plate areas, and then the projection transformation and Hough transformation are used to correct the inclined license plate, so as to build an efficient license plate recognition system in natural environment.… More >

Chaoyu Deng, Guangfu Zeng, Zhiping Cai, Xiaoqiang Xiao^*

Journal on Artificial Intelligence, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jai.2020.011541

Abstract The purpose of automated question answering is to let the machine understand natural language questions and give accurate answers in the form of natural language. This technology requires the machine to store a large amount of background knowledge. In recent years, the rapid development of knowledge graph has made the knowledge based question answering (KBQA) more and more popular. Traditional styles of KBQA methods mainly include semantic parsing, information extraction and vector modeling. With the development of deep learning, KBQA with deep learning has gradually become the mainstream method. This paper introduces the application of deep learning in KBQA mainly… More >

Samih M. Mostafa^1,*, Hirofumi Amano²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3253-3270, 2021, DOI:10.32604/cmc.2021.014675

Abstract CPU scheduling is the basic task within any time-shared operating system. One of the main goals of the researchers interested in CPU scheduling is minimizing time cost. Comparing between CPU scheduling algorithms is subject to some scheduling criteria (e.g., turnaround time, waiting time and number of context switches (NCS)). Scheduling policy is divided into preemptive and non-preemptive. Round Robin (RR) algorithm is the most common preemptive scheduling algorithm used in the time-shared operating systems. In this paper, the authors proposed a modified version of the RR algorithm, called dynamic time slice (DTS), to combine the advantageous of the low scheduling… More >

Shumaila Shahzadi¹, Fahad Ahmad^1,*, Asma Basharat¹, Madallah Alruwaili², Saad Alanazi², Mamoona Humayun², Muhammad Rizwan¹, Shahid Naseem³

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2723-2749, 2021, DOI:10.32604/cmc.2021.014594

Abstract With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to keep the system in the… More >

Fan Zhang^1,2, Fenlin Liu^1,2,*, Rui Xu^3,4, Xiangyang Luo^1,2, Shichang Ding⁵, Hechan Tian^1,2

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3345-3361, 2021, DOI:10.32604/cmc.2021.014526

Abstract Existing IP geolocation algorithms based on delay similarity often rely on the principle that geographically adjacent IPs have similar delays. However, this principle is often invalid in real Internet environment, which leads to unreliable geolocation results. To improve the accuracy and reliability of locating IP in real Internet, a street-level IP geolocation algorithm based on landmarks clustering is proposed. Firstly, we use the probes to measure the known landmarks to obtain their delay vectors, and cluster landmarks using them. Secondly, the landmarks are clustered again by their latitude and longitude, and the intersection of these two clustering results is taken… More >

Jamil J. Jaber^1,2, Noriszura Ismail², Siti Norafidah Mohd Ramli², Baker Albadareen², Nawaf N. Hamadneh^3,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3329-3344, 2021, DOI:10.32604/cmc.2021.014509

Abstract Loss given default (LGD) is a key parameter in credit risk management to calculate the required regulatory minimum capital. The internal ratings-based (IRB) approach under the Basel II allows institutions to determine the loss given default (LGD) on their own. In this study, we have estimated LGD for a credit portfolio data by using beta regression with precision parameter (∅) and mean parameter (μ). The credit portfolio data was obtained from a banking institution in Jordan; for the period of January 2010 until December 2014. In the first stage, we have used the “outstanding amount” and “amount of borrowing” to… More >

Jaiteg Singh¹, Tanya Gera¹, Farman Ali², Deepak Thakur¹, Karamjeet Singh³, Kyung-sup Kwak^4,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2655-2670, 2021, DOI:10.32604/cmc.2021.014504

Abstract Android has been dominating the smartphone market for more than a decade and has managed to capture 87.8% of the market share. Such popularity of Android has drawn the attention of cybercriminals and malware developers. The malicious applications can steal sensitive information like contacts, read personal messages, record calls, send messages to premium-rate numbers, cause financial loss, gain access to the gallery and can access the user’s geographic location. Numerous surveys on Android security have primarily focused on types of malware attack, their propagation, and techniques to mitigate them. To the best of our knowledge, Android malware literature has never… More >

Husam Jasim Mohammed^1,*, Hajem Ati Daham²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2229-2239, 2021, DOI:10.32604/cmc.2021.014445

Abstract In reality, the flipped classroom has gained popularity as a modern way of structuring teaching, where lectures move from in-class procedures to digitally-based assignments, freeing up the debate, and practice exercises class time. Therefore, it is essential to implement and analyze a way of teaching that will improve student performance. The paper aims to develop a model of the method of teaching science in Iraqi schools, and to assess whether teaching flipped classroom affects the achievement, motivation, and creative thinking of students by using the methodology of Multi-Criteria Decision Making (MCDM) in the Analytic Hierarchy Process (AHP). The AHP approach… More >