Yumin Jo¹, Jongho Paik^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4153-4176, 2024, DOI:10.32604/cmc.2024.047046

Abstract Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream. However, when the transmission environment is unstable, problems such as reduction in the lifespan of equipment due to frequent switching and interruption, delay, and stoppage of services may occur. Therefore, applying a machine learning (ML) method, which is possible to automatically judge and classify network-related service anomaly, and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as… More >

Yanjun Yu¹, Lei Yu^1,*, Huiqi Wang², Haodong Zheng¹, Yi Deng¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2225-2243, 2024, DOI:10.32604/cmc.2024.047641

Abstract Bone age assessment (BAA) helps doctors determine how a child’s bones grow and develop in clinical medicine. Traditional BAA methods rely on clinician expertise, leading to time-consuming predictions and inaccurate results. Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations. This operation is costly and subjective. To address these problems, we propose a multi-scale attentional densely connected network (MSADCN) in this paper. MSADCN constructs a multi-scale dense connectivity mechanism, which can avoid overfitting, obtain the local features effectively and prevent gradient vanishing even in limited training data. First, MSADCN designs… More >

Jalaj Pateria^1,*, Laxmi Ahuja¹, Subhranil Som²

Journal of Cyber Security, Vol.4, No.4, pp. 223-238, 2022, DOI:10.32604/jcs.2023.040186

Abstract Cyberattacks have reached their peak during COVID-19, and intruders urge to gain the upper hand in the cybersecurity battlefield, even gaining dominance. Now intruders are trying harder to elude behavior analysis techniques, which in turn gets organization security to come for a toss. This phenomenon is even more prevalent in agentless environments (IOT devices, mobile devices), where we do not have any access to edge devices and rely on packet data to predict any attack and its actors. In this paper, we shall be discussing enhancing the accuracy of anomalous behavior detection techniques for efficient threat intelligence and revamping deception… More >

Jungyeon Lee¹, Malik Summair Asghar^1,2, HyungWon Kim^1,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4357-4375, 2023, DOI:10.32604/cmc.2023.031372

Abstract As deep learning techniques such as Convolutional Neural Networks (CNNs) are widely adopted, the complexity of CNNs is rapidly increasing due to the growing demand for CNN accelerator system-on-chip (SoC). Although conventional CNN accelerators can reduce the computational time of learning and inference tasks, they tend to occupy large chip areas due to many multiply-and-accumulate (MAC) operators when implemented in complex digital circuits, incurring excessive power consumption. To overcome these drawbacks, this work implements an analog convolutional filter consisting of an analog multiply-and-accumulate arithmetic circuit along with an analog-to-digital converter (ADC). This paper introduces the architecture of an analog convolutional… More >

Moeen Tayyab¹, Ayyaz Hussain^2,*, Usama Mir³, M. Aqeel Iqbal⁴, Muhammad Haneef⁵

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6177-6193, 2023, DOI:10.32604/cmc.2023.034669

Abstract The news ticker is a common feature of many different news networks that display headlines and other information. News ticker recognition applications are highly valuable in e-business and news surveillance for media regulatory authorities. In this paper, we focus on the automatic Arabic Ticker Recognition system for the Al-Ekhbariya news channel. The primary emphasis of this research is on ticker recognition methods and storage schemes. To that end, the research is aimed at character-wise explicit segmentation using a semantic segmentation technique and words identification method. The proposed learning architecture considers the grouping of homogeneous-shaped classes. This incorporates linguistic taxonomy in… More >

M. Suresh Kumar^1,*, T. Purosothaman²

Computer Systems Science and Engineering, Vol.45, No.1, pp. 925-938, 2023, DOI:10.32604/csse.2023.027315

Abstract The expanding and ubiquitous availability of the Internet of Things (IoT) have changed everyone’s life easier and more convenient. Same time it also offers a number of issues, such as effectiveness, security, and excessive power consumption, which constitute a danger to intelligent IoT-based apps. Group managing is primarily used for transmitting and multi-pathing communications that are secured with a general group key and it can only be decrypted by an authorized group member. A centralized trustworthy system, which is in charge of key distribution and upgrades, is used to maintain group keys. To provide longitudinal access controls, Software Defined Network… More >

M. Prabhu^1,*, B. Muthu Kumar²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2513-2525, 2023, DOI:10.32604/iasc.2023.027823

Abstract Orthogonal Frequency-Division Multiplexing (OFDM) is the form of a digital system and a way of encoding digital data across multiple frequency components that are used in telecommunication services. Carrier Frequency Offset (CFO) inaccuracy is a major disadvantage of OFDM. This paper proposed a feasible and elegant fuzzy-based resource allocation technique, that overcomes the constraints of the CFO. The suggested Fuzzy linear CFO estimation (FL-CFO) not only estimates the CFO with increased precision but also allocates resources effectively, and achieves maximum utilization of dynamic resources. The suggested FL-CFO error estimation algorithm in OFDM systems employing 1-bit Quadrate errors ADC (1-bit QE)… More >

Shiyan Lu, Yulan Hu, Yilin Chen, Yaru Yang, Yue Jin, Ping Li^*, Xiangyang Hu^*

Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 1879-1891, 2022, DOI:10.32604/phyton.2022.022605

Abstract Putrescine (Put) as the compound of plant polyamines is catalyzed by arginine decarboxylase (ADC), which is encoded by two members, ADC1 and ADC2 in Arabidopsis, and ADC2 is mainly responsible for Put biosynthesis. Accumulated evidence demonstrates the important function of Put in plant growth and development, but its role in regulating seed germination under high temperature (HT) has not been reported yet. SOMNUS (SOM) is the negative regulator for seed germination thermoinhibition by altering downstream gibberellin (GA) and abscisic acid (ABA) metabolism. In this study, we found exogenous application of Put obviously alleviated the inhibition effect of HT on seed… More >

Sha Li^1,2, Qiao Meng^1,*, Irfan Tariq¹, Xi Chen³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6079-6090, 2022, DOI:10.32604/cmc.2022.027404

Abstract This article presents a high speed third-order continuous-time (CT) sigma-delta analog-to-digital converter (SDADC) based on voltage-controlled oscillator (VCO), featuring a digital programmable quantizer structure. To improve the overall performance, not only oversampling technique but also noise-shaping enhancing technique is used to suppress in-band noise. Due to the intrinsic first-order noise-shaping of the VCO quantizer, the proposed third-order SDADC can realize forth-order noise-shaping ideally. As a bright advantage, the proposed programmable VCO quantizer is digital-friendly, which can simplify the design process and improve anti-interference capability of the circuit. A 4-bit programmable VCO quantizer clocked at 2.5 GHz, which is proposed in a… More >

Mumtaz Ali Shah^1,2,*, Farrukh Zeeshan Khan¹, Ghulam Abbas²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2617-2632, 2022, DOI:10.32604/cmc.2022.025981

Abstract Vehicular ad-hoc networks (VANETs) play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities. Direction-based greedy protocols pick the next route vehicle for transmitting emergency messages (EMs) depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic approach. Nevertheless, such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen continuously. Due to the high number of vehicles, it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions. A cluster-based… More >