Open Access

ARTICLE

J. Premalatha^*, A. SahayaAnselin Nisha
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 811-826, 2023, DOI:10.32604/iasc.2023.026523
Abstract The traffic activity of fifth generation (5G) networks demand for new energy management techniques that is dynamic deep and longer duration of sleep as compared to the fourth generation (4G) network technologies that demand always for varied control and data signalling based on control base station (CBS) and data base station (DBS). Hence, this paper discusses the energy management in wireless cellular networks using wide range of control for twice the reduction in energy conservation in non-standalone deployment of 5G network. As the new radio (NR) based 5G network is configured to transmit signal blocks for every 20 ms, the proposed… More >

View

1165

Download

603

Open Access

ARTICLE

C. Ambhika^1,*, C. Murukesh²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 827-838, 2023, DOI:10.32604/iasc.2023.026832
Abstract With the demand for wireless technology, Cognitive Radio (CR) technology is identified as a promising solution for effective spectrum utilization. Connectivity and robustness are the two main difficulties in cognitive radio networks due to their dynamic nature. These problems are solved by using clustering techniques which group the cognitive users into logical groups. The performance of clustering in cognitive network purely depends on cluster head selection and parameters considered for clustering. In this work, an adaptive neuro-fuzzy inference system (ANFIS) based clustering is proposed for the cognitive network. The performance of ANFIS improved using hybrid particle swarm and whale optimization… More >

View

1099

Download

529

Open Access

ARTICLE

B. Murugeshwari^1,*, D. Selvaraj², K. Sudharson³, S. Radhika⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 839-851, 2023, DOI:10.32604/iasc.2023.028548
Abstract Protecting the privacy of data in the multi-cloud is a crucial task. Data mining is a technique that protects the privacy of individual data while mining those data. The most significant task entails obtaining data from numerous remote databases. Mining algorithms can obtain sensitive information once the data is in the data warehouse. Many traditional algorithms/techniques promise to provide safe data transfer, storing, and retrieving over the cloud platform. These strategies are primarily concerned with protecting the privacy of user data. This study aims to present data mining with privacy protection (DMPP) using precise elliptic curve cryptography (PECC), which builds… More >

View

1314

Download

654

Open Access

ARTICLE

S. Sakthivel¹, V. Vivekanandhan^2,*, M. Manikandan²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 853-866, 2023, DOI:10.32604/iasc.2023.026289
Abstract Irrigation plays a significant role in various agricultural cropping methods deployed in semiarid and arid regions where valuable water applications and managing are considered crucial concerns. Multiple factors such as weather, soil, water, and crop data need to be considered for irrigation maintenance in an efficient besides uniform manner from multifaceted and different information-based systems. A Multi-Agent System (MAS) has been proposed recently based on diverse agent subsystems with definite objectives for attaining global MAS objective and is deployed on Cloud Computing paradigm capable of gathering information from Wireless Sensor Networks (WSNs) positioned in rice, cotton, cassava crops for knowledge… More >

View

1383

Download

686

Open Access

ARTICLE

G. Logeswari^*, S. Bose, T. Anitha
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 867-880, 2023, DOI:10.32604/iasc.2023.026769
Abstract Software Defined Networking (SDN) has emerged as a promising and exciting option for the future growth of the internet. SDN has increased the flexibility and transparency of the managed, centralized, and controlled network. On the other hand, these advantages create a more vulnerable environment with substantial risks, culminating in network difficulties, system paralysis, online banking frauds, and robberies. These issues have a significant detrimental impact on organizations, enterprises, and even economies. Accuracy, high performance, and real-time systems are necessary to achieve this goal. Using a SDN to extend intelligent machine learning methodologies in an Intrusion Detection System (IDS) has stimulated… More >

View

1971

Download

1658

Open Access

ARTICLE

C. D. Prem Kumar^1,*, S. Saravana Sundaram²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 881-899, 2023, DOI:10.32604/iasc.2023.025766
Abstract The extensive availability of advanced digital image technologies and image editing tools has simplified the way of manipulating the image content. An effective technique for tampering the identification is the copy-move forgery. Conventional image processing techniques generally search for the patterns linked to the fake content and restrict the usage in massive data classification. Contrastingly, deep learning (DL) models have demonstrated significant performance over the other statistical techniques. With this motivation, this paper presents an Optimal Deep Transfer Learning based Copy Move Forgery Detection (ODTL-CMFD) technique. The presented ODTL-CMFD technique aims to derive a DL model for the classification of… More >

View

1247

Download

650

Open Access

ARTICLE

Rihem Farkh^*, Khaled Aljaloud
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 901-911, 2023, DOI:10.32604/iasc.2023.027614
Abstract In a controlled indoor environment, line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots. A line tracking robot is a self-mobile machine that can recognize and track a painted line on the floor. In general, the path is set and can be visible, such as a black line on a white surface with high contrasting colors. The robot’s path is marked by a distinct line or track, which the robot follows to move. Several scientific contributions from the disciplines of vision and control have been made to mobile robot vision-based navigation. Localization, automated map… More >

View

1496

Download

1093

Open Access

ARTICLE

Chang-Yi Kao¹, Hao-En Chueh^2,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 913-924, 2023, DOI:10.32604/iasc.2023.024734
Abstract

The use of voice to perform biometric authentication is an important technological development, because it is a non-invasive identification method and does not require special hardware, so it is less likely to arouse user disgust. This study tries to apply the voice recognition technology to the speech-driven interactive voice response questionnaire system aiming to upgrade the traditional speech system to an intelligent voice response questionnaire network so that the new device may offer enterprises more precise data for customer relationship management (CRM). The intelligence-type voice response gadget is becoming a new mobile channel at the current time, with functions of… More >

View

1106

Download

766

Open Access

ARTICLE

Adela POP (Puscasiu), Alexandra Fanca^*, Dan Ioan Gota, Honoriu Valean
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 925-940, 2023, DOI:10.32604/iasc.2023.025069
Abstract The amount of moisture in the air is represented by relative humidity (RH); an ideal level of humidity in the interior environment is between 40% and 60% at temperatures between 18° and 20° Celsius. When the RH falls below this level, the environment becomes dry, which can cause skin dryness, irritation, and discomfort at low temperatures. When the humidity level rises above 60%, a wet atmosphere develops, which encourages the growth of mold and mites. Asthma and allergy symptoms may occur as a result. Human health is harmed by excessive humidity or a lack thereof. Dehumidifiers can be used to… More >

View

1037

Download

575

Open Access

ARTICLE

Tao Li¹, Zhiwei Jiang^1,*, Rui Han², Jinyue Xia³, Yongjun Ren⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 941-956, 2023, DOI:10.32604/iasc.2023.029644
Abstract A Generative Adversarial Neural (GAN) network is designed based on deep learning for the Super-Resolution (SR) reconstruction task of temperature fields (comparable to downscaling in the meteorological field), which is limited by the small number of ground stations and the sparse distribution of observations, resulting in a lack of fineness of data. To improve the network’s generalization performance, the residual structure, and batch normalization are used. Applying the nearest interpolation method to avoid over-smoothing of the climate element values instead of the conventional Bicubic interpolation in the computer vision field. Sub-pixel convolution is used instead of transposed convolution or interpolation… More >

View

1371

Download

819

Like

1

Open Access

ARTICLE

T. Shanthi^1,*, M. Ramprasath², A. Kavitha³, T. Muruganantham⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 957-969, 2023, DOI:10.32604/iasc.2023.027775
Abstract The latest 6G improvements secured autonomous driving's realism in Intelligent Autonomous Transport Systems (IATS). Despite the IATS's benefits, security remains a significant challenge. Blockchain technology has grown in popularity as a means of implementing safe, dependable, and decentralised independent IATS systems, allowing for more utilisation of legacy IATS infrastructures and resources, which is especially advantageous for crowdsourcing technologies. Blockchain technology can be used to address security concerns in the IATS and to aid in logistics development. In light of the inadequacy of reliance and inattention to rights created by centralised and conventional logistics systems, this paper discusses the creation of… More >

View

1154

Download

720

Open Access

ARTICLE

K. Sukanya^*, P. Vijayakumar
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 971-982, 2023, DOI:10.32604/iasc.2023.028047
Abstract Frequency deviation has to be controlled in power generation units when there are fluctuations in system frequency. With several renewable energy sources, wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature. Whenever there is a mismatch between generation and demand, the frequency deviation may arise from the actual frequency 50 Hz (in India). To mitigate the frequency deviation issue, it is necessary to develop an effective technique for better frequency control in wind energy systems. In this work, heuristic Fuzzy Logic Based Controller (FLC) is developed for providing… More >

View

1238

Download

618

Open Access

ARTICLE

Ravi Samikannu^1,*, K. Vinoth², Narasimha Rao Dasari³, Senthil Kumar Subburaj⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 983-995, 2023, DOI:10.32604/iasc.2023.026069
Abstract Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing unit. Renewable energy sources are playing a significant role in the modern energy system with rapid development. In renewable sources like fuel combustion and solar energy, the generated voltages change due to their environmental changes. To develop energy resources, electric power generation involved huge awareness. The power and output voltages are plays important role in our work but it not considered in the existing system. For considering the power and voltage, Gaussian PI Controller-Maxpooling Deep Convolutional Neural… More >

View

1162

Download

623

Open Access

ARTICLE

R. S. Preethishri^*, J. Anitha Roseline, K. Murugesan, M. Senthil Kumaran
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 997-1014, 2023, DOI:10.32604/iasc.2023.025510
Abstract The Power Factor Correction (PFC) in Switched Reluctance (SR) motor is discussed in this article. The SR motors are applicable for multiple applications like electric vehicles, wind mills, machineries etc. The doubly salient structure of SR motor causes the occurrence of torque ripples, which affects the power factor of the motor. To improve the power quality, the power factor has to be corrected and the ripples have to be minimized. In order to achieve these objectives, a novel power factor correction (PFC) method is proposed in this work. Here, the conventional Diode Bridge Rectifier (DBR) is replaced by a Bridgeless… More >

View

1008

Download

649

Like

2

Open Access

ARTICLE

Ayman Mohamed Mostafa^*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1015-1034, 2023, DOI:10.32604/iasc.2023.028041
Abstract Sentiment analysis is based on the orientation of user attitudes and satisfaction towards services and subjects. Different methods and techniques have been introduced to analyze sentiments for obtaining high accuracy. The sentiment analysis accuracy depends mainly on supervised and unsupervised mechanisms. Supervised mechanisms are based on machine learning algorithms that achieve moderate or high accuracy but the manual annotation of data is considered a time-consuming process. In unsupervised mechanisms, a lexicon is constructed for storing polarity terms. The accuracy of analyzing data is considered moderate or low if the lexicon contains small terms. In addition, most research methodologies analyze datasets… More >

View

1018

Download

550

Open Access

ARTICLE

Sumit Kumar^1,*, S. Indu², Gurjit Singh Walia¹
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1035-1051, 2023, DOI:10.32604/iasc.2023.024469
Abstract Android Smartphones are proliferating extensively in the digital world due to their widespread applications in a myriad of fields. The increased popularity of the android platform entices malware developers to design malicious apps to achieve their malevolent intents. Also, static analysis approaches fail to detect run-time behaviors of malicious apps. To address these issues, an optimal unification of static and dynamic features for smartphone security analysis is proposed. The proposed solution exploits both static and dynamic features for generating a highly distinct unified feature vector using graph based cross-diffusion strategy. Further, a unified feature is subjected to the fuzzy-based classification… More >

View

1206

Download

472

Open Access

ARTICLE

Praveen Talari^1,*, A. Suresh², M. G. Kavitha³
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1053-1067, 2023, DOI:10.32604/iasc.2023.027024
Abstract As per World Health Organization report which was released in the year of 2019, Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world. Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it. Among the diabetics, it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2. To avoid this situation, we… More >

View

1051

Download

575

Open Access

ARTICLE

G. Arutperumjothi^1,*, K. Suganya Devi², C. Rani³, P. Srinivasan⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1069-1086, 2023, DOI:10.32604/iasc.2023.028423
Abstract In recent years, Peripheral blood smear is a generic analysis to assess the person’s health status. Manual testing of Peripheral blood smear images are difficult, time-consuming and is subject to human intervention and visual error. This method encouraged for researchers to present algorithms and techniques to perform the peripheral blood smear analysis with the help of computer-assisted and decision-making techniques. Existing CAD based methods are lacks in attaining the accurate detection of abnormalities present in the images. In order to mitigate this issue Deep Convolution Neural Network (DCNN) based automatic classification technique is introduced with the classification of eight groups… More >

View

1479

Download

636

Open Access

ARTICLE

Sonia¹, Kapil Sharma^1,*, Monika Bajaj²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1087-1101, 2023, DOI:10.32604/iasc.2023.026134
Abstract Big Data and artificial intelligence are used to transform businesses. Social networking sites have given a new dimension to online data. Social media platforms help gather massive amounts of data to reach a wide variety of customers using influence maximization technique for innovative ideas, products and services. This paper aims to develop a deep learning method that can identify the influential users in a network. This method combines the various aspects of a user into a single graph. In a social network, the most influential user is the most trusted user. These significant users are used for viral marketing as… More >

View

1227

Download

888

Open Access

ARTICLE

T. Saravanakumar, R. Saravana kumar^*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1103-1118, 2023, DOI:10.32604/iasc.2023.025511
Abstract This work focuses on the fuzzy controller for the proposed three-phase interleaved Step-up converter (ISC). The fuzzy controller for the proposed ISC converters for electric vehicles has been discussed in detail. The proposed ISC direct current (DC-DC) converter could also be used in automobiles, satellites, industries, and propulsion. To enhance voltage gain, the proposed ISC Converter combines boost converter and interleaved converter (IC). This design also reduces the number of switches. As a result, ISC converter switching losses are reduced. The proposed ISC Converter topology can produce a 143 V output voltage and 1 kW of power. Due to the… More >

View

1251

Download

668

Like

1

Open Access

ARTICLE

Mohamed Ali Rakrouki^1,2,*, Abeer Aljohani¹, Nawaf Alharbe¹, Abdelaziz Berrais², Talel Ladhari²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1119-1134, 2023, DOI:10.32604/iasc.2023.028604
Abstract In this paper, we consider the problem of minimizing the total tardiness in a deterministic two-machine permutation flowshop scheduling problem subject to release dates of jobs and known unavailability periods of machines. The theoretical and practical importance of minimizing tardiness in flowshop scheduling environment has motivated us to investigate and solve this interested two-machine scheduling problem. Methods that solve this important optimality criterion in flowshop environment are mainly heuristics. In fact, despite the -hardness in the strong sense of the studied problem, to the best of our knowledge there are no approximate algorithms (constructive heuristics or metaheuristics) or an algorithm… More >

View

1253

Download

582

Open Access

ARTICLE

A. Sivaranjani^1,*, B. Vinod²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1135-1150, 2023, DOI:10.32604/iasc.2023.028126
Abstract Autonomous navigation of mobile robots is a challenging task that requires them to travel from their initial position to their destination without collision in an environment. Reinforcement Learning methods enable a state action function in mobile robots suited to their environment. During trial-and-error interaction with its surroundings, it helps a robot to find an ideal behavior on its own. The Deep Q Network (DQN) algorithm is used in TurtleBot 3 (TB3) to achieve the goal by successfully avoiding the obstacles. But it requires a large number of training iterations. This research mainly focuses on a mobility robot’s best path prediction… More >

View

1512

Download

1024

Open Access

ARTICLE

M. Mohan^1,*, P. C. Kishore Raja², P. Velmurugan³, A. Kulothungan⁴
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1151-1163, 2023, DOI:10.32604/iasc.2023.026255
Abstract Prediction of stock market value is highly risky because it is based on the concept of Time Series forecasting system that can be used for investments in a safe environment with minimized chances of loss. The proposed model uses a real time dataset of fifteen Stocks as input into the system and based on the data, predicts or forecast future stock prices of different companies belonging to different sectors. The dataset includes approximately fifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular company or not; the forecasting… More >

View

1436

Download

1184

Like

1

Open Access

ARTICLE

Tahir Alyas¹, Nadia Tabassum², Muhammad Waseem Iqbal^3,*, Abdullah S. Alshahrani⁴, Ahmed Alghamdi⁵, Syed Khuram Shahzad⁶
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1165-1179, 2023, DOI:10.32604/iasc.2023.028815
Abstract Kubernetes, a container orchestrator for cloud-deployed applications, allows the application provider to scale automatically to match the fluctuating intensity of processing demand. Container cluster technology is used to encapsulate, isolate, and deploy applications, addressing the issue of low system reliability due to interlocking failures. Cloud-based platforms usually entail users define application resource supplies for eco container virtualization. There is a constant problem of over-service in data centers for cloud service providers. Higher operating costs and incompetent resource utilization can occur in a waste of resources. Kubernetes revolutionized the orchestration of the container in the cloud-native age. It can adaptively manage… More >

View

1241

Download

613

Open Access

ARTICLE

K. Dharani Sree^*, P. Karpagavalli
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1181-1195, 2023, DOI:10.32604/iasc.2023.025303
Abstract The distributed generators in the radial distribution network are to improve the Grid performance and its efficiency. These Distributed Generators control the PV bus; it is converted as a remote controlled PVQ bus. This PVQ bus reduces the power loss and reactive power. Initially, the distributed generators were placed in the system using mathematical modelling or the optimization. This approach improves the efficiency but it has no effect in loss minimization. To minimize the loss the reconfigured network with Genetic algorithm based Distributed generator placement proposed as existing work. This approach minimizes the loss effectively; but the genetic algorithm takes… More >

View

955

Download

456

Open Access

ARTICLE

R. Gowrishankar^1,*, N. Sathish Kumar²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1197-1209, 2023, DOI:10.32604/iasc.2023.025422
Abstract Adder with high efficiency and accuracy is the major requirement for electronic circuit design. Here the optical logic gate based adder circuit is designed for better performance analysis of optical input signals varied with the wavelength. Efficiency of the adder can be improved by increasing the speed of operation, reducing the complexity and power consumption. To maintain the high efficiency with accuracy, a new combination of adder has been proposed and tested in this work. A new adder by combining the logics of Brent Kung, Sklansky and Kogge Stone adders by Tree Grafting Technique (BSKTGT) has been tested along with… More >

View

1169

Download

517

Open Access

ARTICLE

M. Rekha^1,*, M. Bhuvaneswari²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1211-1227, 2023, DOI:10.32604/iasc.2023.027368
Abstract Due to the unprecedented rate of transformation in the field of wireless communication industry, there is a need to prioritise the coverage, network power and throughput as preconditions. In Heterogeneous Networks (HetNets) the low power node inclusion like Femto and Pico cells creates a network of Multi-Tier (M-Tier) which is regarded as the most significant strategy for enhancing the coverage, throughput, 4G Long Term Evolution (LTE) ability. This work mainly focuses on M-Tier 3D Heterogeneous Networks Energy Efficiency (EE) based Carrier Aggregation (CA) scheme for streaming real-time huge data like images. At first, M-Tier 3D HetNets scheme was made for… More >

View

1040

Download

581

Open Access

ARTICLE

A. Arunkumar^1,*, S. Ramabalan¹, D. Elayaraja²
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1229-1244, 2023, DOI:10.32604/iasc.2023.027388
Abstract Environmental issues like pollution are major threats to human health. Many systems are developed to reduce pollution. In this paper, an optimal mobile robot design to reduce pollution in Green supply chain management system. Green supply chain management involves as similating environmentally and economically feasible solutions into the supply chain life-cycle. Smartness, advanced technologies, and advanced networks are becoming pillars of a sustainable supply chain management system. At the same time, there is much change happening in the logistics industry. They are moving towards a new logistics model. In the new model, robotic logistics has a vital role. The reasons… More >

View

1347

Download

918

Open Access

ARTICLE

Narit Hnoohom¹, Sakorn Mekruksavanich², Anuchit Jitpattanakul^3,4,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1245-1259, 2023, DOI:10.32604/iasc.2023.028290
Abstract Smoking is a major cause of cancer, heart disease and other afflictions that lead to early mortality. An effective smoking classification mechanism that provides insights into individual smoking habits would assist in implementing addiction treatment initiatives. Smoking activities often accompany other activities such as drinking or eating. Consequently, smoking activity recognition can be a challenging topic in human activity recognition (HAR). A deep learning framework for smoking activity recognition (SAR) employing smartwatch sensors was proposed together with a deep residual network combined with squeeze-and-excitation modules (ResNetSE) to increase the effectiveness of the SAR framework. The proposed model was tested against… More >

View

1457

Download

711

Open Access

ARTICLE

Santhana Krishnan Jayapal¹, Sivakumar Poruran^2,*
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1261-1275, 2023, DOI:10.32604/iasc.2023.026564
Abstract Tea plant cultivation plays a significant role in the Indian economy. The Tea board of India supports tea farmers to increase tea production by preventing various diseases in Tea Plant. Various climatic factors and other parameters cause these diseases. In this paper, the image retrieval model is developed to identify whether the given input tea leaf image has a disease or is healthy. Automation in image retrieval is a hot topic in the industry as it doesn’t require any form of metadata related to the images for storing or retrieval. Deep Hashing with Integrated Autoencoders is our proposed method for… More >

View

1491

Download

621