Khadija Manzoor¹, Fiaz Majeed², Ansar Siddique², Talha Meraj³, Hafiz Tayyab Rauf^4,*, Mohammed A. El-Meligy⁵, Mohamed Sharaf⁶, Abd Elatty E. Abd Elgawad⁶

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1617-1630, 2022, DOI:10.32604/cmc.2022.018621 - 07 September 2021

Abstract Skin diseases effectively influence all parts of life. Early and accurate detection of skin cancer is necessary to avoid significant loss. The manual detection of skin diseases by dermatologists leads to misclassification due to the same intensity and color levels. Therefore, an automated system to identify these skin diseases is required. Few studies on skin disease classification using different techniques have been found. However, previous techniques failed to identify multi-class skin disease images due to their similar appearance. In the proposed study, a computer-aided framework for automatic skin disease detection is presented. In the proposed… 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 - 03 September 2021

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 More >

Sulaiman Yousef Alshunaifi, Shailendra Mishra^*, Mohammed Alshehri

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 13-28, 2022, DOI:10.32604/iasc.2022.019121 - 03 September 2021

Abstract 5G technology is widely seen as a game-changer for the IT and telecommunications sectors. Benefits expected from 5G include lower latency, higher capacity, and greater levels of bandwidth. 5G also has the potential to provide additional bandwidth in terms of AI support, further increasing the benefits to the IT and telecom sectors. There are many security threats and organizational vulnerabilities that can be exploited by fraudsters to take over or damage corporate data. This research addresses cybersecurity issues and vulnerabilities in 4G(LTE) and 5G technology. The findings in this research were obtained by using primary… More >

Yue Jiang, Xinyu Zhang, Wohuan Jia, Li Xu^*

Journal on Artificial Intelligence, Vol.3, No.4, pp. 163-169, 2021, DOI:10.32604/jai.2021.027590 - 07 February 2022

Abstract As a new type of knowledge sharing platform, the community question answer website realizes the acquisition and sharing of knowledge, and is loved and sought after by the majority of users. But for multi-answer questions, answer quality assessment becomes a challenge. The answer selection in CQA (Community Question Answer) was proposed as a challenge task in the SemEval competition, which gave a data set and proposed two subtasks. Task-A is to give a question (including short title and extended description) and its answers, and divide each answer into absolutely relevant (good), potentially relevant (potential) and… More >

Jianqiao Sheng¹, Mengzhu Xu², Jin Han^3,*, Xingyan Deng²

Journal on Big Data, Vol.3, No.4, pp. 183-190, 2021, DOI:10.32604/jbd.2021.024892 - 20 December 2021

Abstract Lightning disaster risk assessment, as an intuitive method to reflect the risk of regional lightning disasters, has aroused the research interest of many researchers. Nowadays, there are many schemes for lightning disaster risk assessment, but there are also some shortcomings, such as the resolution of the assessment is not clear enough, the accuracy rate cannot be verified, and the weight distribution has a strong subjective trend. This paper is guided by lightning disaster data and combines lightning data, population data and GDP data. Through support vector machine (SVM), it explores a way to combine More >

S. Poovizhi, T. R. Ganesh Babu, R. Praveena^*

Molecular & Cellular Biomechanics, Vol.18, No.4, pp. 201-219, 2021, DOI:10.32604/mcb.2021.017984 - 27 October 2021

Abstract Skin is the largest organ and outer enclosure of the integumentary system that protects the human body from pathogens. Among various cancers in the world, skin cancer is one of the most commonly diagnosed cancer which can be either melanoma or non-melanoma. Melanoma cancers are very fatal compared with non-melanoma cancers but the chances of survival rate are high when diagnosed and treated earlier. The main aim of this work is to analyze and investigate the performance of Non-Subsampled Bendlet Transform (NSBT) on various classifiers for detecting melanoma from dermoscopic images. NSBT is a multiscale More >

Saeed AlQadhi¹, Javed Mallick^1,*, Swapan Talukdar², Ahmed Ali Bindajam³, Ahmed Ali A. Shohan³, Shahfahad⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 755-786, 2021, DOI:10.32604/cmes.2021.016640 - 08 October 2021

Abstract Given that many cities in Saudi Arabia have been observing rapid urbanization since the 1990s, scarce studies on the spatial pattern of urban expansion in Saudi Arabia have been conducted. Therefore, the present study investigates the evidence of land use and land cover (LULC) dynamics and urban sprawl in Abha City of Saudi Arabia, which has been experiencing rapid urbanization, from the past to the future using novel and sophisticated methods. The SVM classifier was used in this study to classify the LULC maps for 1990, 2000, and 2018. The LULC dynamics between 1990–2000, 2000–2018,… More >

Razi J. Al-Azawi¹, Nadia M. G. Al-Saidi², Hamid A. Jalab^3,*, Rabha W. Ibrahim⁴, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3903-3915, 2021, DOI:10.32604/cmc.2021.020368 - 24 August 2021

Abstract Over the past years, image manipulation tools have become widely accessible and easier to use, which made the issue of image tampering far more severe. As a direct result to the development of sophisticated image-editing applications, it has become near impossible to recognize tampered images with naked eyes. Thus, to overcome this issue, computer techniques and algorithms have been developed to help with the identification of tampered images. Research on detection of tampered images still carries great challenges. In the present study, we particularly focus on image splicing forgery, a type of manipulation where a… More >

Animesh Kumar Dubey^*, Kavita Choudhary, Richa Sharma

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 929-943, 2021, DOI:10.32604/iasc.2021.018382 - 20 August 2021

Abstract Heart disease is a major health concern worldwide. The chances of recovery are bright if it is detected at an early stage. The present report discusses a comparative approach to the classification of heart disease data using machine learning (ML) algorithms and linear regression and classification methods, including logistic regression (LR), decision tree (DT), random forest (RF), support vector machine (SVM), SVM with grid search (SVMG), k-nearest neighbor (KNN), and naive Bayes (NB). The ANOVA F-test feature selection (AFS) method was used to select influential features. For experimentation, two standard benchmark datasets of heart diseases, More >

Liping Yan^1,*, Wei-Chiang Hong²

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1069-1102, 2021, DOI:10.32604/cmes.2021.016499 - 11 August 2021

Abstract The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road. In order to obtain the scientific and real-time forecasting result, this paper constructs a novel hybrid intelligent model based on improved cloud model combined with GRA-TOPSIS and MBA-WLSSVM. Firstly, the factors influencing investment risk of wind energy along the Belt and Road are identified from three dimensions: endogenous risk, exogenous risk and process risk. Through the fuzzy threshold method, the final input index system is selected.… More >