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  • Open Access

    ARTICLE

    Interpretation of the Entangled States

    D. L. Khokhlov*

    Journal of Quantum Computing, Vol.2, No.3, pp. 147-150, 2020, DOI:10.32604/jqc.2020.014734

    Abstract An interpretation of the entangled states is considered. Two-photon states of photon A on path a and photon B on path b with polarizations H, V are constructed. Two synchronized photons, 1 and 2, can take the paths a and b, with equal probability 50%. In the bases a, b and H, V, the states of the photons form the product states. In the basis 1, 2, the states of the photons form the entangled state. The states of the photons in the bases 1, 2; a, b; H, V are inseparable. The correlation of the photons due to the entanglement in the More >

  • Open Access

    ARTICLE

    Translation of Quantum Circuits into Quantum Turing Machines for Deutsch and Deutsch-Jozsa Problems

    Giuseppe Corrente*

    Journal of Quantum Computing, Vol.2, No.3, pp. 137-145, 2020, DOI:10.32604/jqc.2020.014586

    Abstract We want in this article to show the usefulness of Quantum Turing Machine (QTM) in a high-level didactic context as well as in theoretical studies. We use QTM to show its equivalence with quantum circuit model for Deutsch and Deutsch-Jozsa algorithms. Further we introduce a strategy of translation from Quantum Circuit to Quantum Turing models by these examples. Moreover we illustrate some features of Quantum Computing such as superposition from a QTM point of view and starting with few simple examples very known in Quantum Circuit form. More >

  • Open Access

    ARTICLE

    Study on the Status of Urbanization Development and the Change of Cultivated Land Area in Nanjing

    Wenzheng Yu1,*, Jing Liu1, Mengyue Zhu2, Youzhi Yuan2

    Journal of Quantum Computing, Vol.2, No.3, pp. 129-135, 2020, DOI:10.32604/jqc.2020.09222

    Abstract The urbanization rate of Nanjing has increased in the past 55 years. Its development process can be roughly divided into the reverse urbanization phase, the stagnant development phase, the recovery development phase, the steady development phase, and the accelerated development phase. The area of cultivated land has a decreasing trend at each stage. In 1971 and beyond, urbanization development had a significant negative effect on the area of cultivated land, and the coordination between the two was not high and there was a downward trend. More >

  • Open Access

    ARTICLE

    Clustering Algorithms: Taxonomy, Comparison, and Empirical Analysis in 2D Datasets

    Samih M. Mostafa1,2,*

    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 More >

  • Open Access

    ARTICLE

    A Learning Framework for Intelligent Selection of Software Verification Algorithms

    Weipeng Cao1, Zhongwu Xie1, Xiaofei Zhou2, Zhiwu Xu1, Cong Zhou1, Georgios Theodoropoulos3, Qiang Wang3,*

    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 More >

  • Open Access

    ARTICLE

    Vehicle License Plate Recognition System Based on Deep Learning in Natural Scene

    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 More >

  • Open Access

    ARTICLE

    A Survey of Knowledge Based Question Answering with Deep Learning

    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 More >

  • Open Access

    ARTICLE

    An Adjustable Variant of Round Robin Algorithm Based on Clustering Technique

    Samih M. Mostafa1,*, 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… More >

  • Open Access

    ARTICLE

    Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment

    Shumaila Shahzadi1, Fahad Ahmad1,*, 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… More >

  • Open Access

    ARTICLE

    Street-Level IP Geolocation Algorithm Based on Landmarks Clustering

    Fan Zhang1,2, Fenlin Liu1,2,*, Rui Xu3,4, Xiangyang Luo1,2, Shichang Ding5, Hechan Tian1,2

    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… More >

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