Tao Yang¹, Chengyu Wang¹, Tongqing Zhou¹, Zhiping Cai^1,*, Kui Wu², Bingnan Hou¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5179-5198, 2022, DOI:10.32604/cmc.2022.021626

Abstract Malicious attacks can be launched by misusing the network address translation technique as a camouflage. To mitigate such threats, network address translation identification is investigated to identify network address translation devices and detect abnormal behaviors. However, existing methods in this field are mainly developed for relatively small-scale networks and work in an offline manner, which cannot adapt to the real-time inference requirements in high-speed network scenarios. In this paper, we propose a flexible and efficient network address translation identification scheme based on actively measuring the distance of a round trip to a target with decremental time-to-live values. The basic intuition… More >

Walaa Gad^1,*, Anas Alokla¹, Waleed Nazih², Mustafa Aref¹, Abdel-badeeh Salem¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3117-3132, 2022, DOI:10.32604/cmc.2022.019884

Abstract Understanding the content of the source code and its regular expression is very difficult when they are written in an unfamiliar language. Pseudo-code explains and describes the content of the code without using syntax or programming language technologies. However, writing Pseudo-code to each code instruction is laborious. Recently, neural machine translation is used to generate textual descriptions for the source code. In this paper, a novel deep learning-based transformer (DLBT) model is proposed for automatic Pseudo-code generation from the source code. The proposed model uses deep learning which is based on Neural Machine Translation (NMT) to work as a language… More >

Muhammad Sanaullah^1,*, Babar Ahmad², Muhammad Kashif², Tauqeer Safdar², Mehdi Hassan³, Mohd Hilmi Hasan⁴, Norshakirah Aziz⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2471-2488, 2022, DOI:10.32604/cmc.2022.019420

Abstract Communication is a basic need of every human being; by this, they can learn, express their feelings and exchange their ideas, but deaf people cannot listen and speak. For communication, they use various hands gestures, also known as Sign Language (SL), which they learn from special schools. As normal people have not taken SL classes; therefore, they are unable to perform signs of daily routine sentences (e.g., what are the specifications of this mobile phone?). A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people. This paper presents an architecture for… More >

HongGeun Ji^1,2, Soyoung Oh¹, Jina Kim³, Seong Choi^1,2, Eunil Park^1,2,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 669-678, 2022, DOI:10.32604/cmc.2022.019521

Abstract In the field of natural language processing (NLP), the advancement of neural machine translation has paved the way for cross-lingual research. Yet, most studies in NLP have evaluated the proposed language models on well-refined datasets. We investigate whether a machine translation approach is suitable for multilingual analysis of unrefined datasets, particularly, chat messages in Twitch. In order to address it, we collected the dataset, which included 7,066,854 and 3,365,569 chat messages from English and Korean streams, respectively. We employed several machine learning classifiers and neural networks with two different types of embedding: word-sequence embedding and the final layer of a… More >

Summra Saleem^1,2, M. Usman Ghani Khan^1,2, Tanzila Saba³, Ibrahim Abunadi³, Amjad Rehman^3,*, Saeed Ali Bahaj⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 505-521, 2022, DOI:10.32604/cmc.2022.018871

Abstract Image translation plays a significant role in realistic image synthesis, entertainment tasks such as editing and colorization, and security including personal identification. In Edge GAN, the major contribution is attribute guided vector that enables high visual quality content generation. This research study proposes automatic face image realism from freehand sketches based on Edge GAN. We propose a density variant image synthesis model, allowing the input sketch to encompass face features with minute details. The density level is projected into non-latent space, having a linear controlled function parameter. This assists the user to appropriately devise the variant densities of facial sketches… More >

A. Sheryl Oliver¹, T. Jayasankar², K. R. Sekar^3,*, T. Kalavathi Devi⁴, R. Shalini⁵, S. Poojalaxmi⁵, N. G. Viswesh⁵

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 755-770, 2021, DOI:10.32604/iasc.2021.016242

Abstract Lung cancer is a poorly understood disease. Smokers may develop lung cancer due to the inhalation of carcinogenic substances while smoking, but non-smokers may develop this disease as well. Lung cancer can spread to other parts of the body and this process is called metastasis. Because the lung cancer is difficult to identify in the initial stages. The objective of this work is to reduce the mortality rate of the disease by identifying it at an earlier stage based on the existing symptoms. Artificial intelligence plays active roles in tasks such as entropy extraction through preprocessing strategies, ordinal to cardinal… More >

Manjur Kolhar^*, Abdalla Alameen

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 1-9, 2021, DOI:10.32604/iasc.2021.014995

Abstract The use of computer-based technologies by non-native Arabic-speaking teachers for teaching native Arabic-speaking students can result in higher learner engagement. In this study, a machine translation (MT) system is developed as a learning technology. The proposed system can be linked to a digital podium and projector to reduce multitasking. A total of 25 students from Prince Sattam Bin Abdulaziz University, Saudi Arabia participated in our experiment and survey related to the use of the proposed technology-enhanced MT system. An important reason for using this framework is to exploit the high service bandwidth (up to several bandwidths) made available for interactive… More >

Yunpeng Chang¹, Xiaoliang Wang^1,*, Meihua Xue¹, Yuzhen Liu¹, Frank Jiang²

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3921-3931, 2021, DOI:10.32604/cmc.2021.012304

Abstract Translation software has become an important tool for communication between different languages. People’s requirements for translation are higher and higher, mainly reflected in people’s desire for barrier free cultural exchange. With a large corpus, the performance of statistical machine translation based on words and phrases is limited due to the small size of modeling units. Previous statistical methods rely primarily on the size of corpus and number of its statistical results to avoid ambiguity in translation, ignoring context. To support the ongoing improvement of translation methods built upon deep learning, we propose a translation algorithm based on the Hidden Markov… More >

Giuseppe Corrente^*

Journal of Quantum Computing, Vol.2, No.3, pp. 137-145, 2020, DOI:10.32604/jqc.2020.014586

Abstract We want in this article to show the usefulness of Quantum Turing Machine (QTM) in a high-level didactic context as well as in theoretical studies. We use QTM to show its equivalence with quantum circuit model for Deutsch and Deutsch-Jozsa algorithms. Further we introduce a strategy of translation from Quantum Circuit to Quantum Turing models by these examples. Moreover we illustrate some features of Quantum Computing such as superposition from a QTM point of view and starting with few simple examples very known in Quantum Circuit form. More >

Vinay Singh¹, Mohammed Alshehri^2,*, Alok Aggarwal³, Osama Alfarraj⁴, Purushottam Sharma⁵, K. R. Pardasani⁶

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2359-2371, 2021, DOI:10.32604/cmc.2021.013272

Abstract Software development is getting a transition from centralized version control systems (CVCSs) like Subversion to decentralized version control systems (DVCDs) like Git due to lesser efficiency of former in terms of branching, fusion, time, space, merging, offline commits & builds and repository, etc. Git is having a share of 77% of total VCS, followed by Subversion with a share of 13.5%. The majority of software industries are getting a migration from Subversion to Git. Only a few migration tools are available in the software industry. Still, these too lack in many features like lack of identifying the empty directories as… More >