Shinjin Kang¹, Jongin Choi^2,*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1089-1105, 2022, DOI:10.32604/iasc.2022.019979 - 22 September 2021

Abstract The game user interface (UI) provides a large volume of information necessary to analyze the game screen. The availability of such information can be functional in vision-based machine learning algorithms. With this, there will be an enhancement in the application power of vision deep learning neural networks. Therefore, this paper proposes a game UI segmentation technique based on unsupervised learning. We developed synthetic labeling created on the game engine, image-to-image translation and segmented UI components in the game. The network learned in this manner can segment the target UI area in the target game regardless More >

Jari Jussila¹, Eman Alkhammash^2,*, Norah Saleh Alghamdi³, Prashanth Madhala⁴, Mohammad Ayoub Khan⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1845-1856, 2022, DOI:10.32604/cmc.2022.017284 - 07 September 2021

Abstract Social media platforms provide new value for markets and research companies. This article explores the use of social media data to enhance customer value propositions. The case study involves a company that develops wearable Internet of Things (IoT) devices and services for stress management. Netnography and semantic annotation for recognizing and categorizing the context of tweets are conducted to gain a better understanding of users’ stress management practices. The aim is to analyze the tweets about stress management practices and to identify the context from the tweets. Thereafter, we map the tweets on pleasure and… 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 - 03 September 2021

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… More >

Hanyu Shi¹, Weiguang Qu^1,2,*, Tingxin Wei^2,3, Junsheng Zhou¹, Yunfei Long⁴, Yanhui Gu¹, Bin Li²

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4113-4127, 2021, DOI:10.32604/cmc.2021.019518 - 24 August 2021

Abstract In Mandarin Chinese, when the noun head appears in the context, a quantity noun phrase can be reduced to a quantity phrase with the noun head omitted. This phrase structure is called elliptical quantity noun phrase. The automatic recovery of elliptical quantity noun phrase is crucial in syntactic parsing, semantic representation and other downstream tasks. In this paper, we propose a hybrid neural network model to identify the semantic category for elliptical quantity noun phrases and realize the recovery of omitted semantics by supplementing concept categories. Firstly, we use BERT to generate character-level vectors. Secondly,… More >

Nora Shoaip¹, Amira Rezk¹, Shaker EL-Sappagh^2,3, Tamer Abuhmed^4,*, Sherif Barakat¹, Mohammed Elmogy⁵

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3531-3548, 2021, DOI:10.32604/cmc.2021.019069 - 24 August 2021

Abstract Alzheimer’s disease (AD) is a very complex disease that causes brain failure, then eventually, dementia ensues. It is a global health problem. 99% of clinical trials have failed to limit the progression of this disease. The risks and barriers to detecting AD are huge as pathological events begin decades before appearing clinical symptoms. Therapies for AD are likely to be more helpful if the diagnosis is determined early before the final stage of neurological dysfunction. In this regard, the need becomes more urgent for biomarker-based detection. A key issue in understanding AD is the need… More >

Zhe Wang^1,2, Yingying Zhao¹, Hai Dong³, Yulong Xu^1,*, Yali Lv¹

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 419-429, 2021, DOI:10.32604/iasc.2021.016434 - 11 August 2021

Abstract The quick retrieval of target information from a massive amount of information has become a core research area in the field of information retrieval. Semantic information retrieval provides effective methods based on semantic comprehension, whose traditional models focus on multiple rounds of detection to differentiate information. Since a large amount of information must be excluded, retrieval efficiency is low. One of the most common methods used in classification, the decision tree algorithm, first selects attributes with higher information entropy to construct a decision tree. However, the tree only matches words on the grammatical level and… More >

Nadia Tabassum¹, Tahir Alyas², Muhammad Hamid^3,*, Muhammad Saleem⁴, Saadia Malik⁵, Zain Ali², Umer Farooq²

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 175-186, 2021, DOI:10.32604/iasc.2021.018998 - 26 July 2021

Abstract Development in the field of opinion mining and sentiment analysis has been rapid and aims to explore views or texts on various social media sites through machine-learning techniques with the sentiment, subjectivity analysis and calculations of polarity. Sentiment analysis is a natural language processing strategy used to decide if the information is positive, negative, or neutral and it is frequently performed on literature information to help organizations screen brand, item sentiment in client input, and comprehend client needs. In this paper, two strategies for sentiment analysis is proposed for word embedding and a bag of… More >

Mamoona Majid¹, Muhammad Faisal Hayat², Farrukh Zeeshan Khan³, Muneer Ahmad^4,*, NZ Jhanjhi⁵, Mohammad Arif Sobhan Bhuiyan⁶, Mehedi Masud⁷, Mohammed A. AlZain⁸

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 373-386, 2021, DOI:10.32604/iasc.2021.017840 - 26 July 2021

Abstract Choosing the right university program can be very challenging for students. This is especially the case in developing countries such as India and Pakistan, where university admission depends on not only the program of interest but also other factors such as the candidate’s financial standing. Since information on the Internet can be highly scattered, university candidates often need counseling from qualified people to decide their educational programs. Traditional database systems cannot effectively organize the large unstructured data related to university programs. It is challenging, then, for prospective students to acquire the information needed to make More >

Jing Peng^1,2,4, Chaoyang Xia², Yuanwei Xu³, Xiaojie Li², Xi Wu², Xiao Han^1,4, Xinlai Chen⁵, Yucheng Chen³, Zhe Cui^1,4,*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 259-272, 2021, DOI:10.32604/iasc.2021.016749 - 26 July 2021

Abstract Cardiomyopathy is a group of diseases that affect the heart and can cause serious health problems. Segmentation and classification are important for automating the clinical diagnosis and treatment planning for cardiomyopathy. However, this automation is difficult because of the poor quality of cardiac magnetic resonance (CMR) imaging data and varying dimensions caused by movement of the ventricle. To address these problems, a deep multi-task framework based on a convolutional neural network (CNN) is proposed to segment the left ventricle (LV) myocardium and classify cardiopathy simultaneously. The proposed model consists of a longitudinal encoder–decoder structure that… More >

Mohamed Eb-Saad¹, Yunyoung Nam^2,*, Hazem M. El-bakry¹, Samir Abdelrazek¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1483-1501, 2021, DOI:10.32604/cmc.2021.017783 - 21 July 2021

Abstract Web service (WS) presents a good solution to the interoperability of different types of systems that aims to reduce the overhead of high processing in a resource-limited environment. With the increasing demand for mobile WS (MWS), the WS discovery process has become a significant challenging point in the WS lifecycle that aims to identify the relevant MWSs that best match the service requests. This discovery process is a resource-consuming task that cannot be performed efficiently in a mobile computing environment due to the limitations of mobile devices. Meanwhile, a cloud computing can provide rich computing… More >