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A. Jegatheesh^1,*, M. Germin Nisha², N. Kopperundevi³
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 745-760, 2023, DOI:10.32604/iasc.2023.028011
Abstract Interacting The highest storage capacity of a circular tank makes it popular in process industries. Because of the varying surface area of the cross-sections of the tank, this two-tank level system has nonlinear characteristics. Controlling the flow rate of liquid is one of the most difficult challenges in the production process. This proposed effort is critical in preventing time delays and errors by managing the fluid level. Several scholars have explored and explored ways to reduce the problem of nonlinearity, but their techniques have not yielded better results. Different types of controllers with various techniques are implemented by the proposed… More >

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Ghada Abdulsalam¹, Souham Meshoul^2,*, Hadil Shaiba³
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 761-779, 2023, DOI:10.32604/iasc.2023.032262
Abstract Nowadays, quantum machine learning is attracting great interest in a wide range of fields due to its potential superior performance and capabilities. The massive increase in computational capacity and speed of quantum computers can lead to a quantum leap in the healthcare field. Heart disease seriously threatens human health since it is the leading cause of death worldwide. Quantum machine learning methods can propose effective solutions to predict heart disease and aid in early diagnosis. In this study, an ensemble machine learning model based on quantum machine learning classifiers is proposed to predict the risk of heart disease. The proposed… More >

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Prabhu Kaliappan^1,*, Aravindaguru Ilangovan², Sivachitra Muthusamy³, Banumathi Sembanan⁴
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 781-801, 2023, DOI:10.32604/iasc.2023.030047
Abstract This paper presents the design and performance analysis of Differential Evolution (DE) algorithm based Proportional-Integral-Derivative (PID) controller for temperature control of Continuous Stirred Tank Reactor (CSTR) plant in chemical industries. The proposed work deals about the design of Differential Evolution (DE) algorithm in order to improve the performance of CSTR. In this, the process is controlled by controlling the temperature of the liquid through manipulation of the coolant flow rate with the help of modified Model Reference Adaptive Controller (MRAC). The transient response of temperature process is improved by using PID Controller, Differential Evolution Algorithm based PID and fuzzy based… More >

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861

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K. Sugapriya^*, S. Omkumar
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 803-818, 2023, DOI:10.32604/iasc.2023.032163
Abstract The antenna plays an essential role in the medical industry. The short-range 5^th Generation (5G) communication can be used for seamless transmission, reception, patient monitoring, sensing and measuring various processes at high speeds. A passive Ultra Wide Band (UWB) antenna, used as a sensor in the measurement of Prothrombin Time (PT) i.e., blood clot is being proposed. The investigated micro-strip patch UWB antenna operating in the frequency range of 3.1 to 10.6 GHz consists of a circular patch with a diamond-shaped slot made of jeans substrate material with good sensing properties is accomplished by adjusting the copper thickness of the… More >

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591

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K. Rajesh Kumar^1,*, M. Vijayakumar²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 819-832, 2023, DOI:10.32604/iasc.2023.030961
Abstract In past decades, cellular networks have raised the usage of spectrum resources due to the victory of mobile broadband services. Mobile devices create massive data than ever before, facing the way cellular networks are installed presently for satisfying the increased traffic requirements. The development of a new exclusive spectrum offered to meet up the traffic requirements is challenging as spectrum resources are limited, hence costly. Cognitive radio technology is presented to increase the pool of existing spectrum resources for mobile users via Femtocells, placed on the top of the available macrocell network for sharing the same spectrum. Nevertheless, the concurrent… More >

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504

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S. V. Vijaya Karthik^*, J. Arputha Vijaya Selvi
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 833-847, 2023, DOI:10.32604/iasc.2023.025404
Abstract Information-Centric Networking (ICN) is considered a viable strategy for regulating Internet consumption using the Internet’s underlying architecture. Although Named Data Networking (NDN) and its reference-based implementation, the NDN Forwarding Daemon (NFD), are the most established ICN solutions, their vulnerability to the Content Poisoning Attack (CPA) is regarded as a severe threat that might dramatically impact this architecture. Content Poisoning can significantly minimize the impact of NDN’s universal data caching. Using verification signatures to protect against content poisoning attacks may be impractical due to the associated costs and the volume of messages sent across the network, resulting in high computational costs.… More >

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S. Vanitha^1,*, P. Balasubramanie²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 849-864, 2023, DOI:10.32604/iasc.2023.032324
Abstract Internet of things (IOT) possess cultural, commercial and social effect in life in the future. The nodes which are participating in IOT network are basically attracted by the cyber-attack targets. Attack and identification of anomalies in IoT infrastructure is a growing problem in the IoT domain. Machine Learning Based Ensemble Intrusion Detection (MLEID) method is applied in order to resolve the drawback by minimizing malicious actions in related botnet attacks on Message Queue Telemetry Transport (MQTT) and Hyper-Text Transfer Protocol (HTTP) protocols. The proposed work has two significant contributions which are a selection of features and detection of attacks. New… More >

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621

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S. Hanis^*
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 865-878, 2023, DOI:10.32604/iasc.2023.030597
Abstract In the recent past, the storage of images and data in the cloud has shown rapid growth due to the tremendous usage of multimedia applications. In this paper, a modulated version of the Ikeda map and key generation algorithm are proposed, which can be used as a chaotic key for securely storing images in the cloud. The distinctive feature of the proposed map is that it is hyperchaotic, highly sensitive to initial conditions, and depicts chaos over a wide range of control parameter variations. These properties prevent the attacker from detecting and extracting the keys easily. The key generation algorithm… More >

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459

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T. Shanmugapriya^1,*, Dr. K. Kousalya²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 879-894, 2023, DOI:10.32604/iasc.2023.032074
Abstract The Wireless Sensor Network (WSN) is a network of Sensor Nodes (SN) which adopt radio signals for communication amongst themselves. There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things (IoT) and Cyber-Physical Systems (CPS). Data security, detection of faults, management of energy, collection and distribution of data, network protocol, network coverage, mobility of nodes, and network heterogeneity are some of the issues confronted by WSNs. There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data. Towards the goal… More >

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598

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S. Harika^1,*, R. Seyezhai¹, A. Jawahar²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 895-910, 2023, DOI:10.32604/iasc.2023.031829
Abstract The solar powered systems require high step-up converter for efficient energy transfer. For this, quasi-impedance network converter has been introduced. The quasi-impedance network converter (QZNC) is of two types: type-1 and type-2 configuration. Both the type-1 and type-2 QZNC configurations have drooping voltage gain profile due to presence of high switching noise. To overcome this, a new quasi-impedance network converter synchronizing the switching circuit with low frequency noise has been proposed. In this paper, the proposed QZNC configuration utilizes the current controlling diode to prevent the output voltage drop. Thus, the suggested topology provides linear high voltage gain profile, low… More >

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373

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Kisaezehra¹, Muhammad Umer Farooq^1,*, Muhammad Aslam Bhutto², Abdul Karim Kazi¹
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 911-927, 2023, DOI:10.32604/iasc.2023.031359
Abstract The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety (OHS) is of prime importance. Like in other developing countries, this industry pays very little, rather negligible attention to OHS practices in Pakistan, resulting in the occurrence of a wide variety of accidents, mishaps, and near-misses every year. One of the major causes of such mishaps is the non-wearing of safety helmets (hard hats) at construction sites where falling objects from a height are unavoidable. In most cases, this leads to serious brain injuries in people present at… More >

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Lamiaa A. Abou Elazm^1,2, Walid El-Shafai^3,4, Sameh Ibrahim², Mohamed G. Egila¹, H. Shawkey¹, Mohamed K. H. Elsaid², Naglaa F. Soliman⁵, Hussah Nasser AlEisa^6,*, Fathi E. Abd El-Samie³
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 929-955, 2023, DOI:10.32604/iasc.2023.031386
Abstract Biometric security is a growing trend, as it supports the authentication of persons using confidential biometric data. Most of the transmitted data in multimedia systems are susceptible to attacks, which affect the security of these systems. Biometric systems provide sufficient protection and privacy for users. The recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of attacks. In addition, they have not been studied on different and large biometric datasets. Another point that deserves consideration is the hardware implementation of cancellable biometric recognition systems. This paper presents a suggested hybrid cancellable biometric recognition system… More >

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474

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Rashad A. Al-Jawfi^*
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 957-965, 2023, DOI:10.32604/iasc.2023.031700
Abstract Activation functions play an essential role in converting the output of the artificial neural network into nonlinear results, since without this nonlinearity, the results of the network will be less accurate. Nonlinearity is the mission of all nonlinear functions, except for polynomials. The activation function must be differentiable for backpropagation learning. This study’s objective is to determine the best activation functions for the approximation of each fractal image. Different results have been attained using Matlab and Visual Basic programs, which indicate that the bounded function is more helpful than other functions. The non-linearity of the activation function is important when… More >

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437

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Stevica Cvetkovic^1,*, Nemanja Savic¹, Ivan Ciric²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 967-979, 2023, DOI:10.32604/iasc.2023.032526
Abstract Human hand detection in uncontrolled environments is a challenging visual recognition task due to numerous variations of hand poses and background image clutter. To achieve highly accurate results as well as provide real-time execution, we proposed a deep transfer learning approach over the state-of-the-art deep learning object detector. Our method, denoted as YOLOHANDS, is built on top of the You Only Look Once (YOLO) deep learning architecture, which is modified to adapt to the single class hand detection task. The model transfer is performed by modifying the higher convolutional layers including the last fully connected layer, while initializing lower non-modified… More >

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Yao Wang¹, Yubo Wang¹, Zhenhu Ning^1,*, Sadaqat ur Rehman², Muhammad Waqas^1,3
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 981-996, 2023, DOI:10.32604/iasc.2023.030091
Abstract Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced… More >

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522

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R. Muthamil Arasi^1,*, S. Padma²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 997-1012, 2023, DOI:10.32604/iasc.2023.032645
Abstract The developing populace and industrialization power demand prompted the requirement for power generation from elective sources. The desire for this pursuit is solid due to the ever-present common assets of petroleum derivatives and their predominant ecological issues. It is generally acknowledged that sustainable power sources are one of the best answers for the energy emergency. Among these, Photovoltaic (PV) sources have many benefits to bestow a very promising future. If integrated into the existing power distribution infrastructure, the solar source will be more successful, requiring efficient Direct Current (DC)-Alternating Current (AC) conversion. This paper mainly aims to improve controllers’ performance… More >

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544

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534

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A. Reyana^1,*, P. Vijayalakshmi²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1013-1025, 2023, DOI:10.32604/iasc.2023.032538
Abstract Destructive wildfires are becoming an annual event, similar to climate change, resulting in catastrophes that wreak havoc on both humans and the environment. The result, however, is disastrous, causing irreversible damage to the ecosystem. The location of the incident and the hotspot can sometimes have an impact on early fire detection systems. With the advancement of intelligent sensor-based control technologies, the multi-sensor data fusion technique integrates data from multiple sensor nodes. The primary objective to avoid wildfire is to identify the exact location of wildfire occurrence, allowing fire units to respond as soon as possible. Thus to predict the occurrence… More >

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490

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Swarna Sudha Muppudathi¹, Valarmathi Krishnasamy^2,*
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1027-1042, 2023, DOI:10.32604/iasc.2023.031165
Abstract Social Networking Sites (SNSs) are nowadays utilized by the whole world to share ideas, images, and valuable contents by means of a post to reach a group of users. The use of SNS often inflicts the physical and the mental health of the people. Nowadays, researchers often focus on identifying the illegal behaviors in the SNS to reduce its negative influence. The state-of-art Natural Language processing techniques for anomaly detection have utilized a wide annotated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum accuracy. To overcome these issues, the proposed… More >

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463

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V. V. Nijil^*, P. Selvan
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1043-1062, 2023, DOI:10.32604/iasc.2023.028028
Abstract Alternating Current–Direct Current (AC–DC) converters require a high value bulk capacitor or a filter capacitor between the DC–DC conversion stages, which in turn causes many problems in the design of a AC–DC converter. The component package size for this capacitor is large due to its high voltage rating and capacitance value. In addition, the high charging current creates more problems during the product compliance testing phase. The shelf life of these specific high value capacitors is less than that of Multilayer Ceramic Capacitors (MLCC), which limits its use for the highly reliable applications. This paper presents a feasibility study to… More >

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446

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Jyoti Yadav^*, Suman
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1063-1078, 2023, DOI:10.32604/iasc.2023.032883
Abstract Despite the advances mobile devices have endured, they still remain resource-restricted computing devices, so there is a need for a technology that supports these devices. An emerging technology that supports such resource-constrained devices is called fog computing. End devices can offload the task to close-by fog nodes to improve the quality of service and experience. Since computation offloading is a multiobjective problem, we need to consider many factors before taking offloading decisions, such as task length, remaining battery power, latency, communication cost, etc. This study uses the multiobjective grey wolf optimization (MOGWO) technique for optimizing offloading decisions. This is the… More >

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G. Neelamegam^*, P. Marikkannu
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1079-1093, 2023, DOI:10.32604/iasc.2023.031283
Abstract Due to the development of technology in medicine, millions of health-related data such as scanning the images are generated. It is a great challenge to store the data and handle a massive volume of data. Healthcare data is stored in the cloud-fog storage environments. This cloud-Fog based health model allows the users to get health-related data from different sources, and duplicated information is also available in the background. Therefore, it requires an additional storage area, increase in data acquisition time, and insecure data replication in the environment. This paper is proposed to eliminate the de-duplication data using a window size… More >

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586

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Liaqat Ali¹, Saif E. A. Alnawayseh², Mohammed Salahat³, Taher M. Ghazal^4,5,*, Mohsen A. A. Tomh⁶, Beenu Mago⁷
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1095-1104, 2023, DOI:10.32604/iasc.2023.031335
Abstract The immediate international spread of severe acute respiratory syndrome revealed the potential threat of infectious diseases in a closely integrated and interdependent world. When an outbreak occurs, each country must have a well-coordinated and preventative plan to address the situation. Information and Communication Technologies have provided innovative approaches to dealing with numerous facets of daily living. Although intelligent devices and applications have become a vital part of our everyday lives, smart gadgets have also led to several physical and psychological health problems in modern society. Here, we used an artificial intelligence AI-based system for disease prediction using an Artificial Neural… More >

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455

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S. Gnanapriya^1,*, K. Rahimunnisa²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1105-1119, 2023, DOI:10.32604/iasc.2023.032832
Abstract The performance of Hand Gesture Recognition (HGR) depends on the hand shape. Segmentation helps in the recognition of hand gestures for more accuracy and improves the overall performance compared to other existing deep neural networks. The crucial segmentation task is extremely complicated because of the background complexity, variation in illumination etc. The proposed modified UNET and ensemble model of Convolutional Neural Networks (CNN) undergoes a two stage process and results in proper hand gesture recognition. The first stage is segmenting the regions of the hand and the second stage is gesture identification. The modified UNET segmentation model is trained using… More >

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567

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Umut Zeki^1,*, Tolgay Karanfiller², Kamil Yurtkan¹
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1121-1135, 2023, DOI:10.32604/iasc.2023.032554
Abstract Individuals with special needs learn more slowly than their peers and they need repetitions to be permanent. However, in crowded classrooms, it is difficult for a teacher to deal with each student individually. This problem can be overcome by using supportive education applications. However, the majority of such applications are not designed for special education and therefore they are not efficient as expected. Special education students differ from their peers in terms of their development, characteristics, and educational qualifications. The handwriting skills of individuals with special needs are lower than their peers. This makes the task of Handwriting Recognition (HWR)… More >

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517

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P. Saranya^*, P. Asha
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1137-1149, 2023, DOI:10.32604/iasc.2023.031470
Abstract In today’s growing modern world environment, as human food activities are changing, it is affecting human health, thus leading to diseases like cancer. Cancer is a complex disease with many subtypes that affect human health without premature treatment and cause death. So the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observation, which has become necessary to classify the type in cancer research. The research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature treatment. This paper introduces a… More >

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483

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R. K. Negesh^1,*, S. Karthikeyan²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1151-1172, 2023, DOI:10.32604/iasc.2023.027764
Abstract In the recent era, the significance of Renewable Energy (RE) sources in the process of power generation has attained considerable attention as it provides multiple beneficial impacts without harming the environment. The Photovoltaic (PV) and Doubly-Fed Induction Generator (DFIG) fed wind turbine are employed as hybrid power sources in this study. The output voltages of these sources are independently controlled by separate controllers in an optimal manner for effectively maximizing the overall performance of the system. The Reboost Luo converter is introduced in this work to maximize the output voltage of PV in an efficient manner whereas the Grey Wolf… More >

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591

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S. Keerthi^1,*, P. Santhi²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1173-1188, 2023, DOI:10.32604/iasc.2023.029959
Abstract The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain tumors. The brain tumor is characterized by an anomalous proliferation of brain cells that can either be benign or malignant. Most tumors are misdiagnosed due to the variability and complexity of lesions, which reduces the survival rate in patients. Diagnosis of brain tumors via computer vision algorithms is a challenging task. Segmentation and classification of brain tumors are currently one of the most essential surgical and pharmaceutical procedures. Traditional brain tumor identification techniques require manual segmentation or handcrafted… More >

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558

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T. Edwin Ponraj^1,*, J. Charles²
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1189-1203, 2023, DOI:10.32604/iasc.2023.033383
Abstract The mutation is a critical element in determining the proteins’ stability, becoming a core element in portraying the effects of a drug in the pharmaceutical industry. Doing wet laboratory tests to provide a better perspective on protein mutations is expensive and time-intensive since there are so many potential mutations, computational approaches that can reliably anticipate the consequences of amino acid mutations are critical. This work presents a robust methodology to analyze and identify the effects of mutation on a single protein structure. Initially, the context in a collection of words is determined using a knowledge graph for feature selection purposes.… More >

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434

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Ch. Venkat Ramana^*, Niranjan Ramchandra Thote, Arun Kumar Singh
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1205-1214, 2023, DOI:10.32604/iasc.2023.031838
Abstract The tension cracks and joints in rock or soil slopes affect their failure stability. Prediction of rock or soil slope failure is one of the most challenging tasks in the earth sciences. The actual slopes consist of inhomogeneous materials, complex morphology, and erratic joints. Most studies concerning the failure of rock slopes primarily focused on determining Factor of Safety (FoS) and Critical Slip Surface (CSS). In this article, the effect of inclined tension crack on a rock slope failure is studied numerically with Shear Strength Reduction Factor (SRF) method. An inclined Tension Crack (TC) influences the magnitude and location of… More >

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L. Jegan Antony Marcilin^*, N. M. Nandhitha
Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1215-1226, 2023, DOI:10.32604/iasc.2023.028764
Abstract Controlled thermonuclear reactors require consistent monitoring of plasma in the toroidal chamber. Better working conditions of such machines can be monitored by analyzing its radiations. Various wavelengths such as 656.3, 486.1, 464.7 nm are quite significant which are used for health monitoring of thermonuclear machines. The optical thin film filters which work on constructive and destructive interference are the ideal choices. These filters are multilayered with a pair of high and low refractive index dielectric materials. Significantly high transmission index at the desired wavelength and relatively low transmission at the other wavelengths are desired. With this as the objective, it… More >

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