Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (914)
  • Open Access

    ARTICLE

    Breast Cancer Diagnosis Using Feature Selection Approaches and Bayesian Optimization

    Erkan Akkur1, Fuat TURK2,*, Osman Erogul1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1017-1031, 2023, DOI:10.32604/csse.2023.033003

    Abstract Breast cancer seriously affects many women. If breast cancer is detected at an early stage, it may be cured. This paper proposes a novel classification model based improved machine learning algorithms for diagnosis of breast cancer at its initial stage. It has been used by combining feature selection and Bayesian optimization approaches to build improved machine learning models. Support Vector Machine, K-Nearest Neighbor, Naive Bayes, Ensemble Learning and Decision Tree approaches were used as machine learning algorithms. All experiments were tested on two different datasets, which are Wisconsin Breast Cancer Dataset (WBCD) and Mammographic Breast Cancer Dataset (MBCD). Experiments were… More >

  • Open Access

    ARTICLE

    A Secure Framework for Blockchain Transactions Protection

    Wafaa N. Al-Sharu1,*, Majdi K. Qabalin2, Muawya Naser2, Omar A. Saraerh1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1095-1111, 2023, DOI:10.32604/csse.2023.032862

    Abstract One of the most extensively used technologies for improving the security of IoT devices is blockchain technology. It is a new technology that can be utilized to boost the security. It is a decentralized peer-to-peer network with no central authority. Multiple nodes on the network mine or verify the data recorded on the Blockchain. It is a distributed ledger that may be used to keep track of transactions between several parties. No one can tamper with the data on the blockchain since it is unchangeable. Because the blocks are connected by hashes, the transaction data is safe. It is managed… More >

  • Open Access

    ARTICLE

    Feature Matching Combining Variable Velocity Model with Reverse Optical Flow

    Chang Zhao1, Wei Sun1,3,*, Xiaorui Zhang2,3, Xiaozheng He4, Jun Zuo1, Wei Zhao1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1083-1094, 2023, DOI:10.32604/csse.2023.032786

    Abstract The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion, which leads to a false matching, with an inaccurate pose estimation or failed tracking. To address the challenge above, a new method of feature point matching is proposed in this paper, which combines the variable velocity model with the reverse optical flow method. First, the constant velocity model is extended to a new variable velocity model, and the expanded variable velocity model is used to provide the initial pixel shifting for… More >

  • Open Access

    ARTICLE

    NOMA with Adaptive Transmit Power Using Intelligent Reflecting Surfaces

    Raed Alhamad1,*, Hatem Boujemaa2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2059-2070, 2023, DOI:10.32604/csse.2023.032610

    Abstract In this article, we use Intelligent Reflecting Surfaces (IRS) to improve the throughput of Non Orthogonal Multiple Access (NOMA) with Adaptive Transmit Power (ATP). The results are valid for Cognitive Radio Networks (CRN) where secondary source adapts its power to generate low interference at primary receiver. In all previous studies, IRS were implemented with fixed transmit power and previous results are not valid when the power of the secondary source is adaptive. In CRN, secondary nodes are allowed to transmit over the same band as primary users since they adapt their power to minimize the generated interference. Each NOMA user… More >

  • Open Access

    ARTICLE

    Healthcare Monitoring Using Ensemble Classifiers in Fog Computing Framework

    P. M. Arunkumar1, Mehedi Masud2, Sultan Aljahdali2, Mohamed Abouhawwash3,4,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2265-2280, 2023, DOI:10.32604/csse.2023.032571

    Abstract Nowadays, the cloud environment faces numerous issues like synchronizing information before the switch over the data migration. The requirement for a centralized internet of things (IoT)-based system has been restricted to some extent. Due to low scalability on security considerations, the cloud seems uninteresting. Since healthcare networks demand computer operations on large amounts of data, the sensitivity of device latency evolved among health networks is a challenging issue. In comparison to cloud domains, the new paradigms of fog computing give fresh alternatives by bringing resources closer to users by providing low latency and energy-efficient data processing solutions. Previous fog computing… More >

  • Open Access

    ARTICLE

    De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning (MCR)

    Kazim Ali1,*, Adnan N. Qureshi1, Muhammad Shahid Bhatti2, Abid Sohail2, Muhammad Hijji3, Atif Saeed2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1167-1186, 2023, DOI:10.32604/csse.2023.032508

    Abstract Brain magnetic resonance images (MRI) are used to diagnose the different diseases of the brain, such as swelling and tumor detection. The quality of the brain MR images is degraded by different noises, usually salt & pepper and Gaussian noises, which are added to the MR images during the acquisition process. In the presence of these noises, medical experts are facing problems in diagnosing diseases from noisy brain MR images. Therefore, we have proposed a de-noising method by mixing concatenation, and residual deep learning techniques called the MCR de-noising method. Our proposed MCR method is to eliminate salt & pepper… More >

  • Open Access

    ARTICLE

    Al-Biruni Earth Radius (BER) Metaheuristic Search Optimization Algorithm

    El-Sayed M. El-kenawy1,2, Abdelaziz A. Abdelhamid3,4, Abdelhameed Ibrahim5, Seyedali Mirjalili6,7, Nima Khodadad8, Mona A. Al duailij9, Amel Ali Alhussan9,*, Doaa Sami Khafaga9

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1917-1934, 2023, DOI:10.32604/csse.2023.032497

    Abstract Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and fields. Several metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention, such as particle swarm optimization (PSO), whale optimization algorithm (WOA), grey wolf optimization algorithm (GWO), genetic algorithm (GA), and gravitational search algorithm (GSA). According to the literature, no one metaheuristic optimization algorithm can handle all present optimization problems. Hence novel optimization methodologies are still needed. The Al-Biruni earth radius (BER) search optimization algorithm is proposed in this paper. The proposed algorithm was motivated by… More >

  • Open Access

    ARTICLE

    Brain Tumor: Hybrid Feature Extraction Based on UNet and 3DCNN

    Sureshkumar Rajagopal1, Tamilvizhi Thanarajan2,*, Youseef Alotaibi3, Saleh Alghamdi4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2093-2109, 2023, DOI:10.32604/csse.2023.032488

    Abstract Automated segmentation of brain tumors using Magnetic Resonance Imaging (MRI) data is critical in the analysis and monitoring of disease development. As a result, gliomas are aggressive and diverse tumors that may be split into intra-tumoral groups by using effective and accurate segmentation methods. It is intended to extract characteristics from an image using the Gray Level Co-occurrence (GLC) matrix feature extraction method described in the proposed work. Using Convolutional Neural Networks (CNNs), which are commonly used in biomedical image segmentation, CNNs have significantly improved the precision of the state-of-the-art segmentation of a brain tumor. Using two segmentation networks, a… More >

  • Open Access

    ARTICLE

    Efficient-Cost Task Offloading Scheme in Fog-Internet of Vehicle Networks

    Alla Abbas Khadir1, Seyed Amin Hosseini Seno1,2,*, Baydaa Fadhil Dhahir2,3, Rahmat Budiarto4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2223-2234, 2023, DOI:10.32604/csse.2023.032316

    Abstract Fog computing became a traditional OffLad Destination (OLD) to compute the offloaded tasks of the Internet of Vehicles (IoV). Nevertheless, the limited computing resources of the fog node leads to re-offload these tasks to the neighboring fog nodes or the cloud. Thus, the IoV will incur additional offloading costs. In this paper, we propose a new offloading scheme by utilizing RoadSide Parked Vehicles (RSPV) as an alternative OLD for IoV. The idle computing resources of the RSPVs can compute large tasks with low offloading costs compared with fog nodes and the cloud. Finally, a performance evaluation of the proposed scheme… More >

  • Open Access

    ARTICLE

    Early Warning of Commercial Housing Market Based on Bagging-GWO-SVM

    Yonghui Duan1, Keqing Zhao1,*, Yibin Guo2, Xiang Wang2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2207-2222, 2023, DOI:10.32604/csse.2023.032297

    Abstract A number of risks exist in commercial housing, and it is critical for the government, the real estate industry, and consumers to establish an objective early warning indicator system for commercial housing risks and to conduct research regarding its measurement and early warning. In this paper, we examine the commodity housing market and construct a risk index for the commodity housing market at three levels: market level, the real estate industry and the national economy. Using the Bootstrap aggregating-grey wolf optimizer-support vector machine (Bagging-GWO-SVM) model after synthesizing the risk index by applying the CRITIC objective weighting method, the commercial housing… More >

Displaying 1-10 on page 1 of 914. Per Page  

Share Link

WeChat scan