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Fadl Dahan^1,2,*, Abdulelah Alwabel³
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3385-3402, 2023, DOI:10.32604/iasc.2023.030651
Abstract In recent years, cloud computing has provided a Software As A Service (SaaS) platform where the software can be reused and applied to fulfill complicated user demands according to specific Quality of Services (QoS) constraints. The user requirements are formulated as a workflow consisting of a set of tasks. However, many services may satisfy the functionality of each task; thus, searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem. This work will introduce a hybrid Artificial Bee Colony (ABC) with a Cuckoo Search (CS) algorithm to untangle service composition problem. The… More >

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S. Ayshwarya Lakshmi^1,*, K. Anandavelu²
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3403-3413, 2023, DOI:10.32604/iasc.2023.030970
Abstract Skin cancer segmentation is a critical task in a clinical decision support system for skin cancer detection. The suggested enhanced cuckoo search based optimization model will be used to evaluate several metrics in the skin cancer picture segmentation process. Because time and resources are always limited, the proposed enhanced cuckoo search optimization algorithm is one of the most effective strategies for dealing with global optimization difficulties. One of the most significant requirements is to design optimal solutions to optimize their use. There is no particular technique that can answer all optimization issues. The proposed enhanced cuckoo search optimization method indicates… More >

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521

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E. Gokulakannan^*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3415-3427, 2023, DOI:10.32604/iasc.2023.030965
Abstract Deep learning is the subset of artificial intelligence and it is used for effective decision making. Wireless Sensor based automated irrigation system is proposed to monitor and cultivate crop. Our system consists of Distributed wireless sensor environment to handle the moisture of the soil and temperature levels. It is automated process and useful for minimizing the usage of resources such as water level, quality of the soil, fertilizer values and controlling the whole system. The mobile app based smart control system is designed using deep belief network. This system has multiple sensors placed in agricultural field and collect the data.… More >

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376

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C. Gnana Thilaka^*, M. Mary Linda
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3429-3445, 2023, DOI:10.32604/iasc.2023.024028
Abstract The application of non-linear loads in the power electronic device causes serious harmonic issues in the power system since it has the intrinsic property of retrieving harmonic current and reactive power from Alternating Current (AC) supply that leads to voltage instability. To maintain a reliable power flow in the power system, an innovative Unified Power Flow Converter (UPFC) is utilized in this proposed approach. The conventional series converter is replaced with the Modular Multilevel Converter (MMC) that improves the power handling capability and achieves higher modular level with minimized distortions. The shunt compensator assists in minimizing the voltage fluctuations and… More >

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420

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U. Muthaiah^1,*, S. Chitra²
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3447-3458, 2023, DOI:10.32604/iasc.2023.028869
Abstract Image processing, agricultural production, and field monitoring are essential studies in the research field. Plant diseases have an impact on agricultural production and quality. Agricultural disease detection at a preliminary phase reduces economic losses and improves the quality of crops. Manually identifying the agricultural pests is usually evident in plants; also, it takes more time and is an expensive technique. A drone system has been developed to gather photographs over enormous regions such as farm areas and plantations. An atmosphere generates vast amounts of data as it is monitored closely; the evaluation of this big data would increase the production… More >

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T. J. Thomas Thangam^*, K. Muthu Vel
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3459-3478, 2023, DOI:10.32604/iasc.2023.025521
Abstract The generation of electricity based on renewable energy sources, particularly Photovoltaic (PV) system has been greatly increased and it is simply instigated for both domestic and commercial uses. The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power. An improved interleaved Single-ended Primary Inductor-Converter (SEPIC) converter is employed in proposed work to extricate most of power from renewable source. This proposed converter minimizes ripples, reduces electromagnetic interference due to filter elements and the continuous input current improves the power output of PV panel. A… More >

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480

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M. Vargheese^1,*, S. Vanithamani², D. Stalin David³, Ganga Rama Koteswara Rao⁴
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3479-3499, 2023, DOI:10.32604/iasc.2023.030948
Abstract Wireless networks with no infrastructure arise as a result of multiple wireless devices working together. The Mobile Ad hoc Network (MANET) is a system for connecting independently located Mobile Nodes (MNs) via wireless links. A MANET is self-configuring in telecommunications, while MN produces non-infrastructure networks that are entirely decentralized. Both the MAC and routing layers of MANETs take into account issues related to Quality of Service (QoS). When culling a line of optical discernment communication, MANET can be an effective and cost-saving route cull option. To maintain QoS, however, more or fewer challenges must be overcome. This paper proposes a… More >

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445

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M. Daniel Nareshkumar^1,*, B. Jaison²
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3501-3515, 2023, DOI:10.32604/iasc.2023.027848
Abstract With advancements in computing powers and the overall quality of images captured on everyday cameras, a much wider range of possibilities has opened in various scenarios. This fact has several implications for deaf and dumb people as they have a chance to communicate with a greater number of people much easier. More than ever before, there is a plethora of info about sign language usage in the real world. Sign languages, and by extension the datasets available, are of two forms, isolated sign language and continuous sign language. The main difference between the two types is that in isolated sign… More >

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4

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Le Quang Thao^1,2,*, Duong Duc Cuong², Vu Manh Hung³, Le Thanh Vinh³, Doan Trong Nghia⁴, Dinh Ha Hai³, Nguyen Nhan Nhi³
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3517-3530, 2023, DOI:10.32604/iasc.2023.031026
Abstract The recent outbreak of the coronavirus disease of 2019 (Covid-19) has been causing many disruptions among the education systems worldwide, most of them due to the abrupt transition to online learning. The sudden upsurge in digital electronic devices usage, namely personal computers, laptops, tablets and smartphones is unprecedented, which leads to a new wave of both mental and physical health problems among students, for example eye-related illnesses. The overexposure to electronic devices, extended screen time usage and lack of outdoor sunlight have put a consequential strain on the student’s ophthalmic health because of their young age and a relative lack… More >

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Vani Haridasan^*, Kavitha Muthukumaran, K. Hariharanath
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3531-3544, 2023, DOI:10.32604/iasc.2023.030628
Abstract Customer retention is one of the challenging issues in different business sectors, and various firms utilize customer churn prediction (CCP) process to retain existing customers. Because of the direct impact on the company revenues, particularly in the telecommunication sector, firms are needed to design effective CCP models. The recent advances in machine learning (ML) and deep learning (DL) models enable researchers to introduce accurate CCP models in the telecommunication sector. CCP can be considered as a classification problem, which aims to classify the customer into churners and non-churners. With this motivation, this article focuses on designing an arithmetic optimization algorithm… More >

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506

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C. P. Thamil Selvi^1,*, P. Muneeshwari², K. Selvasheela³, D. Prasanna⁴
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3545-3555, 2023, DOI:10.32604/iasc.2023.031097
Abstract The term sentiment analysis deals with sentiment classification based on the review made by the user in a social network. The sentiment classification accuracy is evaluated using various selection methods, especially those that deal with algorithm selection. In this work, every sentiment received through user expressions is ranked in order to categorise sentiments as informative and non-informative. In order to do so, the work focus on Query Expansion Ranking (QER) algorithm that takes user text as input and process for sentiment analysis and finally produces the results as informative or non-informative. The challenge is to convert non-informative into informative using… More >

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530

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Harish Gunigari^1,*, S. Chitra²
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3557-3571, 2023, DOI:10.32604/iasc.2023.029155
Abstract Real-time applications based on Wireless Sensor Network (WSN) technologies quickly lead to the growth of an intelligent environment. Sensor nodes play an essential role in distributing information from networking and its transfer to the sinks. The ability of dynamical technologies and related techniques to be aided by data collection and analysis across the Internet of Things (IoT) network is widely recognized. Sensor nodes are low-power devices with low power devices, storage, and quantitative processing capabilities. The existing system uses the Artificial Immune System-Particle Swarm Optimization method to minimize the energy and improve the network’s lifespan. In the proposed system, a… More >

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498

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Fei Wang^1,2, Yinxing Wan¹, Man Li^1,2, Haiyun Huang^1,2, Li Li¹, Xueying Hou¹, Jiahui Pan^1,2, Zhenfu Wen³, Jingcong Li^1,2,*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3573-3586, 2023, DOI:10.32604/iasc.2023.029698
Abstract Fatigue is a state commonly caused by overworked, which seriously affects daily work and life. How to detect mental fatigue has always been a hot spot for researchers to explore. Electroencephalogram (EEG) is considered one of the most accurate and objective indicators. This article investigated the development of classification algorithms applied in EEG-based fatigue detection in recent years. According to the different source of the data, we can divide these classification algorithms into two categories, intra-subject (within the same subject) and cross-subject (across different subjects). In most studies, traditional machine learning algorithms with artificial feature extraction methods were commonly used… More >

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Monika Khandelwal¹, Ranjeet Kumar Rout¹, Saiyed Umer², Kshira Sagar Sahoo³, NZ Jhanjhi^4,*, Mohammad Shorfuzzaman⁵, Mehedi Masud⁵
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3587-3598, 2023, DOI:10.32604/iasc.2023.029785
Abstract Classification of the patterns is a crucial structure of research and applications. Using fuzzy set theory, classifying the patterns has become of great interest because of its ability to understand the parameters. One of the problems observed in the fuzzification of an unknown pattern is that importance is given only to the known patterns but not to their features. In contrast, features of the patterns play an essential role when their respective patterns overlap. In this paper, an optimal fuzzy nearest neighbor model has been introduced in which a fuzzification process has been carried out for the unknown pattern using… More >

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369

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Ahmad Ali AlZubi^*, Jazem Mutared Alanazi
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3599-3611, 2023, DOI:10.32604/iasc.2023.027913
Abstract Pathway reconstruction, which remains a primary goal for many investigations, requires accurate inference of gene interactions and causality. Non-coding RNA (ncRNA) is studied because it has a significant regulatory role in many plant and animal life activities, but interacting micro-RNA (miRNA) and long non-coding RNA (lncRNA) are more important. Their interactions not only aid in the in-depth research of genes’ biological roles, but also bring new ideas for illness detection and therapy, as well as plant genetic breeding. Biological investigations and classical machine learning methods are now used to predict miRNA-lncRNA interactions. Because biological identification is expensive and time-consuming, machine… More >

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418

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C. Narmadha¹, T. Kavitha², R. Poonguzhali², V. Hamsadhwani³, Ranjan walia⁴, Monia⁵, B. Jegajothi^6,*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3613-3626, 2023, DOI:10.32604/iasc.2023.029323
Abstract At present days, object detection and tracking concepts have gained more importance among researchers and business people. Presently, deep learning (DL) approaches have been used for object tracking as it increases the performance and speed of the tracking process. This paper presents a novel robust DL based object detection and tracking algorithm using Automated Image Annotation with ResNet based Faster regional convolutional neural network (R-CNN) named (AIA-FRCNN) model. The AIA-RFRCNN method performs image annotation using a Discriminative Correlation Filter (DCF) with Channel and Spatial Reliability tracker (CSR) called DCF-CSRT model. The AIA-RFRCNN model makes use of Faster RCNN as an… More >

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528

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Wenjia Xiang¹, Xiaoyu Li^1,*, Zirui He¹, Chenjing Su¹, Wangchi Cheng², Chao Lu³, Shan Yang⁴
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3627-3639, 2023, DOI:10.32604/iasc.2023.030904
Abstract Estimating the intention of space objects plays an important role in aircraft design, aviation safety, military and other fields, and is an important reference basis for air situation analysis and command decision-making. This paper studies an intention estimation method based on fuzzy theory, combining probability to calculate the intention between two objects. This method takes a space object as the origin of coordinates, observes the target’s distance, speed, relative heading angle, altitude difference, steering trend and etc., then introduces the specific calculation methods of these parameters. Through calculation, values are input into the fuzzy inference model, and finally the action… More >

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348

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Meherab Mamun Ratul, Kazi Ayesha Rahman, Javeria Fazal, Naimur Rahman Abanto, Riasat Khan^*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3641-3658, 2023, DOI:10.32604/iasc.2023.030638
Abstract The coronavirus (COVID-19) is a lethal virus causing a rapidly infectious disease throughout the globe. Spreading awareness, taking preventive measures, imposing strict restrictions on public gatherings, wearing facial masks, and maintaining safe social distancing have become crucial factors in keeping the virus at bay. Even though the world has spent a whole year preventing and curing the disease caused by the COVID-19 virus, the statistics show that the virus can cause an outbreak at any time on a large scale if thorough preventive measures are not maintained accordingly. To fight the spread of this virus, technologically developed systems have become… More >

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Mohamed Ezz¹, Ayman Mohamed Mostafa^1,*, Ayman Elshenawy^2,3
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3659-3675, 2023, DOI:10.32604/iasc.2023.031561
Abstract Face authentication is an important biometric authentication method commonly used in security applications. It is vulnerable to different types of attacks that use authorized users’ facial images and videos captured from social media to perform spoofing attacks and dynamic movements for penetrating security applications. This paper presents an innovative challenge-response emotions authentication model based on the horizontal ensemble technique. The proposed model provides high accurate face authentication process by challenging the authorized user using a random sequence of emotions to provide a specific response for every authentication trial with a different sequence of emotions. The proposed model is applied to… More >

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689

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S. Maheswari, R. Vijayabhasker^*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3677-3692, 2023, DOI:10.32604/iasc.2023.031422
Abstract Mobile Ad-hoc Networks (MANET) usage across the globe is increasing by the day. Evaluating a node’s trust value has significant advantages since such network applications only run efficiently by involving trustable nodes. The trust values are estimated based on the reputation values of each node in the network by using different mechanisms. However, these mechanisms have various challenging issues which degrade the network performance. Hence, a novel Quality of Service (QoS) Trust Estimation with Black/Gray hole Attack Detection approach is proposed in this research work. Initially, the QoS-based trust estimation is proposed by using a Fuzzy logic scheme. The trust… More >

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451

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Jazem Mutared Alanazi, Ahmad Ali AlZubi^*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3693-3712, 2023, DOI:10.32604/iasc.2023.030287
Abstract Technological advancement has made a significant contribution to the change of the economy and the advancement of humanity. Because it is changing how economic transactions are carried out, the blockchain is one of the technical developments that has a lot of promise for this progress. The public record of the Bitcoin blockchain provides dispersed users with evidence of transaction ownership by publishing all transaction data from block reward transactions to unspent transaction outputs. Attacks on the public ledger, on the other hand, are a result of the fact that all transaction information are exposed. De-anonymization attacks allow users to link… More >

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406

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G. Pandiaraj^*, S. Muralidharan
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3713-3726, 2023, DOI:10.32604/iasc.2023.031463
Abstract Four-wheeled, individual-driven, nonholonomic structured mobile robots are widely used in industries for automated work, inspection and exploration purposes. The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure. The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots. However, there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion. As a result, the mobile robot has limited performance, such as chattering during curved movement. In this research work, a… More >

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665

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Hanan A. Hosni Mahmoud^1,*, Alaaeldin M. Hafez², Fahd Althukair³
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3727-3741, 2023, DOI:10.32604/iasc.2023.031442
Abstract Infinite Gaussian mixture process is a model that computes the Gaussian mixture parameters with order. This process is a probability density distribution with adequate training data that can converge to the input density curve. In this paper, we propose a data mining model namely Beta hierarchical distribution that can solve axial data modeling. A novel hierarchical Two-Hyper-Parameter Poisson stochastic process is developed to solve grouped data modelling. The solution uses data mining techniques to link datum in groups by linking their components. The learning techniques are novel presentations of Gaussian modelling that use prior knowledge of the representation hyper-parameters and… More >

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501

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P. Nithya^*, A. M. Kalpana
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3743-3755, 2023, DOI:10.32604/iasc.2023.030394
Abstract Agriculture plays a vital role in economic development. The major problem faced by the farmers are the selection of suitable crops based on environmental conditions such as weather, soil nutrients, etc. The farmers were following ancestral patterns, which could sometimes lead to the wrong selection of crops. In this research work, the feature selection method is adopted to improve the performance of the classification. The most relevant features from the dataset are obtained using a Probabilistic Feature Selection (PFS) approach, and classification is done using a Neural Fuzzy Classifier (NFC). Scaling Conjugate Gradient (SCG) optimization method is used to update… More >

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424

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E. Jayabalan^*, R. Pugazendi
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3757-3784, 2023, DOI:10.32604/iasc.2023.031200
Abstract In this paper, a communication model in cognitive radios is developed and uses machine learning to learn the dynamics of jamming attacks in cognitive radios. It is designed further to make their transmission decision that automatically adapts to the transmission dynamics to mitigate the launched jamming attacks. The generative adversarial learning neural network (GALNN) or generative dynamic neural network (GDNN) automatically learns with the synthesized training data (training) with a generator and discriminator type neural networks that encompass minimax game theory. The elimination of the jamming attack is carried out with the assistance of the defense strategies and with an… More >

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Talal H. Noor^1,*, El-Sayed Atlam², Abdulqader M. Almars¹, Ayman Noor³, Amer S. Malki¹
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3785-3799, 2023, DOI:10.32604/iasc.2023.032250
Abstract With the increase of energy consumption worldwide in several domains such as industry, education, and transportation, several technologies played an influential role in energy conservation such as the Internet of Things (IoT). In this article, we describe the design and implementation of an IoT-based energy conservation smart classroom system that contributes to energy conservation in the education domain. The proposed system not only allows the user to access and control IoT devices (e.g., lights, projectors, and air conditions) in real-time, it also has the capability to aggregate the estimated energy consumption of an IoT device, the smart classroom, and the… More >

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P. Prathap Nayudu, Krovi Raja Sekhar^*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3801-3813, 2023, DOI:10.32604/iasc.2023.032267
Abstract Due to the mobility of users in an organization, inclusion of dynamic attributes such as time and location becomes the major challenge in Ciphertext-Policy Attribute-Based Encryption (CP-ABE). By considering this challenge; we focus to present dynamic time and location information in CP-ABE with multi-authorization. At first, along with the set of attributes of the users, their corresponding location is also embedded. Geohash is used to encode the latitude and longitude of the user’s position. Then, decrypt time period and access time period of users are defined using the new time tree (NTT) structure. The NTT sets the encrypted duration of… More >

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659

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C. Gowdham^*, S. Nithyanandam
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3815-3827, 2023, DOI:10.32604/iasc.2023.031876
Abstract The Wireless Sensor Networks (WSN) are vulnerable to assaults due to the fact that the devices connected to them have a reliable connection to the internet. A malicious node acts as the controller and uses a grey hole attack to get the data from all of the other nodes in the network. Additionally, the nodes are discarding and modifying the data packets according to the requirements of the system. The assault modifies the fundamental concept of the WSNs, which is that different devices should communicate with one another. In the proposed system, there is a fuzzy idea offered for the… More >

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Siva Sankari Subbiah¹, Senthil Kumar Paramasivan^2,*, Karmel Arockiasamy³, Saminathan Senthivel⁴, Muthamilselvan Thangavel²
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3829-3844, 2023, DOI:10.32604/iasc.2023.030480
Abstract Wind speed forecasting is important for wind energy forecasting. In the modern era, the increase in energy demand can be managed effectively by forecasting the wind speed accurately. The main objective of this research is to improve the performance of wind speed forecasting by handling uncertainty, the curse of dimensionality, overfitting and non-linearity issues. The curse of dimensionality and overfitting issues are handled by using Boruta feature selection. The uncertainty and the non-linearity issues are addressed by using the deep learning based Bi-directional Long Short Term Memory (Bi-LSTM). In this paper, Bi-LSTM with Boruta feature selection named BFS-Bi-LSTM is proposed… More >

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P. N. Ramesh^1,*, S. Kannimuthu²
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3845-3860, 2023, DOI:10.32604/iasc.2023.031329
Abstract The use of programming online judges (POJs) has risen dramatically in recent years, owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming. Since POJs have greater number of programming problems in their repository, learners experience information overload. Recommender systems are a common solution to information overload. Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners’ current context, like learning goals and current skill level (topic knowledge and difficulty level). To overcome the issue, we propose a context-aware practice problem recommender system based on learners’ skill level… More >

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