Raham Hashim Yosuf¹, Rania A. Mokhtar², Rashid A. Saeed^2,*, Hesham Alhumyani², S. Abdel-Khalek³

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 581-590, 2022, DOI:10.32604/iasc.2022.019928

Abstract The grid computing is one of the strong initiatives and technologies that has been introduced in the last decade for improve the resources utilization, optimization and provide very high throughput computation for wide range of applications. To attain these goals an effective scheduling for grid systems is a vital issue to realize the intended performance. The processes scheduling could be executed in various methods and protocols that have been extensively address in the literature. This works utilized shortest process first (SPF) protocol which gives the shortest jobs the highest priorities. For longer jobs, it should have lower priorities and wait… More >

Suliman A. Alsuhibany^*, Hessah Abdulaziz Alhodathi

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 523-537, 2022, DOI:10.32604/iasc.2022.019913

Abstract The Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) technique has been an interesting topic for several years. An Arabic CAPTCHA has recently been proposed to serve Arab users. Since there have been few scientific studies supporting a systematic design or tuning for users, this paper aims to analyze the Arabic text-based CAPTCHA at the parameter level by conducting an experimental study. Based on the results of this study, we propose an Arabic text-based CAPTCHA scheme with Fast Gradient Sign Method (FGSM) adversarial images. To evaluate the security of the proposed scheme, we ran four filter… More >

Jun Oh Jang^*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 481-494, 2022, DOI:10.32604/iasc.2022.019848

Abstract A neural networks(NN) hysteresis compensator is proposed for dynamic systems. The NN compensator uses the back-stepping scheme for inverting the hysteresis nonlinearity in the feed-forward path. This scheme provides a general step for using NN to determine the dynamic pre-inversion of the reversible dynamic system. A tuning algorithm is proposed for the NN hysteresis compensator which yields a stable closed-loop system. Nonlinear stability proofs are provided to reveal that the tracking error is small. By increasing the gain we can reduce the stability radius to some extent. PI control without hysteresis compensation requires much higher gains to achieve similar performance.… More >

Saadia Malik¹, Nadia Tabassum², Muhammad Saleem³, Tahir Alyas⁴, Muhammad Hamid^5,*, Umer Farooq⁴

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 471-480, 2022, DOI:10.32604/iasc.2022.019837

Abstract With the ongoing revolution in the Internet of Things (IoT) and cloud computing has made the potential of every stack holder that is connected through the Internet, to exchange and transfer data. Various users perceive this connection and interaction with devices as very helpful and serviceable in their daily life. However, an improperly configured network system is a soft target to security threats, therefore there is a dire need for a security embedded framework for IoT and cloud communication models is the latest research area. In this paper, different IoT and cloud computing frameworks are discussed in detail and describes… More >

R. Kanthavel^1,*, R. Dhaya²

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 649-659, 2022, DOI:10.32604/iasc.2022.019779

Abstract Wireless Underground Sensor Networks (WUSNs) refer to a group of nodes working underneath the earth plane that has been predicted to render concurrent observation capability in the hostile subversive and underwater surroundings. The accurate monitoring in places like underground earth, water, lubricates so on called non-conventional media need high accuracy of tiny sized sensors with antennas at a similar size. Therefore, an investigation is needed to study the opportunities and drawbacks of utilizing WUSNs without compromising the effectiveness of real-time monitoring procedures. With this, the major confrontation is to institute a trustworthy underground communication regardless of the complex environment that… More >

Taher M. Ghazal^1,2, Sajida Noreen³, Raed A. Said⁴, Muhammad Adnan Khan^5,*, Shahan Yamin Siddiqui^3,6, Sagheer Abbas³, Shabib Aftab³, Munir Ahmad³

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 539-553, 2022, DOI:10.32604/iasc.2022.019658

Abstract The usage of IoT-based smart meter in electric power consumption shows a significant role in helping the users to manage and control their electric power consumption. It produces smooth communication to build equitable electric power distribution for users and improved management of the entire electric system for providers. Machine learning predicting algorithms have been worked to apply the electric efficiency and response of progressive energy creation, transmission, and consumption. In the proposed model, an IoT-based smart meter uses a support vector machine and deep extreme machine learning techniques for professional energy management. A deep extreme machine learning approach applied to… More >

Mohd Nadeem¹, Jehad F. Al-Amri², Ahmad F. Subahi³, Adil Hussain Seh¹, Suhel Ahmad Khan⁴, Alka Agrawal¹, Raees Ahmad Khan^1,*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 61-82, 2022, DOI:10.32604/iasc.2022.019624

Abstract Present day healthcare sector is frequently victimized by the intruders. Healthcare data industry has borne the brunt of the highest number of data breach episodes in the last few years. The key reason for this is attributed to the sensitivity of healthcare data and the high costs entailed in trading the data over the dark web. Hence, usable-security evaluation of healthcare information systems is the need of hour so as to identify the vulnerabilities and provide preventive measures as a shield against the breaches. Usable-security assessment will help the software designers and developers to prioritize usable-security attributes according to the… More >

Chandrasekar Thaventhiran, K. R. Sekar^*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 495-506, 2022, DOI:10.32604/iasc.2022.019546

Abstract Prediction of lung cancer at early stages is essential for diagnosing and prescribing the correct treatment. With the continuous development of medical data in healthcare services, Lung cancer prediction is the most concerning area of interest. Therefore, early prediction of cancer helps in reducing the mortality rate of humans. The existing techniques are time-consuming and have very low accuracy. The proposed work introduces a novel technique called Target Projection Feature Matched Deep Artificial Neural Network with LSTM (TPFMDANN-LSTM) for accurate lung cancer prediction with minimum time consumption. The proposed deep learning model consists of multiple layers to learn the given… More >

Najlaa Hindi Alsaedi^*, Emad Sami Jaha

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 407-427, 2022, DOI:10.32604/iasc.2022.019538

Abstract Accurate recognition of person identity is a critical task in civil society for various application and different needs. There are different well-established biometric modalities that can be used for recognition purposes such as face, voice, fingerprint, iris, etc. Recently, face images have been widely used for person recognition, since the human face is the most natural and user-friendly recognition method. However, in real-life applications, some factors may degrade the recognition performance, such as partial face occlusion, poses, illumination conditions, facial expressions, etc. In this paper, we propose two dynamic feature subset selection (DFSS) methods to achieve better recognition for occluded… More >

Rawan Sulaiman Howyan^1,2,*, Emad Sami Jaha¹

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 555-580, 2022, DOI:10.32604/iasc.2022.019533

Abstract Human face is one of the most widely used biometrics based on computer-vision to derive various useful information such as gender, ethnicity, age, and even identity. Facial age estimation has received great attention during the last decades because of its influence in many applications, like face recognition and verification, which may be affected by aging changes and signs which appear on human face along with age progression. Thus, it becomes a prominent challenge for many researchers. One of the most influential factors on age estimation is the type of features used in the model training process. Computer-vision is characterized by… More >