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ARTICLE

D. Anuradha^1,*, R. Srinivasan², T. Ch. Anil Kumar³, J. Faritha Banu⁴, Aditya Kumar Singh Pundir⁵, D. Vijendra Babu⁶
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1325-1341, 2022, DOI:10.32604/iasc.2022.021946 - 09 December 2021
Abstract Wireless sensor network (WSN) becomes a hot research area owing to an extensive set of applications. In order to accomplish energy efficiency in WSN, most of the earlier works have focused on the clustering process which enables to elect CHs and organize unequal clusters. However, the clustering process results in hot spot problem and can be addressed by the use of unequal clustering techniques, which enables to construct of clusters of unequal sizes to equalize the energy dissipation in the WSN. Unequal clustering can be formulated as an NP-hard issue and can be solved by… More >

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Virginijus Baranauskas^1,*, Žydrūnas Jakas¹, Kastytis Kiprijonas Šarkauskas¹, Stanislovas Bartkevičius², Gintaras Dervinis¹, Alma Dervinienė³, Leonas Balaševičius¹, Vidas Raudonis¹, Renaldas Urniežius¹, Jolanta Repšytė¹
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1343-1356, 2022, DOI:10.32604/iasc.2022.022288 - 09 December 2021
（This article belongs to the Special Issue: Soft Computing Methods for Intelligent Automation Systems)
Abstract The research work presents a collision prediction method of mobile robots. The authors of the work use so-called, virtual cocoons to evaluate the collision criteria of two robots. The idea, mathematical representation of the calculations and experimental simulations are presented in the paper work. A virtual model of the industrial process with moving mobile robots was created. Obstacle avoidance was not solved here. The authors of the article were working on collision avoidance problem solving between moving robots. Theoretical approach presents mathematical calculations and dependences of path angles of mobile robots. Experimental simulations, using the… More >

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1087

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Arfat Ahmad Khan^1,*, Faizan Ahmed Khan²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1357-1367, 2022, DOI:10.32604/iasc.2022.022958 - 09 December 2021
Abstract Radiation monitoring is essential for examining and refraining the unwanted situations in the vicinity of nuclear plants as high levels of radiation are quite dangerous for human beings. Meanwhile, Wireless Sensor Networks (WSNs) are proved to be an auspicious candidate to address that issue. Actually, WSNs are pretty beneficial to monitor an area with the aim of avoiding undesirable situations. In this paper, we have designed and implemented a cost-efficient radiation and the temperature monitoring system. We have used ZigBee to develop the sensor nodes, and the sensor nodes are instilled with the radiation and More >

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914

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Novak Zagradjanin^1,*, Dragan Pamucar², Kosta Jovanovic¹, Nikola Knezevic¹, Bojan Pavkovic³
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1369-1386, 2022, DOI:10.32604/iasc.2022.021979 - 09 December 2021
（This article belongs to the Special Issue: Soft Computing Methods for Intelligent Automation Systems)
Abstract An autonomous robot is often in a situation to perform tasks or missions in an initially unknown environment. A logical approach to doing this implies discovering the environment by the incremental principle defined by the applied exploration strategy. A large number of exploration strategies apply the technique of selecting the next robot position between candidate locations on the frontier between the unknown and the known parts of the environment using the function that combines different criteria. The exploration strategies based on Multi-Criteria Decision-Making (MCDM) using the standard SAW, COPRAS and TOPSIS methods are presented in… More >

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Wen-Tsai Sung¹, Ihzany Vilia Devi¹, Sung-Jung Hsiao^2,*, Fathria Nurul Fadillah¹
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1387-1401, 2022, DOI:10.32604/iasc.2022.022828 - 09 December 2021
Abstract Waste management and monitoring is a major concern in the context of the environment, and has a significant impact on human health. The concept of the Artificial Intelligence of Things (AIoT) can help people in everyday tasks in life. This study proposes a smart trash bin to help solve the problem of waste management and monitoring. Traditional methods of garbage disposal require human labor, and pose a hazard to the worker. The proposed smart garbage bin can move itself by using ultrasonic sensors and a web camera, which serves as its “eyes.” Because the smart More >

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Masoud Alajmi^1,*, Osama A. Elshakankiry², Walid El-Shafai³, Hala S. El-Sayed⁴, Ahmed I. Sallam⁵, Heba M. El-Hoseny⁶, Ahmed Sedik⁷, Osama S. Faragallah²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1403-1413, 2022, DOI:10.32604/iasc.2022.021211 - 09 December 2021
Abstract Machine Learning (ML) techniques have been combined with modern technologies across medical fields to detect and diagnose many diseases. Meanwhile, given the limited and unclear statistics on the Coronavirus Disease 2019 (COVID-19), the greatest challenge for all clinicians is to find effective and accurate methods for early diagnosis of the virus at a low cost. Medical imaging has found a role in this critical task utilizing a smart technology through different image modalities for COVID-19 cases, including X-ray imaging, Computed Tomography (CT) and magnetic resonance image (MRI) that can be used for diagnosis by radiologists.… More >

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967

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T. Thomas Leonid^1,*, R. Jayaparvathy²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1415-1426, 2022, DOI:10.32604/iasc.2022.021939 - 09 December 2021
Abstract Human-elephant conflict is the most common problem across elephant habitat Zones across the world. Human elephant conflict (HEC) is due to the migration of elephants from their living habitat to the residential areas of humans in search of water and food. One of the important techniques used to track the movements of elephants is based on the detection of Elephant Voice. Our previous work [] on Elephant Voice Detection to avoid HEC was based on Feature set Extraction using Support Vector Machine (SVM). This research article is an improved continuum of the previous method using… More >

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Sobia Pervaiz¹, Waqas Haider Bangyal², Adnan Ashraf³, Kashif Nisar^4,*, Muhammad Reazul Haque⁵, Ag. Asri Bin Ag. Ibrahim⁴, BS Chowdhry⁶, Waqas Rasheed⁷, Joel J. P. C. Rodrigues^8,9, Richard Etengu⁵, Danda B. Rawat¹⁰
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1427-1444, 2022, DOI:10.32604/iasc.2022.017304 - 09 December 2021
Abstract In existing meta-heuristic algorithms, population initialization forms a huge part towards problem optimization. These calculations can impact variety and combination to locate a productive ideal arrangement. Especially, for perceiving the significance of variety and intermingling, different specialists have attempted to improve the presentation of meta-heuristic algorithms. Particle Swarm Optimization (PSO) algorithm is a populace-based, shrewd stochastic inquiry strategy that is motivated by the inherent honey bee swarm food search mechanism. Population initialization is an indispensable factor in the PSO algorithm. To improve the variety and combination factors, rather than applying the irregular circulation for the… More >

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P. Dhilipkumar^1,*, G. Mohanbabu²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1445-1458, 2022, DOI:10.32604/iasc.2022.021663 - 09 December 2021
Abstract Low Power circuits play a significant role in designing large-scale devices with high energy and power consumption. Adiabatic circuits are one such energy-saving circuits that utilize reversible power. Several methodologies used previously infer the use of CMOS circuits for reducing power dissipation in logic circuits. However, CMOS devices hardly manage in maintaining their performance when it comes to fast switching networks. Adiabatic technology is employed to overcome these difficulties, which can further scale down the dissipation of power by charging and discharging. An Efficient Charge Recovery Logic (ECRL) based adiabatic technology is used here to… More >

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1180

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S. Manikandan^1,*, M. Chinnadurai²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1459-1466, 2022, DOI:10.32604/iasc.2022.022527 - 09 December 2021
Abstract Load Balancing is an important factor handling resource during running and execution time in real time applications. Virtual machines are used for dynamically access and share the resources. As per current scenario cloud computing is played major for storage, resource accessing, resource pooling and internet based service offering. Usage of cloud computing services is dynamically increased such as online shopping, education, ticketing, etc. Many users can use the cloud resources and load balancing is used for adjusting the virtual machine and balance the node. Our proposed virtualized genetic algorithms are to provide balanced virtual machine More >

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858

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E. Elamaran^1,*, B. Sudhakar²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1467-1477, 2022, DOI:10.32604/iasc.2022.020625 - 09 December 2021
Abstract Essential components in wireless systems are schedulin and resource allocation. The problems in scheduling refers to inactive users in a given time slot and in terms of resource allocation it refers to the issues in the allocation of physical layer resources such as power and bandwidth among the active users. In the Long Time Evolution (LTE) downlink scheduling the optimized problem refers to the flow deadlines that incorporate the formulation in the surveyed scheduling algorithm for achieving enhanced performance levels. The major challenges appear in the areas of quality and bandwidth constrains in the video… More >

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1059

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Gautham Praveen Ramalingam¹, R. Arockia Xavier Annie¹, Shobana Gopalakrishnan^2,*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1479-1492, 2022, DOI:10.32604/iasc.2022.022211 - 09 December 2021
Abstract Detection of intrusion plays an important part in data protection. Intruders will carry out attacks from a compromised user account without being identified. The key technology is the effective detection of sundry threats inside the network. However, process automation is experiencing expanded use of information communication systems, due to high versatility of interoperability and ease off 34 administration. Traditional knowledge technology intrusion detection systems are not completely tailored to process automation. The combined use of fuzziness-based and RNN-IDS is therefore highly suited to high-precision classification, and its efficiency is better compared to that of conventional More >

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1038

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ARTICLE

Sourav Kumar Bhoi¹, Sanjaya Kumar Panda², Kalyan Kumar Jena¹, Kshira Sagar Sahoo³, N. Z. Jhanjhi^4,*, Mehedi Masud⁵, Sultan Aljahdali⁵
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1493-1507, 2022, DOI:10.32604/iasc.2022.022833 - 09 December 2021
Abstract Environment monitoring is an important area apart from environmental safety and pollution control. Such monitoring performed by the physical models of the atmosphere is unstable and inaccurate. Machine Learning (ML) techniques on the other hand are more robust in capturing the dynamics in the environment. In this paper, a novel approach is proposed to build a cost-effective standardized environment monitoring system (IoT-EMS) in volunteer computing environment. In volunteer computing, the volunteers (people) share their resources for distributed computing to perform a task (environment monitoring). The system is based on the Internet of Things and is… More >

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1229

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ARTICLE

A. Indumathi^*, G. Sumathi
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1509-1524, 2022, DOI:10.32604/iasc.2022.022743 - 09 December 2021
Abstract As cloud storage systems have developed and been applied in complex environments, their data security has become more prevalent in recent years. The issue has been approached through many models. Data is encrypted and stored in these models. One of the most widely used encryption methods is the Advanced Encryption Standard (AES). In AES, the Substitution box(S-box) is playing a significant part in imparting the job of confusion. The security of the entire cryptosystem depends on its nonlinearity. In this work, a robust and secure S-box is constructed using a novel method, i.e., fingerprint features-based permutation… More >

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1783

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998

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ARTICLE

D. Arivudainambi¹, S. Mangairkarasi^1,*, K. A. Varun Kumar²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1525-1540, 2022, DOI:10.32604/iasc.2022.020463 - 09 December 2021
Abstract Cognitive Radio (CR) aims to achieve efficient utilization of scarcely available radio spectrum. Spectrum sensing in CR is a basic process for identifying the existence or absence of primary users. In spectrum sensing, CR users suffer from deep fading effects and it requires additional sensing time to identify the primary user. To overcome these challenges, we frame Spectrum Prediction-Channel Allocation (SP-CA) algorithm which consists of three phases. First, clustering mechanisms to select the spectrum coordinator. Second, Eigenvalue based detection method to expand the sensing accuracy of the secondary user. Third, Bayesian inference approach to reduce More >

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1497

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1058

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ARTICLE

Do-kyeong Lee¹, Tae-won Kim², Yoo-joo Choi², Min Hong^3,*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1541-1556, 2022, DOI:10.32604/iasc.2022.020674 - 09 December 2021
Abstract In real-time contents, such as games and interactive simulators, it is very important to reduce the amount of simulation computation of 3D deformable objects. Although position-based dynamics has been proposed to reduce the amount of computation, the number of nodes for the tetrahedral model to represent a volumetric deformable object has to be increased, which makes the real-time simulation difficult. Therefore, this paper proposes an Internal shape preserving constraint(ISPC) generation algorithm integrated into the position-based dynamics to represent the physical properties of the 3D volumetric deformable object, while reducing the number of nodes filling the More >

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1104

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ARTICLE

Shaik Karimulla, K. Ravi^*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1557-1572, 2022, DOI:10.32604/iasc.2022.022953 - 09 December 2021
Abstract The usage of energy in everyday life is growing day by day as a result of the rapid growth in the human population. One solution is to increase electricity generation to the same extent as the human population, but this is usually practically impossible. As the population is increasing, the need for electrical usage is also increasing. Therefore, smart grids play an important role in making efficient use of existing energy sources like solar, wind and battery storage systems. By managing demand, the minimization of power consumption and its consequent costs. On the load side,… More >

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1011

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ARTICLE

Haolin Wang¹, Lihui Dong¹, Wei Song^1,2,3,*, Xiaobin Zhao^1,3, Jianxin Xia⁴, Tongmu Liu⁵
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1573-1586, 2022, DOI:10.32604/iasc.2022.023994 - 09 December 2021
Abstract Autonomous underwater vehicle (AUV) has many intelligent optical system, which can collect underwater signal information to make the system decision. One of them is the intelligent vision system, and it can capture the images to analyze. The performance of the particle image segmentation plays an important role in the monitoring of underwater mineral resources. In order to improve the underwater mineral image segmentation performance, some novel segmentation algorithm architectures are proposed. In this paper, an improved mineral image segmentation is proposed based on the modified U-Net. The pyramid upsampling module and residual module are bring More >

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2006

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ARTICLE

Raed Alsaqour¹, Ammar Al-hamadani², Maha Abdelhaq^3,*, Joud Almeheimidy³
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1587-1603, 2022, DOI:10.32604/iasc.2022.021127 - 09 December 2021
Abstract Current efforts for providing an efficient dynamic source routing protocol (DSR) for use in multi-hop ad-hoc wireless are promising. This is since DSR has a unique characteristic in that it uses source routing, instead of relying on the routing table at each intermediate device. This study addresses the current challenges facing DSR protocol in terms of the dynamic changes of the route and how to update such changes into the route cache of the DSR. The challenges typically persist when a sudden route break occurs resulting in a delay in updating the new node location… More >

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1404

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965

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Van-Phuong Ta^*, Dinh-Nhon Truong, Nguyen-Thanh Nhan
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1605-1615, 2022, DOI:10.32604/iasc.2022.022374 - 09 December 2021
Abstract Water Distribution System (WDS) is one of the important phases of the Water Treatment Plant (WTP) and plays a crucial role in plant, animal, and human life. The WDS aims not only to supply a continuous, stable water amount but also to reduce energy consumption as little as possible during operation. To keep the continuous, stable water amount, the water pressure in the pipe network of the WDS must be maintained at desired set points under the effecting of uncertainties, disturbances, and noises. For saving the energy requirement, a Variable Frequency Driver (VFD) was utilized More >

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1334

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884

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ARTICLE

S. Neelakandan^1,*, A. Arun², Raghu Ram Bhukya³, Bhalchandra M. Hardas⁴, T. Ch. Anil Kumar⁵, M. Ashok⁶
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1617-1632, 2022, DOI:10.32604/iasc.2022.022209 - 09 December 2021
Abstract In recent years, web crawling has gained a significant attention due to the drastic advancements in the World Wide Web. Web Search Engines have the issue of retrieving massive quantity of web documents. One among the web crawlers is the focused crawler, that intends to selectively gather web pages from the Internet. But the efficiency of the focused crawling can easily be affected by the environment of web pages. In this view, this paper presents an Automated Word Embedding with Parameter Tuned Deep Learning (AWE-PTDL) model for focused web crawling. The proposed model involves different… More >

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ARTICLE

Rashad Mahmood Saqib¹, Adnan Shahid Khan^1,*, Yasir Javed², Shakil Ahmad², Kashif Nisar³, Irshad A. Abbasi⁴, Muhammad Reazul Haque⁵, Azlina Ahmadi Julaihi¹
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1633-1647, 2022, DOI:10.32604/iasc.2022.021786 - 09 December 2021
Abstract This study presents the current state of research on multi-factor authentication. Authentication is one of the important traits in the security domain as it ensures that legitimate users have access to the secure resource. Attacks on authentication occur even before digital access is given, but it becomes quite challenging with remote access to secure resources. With increasing threats to single authentication schemes, 2Factor and later multi-factor authentication approaches came into practice. Several studies have been done in the multi-factor authentication discipline, and most of them proposed the best possible approaches, but there are very limited… More >

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ARTICLE

Wen-Tsai Sung¹, Shuo-Chen Tasi¹, Sung-Jung Hsiao^2,*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1649-1666, 2022, DOI:10.32604/iasc.2022.022501 - 09 December 2021
Abstract With the ever-increasing richness of social resources, the number of devices using the Internet of Things is also increasing. Currently, many people keep pets such as fish in their homes, and they need to be carefully taken care of. In particular, it is necessary to create a safe and comfortable environment for them and to maintain this environment continuously. An adverse environment can affect the growth of fish and may even result in their death. This study used the LinkIt 7697 module and the BlocklyDuino editor to produce a control system for a smart aquarium.… More >

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G. Geethamahalakshmi^1,*, N. Kalaiarasi², D. Nageswari¹
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1667-1685, 2022, DOI:10.32604/iasc.2022.022728 - 09 December 2021
Abstract Solar energy is the radiant heat and light energy harvested by ultra violet rays to convert into electrical Direct Current (DC). The solar energy stood ahead of other renewable energy as it can produce a constant level of alternating current over the year with minimal harmonic distortions. The renewable energy attracts the energy harvesters as there is rise of deficiency of carbon and reduction of efficiency in thermal energy generation. The concerns associated with the solar power generation are the fluctuation in the generated direct current due to the displacement of sun and deviation in… More >

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1049

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S. Vimalnath^1,*, G. Ravi²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1687-1699, 2022, DOI:10.32604/iasc.2022.023083 - 09 December 2021
Abstract With recent advancements in machine-to-machine (M2M), the demand for fastest communication is an utmost concern of the M2M technology. The advent of 5G telecommunication networks enables to bridge the demand on satisfying the Quality-of-Service (QoS) concerns in M2M communication. The massive number of devices in M2M communication is henceforth do not lie under limited resource allocation by embedding the 5G telecommunication network. In this paper, we address the above limitation of allocation the resource to prominent M2M devices using Adaptive Neuro Fuzzy Inference System (ANFIS). In ANFIS, the adoption of rules will imply the resource More >

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911

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ARTICLE

Fawaz Alassery¹, Ahmed Alzahrani², Asif Irshad Khan², Ashi Khan^3,*, Mohd Nadeem⁴, Md Tarique Jamal Ansari⁴
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1701-1715, 2022, DOI:10.32604/iasc.2022.023314 - 09 December 2021
Abstract A large number of people live in diabetes worldwide. Type-2 Diabetes (D2) accounts for 92% of patients with D2 and puts a huge burden on the healthcare industry. This multi-criterion medical research is based on the data collected from the hospitals of Uttar Pradesh, India. In recent times there is a need for a web-based electronic system to determine the impact of mental health in D2 patients. This study will examine the impact assessment in D2 patients. This paper used the integrated methodology of Fuzzy Analytic Hierarchy (FAHP) and Fuzzy Technique for Order Performance by… More >

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Paramjeet Kaur¹, Parma Nand¹, Salman Naseer², Akber Abid Gardezi³, Fawaz Alassery⁴, Habib Hamam⁵, Omar Cheikhrouhou⁶, Muhammad Shafiq^7,*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1717-1728, 2022, DOI:10.32604/iasc.2022.023063 - 09 December 2021
Abstract The public sector provides open data to create new opportunities, stimulate innovation, and implement new solutions that benefit academia and society. However, open data is usually available in large quantities and often lacks quality, accuracy, and completeness. It may be difficult to find the right data to analyze a target. There are many rich open data repositories, but they are difficult to understand and use because these data can only be used with a complex set of keyword search options, and even then, irrelevant or insufficient data may eventually be retrieved. To alleviate this situation,… More >

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Fuad Ali Mohammed Al-Yarimi^*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1729-1742, 2022, DOI:10.32604/iasc.2022.022418 - 09 December 2021
Abstract Computer-aided arrhythmia prediction from ECG (electrocardiograms) is essential in clinical practices, which promises to reduce the mortality caused by inexperienced clinical practitioners. Moreover, computer-aided methods often succeed in the early detection of arrhythmia scope from electrocardiogram reports. Machine learning is the buzz of computer-aided clinical practices. Particularly, computer-aided arrhythmia prediction methods highly adopted machine learning methods. However, the high dimensionality in feature values considered for the machine learning models’ training phase often causes false alarming. This manuscript addressed the high dimensionality in the learning phase and proposed an (Ensemble Learning method for Arrhythmia Prediction) ELAP… More >

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806

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Adel Rajab^*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1743-1761, 2022, DOI:10.32604/iasc.2022.021922 - 09 December 2021
Abstract Wireless sensor networks (WSN) deploy many nodes over an extended area for traffic surveillance, environmental monitoring, healthcare, tracking wildlife, and military sensing. Nodes of the WSN have a limited amount of energy. Each sensor node collects information from the surrounding area and forwards it onto the cluster head, which then sends it on to the base station (BS). WSNs extend the lifetime of the network through clustering techniques. Choosing nodes with the greatest residual energy as cluster heads is based on the idea that energy consumption is periodically distributed between nodes. The sink node gathers… More >

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Ahmed H. Almulihi¹, Fawaz Alassery², Asif Irshad Khan³, Sarita Shukla⁴, Bineet Kumar Gupta⁴, Rajeev Kumar^4,*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1763-1779, 2022, DOI:10.32604/iasc.2022.023460 - 09 December 2021
Abstract The contributions of the Internet of Medical Things (IoMT), cloud services, information systems, and smart devices are useful for the healthcare industry. With the help of digital healthcare, our lives have been made much more secure and effortless and provide more convenient and accessible treatment. In current, the modern healthcare sector has become more significant and convenient for the purpose of both external and internal threats. Big data breaches affect clients, stakeholders, organisations, and businesses, and they are a source of concern and complication for security professionals. This research examines the many types and categories… More >

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Wenshun Sheng^1,*, Aiping Xu², Shengli Wu³
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1781-1795, 2022, DOI:10.32604/iasc.2022.022571 - 09 December 2021
Abstract In big data applications, the data are usually stored in data files, whose data file structures, field structures, data types and lengths are not uniform. Therefore, if these data are stored in the traditional relational database, it is difficult to meet the requirements of fast storage and access. To solve this problem, we propose the mapping model between the source data file and the target HBase file. Our method solves the heterogeneity of the file object and the universality of the storage conversion. Firstly, based on the mapping model, we design “RowKey”, generation rules and More >

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869

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Betania Hernández-Ocaña, Adrian García-López, José Hernández-Torruco, Oscar Chávez-Bosquez^*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1797-1813, 2022, DOI:10.32604/iasc.2022.023570 - 09 December 2021
（This article belongs to the Special Issue: Soft Computing Methods for Intelligent Automation Systems)
Abstract The Bacterial Foraging Algorithm (BFOA) is a well-known swarm collective intelligence algorithm used to solve a variety of constraint optimization problems with wide success. Despite its universality, implementing the BFOA may be complex due to the calibration of multiple parameters. Moreover, the Two-Swim Modified Bacterial Foraging Optimization Algorithm (TS-MBFOA) is a state-of-the-art modification of the BFOA which may lead to solutions close to the optimal but with more parameters than the original BFOA. That is why in this paper we present the design using the Unified Modeling Language (UML) and the implementation in the MATLAB… More >

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B. Jaishankar^1,*, Santosh Vishwakarma², Prakash Mohan³, Aditya Kumar Singh Pundir⁴, Ibrahim Patel⁵, N. Arulkumar⁶
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1815-1829, 2022, DOI:10.32604/iasc.2022.021822 - 09 December 2021
Abstract The Healthcare system is an organization that consists of important requirements corresponding to security and privacy, for example, protecting patients’ medical information from unauthorized access, communication with transport like ambulance and smart e-health monitoring. Due to lack of expert design of security protocols, the healthcare system is facing many security threats such as authenticity, data sharing, the conveying of medical data. In such situation, block chain protocol is used. In this manuscript, Efficient Block chain Network for securing Healthcare data using Multi-Objective Squirrel Search Optimization Algorithm (MOSSA) is proposed to generate smart and secure Healthcare… More >

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Liang Dai¹, AoSong He¹, Guang Sun^1,3, Yuxing Pan^2,*
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1831-1842, 2022, DOI:10.32604/iasc.2022.022438 - 09 December 2021
Abstract In order to unify the management and scheduling of cloud resources, cloud platforms use virtualization technology to re-integrate multiple computing resources in the cloud and build virtual units on physical machines to achieve dynamic provisioning of resources by configuring virtual units of various sizes. Therefore, how to reasonably determine the mapping relationship between virtual units and physical machines is an important research topic for cloud resource scheduling. In this paper, we propose a fair cloud virtual machine resource allocation method of using the stable matching theory. Our allocation method considers the allocation of resources from… More >

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878

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D. Palanikkumar¹, Kamal Upreti², S. Venkatraman^3,*, J. Roselin Suganthi⁴, Sridharan Kannan⁵, S. Srinivasan⁶
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1843-1854, 2022, DOI:10.32604/iasc.2022.023350 - 09 December 2021
Abstract The Selection of the mining method for underground minerals extraction is the crucial task for the mining engineers. Underground minerals extraction is a multi-criteria decision making problem due to many criteria to be considered in the selection process. There are many studies on selection of underground mining method using Multi Criteria Decision Making (MCDM) techniques or approaches. Extracting minerals from the underground involves many geological characteristics also called as input parameters. The geological characteristics of any mineral deposit vary from one location to another location. Thus only one mineral extraction method is not suitable for… More >

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K. Karnavel^1,*, G. Shanmugasundaram², Satish S. Salunkhe³, V. Kamatchi Sundari⁴, M. Shunmugathammal⁴, Bal Krishna Saraswat⁵
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1855-1865, 2022, DOI:10.32604/iasc.2022.023524 - 09 December 2021
Abstract Soft robotics is a new field that uses actuators that are non-standard and compatible materials. Industrial robotics is high-throughput manufacturing devices that are quick and accurate. They are built on rigid-body mechanisms. The advancement of robotic production now depends on the inclusion of staff in manufacturing processes, allowing for the completion of activities that need cognitive abilities that are now beyond the scope of artificial networks. Hydrostatic pressure is used to achieve high deflections of structures that are based on the elastomeric in Fluid Actuators (FAs). Soft actuators based on the fluid are a popular… More >

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J. Haritha^1,*, R. S. Valarmathi², M. Kalamani³
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1867-1880, 2022, DOI:10.32604/iasc.2022.022547 - 09 December 2021
Abstract Urea is the most common fertilizer used by the farmers. In this study, the variation of mid-infrared transmittance spectra with addition of urea in soil was studied for five different concentrations of urea. 150 gm of soil is taken and dried in a hot air oven for 5 h at 80°C and then samples are prepared by adding urea and water to it. The spectral signature of soil with urea is obtained by using an Infrared Spectrometer that reads the spectra in the mid infra-red region. The analysis is done using Partial Least Square Regression… More >

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Naglaa. F. Soliman^1,*, Samia M. Abd-Alhalem², Walid El-Shafai², Salah Eldin S. E. Abdulrahman³, N. Ismaiel³, El-Sayed M. El-Rabaie², Abeer D. Algarni¹, Fatimah Algarni⁴, Amel A. Alhussan⁵, Fathi E. Abd El-Samie^1,2
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1881-1891, 2022, DOI:10.32604/iasc.2022.017683 - 09 December 2021
Abstract Recently, deep learning has opened a remarkable research direction in the track of bioinformatics, especially for the applications that need classification and regression. With deep learning techniques, DNA sequences can be classified with high accuracy. Firstly, a DNA sequence should be represented, numerically. After that, DNA features are extracted from the numerical representations based on deep learning techniques to improve the classification process. Recently, several architectures have been developed based on deep learning for DNA sequence classification. Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are the default deep learning architectures used for this… More >

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Mahmoud Awad¹, Mohamed Abouhawwash^1,2,*, H. N. Agiza¹
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1893-1904, 2022, DOI:10.32604/iasc.2022.023510 - 09 December 2021
Abstract To solve single and multi-objective optimization problems, evolutionary algorithms have been created. We use the non-dominated sorting genetic algorithm (NSGA-II) to find the Pareto front in a two-objective portfolio query, and its extended variant NSGA-III to find the Pareto front in a three-objective portfolio problem, in this article. Furthermore, in both portfolio problems, we quantify the Karush-Kuhn-Tucker Proximity Measure (KKTPM) for each generation to determine how far we are from the effective front and to provide knowledge about the Pareto optimal solution. In the portfolio problem, looking for the optimal set of stock or assets… More >

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S. Nithyanantham^1,*, G. Singaravel²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1905-1919, 2022, DOI:10.32604/iasc.2022.022499 - 09 December 2021
Abstract In recent times, a huge amount of data is being created from different sources and the size of the data generated on the Internet has already surpassed two Exabytes. Big Data processing and analysis can be employed in many disciplines which can aid the decision-making process with privacy preservation of users’ private data. To store large quantity of data, Geo-Distributed Data Centres (GDDC) are developed. In recent times, several applications comprising data analytics and machine learning have been designed for GDDC. In this view, this paper presents a hybrid deep learning framework for privacy preservation… More >

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Fahad Albogamy¹, Mohammed Faisal^2,3,*, Mohammed Arafah⁴, Hebah ElGibreen^3,5
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1921-1937, 2022, DOI:10.32604/iasc.2022.022559 - 09 December 2021
Abstract The inflationary illness caused by extreme acute respiratory syndrome coronavirus in 2019 (COVID-19) is an infectious and deadly disease. COVID-19 was first found in Wuhan, China, in December 2019, and has since spread worldwide. Globally, there have been more than 198 M cases and over 4.22 M deaths, as of the first of Augest, 2021. Therefore, an automated and fast diagnosis system needs to be introduced as a simple, alternative diagnosis choice to avoid the spread of COVID-19. The main contributions of this research are 1) the COVID-19 Period Detection System (CPDS), that used to… More >

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Chih-Fang Huang^1,*, Cheng-Yuan Huang²
Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1939-1953, 2022, DOI:10.32604/iasc.2022.017559 - 09 December 2021
（This article belongs to the Special Issue: Machine Learning and Deep Learning for Transportation)
Abstract Musical emotion is important for the listener’s cognition. A smooth emotional expression generated through listening to music makes driving a car safer. Music has become more diverse and prolific with rapid technological developments. However, the cost of music production remains very high. At present, because the cost of music creation and the playing copyright are still very expensive, the music that needs to be listened to while driving can be executed by the way of automated composition of AI to achieve the purpose of driving safety and convenience. To address this problem, automated AI music… More >

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