Manjur Kolhar^*, Abdalla Alameen

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1215-1226, 2021, DOI:10.32604/cmc.2020.012658 - 26 November 2020

Abstract Plagiarism refers to the use of other people’s ideas and information without acknowledging the source. In this research, anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’ written assignments and laboratory reports. The proposed framework collected original documents to identify plagiarized text using natural language processing. Our research proposes a method to detect plagiarism by applying the core concept of text, which is semantic associations of words and their syntactic composition. Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri, and it is… More >

Rizwan Ali Naqvi¹, Dildar Hussain², Woong-Kee Loh^3,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 715-732, 2021, DOI:10.32604/cmc.2020.013249 - 30 October 2020

Abstract Multiple ocular region segmentation plays an important role in different applications such as biometrics, liveness detection, healthcare, and gaze estimation. Typically, segmentation techniques focus on a single region of the eye at a time. Despite the number of obvious advantages, very limited research has focused on multiple regions of the eye. Similarly, accurate segmentation of multiple eye regions is necessary in challenging scenarios involving blur, ghost effects low resolution, off-angles, and unusual glints. Currently, the available segmentation methods cannot address these constraints. In this paper, to address the accurate segmentation of multiple eye regions in… More >

Weifeng Ma^*, Jiao Lou, Caoting Ji, Laibin Ma

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 179-193, 2021, DOI:10.32604/cmc.2020.011969 - 30 October 2020

Abstract Given the limitations of the community question answering (CQA) answer quality prediction method in measuring the semantic information of the answer text, this paper proposes an answer quality prediction model based on the question-answer joint learning (ACLSTM). The attention mechanism is used to obtain the dependency relationship between the Question-and-Answer (Q&A) pairs. Convolutional Neural Network (CNN) and Long Short-term Memory Network (LSTM) are used to extract semantic features of Q&A pairs and calculate their matching degree. Besides, answer semantic representation is combined with other effective extended features as the input representation of the fully connected More >

Aziguli Wulamu^1,2,*, Jingyue Sang³, Dezheng Zhang^1,2, Zuxian Shi^1,2

Journal of New Media, Vol.2, No.4, pp. 149-155, 2020, DOI:10.32604/jnm.2020.014115 - 23 December 2020

Abstract Cultivated land extraction is essential for sustainable development and agriculture. In this paper, the network we propose is based on the encoderdecoder structure, which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation solutions. The encoder consists of two part: the first is the modified Xception, it can used as the feature extraction network, and the second is the atrous convolution, it can used to expand the receptive field and the context information to extract richer feature information. The decoder part uses the conventional upsampling operation More >

Belal Abdullah Hezam Murshed^1,∗, Hasib Daowd Esmail Al-ariki^2,†, Suresha Mallappa^3,‡

Computer Systems Science and Engineering, Vol.35, No.6, pp. 495-512, 2020, DOI:10.32604/csse.2020.35.495

Abstract This paper conducts a comprehensive review of various word and sentence semantic similarity techniques proposed in the literature. Corpus-based, Knowledge-based, and Feature-based are categorized under word semantic similarity techniques. String and set-based, Word Order-based Similarity, POSbased, Syntactic dependency-based are categorized as sentence semantic similarity techniques. Using these techniques, we propose a model for computing the overall accuracy of the twitter dataset. The proposed model has been tested on the following four measures: Atish’s measure, Li’s measure, Mihalcea’s measure with path similarity, and Mihalcea’s measure with Wu and Palmer’s (WuP) similarity. Finally, we evaluate the proposed More >

Hui Li¹, Wei Zeng^1,*, Guorong Xiao², Huabin Wang¹

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 841-846, 2020, DOI:10.32604/iasc.2020.010118

Abstract Recent progress on image colorization is substantial and benefiting mostly from the great development of the deep convolutional neural networks. However, one type of object can be colored by different kinds of colors. Due to the uncertain relationship between the object and color, the deep neural network is unstable and difficult to converge during the training process. In order to solve this problem, this paper proposes an instance-aware automatic image colorization algorithm, which uses the semantic features of the object instance as prior knowledge to guide the deep neural network to do the colorization task. More >

Ping Wang¹ HongGuo Cai^2,*, LuKun Wang³

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 519-529, 2020, DOI:10.32604/iasc.2020.013929

Abstract In order to improve the quality of intelligent English translation, an intelligent English translation algorithm based on the fuzzy semantic network is designed. By calculating the distance of fuzzy semantic network, classifying and ordering the English semantics to determine the optimal similarity and outputting the optimal translation results, the experiments show the average BLEU and NIST of the three test sets are 25.85 and 5.8925 respectively. The translation accuracy is higher than 95%. The algorithm can translate 246 Chinese sentences per second. This shows it is a high-performance intelligent translation algorithm and can be applied More >

Ebtsam Adel¹, Shaker El-sappagh², Mohammed Elmogy³, Sherif Barakat¹, Kyung-Sup Kwak^4,*

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 237-251, 2020, DOI:10.31209/2019.100000151

Abstract Information technology is a beneficial tool for the healthcare industry. Health informatics is concerned with using ICT within the healthcare system. Different electronic health record (EHR) systems independently store large amounts of medical data in various structures and formats. Achieving semantic interoperability in EHR environments will improve the healthcare industry. In our previous studies, we proposed a framework that identifies the different heterogeneous medical data sources. In this paper, we move towards implementing the first module of that framework. We expect our framework to be a step towards improving performance and reducing both human mediation More >

Farhan Ullah^1,4,*, Abdullah Bajahzar², Hamza Aldabbas³, Muhammad Farhan⁴, Hamad Naeem¹, S. Sabahat H. Bukhari^4,5, Kaleem Razzaq Malik⁶

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 169-180, 2020, DOI:10.31209/2019.100000138

Abstract This research aims to an electronic assessment (e-assessment) of students’ replies in response to the standard answer of teacher’s question to automate the assessment by WordNet semantic similarity. For this purpose, a new methodology for Semantic Similarity through WordNet Semantic Similarity Techniques (SS-WSST) has been proposed to calculate semantic similarity among teacher’ query and student’s reply. In the pilot study-1 42 words’ pairs extracted from 8 students’ replies, which marked by semantic similarity measures and compared with manually assigned teacher’s marks. The teacher is provided with 4 bins of the mark while our designed methodology More >

Isma Farah Siddiqui¹, Scott Uk-Jin Lee^2,*, Asad Abbas³

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 107-119, 2020, DOI:10.31209/2019.100000132

Abstract The issue of battery drainage in the gigantic smart meters network such as semantic-aware IoT-enabled smart meter has become a serious concern in the smart grid framework. The grid core migrates existing tabular datasets i.e., Relational data to semantic-aware tuples in its Resource Description Framework (RDF) format, for effective integration among multiple components to work aligned with IoT. For this purpose, WWW Consortium (W3C) recommends two specifications as mapping languages. However, both specifications use entire RDB schema to generate data transformation mapping patterns and results large quantity of unnecessary transformation. As a result, smart meters… More >