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  • Open Access

    ARTICLE

    ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images

    Yanyun Jiang1, Yuanjie Zheng1,2,*, Xiaodan Sui1, Wanzhen Jiao3, Yunlong He4, Weikuan Jia1

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 537-549, 2021, DOI:10.32604/csse.2021.014578

    Abstract Multispectral imaging (MSI) technique is often used to capture images of the fundus by illuminating it with different wavelengths of light. However, these images are taken at different points in time such that eyeball movements can cause misalignment between consecutive images. The multispectral image sequence reveals important information in the form of retinal and choroidal blood vessel maps, which can help ophthalmologists to analyze the morphology of these blood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deep learning framework called “Adversarial Segmentation… More >

  • Open Access

    ARTICLE

    A Storage Optimization Scheme for Blockchain Transaction Databases

    Jingyu Zhang1,2, Siqi Zhong1, Jin Wang1,3, Xiaofeng Yu4,*, Osama Alfarraj5

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 521-535, 2021, DOI:10.32604/csse.2021.014530

    Abstract As the typical peer-to-peer distributed networks, blockchain systems require each node to copy a complete transaction database, so as to ensure new transactions can by verified independently. In a blockchain system (e.g., bitcoin system), the node does not rely on any central organization, and every node keeps an entire copy of the transaction database. However, this feature determines that the size of blockchain transaction database is growing rapidly. Therefore, with the continuous system operations, the node memory also needs to be expanded to support the system running. Especially in the big data era, the increasing network traffic will lead to… More >

  • Open Access

    ARTICLE

    Efficient Anti-Glare Ceramic Decals Defect Detection by Incorporating Homomorphic Filtering

    Xin Chen1, Ying Zhang2, Lang Lin1, Junxiang Wang2,*, Jiangqun Ni3

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 551-564, 2021, DOI:10.32604/csse.2021.014495

    Abstract Nowadays the computer vision technique has widely found applications in industrial manufacturing process to improve their efficiency. However, it is hardly applied in the field of daily ceramic detection due to the following two key reasons: (1) Low detection accuracy as a result of ceramic glare, and (2) Lack of efficient detection algorithms. To tackle these problems, a homomorphic filtering based anti-glare ceramic decals defect detection technique is proposed in this paper. Considering that smooth ceramic surface usually causes glare effects and leads to low detection results, in our approach, the ceramic samples are taken in low light environment and… More >

  • Open Access

    ARTICLE

    On Computer Implementation for Comparison of Inverse Numerical Schemes for Non-Linear Equations

    Mudassir Shams1,*, Naila Rafiq2, Nazir Ahmad Mir1,2, Babar Ahmad3, Saqib Abbasi1, Mutee-Ur-Rehman Kayani1

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 493-507, 2021, DOI:10.32604/csse.2021.014476

    Abstract In this research article, we interrogate two new modifications in inverse Weierstrass iterative method for estimating all roots of non-linear equation simultaneously. These modifications enables us to accelerate the convergence order of inverse Weierstrass method from 2 to 3. Convergence analysis proves that the orders of convergence of the two newly constructed inverse methods are 3. Using computer algebra system Mathematica, we find the lower bound of the convergence order and verify it theoretically. Dynamical planes of the inverse simultaneous methods and classical iterative methods are generated using MATLAB (R2011b), to present the global convergence properties of inverse simultaneous iterative… More >

  • Open Access

    ARTICLE

    Cervical Diseases Prediction Using LHVR Techniques

    Praveena Rajasekaran*, Preetha Jaganathan, Anjali Annadurai

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 477-484, 2021, DOI:10.32604/csse.2021.014247

    Abstract The stabilizing mechanisms of cervical spine spondylosis are involved in the degenerating segmentation vertebra, which often causes pain. Health of the individual is affected, both physically and mentally. Due to depression, nervousness, and psychological damages occur thereby losing their human activity functions. The nucleus pulposus of spinal disc herniation is prolapsed through a deficiency of annulus fibrosus. A jelly-like core part of the disc contains proteins that cause the tissues to become swollen when it touches the nucleus pulposus. The proposed Gradient Linear Classification (GLC) algorithm is used for the efficient automatic classification of disc degeneration herniation of Inter vertebral/… More >

  • Open Access

    ARTICLE

    Stock Price Forecasting: An Echo State Network Approach

    Guang Sun1, Jingjing Lin1,*, Chen Yang1, Xiangyang Yin1, Ziyu Li1, Peng Guo1,2, Junqi Sun3, Xiaoping Fan1, Bin Pan1

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 509-520, 2021, DOI:10.32604/csse.2021.014189

    Abstract Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean… More >

  • Open Access

    REVIEW

    A Review of Energy-Related Cost Issues and Prediction Models in Cloud Computing Environments

    Mohammad Aldossary*

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 353-368, 2021, DOI:10.32604/csse.2021.014974

    Abstract With the expansion of cloud computing, optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important, since it directly affects providers’ revenue and customers’ payment. Thus, providing prediction information of the cloud services can be very beneficial for the service providers, as they need to carefully predict their business growths and efficiently manage their resources. To optimize the use of cloud services, predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs. However, such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine (PM) but… More >

  • Open Access

    ARTICLE

    Atrocious Impinging of COVID-19 Pandemic on Software Development Industries

    Wajdi Alhakami1, Ahmed Binmahfoudh2, Abdullah Baz3, Hosam Alhakami4, Md Tarique Jamal Ansari5, Raees Ahmad Khan5,*

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 323-338, 2021, DOI:10.32604/csse.2021.014929

    Abstract COVID-19 is the contagious disease transmitted by Coronavirus. The majority of people diagnosed with COVID-19 may suffer from moderate-to- severe respiratory illnesses and stabilize without preferential treatment. Those who are most likely to experience significant infections include the elderly as well as people with a history of significant medical issues including heart disease, diabetes, or chronic breathing problems. The novel Coronavirus has affected not only the physical and mental health of the people but also had adverse impact on their emotional well-being. For months on end now, due to constant monitoring and containment measures to combat COVID-19, people have been… More >

  • Open Access

    ARTICLE

    Comparative Study of Valency-Based Topological Descriptor for Hexagon Star Network

    Ali N. A. Koam1, Ali Ahmad2,*, M. F. Nadeem3

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 293-306, 2021, DOI:10.32604/csse.2021.014896

    Abstract A class of graph invariants referred to today as topological indices are inefficient progressively acknowledged by scientific experts and others to be integral assets in the depiction of structural phenomena. The structure of an interconnection network can be represented by a graph. In the network, vertices represent the processor nodes and edges represent the links between the processor nodes. Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks. A topological descriptor is a numerical total related to a structure that portray the topology of structure and is invariant under structure automorphism.… More >

  • Open Access

    ARTICLE

    Blockchain Consistency Check Protocol for Improved Reliability

    Mohammed Alwabel, Youngmi Kwon*

    Computer Systems Science and Engineering, Vol.36, No.2, pp. 281-292, 2021, DOI:10.32604/csse.2021.014630

    Abstract Blockchain is a technology that provides security features that can be used for more than just cryptocurrencies. Blockchain achieves security by saving the information of one block in the next block. Changing the information of one block will require changes to all the next block in order for that change to take effect. Which makes it unfeasible for such an attack to happen. However, the structure of how blockchain works makes the last block always vulnerable for attacks, given that its information is not saved yet in any block. This allows malicious node to change the information of the last… More >

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