Sudan Prasad Uprety, Seung Ryul Jeong^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3937-3952, 2022, DOI:10.32604/cmc.2022.023127

Abstract Artificial intelligent based dialog systems are getting attention from both business and academic communities. The key parts for such intelligent chatbot systems are domain classification, intent detection, and named entity recognition. Various supervised, unsupervised, and hybrid approaches are used to detect each field. Such intelligent systems, also called natural language understanding systems analyze user requests in sequential order: domain classification, intent, and entity recognition based on the semantic rules of the classified domain. This sequential approach propagates the downstream error; i.e., if the domain classification model fails to classify the domain, intent and entity recognition fail. Furthermore, training such intelligent… More >

Dhiaa A. Musleh, Taef A. Alkhales, Reem A. Almakki^*, Shahad E. Alnajim, Shaden K. Almarshad, Rana S. Alhasaniah, Sumayh S. Aljameel, Abdullah A. Almuqhim

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3463-3477, 2022, DOI:10.32604/cmc.2022.022508

Abstract Depression has been a major global concern for a long time, with the disease affecting aspects of many people's daily lives, such as their moods, eating habits, and social interactions. In Arabic culture, there is a lack of awareness regarding the importance of facing and curing mental health diseases. However, people all over the world, including Arab citizens, tend to express their feelings openly on social media, especially Twitter, as it is a platform designed to enable the expression of emotions through short texts, pictures, or videos. Users are inclined to treat their Twitter accounts as diaries because the platform… More >

Simon Crase^1,2, Benjamin Hall², Suresh N. Thennadil^3,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2435-2458, 2022, DOI:10.32604/cmc.2022.022414

Abstract Cluster analysis in spectroscopy presents some unique challenges due to the specific data characteristics in spectroscopy, namely, high dimensionality and small sample size. In order to improve cluster analysis outcomes, feature selection can be used to remove redundant or irrelevant features and reduce the dimensionality. However, for cluster analysis, this must be done in an unsupervised manner without the benefit of data labels. This paper presents a novel feature selection approach for cluster analysis, utilizing clusterability metrics to remove features that least contribute to a dataset's tendency to cluster. Two versions are presented and evaluated: The Hopkins clusterability filter which… More >

P. Prabu¹, K. Venkatachalam², Ala Saleh Alluhaidan^3,*, Radwa Marzouk⁴, Myriam Hadjouni⁵, Sahar A. El_Rahman^5,6

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1133-1152, 2022, DOI:10.32604/cmc.2022.020919

Abstract COVID’19 has caused the entire universe to be in existential health crisis by spreading globally in the year 2020. The lungs infection is detected in Computed Tomography (CT) images which provide the best way to increase the existing healthcare schemes in preventing the deadly virus. Nevertheless, separating the infected areas in CT images faces various issues such as low-intensity difference among normal and infectious tissue and high changes in the characteristics of the infection. To resolve these issues, a new inf-Net (Lung Infection Segmentation Deep Network) is designed for detecting the affected areas from the CT images automatically. For the… More >

M. Prabhavathy^1,*, S. UmaMaheswari²

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 101-114, 2022, DOI:10.32604/iasc.2022.018257

Abstract Cloud computing utilizes various Internet-based technologies to enhance the Internet user experience. Cloud systems are on the rise, as this technology has completely revolutionized the digital industry. Currently, many users rely on cloud-based solutions to acquire business information and knowledge. As a result, cloud computing services such as SaaS and PaaS store a warehouse of sensitive and valuable information, which has turned the cloud systems into the obvious target for many malware creators and hackers. These malicious attackers attempt to gain illegal access to a myriad of valuable information such as user personal information, password, credit/debit card numbers, etc., from… More >

Amgad Muneer^1,2,*, Shakirah Mohd Taib^1,2, Suliman Mohamed Fati³, Abdullateef O. Balogun¹, Izzatdin Abdul Aziz^1,2

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5363-5381, 2022, DOI:10.32604/cmc.2022.021113

Abstract Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data. Such a phenomenon is referred to as the “curse of dimensionality” that affects traditional techniques in terms of both accuracy and performance. Thus, this research proposed a hybrid model based on Deep Autoencoder Neural Network (DANN) with five layers to reduce the difference between the input and output. The proposed model was applied to a… More >

Nasir Mahmood^*, Muhammad Usman Ghani Khan

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4411-4428, 2022, DOI:10.32604/cmc.2022.013956

Abstract This study proposes an architecture for the prediction of extremist human behaviour from projected suicide bombings. By linking ‘dots’ of police data comprising scattered information of people, groups, logistics, locations, communication, and spatiotemporal characters on different social media groups, the proposed architecture will spawn beneficial information. This useful information will, in turn, help the police both in predicting potential terrorist events and in investigating previous events. Furthermore, this architecture will aid in the identification of criminals and their associates and handlers. Terrorism is psychological warfare, which, in the broadest sense, can be defined as the utilisation of deliberate violence for… More >

Karunanithi Praveen kumar, Perumal Sivanesan^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 67-82, 2022, DOI:10.32604/csse.2022.018867

Abstract In this work, we propose a context-aware switching of routing protocol scheme for specific application requirements of IoT in real-time using a software-defined networking controller in wireless sensor networks. The work planned has two stages i) Selection of suitable routing protocol (RP) for given IoT applications using higher cognitive process and ii) Deployment of the corresponding routing protocol. We use the supervised learning-regression method for classification of the routing protocol while considering the network parameters like stability, path delay, energy utilization, and throughput. The chosen routing protocol will be set in the sensor network using a software-defined networking controller in… More >

Saleh Nagi Alsubari¹, Sachin N. Deshmukh¹, Ahmed Abdullah Alqarni², Nizar Alsharif³, Theyazn H. H. Aldhyani^4,*, Fawaz Waselallah Alsaade⁵, Osamah I. Khalaf⁶

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3189-3204, 2022, DOI:10.32604/cmc.2022.019625

Abstract Fake reviews, also known as deceptive opinions, are used to mislead people and have gained more importance recently. This is due to the rapid increase in online marketing transactions, such as selling and purchasing. E-commerce provides a facility for customers to post reviews and comment about the product or service when purchased. New customers usually go through the posted reviews or comments on the website before making a purchase decision. However, the current challenge is how new individuals can distinguish truthful reviews from fake ones, which later deceive customers, inflict losses, and tarnish the reputation of companies. The present paper… More >

Farzaneh Khorasani¹, Morteza Mohammadi Zanjireh^1,*, Mahdi Bahaghighat¹, Qin Xin²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1085-1098, 2022, DOI:10.32604/csse.2022.016003

Abstract With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected… More >