V. P. Ajay^1,*, M. Nesasudha²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 193-204, 2022, DOI:10.32604/iasc.2022.024839

Abstract Cognitive radio network (CRN) is a growing technology targeting more resourcefully exploiting the available spectrum for opportunistic network usage. By the concept of cognitive radio, the wastage of available spectrum reduced about 30% worldwide. The key operation of CRN is spectrum sensing. The sensing results about the spectrum are directly proportional to the performance of the network. In CRN, the final result about the available spectrum is decided by combing the local sensing results. The presence or participation of attackers in the network leads to false decisions and the performance of the network will be degraded. In this work, an… More >

Sandeep Kumar¹, Arpit Jain^2,*, Shilpa Rani³, Hammam Alshazly⁴, Sahar Ahmed Idris⁵, Sami Bourouis⁶

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 119-131, 2022, DOI:10.32604/iasc.2022.024812

Abstract The detection of the objects in the ariel image has a significant impact on the field of parking space management, traffic management activities and surveillance systems. Traditional vehicle detection algorithms have some limitations as these algorithms are not working with the complex background and with the small size of object in bigger scenes. It is observed that researchers are facing numerous problems in vehicle detection and classification, i.e., complicated background, the vehicle’s modest size, other objects with similar visual appearances are not correctly addressed. A robust algorithm for vehicle detection and classification has been proposed to overcome the limitation of… More >

Niraj Kumar^1,*, Vishnu Mohan Mishra², Adesh Kumar³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 623-638, 2022, DOI:10.32604/iasc.2022.024804

Abstract Supervisory control and data acquisition (SCADA) systems continuously monitor the real-time processes in the smart grid. The system software, which is based on a human-machine interface (HMI), makes intelligent decisions to assist the system operator and perform normal grid management activities. The management of SCADA networks and monitoring without proper security is a major concern, as many grids and plant networks still lack necessary monitoring and detection systems, making them vulnerable to attack. SCADA networks exploit physical weaknesses as well as cyber-attacks. Researchers have developed a monitoring system based on a field-programmable gate array (FPGA) and a microcontroller that allows… More >

Saydul Akbar Murad¹, Apurba Adhikary², Abu Jafar Md Muzahid¹, Md. Murad Hossain Sarker³, Md. Ashikur Rahman Khan², Md. Bipul Hossain², Anupam Kumar Bairagi^4,*, Mehedi Masud⁵, Md. Kowsher⁶

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 87-103, 2022, DOI:10.32604/iasc.2022.024777

Abstract Asthma is a disease which attacks the lungs and that affects people of all ages. Asthma prediction is crucial since many individuals already have asthma and increasing asthma patients is continuous. Machine learning (ML) has been demonstrated to help individuals make judgments and predictions based on vast amounts of data. Because Android applications are widely available, it will be highly beneficial to individuals if they can receive therapy through a simple app. In this study, the machine learning approach is utilized to determine whether or not a person is affected by asthma. Besides, an android application is being created to… More >

Gurram Sunitha^1,*, M. N. Pushpalatha², A. Parkavi³, Prasanthi Boyapati⁴, Ranjan Walia⁵, Rachna Kohar⁶, Kashif Qureshi⁷

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 423-437, 2022, DOI:10.32604/iasc.2022.024757

Abstract Crop yield is an extremely difficult trait identified using many factors like genotype, environment and their interaction. Accurate Crop Yield Prediction (CYP) necessitates the basic understanding of the functional relativity among yields and the collaborative factor. Disclosing such connection requires both wide-ranging datasets and an efficient model. The CYP is important to accomplish irrigation scheduling and assessing labor necessities for reaping and storing. Predicting yield using various kinds of irrigation is effective for optimizing resources, but CYP is a difficult process owing to the existence of distinct factors. Recently, Deep Learning (DL) approaches offer solutions to complicated data like weather… More >

R Punithavathi¹, K Venkatachalam², Mehedi Masud³, Mohammed A. AlZain⁴, Mohamed Abouhawwash^5,6,*

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 559-574, 2022, DOI:10.32604/iasc.2022.024715

Abstract The challenges in providing e-health services with the help of Internet of Medical Things (IoMT) is done by connecting to the smart medical devices. Through IoMT sensor devices/smart devices, physicians share the sensitive information of the patient. However, protecting the patient health care details from malware attack is necessary in this advanced digital scenario. Therefore, it is needed to implement cryptographic algorithm to enhance security, safety, reliability, preventing details from malware attacks and privacy of medical data. Nowadays blockchain has become a prominent technology for storing medical data securely and transmit through IoMT concept. The issues in the existing research… More >

M. Murugesan^*, S. Thilagamani

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 389-405, 2022, DOI:10.32604/iasc.2022.024641

Abstract Automatic anomaly activity detection is difficult in video surveillance applications due to variations in size, type, shape, and objects’ location. The traditional anomaly detection and classification methods may affect the overall segmentation accuracy. It requires the working groups to judge their constant attention if the captured activities are anomalous or suspicious. Therefore, this defect creates the need to automate this process with high accuracy. In addition to being extraordinary or questionable, the display does not contain the necessary recording frame and activity standard to help the quick judgment of the parts’ specialized action. Therefore, to reduce the wastage of time… More >

Vishnu Kumar Kaliappan¹, Tuan Anh Nguyen¹, Dugki Min^2,*, Jae-Woo Lee¹, U. Sakthi³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 575-591, 2022, DOI:10.32604/iasc.2022.024577

Abstract In recent years, the applications of rotorcraft-based unmanned aerial vehicles (RUAV) have increased rapidly. In particular, the integration of bio-inspired techniques to enhance intelligence in coordinating multiple Rotorcraft-based Unmanned Aerial Vehicles (RUAVs) has been a focus of recent research and development. Due to the limitation in intelligence, these RUAVs are restricted in flying low altitude with high maneuverability. To make it possible, the RUAVs must have the ability to avoid both static and dynamic obstacles while operating at low altitudes. Therefore, developing a state-of-the-art intelligent control algorithm is necessary to avoid low altitude obstacles and coordinate without collision while executing… More >

Debasis Mohapatra¹, Sourav Kumar Bhoi¹, Kalyan Kumar Jena¹, Chittaranjan Mallick², Kshira Sagar Sahoo³, N. Z. Jhanjhi^4,*, Mehedi Masud⁵

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 51-64, 2022, DOI:10.32604/iasc.2022.024561

Abstract Most of the recent works on network science are focused on investigating various interactions among a set of entities present in a system that can be represented by multiplex network. Each type of relationship is treated as a layer of multiplex network. Some of the recent works on multiplex networks are focused on deriving layer similarity from node similarity where node similarity is evaluated using neighborhood similarity measures like cosine similarity and Jaccard similarity. But this type of analysis lacks in finding the set of nodes having the same influence in both the network. The discovery of influence similarity between… More >

G. R. Sreekanth¹, Adel Fahad Alrasheedi², K. Venkatachalam³, Mohamed Abouhawwash^4,5,*, S. S. Askar²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 249-265, 2022, DOI:10.32604/iasc.2022.024538

Abstract Brain tumor is considered as an unusual cell that presents and grows in the brain. Similarly, it may lead to cancerous or non-cancerous. So, to improve the survival rate of the patient and to give the best treatment at the earliest, it’s very necessary for early prediction of tumor. Accurate classification of tumor in the brain is important for improving the diagnosis. In accordance with that, various research programs are invited for the better treatment of the patients. Machine Learning (ML) algorithms are applied to help the health associates for the classification of brain tumor and present their diagnosis. This… More >