Sarah Alzahrani¹, Joud Alderaan¹, Dalya Alatawi¹, Bandar Alotaibi^1,2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 651-667, 2023, DOI:10.32604/cmc.2023.035173

Abstract Internet of Things (IoT) devices incorporate a large amount of data in several fields, including those of medicine, business, and engineering. User authentication is paramount in the IoT era to assure connected devices’ security. However, traditional authentication methods and conventional biometrics-based authentication approaches such as face recognition, fingerprints, and password are vulnerable to various attacks, including smudge attacks, heat attacks, and shoulder surfing attacks. Behavioral biometrics is introduced by the powerful sensing capabilities of IoT devices such as smart wearables and smartphones, enabling continuous authentication. Artificial Intelligence (AI)-based approaches introduce a bright future in refining large amounts of homogeneous biometric… More >

Inshirah Ali AlMutairi^*, Ali Mustafa Qamar

Journal on Artificial Intelligence, Vol.4, No.3, pp. 155-165, 2022, DOI:10.32604/jai.2022.032390

Abstract Neural talk models play a leading role in the growing popular building of conversational managers. A commonplace criticism of those systems is that they seldom understand or use the conversation data efficiently. The development of profound concentration on innovations has increased the use of neural models for a discussion display. In recent years, deep learning (DL) models have achieved significant success in various tasks, and many dialogue systems are also employing DL techniques. The primary issues involved in the generation of the dialogue system are acquiring perspectives into instinctual linguistics, comprehension provision, and conversation assessment. In this paper, we mainly… More >

A. Venkatesh¹, S. Asha^2,*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1375-1392, 2023, DOI:10.32604/csse.2023.030944

Abstract A Wireless Sensor Network (WSN) is constructed with numerous sensors over geographical regions. The basic challenge experienced while designing WSN is in increasing the network lifetime and use of low energy. As sensor nodes are resource constrained in nature, novel techniques are essential to improve lifetime of nodes in WSN. Nodes energy is considered as an important resource for sensor node which are battery powered based. In WSN, energy is consumed mainly while data is being transferred among nodes in the network. Several research works are carried out focusing on preserving energy of nodes in the network and made network… More >

Hyun-Sam Shin¹, Jun-Ki Hong^2,*

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 235-248, 2023, DOI:10.32604/iasc.2023.033082

Abstract Recently, artificial-intelligence-based automatic customer response system has been widely used instead of customer service representatives. Therefore, it is important for automatic customer service to promptly recognize emotions in a customer’s voice to provide the appropriate service accordingly. Therefore, we analyzed the performance of the emotion recognition (ER) accuracy as a function of the simulation time using the proposed chunk-based speech ER (CSER) model. The proposed CSER model divides voice signals into 3-s long chunks to efficiently recognize characteristically inherent emotions in the customer’s voice. We evaluated the performance of the ER of voice signal chunks by applying four RNN techniques—long… More >

Elumalaivasan Poongavanam^1,*, Padmanathan Kasinathan², Kulothungan Kanagasabai³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 249-265, 2023, DOI:10.32604/iasc.2023.030101

Abstract The nation deserves to learn what India’s future energy demand will be in order to plan and implement an energy policy. This energy demand will have to be fulfilled by an adequate mix of existing energy sources, considering the constraints imposed by future economic and social changes in the direction of a more sustainable world. Forecasting energy demand, on the other hand, is a tricky task because it is influenced by numerous micro-variables. As a result, an macro model with only a few factors that may be predicted globally, rather than a detailed analysis for each of these variables, is… More >

P. Ganesan^1,*, S. Arockia Edwin Xavier²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2979-2996, 2023, DOI:10.32604/iasc.2023.029264

Abstract Typically, smart grid systems enhance the ability of conventional power system networks as it is vulnerable to several kinds of attacks. These vulnerabilities might cause the attackers or intruders to collapse the entire network system thus breaching the confidentiality and integrity of smart grid systems. Thus, for this purpose, Intrusion detection system (IDS) plays a pivotal part in offering a reliable and secured range of services in the smart grid framework. Several existing approaches are there to detect the intrusions in smart grid framework, however they are utilizing an old dataset to detect anomaly thus resulting in reduced rate of… More >

K. Saraswathi^1,*, V. Mohanraj², Y. Suresh², J. Senthilkumar²

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1691-1702, 2023, DOI:10.32604/csse.2023.027987

Abstract Nowadays, review systems have been developed with social media Recommendation systems (RS). Although research on RS social media is increasing year by year, the comprehensive literature review and classification of this RS research is limited and needs to be improved. The previous method did not find any user reviews within a time, so it gets poor accuracy and doesn’t filter the irrelevant comments efficiently. The Recursive Neural Network-based Trust Recommender System (RNN-TRS) is proposed to overcome this method’s problem. So it is efficient to analyse the trust comment and remove the irrelevant sentence appropriately. The first step is to collect… More >

V. Premanand^*, Dhananjay Kumar

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1807-1821, 2023, DOI:10.32604/csse.2023.026742

Abstract On grounds of the advent of real-time applications, like autonomous driving, visual surveillance, and sports analysis, there is an augmenting focus of attention towards Multiple-Object Tracking (MOT). The tracking-by-detection paradigm, a commonly utilized approach, connects the existing recognition hypotheses to the formerly assessed object trajectories by comparing the similarities of the appearance or the motion between them. For an efficient detection and tracking of the numerous objects in a complex environment, a Pearson Similarity-centred Kuhn-Munkres (PS-KM) algorithm was proposed in the present study. In this light, the input videos were, initially, gathered from the MOT dataset and converted into frames.… More >

S. P. Abirami^1,*, G. Kousalya¹, R. Karthick²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 595-607, 2023, DOI:10.32604/iasc.2023.027562

Abstract Autism Spectrum Disorder (ASD) is found to be a major concern among various occupational therapists. The foremost challenge of this neurodevelopmental disorder lies in the fact of analyzing and exploring various symptoms of the children at their early stage of development. Such early identification could prop up the therapists and clinicians to provide proper assistive support to make the children lead an independent life. Facial expressions and emotions perceived by the children could contribute to such early intervention of autism. In this regard, the paper implements in identifying basic facial expression and exploring their emotions upon a time-variant factor. The… More >

İhsan Uluocak^1,*, Hakan Yavuz²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 221-234, 2023, DOI:10.32604/csse.2023.025426

Abstract The recent studies on Artificial Intelligence (AI) accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adaptiveness and fast responding features. The Model Predictive Control (MPC) technique is a widely used, safe and reliable control method based on constraints. On the other hand, the Eddy Current dynamometers are highly nonlinear braking systems whose performance parameters are related to many processes related variables. This study is based on an adaptive model predictive control that utilizes selected AI methods. The presented approach presents an updated the mathematical model of… More >