Nouh Sabri Elmitwally^1,2, Asma Kanwal^3,4, Sagheer Abbas³, Muhammad A. Khan⁵, Muhammad Adnan Khan^6,*, Munir Ahmad³, Saad Alanazi¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4947-4964, 2022, DOI:10.32604/cmc.2022.021104

Abstract Detection of personality using emotions is a research domain in artificial intelligence. At present, some agents can keep the human’s profile for interaction and adapts themselves according to their preferences. However, the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject. The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior. In our daily life, humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input. This paper presents a conceptual personality model… More >

Chinu Singla¹, Fahd N. Al-Wesabi^2,3, Yash Singh Pathania¹, Badria Sulaiman Alfurhood⁴, Anwer Mustafa Hilal^5,*, Mohammed Rizwanullah⁵, Manar Ahmed Hamza⁵, Mohammad Mahzari⁶

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6365-6380, 2022, DOI:10.32604/cmc.2022.020480

Abstract The task of automatically analyzing sentiments from a tweet has more use now than ever due to the spectrum of emotions expressed from national leaders to the average man. Analyzing this data can be critical for any organization. Sentiments are often expressed with different intensity and topics which can provide great insight into how something affects society. Sentiment analysis in Twitter mitigates the various issues of analyzing the tweets in terms of views expressed and several approaches have already been proposed for sentiment analysis in twitter. Resources used for analyzing tweet emotions are also briefly presented in literature survey section.… More >

Adnan Muhammad Shah, KangYoon Lee^*

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1719-1735, 2022, DOI:10.32604/iasc.2022.019666

Abstract Online physician reviews (OPRs) critically influence the patients’ consultation decisions on physician rating websites. The increasing number of OPRs contributes to the challenge of information overload. The worth of development needs to be explored further. Based on the OPRs collected from RateMDs and Healthgrades, and Plutchik’s wheel on human emotions framework, the purpose of this study was to examine the impact of emotional intensity (positive and negative) incorporated in OPRs on review helpfulness (RH). The proposed model was empirically tested using data from two physician rating websites and applying a mixed-methods approach (text mining and econometrics). The results suggested that… More >

Ibrahim Alsukayti¹, Aman Singh^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2489-2505, 2022, DOI:10.32604/cmc.2022.020264

Abstract A famous psychologist or researcher, Daniel Goleman, gave a theory on the importance of Emotional Intelligence for the success of an individual’s life. Daniel Goleman quoted in the research that “The contribution of an individual’s Intelligence Quotient (IQ) is only 20% for their success, the remaining 80% is due to Emotional Intelligence (EQ)”. However, in the absence of a reliable technique for EQ evaluation, this factor of overall intelligence is ignored in most of the intelligence evaluation mechanisms. This research presented an analysis based on basic statistical tools along with more sophisticated deep learning tools. The proposed cross intelligence evaluation… More >

B. T. Shobana^1,*, G. A. Sathish Kumar²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1007-1021, 2022, DOI:10.32604/csse.2022.019523

Abstract Electronic learning (e-learning) has become one of the widely used modes of pedagogy in higher education today due to the convenience and flexibility offered in comparison to traditional learning activities. Advancements in Information and Communication Technology have eased learner connectivity online and enabled access to an extensive range of learning materials on the World Wide Web. Post covid-19 pandemic, online learning has become the most essential and inevitable medium of learning in primary, secondary and higher education. In recent times, Massive Open Online Courses (MOOCs) have transformed the current education strategy by offering a technology-rich and flexible form of online… More >

H. Varun Chand^*, J. Karthikeyan

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 717-728, 2022, DOI:10.32604/iasc.2022.020008

Abstract

The drowsiness of the driver and rash driving are the major causes of road accidents, which result in loss of valuable life, and deteriorate the safety in the road traffic. Reliable and precise driver drowsiness systems are required to prevent road accidents and to improve road traffic safety. Various driver drowsiness detection systems have been designed with different technologies which have an affinity towards the unique parameter of detecting the drowsiness of the driver. This paper proposes a novel model of multi-level distribution of detecting the driver drowsiness using the Convolution Neural Networks (CNN) followed by the emotion analysis. The… More >

Amit Verma¹, Mohammed Baljon², Shailendra Mishra^2,*, Iqbaldeep Kaur¹, Ritika Saini¹, Sharad Saxena³, Sanjay Kumar Sharma⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1955-1974, 2022, DOI:10.32604/cmc.2022.020084

Abstract Biometric applications widely use the face as a component for recognition and automatic detection. Face rotation is a variable component and makes face detection a complex and challenging task with varied angles and rotation. This problem has been investigated, and a novice algorithm, namely RIFDS (Rotation Invariant Face Detection System), has been devised. The objective of the paper is to implement a robust method for face detection taken at various angle. Further to achieve better results than known algorithms for face detection. In RIFDS Polar Harmonic Transforms (PHT) technique is combined with Multi-Block Local Binary Pattern (MBLBP) in a hybrid… More >

Ishaani Priyadarshini^*, Chase Cotton

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 781-800, 2022, DOI:10.32604/cmc.2022.019284

Abstract

The increasing capabilities of Artificial Intelligence (AI), has led researchers and visionaries to think in the direction of machines outperforming humans by gaining intelligence equal to or greater than humans, which may not always have a positive impact on the society. AI gone rogue, and Technological Singularity are major concerns in academia as well as the industry. It is necessary to identify the limitations of machines and analyze their incompetence, which could draw a line between human and machine intelligence. Internet memes are an amalgam of pictures, videos, underlying messages, ideas, sentiments, humor, and experiences, hence the way an internet… More >

Husam Ali Abdulmohsin^1,*, Hala Bahjat Abdul Wahab², Abdul Mohssen Jaber Abdul Hossen³

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 339-355, 2022, DOI:10.32604/iasc.2022.018045

Abstract Classification is the last, and usually the most time-consuming step in recognition. Most recently proposed classification algorithms have adopted machine learning (ML) as the main classification approach, regardless of time consumption. This study proposes a statistical feature classification cubic spline interpolation (FC-CSI) algorithm to classify emotions in speech using a curve fitting technique. FC-CSI is utilized in a speech emotion recognition system (SERS). The idea is to sketch the cubic spline interpolation (CSI) for each audio file in a dataset and the mean cubic spline interpolations (MCSIs) representing each emotion in the dataset. CSI interpolation is generated by connecting the… More >

S. Lalitha¹, Deepa Gupta^2,*, Mohammed Zakariah³, Yousef Ajami Alotaibi³

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3217-3238, 2021, DOI:10.32604/cmc.2021.018406

Abstract Automatic recognition of human emotions in a continuous dialog model remains challenging where a speaker’s utterance includes several sentences that may not always carry a single emotion. Limited work with standalone speech emotion recognition (SER) systems proposed for continuous speech only has been reported. In the recent decade, various effective SER systems have been proposed for discrete speech, i.e., short speech phrases. It would be more helpful if these systems could also recognize emotions from continuous speech. However, if these systems are applied directly to test emotions from continuous speech, emotion recognition performance would not be similar to that achieved… More >