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Prasanalakshmi Balaji^*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1-14, 2023, DOI:10.32604/iasc.2023.026341
Abstract Medical image assessment is based on segmentation at its fundamental stage. Deep neural networks have been more popular for segmentation work in recent years. However, the quality of labels has an impact on the training performance of these algorithms, particularly in the medical image domain, where both the interpretation cost and inter-observer variation are considerable. For this reason, a novel optimized deep learning approach is proposed for medical image segmentation. Optimization plays an important role in terms of resources used, accuracy, and the time taken. The noise in the raw medical image are processed using Quasi-Continuous Wavelet Transform (QCWT). Then,… More >

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Hafsa Naveed¹, Abid Sohail², Jasni Mohamad Zain^3,*, Noman Saleem⁴, Rao Faizan Ali⁵, Shahid Anwar⁶
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 15-30, 2023, DOI:10.32604/iasc.2023.023277
Abstract Question and answer websites such as Quora, Stack Overflow, Yahoo Answers and Answer Bag are used by professionals. Multiple users post questions on these websites to get the answers from domain specific professionals. These websites are multilingual meaning they are available in many different languages. Current problem for these types of websites is to handle meaningless and irrelevant content. In this paper we have worked on the Quora insincere questions (questions which are based on false assumptions or questions which are trying to make a statement rather than seeking for helpful answers) dataset in order to identify user insincere questions,… More >

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M. Ramya Devi^*, I. Jasmine Selvakumari Jeya
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 31-45, 2023, DOI:10.32604/iasc.2023.026152
Abstract Internet of Vehicles (IoV) is an intelligent vehicular technology that allows vehicles to communicate with each other via internet. Communications and the Internet of Things (IoT) enable cutting-edge technologies including such self-driving cars. In the existing systems, there is a maximum communication delay while transmitting the messages. The proposed system uses hybrid Co-operative, Vehicular Communication Management Framework called CAMINO (CA). Further it uses, energy efficient fast message routing protocol with Common Vulnerability Scoring System (CVSS) methodology for improving the communication delay, throughput. It improves security while transmitting the messages through networks. In this research, we present a unique intelligent vehicular… More >

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851

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Nik Muhammad Farhan Hakim Nik Badrul Alam^1,2, Ku Muhammad Naim Ku Khalif^1,*, Nor Izzati Jaini¹
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 47-61, 2023, DOI:10.32604/iasc.2023.024660
Abstract Intuitionistic fuzzy numbers incorporate the membership and non-membership degrees. In contrast, Z-numbers consist of restriction components, with the existence of a reliability component describing the degree of certainty for the restriction. The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers, namely intuitionistic Z-numbers (IZN). The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are characterized by the membership and non-membership functions, exhibiting the degree of the hesitancy of decision-makers. This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.… More >

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Venkata Sunil Srikanth^*, S. Krithiga
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 63-78, 2023, DOI:10.32604/iasc.2023.023474
Abstract Deep neural network (DNN) based computer-aided breast tumor diagnosis (CABTD) method plays a vital role in the early detection and diagnosis of breast tumors. However, a Brightness mode (B-mode) ultrasound image derives training feature samples that make closer isolation toward the infection part. Hence, it is expensive due to a meta-heuristic search of features occupying the global region of interest (ROI) structures of input images. Thus, it may lead to the high computational complexity of the pre-trained DNN-based CABTD method. This paper proposes a novel ensemble pre-trained DNN-based CABTD method using global- and local-ROI-structures of B-mode ultrasound images. It conveys… More >

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655

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R. S. Aashmi¹, T. Jaya^2,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 79-95, 2023, DOI:10.32604/iasc.2023.024291
Abstract

Cloud computing is the technology that is currently used to provide users with infrastructure, platform, and software services effectively. Under this system, Platform as a Service (PaaS) offers a medium headed for a web development platform that uniformly distributes the requests and resources. Hackers using Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks abruptly interrupt these requests. Even though several existing methods like signature-based, statistical anomaly-based, and stateful protocol analysis are available, they are not sufficient enough to get rid of Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks and hence there is a… More >

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742

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Mahmood Al-Bahri¹, Abdelhamied Ateya^2,3, Ammar Muthanna³, Abeer D. Algarni⁴, Naglaa F. Soliman^4,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 97-110, 2023, DOI:10.32604/iasc.2023.026115
Abstract The Internet of Things (IoT) is a recent technology, which implies the union of objects, “things”, into a single worldwide network. This promising paradigm faces many design challenges associated with the dramatic increase in the number of end-devices. Device identification is one of these challenges that becomes complicated with the increase of network devices. Despite this, there is still no universally accepted method of identifying things that would satisfy all requirements of the existing IoT devices and applications. In this regard, one of the most important problems is choosing an identification system for all IoT devices connected to the public… More >

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684

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K. Meenakshi^*, K. Sashi Rekha
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 111-128, 2023, DOI:10.32604/iasc.2023.025032
Abstract Blockchain technology is a shared database of logs of all consumer transactions which are registered on all machines on a network. Both transactions in the system are carried out by consensus processes and to preserve confidentiality all the files contained cannot be changed. Blockchain technology is the fundamental software behind digital currencies like Bitcoin, which is common in the marketplace. Cloud computing is a method of using a network of external machines to store, monitor, and process information, rather than using the local computer or a local personal computer. The software is currently facing multiple problems including lack of data… More >

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838

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S. Sathishkumar^1,*, R. Devi Priya²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 129-148, 2023, DOI:10.32604/iasc.2023.023817
Abstract Electrocardiogram (ECG) is a diagnostic method that helps to assess and record the electrical impulses of heart. The traditional methods in the extraction of ECG features is inneffective for avoiding the computational abstractions in the ECG signal. The cardiologist and medical specialist find numerous difficulties in the process of traditional approaches. The specified restrictions are eliminated in the proposed classifier. The fundamental aim of this work is to find the R-R interval. To analyze the blockage, different approaches are implemented, which make the computation as facile with high accuracy. The information are recovered from the MIT-BIH dataset. The retrieved data… More >

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840

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Tamara al Shloul¹, Madiha Javeed², Munkhjargal Gochoo³, Suliman A. Alsuhibany⁴, Yazeed Yasin Ghadi⁵, Ahmad Jalal², Jeongmin Park^6,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 149-161, 2023, DOI:10.32604/iasc.2023.026051
Abstract Due to the recently increased requirements of e-learning systems, multiple educational institutes such as kindergarten have transformed their learning towards virtual education. Automated student health exercise is a difficult task but an important one due to the physical education needs especially in young learners. The proposed system focuses on the necessary implementation of student health exercise recognition (SHER) using a modified Quaternion-based filter for inertial data refining and data fusion as the pre-processing steps. Further, cleansed data has been segmented using an overlapping windowing approach followed by patterns identification in the form of static and kinematic signal patterns. Furthermore, these… More >

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Yassir Edrees Almalki¹, Maryam Zaffar^2,*, Muhammad Irfan³, Mohammad Ali Abbas², Maida Khalid², K.S. Quraishi⁴, Tariq Ali⁵, Fahad Alshehri⁶, Sharifa Khalid Alduraibi⁶, Abdullah A. Asiri⁷, Mohammad Abd Alkhalik Basha⁸, Alaa Alduraibi⁶, M.K. Saeed⁷, Saifur Rahman³
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 163-180, 2023, DOI:10.32604/iasc.2023.025580
Abstract The numbers of cases and deaths due to the COVID-19 virus have increased daily all around the world. Chest X-ray is considered very useful and less time-consuming for monitoring COVID disease. No doubt, X-ray is considered as a quick screening method, but due to variations in features of images which are of X-rays category with Corona confirmed cases, the domain expert is needed. To address this issue, we proposed to utilize deep learning approaches. In this study, the dataset of COVID-19, lung opacity, viral pneumonia, and lastly healthy patients’ images of category X-rays are utilized to evaluate the performance of… More >

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725

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Smarajit Ghosh^*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 181-197, 2023, DOI:10.32604/iasc.2023.026496
Abstract The primary purpose of the Energy Management Scheme (EMS) is to monitor the energy fluctuations present in the load profile. In this paper, the improved model predictive controller is adopted for the EMS in the power system. Emperor Penguin Optimization (EPO) algorithm optimized Artificial Neural Network (ANN) with Model Predictive Control (MPC) scheme for accurate prediction of load and power forecasting at the time of pre-optimizing EMS is presented. For the power generation, Renewable Energy Sources (RES) such as photo voltaic (PV) and wind turbine (WT) are utilized along with that the fuel cell is also presented in case of… More >

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621

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Soma Prathibha^1,*, Deepak Dahiya², C. R. Rene Robin³, Cherukuru Venkata Nishkala⁴, S. Swedha⁵
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 199-214, 2023, DOI:10.32604/iasc.2023.025819
Abstract Thyroid disease is a medical condition caused due to the excess release of thyroid hormone. It is released by the thyroid gland which is in front of the neck just below the larynx. Medical pictures such as X-rays and CT scans can, however, be used to diagnose it. In this proposed model, Deep Learning technology is used to detect thyroid diseases. A Convolution Neural Network (CNN) based modified ResNet architecture is employed to detect five different types of thyroid diseases namely 1. Hypothyroid 2. Hyperthyroid 3. Thyroid cancer 4. Thyroiditis 5. Thyroid nodules. In the proposed work, the training method… More >

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815

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S. Muthukumaran^1,*, P. Geetha², E. Ramaraj¹
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 215-230, 2023, DOI:10.32604/iasc.2023.027449
Abstract Agriculture plays a vital role in the food production process that occupies nearly one-third of the total surface of the earth. Rice is propagated from the seeds of paddy and it is a stable food almost used by fifty percent of the total world population. The extensive growth of the human population alarms us to ensure food security and the country should take proper food steps to improve the yield of food grains. This paper concentrates on improving the yield of paddy by predicting the factors that influence the growth of paddy with the help of Evolutionary Computation Techniques. Most… More >

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1650

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V. Kavitha^1,*, K. Subramanian²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 231-241, 2023, DOI:10.32604/iasc.2023.024257
Abstract Induction motor drives (IMDs) can achieve high performance levels comparable to dc motor drives. A major problem in getting high dynamic performance in an IMD is the coupling between the flux and torque producing components of stator current. This is successfully overcome in FOC (Field-Oriented Control) IM, making it to the industry standard control. The performance of an IMD with an improved power quality converter at the front end is presented in this study. In the IMD, boost converter is employed to reduce power quality difficulties at the utility interface. As the boost converter contains only one switch, it results… More >

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701

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J. Priya^*, C. Palanisamy
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 243-259, 2023, DOI:10.32604/iasc.2023.025719
Abstract The Internet of Things (IoT) and Cloud computing are gaining popularity due to their numerous advantages, including the efficient utilization of internet and computing resources. In recent years, many more IoT applications have been extensively used. For instance, Healthcare applications execute computations utilizing the user’s private data stored on cloud servers. However, the main obstacles faced by the extensive acceptance and usage of these emerging technologies are security and privacy. Moreover, many healthcare data management system applications have emerged, offering solutions for distinct circumstances. But still, the existing system has issues with specific security issues, privacy-preserving rate, information loss, etc.… More >

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694

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R. Priyadharsini^*, A. Kunthavai
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 261-279, 2023, DOI:10.32604/iasc.2023.025884
Abstract Radio waves and strong magnetic fields are used by Magnetic Resonance Imaging (MRI) scanners to detect tumours, wounds and visualize detailed images of the human body. Wi-Fi and other medical devices placed in the MRI procedure room produces RF noise in MRI Images. The RF noise is the result of electromagnetic emissions produced by Wi-Fi and other medical devices that interfere with the operation of the MRI scanner. Existing techniques for RF noise mitigation involve RF shielding techniques which induce eddy currents that affect the MRI image quality. RF shielding techniques are complex and lead to RF leakage. VLC (Visible… More >

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533

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ARTICLE

Gurwinder Kaur^*, Ashwani Kumar
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 281-296, 2023, DOI:10.32604/iasc.2023.026393
Abstract Blur is produced in a digital image due to low pass filtering, moving objects or defocus of the camera lens during capture. Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a result. The high-quality input is relevant to communication service providers and imaging product makers because it may help them improve their processes. Human-based blur assessment is time-consuming, expensive and must adhere to subjective evaluation standards. This paper presents a revolutionary no-reference blur assessment algorithm based on re-blurring blurred images using a special mask developed with a Markov basis and Laplace filter. The final… More >

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645

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Rasha Almarshdi^1,2,*, Laila Nassef¹, Etimad Fadel¹, Nahed Alowidi¹
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 297-320, 2023, DOI:10.32604/iasc.2023.026799
Abstract Internet of Things (IoT) is the most widespread and fastest growing technology today. Due to the increasing of IoT devices connected to the Internet, the IoT is the most technology under security attacks. The IoT devices are not designed with security because they are resource constrained devices. Therefore, having an accurate IoT security system to detect security attacks is challenging. Intrusion Detection Systems (IDSs) using machine learning and deep learning techniques can detect security attacks accurately. This paper develops an IDS architecture based on Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) deep learning algorithms. We implement our model… More >

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887

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Hanan A. Hosni Mahmoud¹, Alaaeldin M. Hafez², Eatedal Alabdulkreem^1,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 321-334, 2023, DOI:10.32604/iasc.2023.026235
Abstract Languages–independent text tokenization can aid in classification of languages with few sources. There is a global research effort to generate text classification for any language. Human text classification is a slow procedure. Consequently, the text summary generation of different languages, using machine text classification, has been considered in recent years. There is no research on the machine text classification for many languages such as Czech, Rome, Urdu. This research proposes a cross-language text tokenization model using a Transformer technique. The proposed Transformer employs an encoder that has ten layers with self-attention encoding and a feedforward sublayer. This model improves the… More >

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804

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Rachid Karra^*, Abdelali Lasfar
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 335-349, 2023, DOI:10.32604/iasc.2023.026695
Abstract In contrast with the research of new models, little attention has been paid to the impact of low or high-quality data feeding a dialogue system. The present paper makes the first attempt to fill this gap by extending our previous work on question-answering (QA) systems by investigating the effect of misspelling on QA agents and how context changes can enhance the responses. Instead of using large language models trained on huge datasets, we propose a method that enhances the model's score by modifying only the quality and structure of the data feed to the model. It is important to identify… More >

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639

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Anitha Govindhan^1,*, Karnam Anantha Sunitha², Sivanathan Kandhasamy³
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 351-365, 2023, DOI:10.32604/iasc.2023.026361
Abstract This paper presents a Model-Based Design (MBD) approach for the design and control of a customized manipulator intended for drilling and positioning of dental implants accurately with minimal human intervention. While performing an intra-oral surgery for a prolonged duration within a limited oral cavity, the tremor of dentist's hand is inevitable. As a result, wielding the drilling tool and inserting the dental implants safely in accurate position and orientation is highly challenging even for experienced dentists. Therefore, we introduce a customized manipulator that is designed ergonomically by taking in to account the dental chair specifications and anthropomorphic data such that… More >

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Ashit Kumar Dutta^1,*, Yasser Albagory², Majed Alsanea³, Abdul Rahaman Wahab Sait⁴, Hazim Saleh AlRawashdeh⁵
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 367-380, 2023, DOI:10.32604/iasc.2023.027076
Abstract Wireless sensor network (WSN) plays a vital part in real time tracking and data collection applications. WSN incorporates a set of numerous sensor nodes (SNs) commonly utilized to observe the target region. The SNs operate using an inbuilt battery and it is not easier to replace or charge it. Therefore, proper utilization of available energy in the SNs is essential to prolong the lifetime of the WSN. In this study, an effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection (TFL-BOARS) has been developed for clustered WSN. The TFL-BOARS technique intends to optimally select the cluster heads (CHs) and… More >

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P. Srinivasan^1,*, P. Jagatheeswari²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 381-397, 2023, DOI:10.32604/iasc.2023.024179
Abstract Renewable energy production plays a major role in satisfying electricity demand. Wind power conversion is one of the most popular renewable energy sources compared to other sources. Wind energy conversion has two major types of generators such as the Permanent Magnet Synchronous Generator (PMSG) and the Doubly Fed Induction Generator (DFIG). The maximum power tracking algorithm is a crucial controller, a wind energy conversion system for generating maximum power in different wind speed conditions. In this article, the DFIG wind energy conversion system was developed in Matrix Laboratory (MATLAB) and designed a machine learning (ML) algorithm for the rotor and… More >

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696

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Ulagammai Meyyappan^*, S. Joyal Isac
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 399-413, 2023, DOI:10.32604/iasc.2023.026627
Abstract Demand Response (DR) is one of the most cost-effective and unfailing techniques used by utilities for consumer load shifting. This research paper presents different DR programs in deregulated environments. The description and the classification of DR along with their potential benefits and associated cost components are presented. In addition, most DR measurement indices and their evaluation are also highlighted. Initially, the economic load model incorporated thermal, wind, and energy storage by considering the elasticity market price from its calculated locational marginal pricing (LMP). The various DR programs like direct load control, critical peak pricing, real-time pricing, time of use, and… More >

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Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 415-430, 2023, DOI:10.32604/iasc.2023.027618
Abstract This study mainly uses the concept of the Internet of Things (IoT) to establish a smart house with an indoor, comfortable, environmental, and real-time monitoring system. In the smart house, this investigation employed the temperature- and humidity-sensing module and the lightness module to monitor any condition for an intelligent-living house. The data of temperature, humidity, and lightness are transmitted wirelessly to the human-machine interface. The correlation of the weight of the extension theory is used to analyze the ideal and comfortable environment so that people in the indoor environment can feel better thermal comfort and lightness. In this study, improved… More >

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581

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T. R. Manikandan^*, Venkatesan Thangavelu
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 431-447, 2023, DOI:10.32604/iasc.2023.026546
Abstract The purpose of the Combined Economic Emission Dispatch (CEED) of electric power is to offer the most exceptional schedule for production units, which must run with both low fuel costs and emission levels concurrently, thereby meeting the lack of system equality and inequality constraints. Economic and emissions dispatching has become a primary and significant concern in power system networks. Consequences of using non-renewable fuels as input to exhaust power systems with toxic gas emissions and depleted resources for future generations. The optimal power allocation to generators serves as a solution to this problem. Emission dispatch reduces emissions while ignoring economic… More >

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T. Jagadesh^1,2, B. Sheela Rani^3,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 449-463, 2023, DOI:10.32604/iasc.2023.026868
Abstract Interference is a key factor in radar return misdetection. Strong interference might make it difficult to detect the signal or targets. When interference occurs in the sidelobes of the antenna pattern, Sidelobe Cancellation (SLC) and Sidelobe Blanking are two unique solutions to solve this problem (SLB). Aside from this approach, the probability of false alert and likelihood of detection are the most essential parameters in radar. The chance of a false alarm for any radar system should be minimal, and as a result, the probability of detection should be high. There are several interference cancellation strategies in the literature that… More >

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S. Leo Pauline^1,*, T. R. GaneshBabu²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 465-473, 2023, DOI:10.32604/iasc.2023.024030
Abstract In this paper Substrate Integrated Waveguide-based filtenna operating at Ku band is proposed. The model is designed on a low loss dielectric substrate having a thickness of 0.508 mm and comprises of shorting vias along two edges of the substrate walls. To realize a bandpass filter, secondary shorting vias are placed close to primary shorting vias. The dimension and position of the vias are carefully analyzed for Ku band frequencies. The model is fabricated on Roger RT/duroid 5880 and the performance characteristics are measured. The proposed model achieves significant impedance characteristics with wider bandwidth in the Ku band. The model also… More >

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G. Nagalalli^*, G. Ravi
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 475-490, 2023, DOI:10.32604/iasc.2023.026571
Abstract Wireless Sensor Network (WSN), which finds as one of the major components of modern electronic and wireless systems. A WSN consists of numerous sensor nodes for the discovery of sensor networks to leverage features like data sensing, data processing, and communication. In the field of medical health care, these network plays a very vital role in transmitting highly sensitive data from different geographic regions and collecting this information by the respective network. But the fear of different attacks on health care data typically increases day by day. In a very short period, these attacks may cause adversarial effects to the… More >

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S. Padmapriya¹, R. Shankar², R. Thiagarajan^1,*, N. Partheeban³, A. Daniel³, S. Arun⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 491-505, 2023, DOI:10.32604/iasc.2023.027719
Abstract The Mobile Ad-hoc Network (MANET) is a dynamic topology that provides a variety of executions in various disciplines. The most sticky topic in organizational fields was MANET protection. MANET is helpless against various threats that affect its usability and accessibility. The dark opening assault is considered one of the most far-reaching dynamic assaults that deteriorate the organization's execution and reliability by dropping all approaching packages via the noxious node. The Dark Opening Node aims to deceive any node in the company that wishes to connect to another node by pretending to get the most delicate ability to support the target… More >

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552

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K. S. Riya¹, R. Surendran^2,*, Carlos Andrés Tavera Romero³, M. Sadish Sendil⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 507-520, 2023, DOI:10.32604/iasc.2023.027779
Abstract Internet of Medical Things (IoMT) enabled e-healthcare has the potential to greately improve conventional healthcare services significantly. However, security and privacy become major issues of IoMT because of the restricted processing abilities, storage, and energy constraints of the sensors. Therefore, it leads to infeasibility of developing traditional cryptographic solutions to the IoMT sensors. In order to ensure security on sensitive medical data, effective encryption and authentication techniques need to be designed to assure security of the patients and healthcare service providers. In this view, this study designs an effective metaheuristic optimization based encryption with user authentication (EMOE-UA) technique for IoMT… More >

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Kavitha Muthukumaran^*, K. Hariharanath
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 521-536, 2023, DOI:10.32604/iasc.2023.025968
Abstract Recently, data science techniques utilize artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to take an influence and grow their businesses. For SMEs, owing to the inexistence of consistent data and other features, evaluating credit risks is difficult and costly. On the other hand, it becomes necessary to design efficient models for predicting business failures or financial crises of SMEs. Various data classification approaches for financial crisis prediction (FCP) have been presented for predicting the financial status of the organization by the use of past data. A major process involved in the design of FCP… More >

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Amishi Mahesh Kapadia^*, P. Nithyanandam
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 537-552, 2023, DOI:10.32604/iasc.2023.027070
Abstract Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret image. We suggested a technique in this research that uses a recursive embedding method to increase capacity substantially using the Integer wavelet transform and the Arnold transform. The notion of Integer wavelet transforms is to ensure that all coefficients of the cover images are used during embedding with an increase in payload. By scrambling the cover image, Arnold transform adds security to the information that gets embedded and also allows embedding more information in each iteration.… More >

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Ayman Altameem¹, Ramesh Chandra Poonia², Ankit Kumar³, Linesh Raja⁴, Abdul Khader Jilani Saudagar^5,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 553-566, 2023, DOI:10.32604/iasc.2023.027579
Abstract Data clustering is crucial when it comes to data processing and analytics. The new clustering method overcomes the challenge of evaluating and extracting data from big data. Numerical or categorical data can be grouped. Existing clustering methods favor numerical data clustering and ignore categorical data clustering. Until recently, the only way to cluster categorical data was to convert it to a numeric representation and then cluster it using current numeric clustering methods. However, these algorithms could not use the concept of categorical data for clustering. Following that, suggestions for expanding traditional categorical data processing methods were made. In addition to… More >

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M. P. Karthikeyan^1,*, E. A. Mary Anita²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 567-580, 2023, DOI:10.32604/iasc.2023.026243
Abstract In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indicator of diabetic retinopathy. With that in mind, the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine… More >

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Sagar Mekala^1,*, K. Shahu Chatrapati²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 581-593, 2023, DOI:10.32604/iasc.2023.023539
Abstract In the contemporary era of unprecedented innovations such as Internet of Things (IoT), modern applications cannot be imagined without the presence of Wireless Sensor Network (WSN). Nodes in WSN use neighbour discovery (ND) protocols to have necessary communication among the nodes. Neighbour discovery process is crucial as it is to be done with energy efficiency and minimize discovery latency and maximize percentage of neighbours discovered. The current ND approaches that are indirect in nature are categorized into methods of removal of active slots from wake-up schedules and intelligent addition of new slots. The two methods are found to have certain… More >

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S. P. Abirami^1,*, G. Kousalya¹, R. Karthick²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 595-607, 2023, DOI:10.32604/iasc.2023.027562
Abstract Autism Spectrum Disorder (ASD) is found to be a major concern among various occupational therapists. The foremost challenge of this neurodevelopmental disorder lies in the fact of analyzing and exploring various symptoms of the children at their early stage of development. Such early identification could prop up the therapists and clinicians to provide proper assistive support to make the children lead an independent life. Facial expressions and emotions perceived by the children could contribute to such early intervention of autism. In this regard, the paper implements in identifying basic facial expression and exploring their emotions upon a time-variant factor. The… More >

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525

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G. Girishkumar^1,*, S. Ganesan², N. Jayakumar³, S. Subramanian⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 609-625, 2023, DOI:10.32604/iasc.2023.027514
Abstract The optimization field has grown tremendously, and new optimization techniques are developed based on statistics and evolutionary procedures. Therefore, it is necessary to identify a suitable optimization technique for a particular application. In this work, Black Widow Optimization (BWO) algorithm is introduced to minimize the cost functions in order to optimize the Multi-Area Economic Dispatch (MAED). The BWO is implemented for two different-scale test systems, comprising 16 and 40 units with three and four areas. The performance of BWO is compared with the available optimization techniques in the literature to demonstrate the strategy’s efficacy. Results show that the optimized cost… More >

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522

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K. Meenakshi^1,*, G. Maragatham²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 627-643, 2023, DOI:10.32604/iasc.2023.026961
Abstract Deep Learning is one of the most popular computer science techniques, with applications in natural language processing, image processing, pattern identification, and various other fields. Despite the success of these deep learning algorithms in multiple scenarios, such as spam detection, malware detection, object detection and tracking, face recognition, and automatic driving, these algorithms and their associated training data are rather vulnerable to numerous security threats. These threats ultimately result in significant performance degradation. Moreover, the supervised based learning models are affected by manipulated data known as adversarial examples, which are images with a particular level of noise that is invisible… More >

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669

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D. Karthikeyan^1,*, V. Mohan Raj², J. Senthilkumar², Y. Suresh²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 645-659, 2023, DOI:10.32604/iasc.2023.027039
Abstract The number of attacks is growing tremendously in tandem with the growth of internet technologies. As a result, protecting the private data from prying eyes has become a critical and tough undertaking. Many intrusion detection solutions have been offered by researchers in order to decrease the effect of these attacks. For attack detection, the prior system has created an SMSRPF (Stacking Model Significant Rule Power Factor) classifier. To provide creative instance detection, the SMSRPF combines the detection of trained classifiers such as DT (Decision Tree) and RF (Random Forest). Nevertheless, it does not generate any accurate findings that are adequate.… More >

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709

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Chih-Fang Huang^1,*, Ai-Hsien Fan², Jin-Huang Huang³, Hsing-Cheng Huang³
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 661-673, 2023, DOI:10.32604/iasc.2023.027165
Abstract This study applies the diatonic chord in music theory, utilization rate, and the close relationship between the main chord system, the dominant chord system, and the subordinate chord system. From the perspective of music theory, the computer can automatically and quickly analyze the music, and establish a set of algorithms for configuring the chord accompaniment for the main melody, called the symmetrical circle of fifths algorithm, SCFA (Symmetrical Circle of Fifths Algorithm). SCFA can immediately confirm the key, perform harmony analysis, configure chord accompaniment for the main melody, and effectively and correctly complete any given melody or interval. It can… More >

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718

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A. Soujanya^1,*, N. Nandhagopal²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 675-687, 2023, DOI:10.32604/iasc.2023.025930
Abstract Due to the rising occurrence of skin cancer and inadequate clinical expertise, it is needed to design Artificial Intelligence (AI) based tools to diagnose skin cancer at an earlier stage. Since massive skin lesion datasets have existed in the literature, the AI-based Deep Learning (DL) models find useful to differentiate benign and malignant skin lesions using dermoscopic images. This study develops an Automated Seeded Growing Segmentation with Optimal EfficientNet (ARGS-OEN) technique for skin lesion segmentation and classification. The proposed ASRGS-OEN technique involves the design of an optimal EfficientNet model in which the hyper-parameter tuning process takes place using the Flower… More >

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677

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M. N. Kavitha^1,*, A. RajivKannan²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 689-704, 2023, DOI:10.32604/iasc.2023.025437
Abstract Facial Expression Recognition (FER) has been an important field of research for several decades. Extraction of emotional characteristics is crucial to FERs, but is complex to process as they have significant intra-class variances. Facial characteristics have not been completely explored in static pictures. Previous studies used Convolution Neural Networks (CNNs) based on transfer learning and hyperparameter optimizations for static facial emotional recognitions. Particle Swarm Optimizations (PSOs) have also been used for tuning hyperparameters. However, these methods achieve about 92 percent in terms of accuracy. The existing algorithms have issues with FER accuracy and precision. Hence, the overall FER performance is… More >

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680

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M. Suresh Kumar^1,*, G. A. Sathish Kumar²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 705-725, 2023, DOI:10.32604/iasc.2023.027545
Abstract The growth of Wireless Sensor Networks (WSNs) has revolutionized the field of technology and it is used in different application frameworks. Unmanned edges and other critical locations can be monitored using the navigation sensor node. The WSN required low energy consumption to provide a high network and guarantee the ultimate goal. The main objective of this work is to propose hybrid energy optimization in local aware environments. The hybrid proposed work consists of clustering, optimization, direct and indirect communication and routing. The aim of this research work is to provide and framework for reduced energy and trusted communication with the… More >

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624

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Dae-Young Kim, Seokhoon Kim^*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 727-737, 2023, DOI:10.32604/iasc.2023.027563
Abstract As the Internet of Things (IoT) advances, machine-type devices are densely deployed and massive networks such as ultra-dense networks (UDNs) are formed. Various devices attend to the network to transmit data using machine-type communication (MTC), whereby numerous, various are generated. MTC devices generally have resource constraints and use wireless communication. In this kind of network, data aggregation is a key function to provide transmission efficiency. It can reduce the number of transmitted data in the network, and this leads to energy saving and reducing transmission delays. In order to effectively operate data aggregation in UDNs, it is important to select… More >

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538

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K. Subramanian^*, S. Shanmugavel
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 739-754, 2023, DOI:10.32604/iasc.2023.027248
Abstract Target coverage and continuous connection are the major recital factors for Wireless Sensor Network (WSN). Several previous research works studied various algorithms for target coverage difficulties; however they lacked to focus on improving the network’s life time in terms of energy. This research work mainly focuses on target coverage and area coverage problem in a heterogeneous WSN with increased network lifetime. The dynamic behavior of the target nodes is unpredictable, because the target nodes may move at any time in any direction of the network. Thus, target coverage becomes a major problem in WSN and its applications. To solve the… More >

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Ziad M. Ali^1,2,*, Ahmed M. Galal^1,3, Salem Alkhalaf⁴, Imran Khan⁵
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 755-767, 2023, DOI:10.32604/iasc.2023.027568
Abstract The large-scale application of renewable energy power generation technology brings new challenges to the operation of traditional power grids and energy management on the load side. Microgrid can effectively solve this problem by using its regulation and flexibility, and is considered to be an ideal platform. The traditional method of computing total transfer capability is difficult due to the central integration of wind farms. As a result, the differential evolution extreme learning machine is offered as a data mining approach for extracting operating rules for the total transfer capability of tie-lines in wind-integrated power systems. K-medoids clustering under the two-dimensional… More >

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726

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Mahmoud Helal^1,2, Elsayed Fathallah^3,4, Abdulaziz H Alghtani¹, Hussein Shawki Osman⁵, Jong Wan Hu^6,7,*, Hasan Eleashy⁸
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 769-793, 2023, DOI:10.32604/iasc.2023.025618
Abstract To increase the payload, reduce energy consumption, improve work efficiency and therefore must accordingly reduce the total hull weight of the submersible. This paper introduces a design optimization process for the pressure-hull of submarines under uniform external hydrostatic pressure using both finite element analysis (FEA) and optimization tools. A comprehensive study about the optimum design of the pressure hull, to minimize the weight and increase the volume, to reach minimum buoyancy factor and maximum operating depth minimizing the buoyancy factor (B.F) is taken as an objective function with constraints of plate and frame yielding, general instability and deflection. The optimization… More >

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Kiran Jot Singh¹, Divneet Singh Kapoor^1,*, Mohamed Abouhawwash^2,3, Jehad F. Al-Amri⁴, Shubham Mahajan⁵, Amit Kant Pandit⁵
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 795-810, 2023, DOI:10.32604/iasc.2023.025177
Abstract Navigation is an essential skill for robots. It becomes a cumbersome task for the robot in a human-populated environment, and Industry 5.0 is an emerging trend that focuses on the interaction between humans and robots. Robot behavior in a social setting is the key to human acceptance while ensuring human comfort and safety. With the advancement in robotics technology, the true use cases of robots in the tourism and hospitality industry are expanding in number. There are very few experimental studies focusing on how people perceive the navigation behavior of a delivery robot. A robotic platform named “PI” has been… More >

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