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  • Open Access

    ARTICLE

    Hybrid Computational Modeling for Web Application Security Assessment

    Adil Hussain Seh1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Md Tarique Jamal Ansari1, Rajeev Kumar4,*, Mohammad Ubaidullah Bokhari5, Raees Ahmad Khan1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 469-489, 2022, DOI:10.32604/cmc.2022.019593

    Abstract Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The cyber invaders continuously penetrate the… More >

  • Open Access

    ARTICLE

    Multi-Factor Authentication for Secured Financial Transactions in Cloud Environment

    D. Prabakaran1,*, Shyamala Ramachandran2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1781-1798, 2022, DOI:10.32604/cmc.2022.019591

    Abstract The rise of the digital economy and the comfort of accessing by way of user mobile devices expedite human endeavors in financial transactions over the Virtual Private Network (VPN) backbone. This prominent application of VPN evades the hurdles involved in physical money exchange. The VPN acts as a gateway for the authorized user in accessing the banking server to provide mutual authentication between the user and the server. The security in the cloud authentication server remains vulnerable to the results of threat in JP Morgan Data breach in 2014, Capital One Data Breach in 2019, and many more cloud server… More >

  • Open Access

    ARTICLE

    Power Domain Multiplexing Waveform for 5G Wireless Networks

    Korhan Cengiz1, Imran Baig2, Sumit Chakravarty3, Arun Kumar4, Mahmoud A. Albreem5, Mohammed H. Alsharif6, Peerapong Uthansakul7,*, Jamel Nebhen8, Ayman A. Aly9

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 2083-2095, 2022, DOI:10.32604/cmc.2022.019578

    Abstract Power domain non-orthogonal multiple access combined with a universal filtered multi-carrier (NOMA-UFMC) has the potential to cope with fifth generation (5G) unprecedented challenges. NOMA employs power-domain multiplexing to support several users, whereas UFMC is robust to timing and frequency misalignments. Unfortunately, NOMA-UFMC waveform has a high peak-to-average power (PAPR) issue that creates a negative affect due to multicarrier modulations, rendering it is inefficient for the impending 5G mobile and wireless networks. Therefore, this article seeks to presents a discrete Hartley transform (DHT) pre-coding-based NOMA enabled universal filter multicarrier (UFMC) (DHT-NOMA-UFMC) waveform design for lowering the high PAPR. Additionally, DHT precoding… More >

  • Open Access

    ARTICLE

    Recognition and Tracking of Objects in a Clustered Remote Scene Environment

    Haris Masood1, Amad Zafar2, Muhammad Umair Ali3, Muhammad Attique Khan4, Salman Ahmed1, Usman Tariq5, Byeong-Gwon Kang6, Yunyoung Nam6,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1699-1719, 2022, DOI:10.32604/cmc.2022.019572

    Abstract Object recognition and tracking are two of the most dynamic research sub-areas that belong to the field of Computer Vision. Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision. This paper presents an efficient ensemble algorithm for the recognition and tracking of fixed shape moving objects while accommodating the shift and scale invariances that the object may encounter. The first part uses the Maximum Average Correlation Height (MACH) filter for object recognition and determines the bounding box coordinates. In case the correlation based MACH filter fails, the algorithms… More >

  • Open Access

    ARTICLE

    Real-Time and Intelligent Flood Forecasting Using UAV-Assisted Wireless Sensor Network

    Shidrokh Goudarzi1,2,*, Seyed Ahmad Soleymani2,3, Mohammad Hossein Anisi4, Domenico Ciuonzo5, Nazri Kama6, Salwani Abdullah1, Mohammad Abdollahi Azgomi2, Zenon Chaczko7, Azri Azmi6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 715-738, 2022, DOI:10.32604/cmc.2022.019550

    Abstract The Wireless Sensor Network (WSN) is a promising technology that could be used to monitor rivers’ water levels for early warning flood detection in the 5G context. However, during a flood, sensor nodes may be washed up or become faulty, which seriously affects network connectivity. To address this issue, Unmanned Aerial Vehicles (UAVs) could be integrated with WSN as routers or data mules to provide reliable data collection and flood prediction. In light of this, we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river levels. The framework is capable to provide seamless data… More >

  • Open Access

    ARTICLE

    Defect Detection in Printed Circuit Boards with Pre-Trained Feature Extraction Methodology with Convolution Neural Networks

    Mohammed A. Alghassab*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 637-652, 2022, DOI:10.32604/cmc.2022.019527

    Abstract Printed Circuit Boards (PCBs) are very important for proper functioning of any electronic device. PCBs are installed in almost all the electronic device and their functionality is dependent on the perfection of PCBs. If PCBs do not function properly then the whole electric machine might fail. So, keeping this in mind researchers are working in this field to develop error free PCBs. Initially these PCBs were examined by the human beings manually, but the human error did not give good results as sometime defected PCBs were categorized as non-defective. So, researchers and experts transformed this manual traditional examination to automated… More >

  • Open Access

    ARTICLE

    Integrating Deep Learning and Machine Translation for Understanding Unrefined Languages

    HongGeun Ji1,2, Soyoung Oh1, Jina Kim3, Seong Choi1,2, Eunil Park1,2,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 669-678, 2022, DOI:10.32604/cmc.2022.019521

    Abstract In the field of natural language processing (NLP), the advancement of neural machine translation has paved the way for cross-lingual research. Yet, most studies in NLP have evaluated the proposed language models on well-refined datasets. We investigate whether a machine translation approach is suitable for multilingual analysis of unrefined datasets, particularly, chat messages in Twitch. In order to address it, we collected the dataset, which included 7,066,854 and 3,365,569 chat messages from English and Korean streams, respectively. We employed several machine learning classifiers and neural networks with two different types of embedding: word-sequence embedding and the final layer of a… More >

  • Open Access

    ARTICLE

    Flow Management Mechanism in Software-Defined Network

    Eugene Tan, Yung-Wey Chong*, Mohammed F. R. Anbar

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1437-1459, 2022, DOI:10.32604/cmc.2022.019516

    Abstract Software-defined networking (SDN) is a paradigm shift in modern networking. However, centralised controller architecture in SDN imposed flow setup overhead issue as the control plane handles all flows regardless of size and priority. Existing frameworks strictly reduce control plane overhead and it does not focus on rule placement of the flows itself. Furthermore, existing frameworks do not focus on managing elephant flows like RTSP. Thus, the proposed mechanism will use the flow statistics gathering method such as random packet sampling to determine elephant flow and microflow via a pre-defined threshold. This mechanism will ensure that the control plane works at… More >

  • Open Access

    ARTICLE

    Covid-19 Detection from Chest X-Ray Images Using Advanced Deep Learning Techniques

    Shubham Mahajan1,*, Akshay Raina2, Mohamed Abouhawwash3,4, Xiao-Zhi Gao5, Amit Kant Pandit1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1541-1556, 2022, DOI:10.32604/cmc.2022.019496

    Abstract Like the Covid-19 pandemic, smallpox virus infection broke out in the last century, wherein 500 million deaths were reported along with enormous economic loss. But unlike smallpox, the Covid-19 recorded a low exponential infection rate and mortality rate due to advancement in medical aid and diagnostics. Data analytics, machine learning, and automation techniques can help in early diagnostics and supporting treatments of many reported patients. This paper proposes a robust and efficient methodology for the early detection of COVID-19 from Chest X-Ray scans utilizing enhanced deep learning techniques. Our study suggests that using the Prediction and Deconvolutional Modules in combination… More >

  • Open Access

    ARTICLE

    Helix Inspired 28 GHz Broadband Antenna with End-Fire Radiation Pattern

    Hijab Zahra1, Wahaj Abbas Awan2, Niamat Hussain3,*, Syed Muzahir Abbas1,4, Subhas Mukhopadhyay1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1935-1944, 2022, DOI:10.32604/cmc.2022.019495

    Abstract This paper presents the design and characterization of a via free planar single turn helix for 28 GHz broadband applications. The proposed antenna is designed using ROGERS RO4003 material, having a simple structure and end-fire radiation pattern. The antenna comprises of a compact dimension of 1.36 λ0 × 0.9 λ0 with a thickness of 0.0189 λ0 (where λ0 is the free-space wavelength at the central frequency of 28 GHz). Parametric study has been carried out to investigate the impact of key design parameters and to achieve an optimum design. Results show a good agreement between the simulated and measured results.… More >

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