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 >

Shayesteh Tabatabaei^1,∗

Computer Systems Science and Engineering, Vol.35, No.6, pp. 477-494, 2020, DOI:10.32604/csse.2020.35.477

Abstract In recent years, the application of WSNs has been remarkably increased and notable developments and advances have been achieved in this regard. In particular, thanks to smart, cheaper and smaller nodes, different types of information can be detected and gathered in different environments and under different conditions. As the popularity of WSNs has increased, the problems and issues related to networks are examined and investigated. As a case in point, routing issue is one of the main challenges in this regard which has a direct impact on the performance of sensor networks. In WSN routing,… More >

Umid Suleymanov¹, Behnam Kiani Kalejahi^1,2,*, Elkhan Amrahov¹, Rashid Badirkhanli¹

Computer Systems Science and Engineering, Vol.35, No.6, pp. 467-475, 2020, DOI:10.32604/csse.2020.35.467

Abstract Text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For More >

Vankamamidi S. Naresh^1,∗, Sivaranjani Reddi²

Computer Systems Science and Engineering, Vol.35, No.6, pp. 457-465, 2020, DOI:10.32604/csse.2020.35.457

Abstract Multiparty Key Agreement (MKA) is the backbone for secure multiparty communication. Although numerous efficient MKA-cryptosystems are available in the classical field, their security relies on the assumption that some computational issues are infeasible. To overcome this dependency, a new area, quantum cryptography, evolves to support key agreement among two or more participants securely. In this paper, first, we present a two-part quantum key agreement with Strong Fairness Property (SFP) and extends it to a Multiparty Quantum Key Agreement (MQKA) protocol. In the first round of proposed MQKA, a participant will act as a group controller… More >

Ahmed A. M. Jamel^1,∗, Bahriye Akay^2,†

Computer Systems Science and Engineering, Vol.35, No.6, pp. 441-456, 2020, DOI:10.32604/csse.2020.35.441

Abstract Recently, owing to the capability of mobile and wearable devices to sense daily human activity, human activity recognition (HAR) datasets have become a large-scale data resource. Due to the heterogeneity and nonlinearly separable nature of the data recorded by these sensors, the datasets generated require special techniques to accurately predict human activity and mitigate the considerable heterogeneity. Consequently, classic clustering algorithms do not work well with these data. Hence, kernelization, which converts the data into a new feature vector representation, is performed on nonlinearly separable data. This study aims to present a robust method to… More >

Özkan inik^1,∗, Erkan Ülker², ismail Koç²

Computer Systems Science and Engineering, Vol.35, No.6, pp. 431-440, 2020, DOI:10.32604/csse.2020.35.431

Abstract The location of knot points and estimation of the number of knots are undoubtedly known as one of the most difficult problems in B-Spline curve approximation. In the literature, different researchers have been seen to use more than one optimization algorithm in order to solve this problem. In this paper, Big Bang-Big Crunch method (BB-BC) which is one of the evolutionary based optimization algorithms was introduced and then the approximation of B-Spline curve knots was conducted by this method. The technique of reverse engineering was implemented for the curve knot approximation. The detection of knot More >

Morteza Okhovvat^1,∗, Mohsen Sharifi^2,†, Behrouz Minaei Bidgoli^2,‡

Computer Systems Science and Engineering, Vol.35, No.6, pp. 423-430, 2020, DOI:10.32604/csse.2020.35.423

Abstract The processing of any natural language requires that the grammatical properties of every word in that language are tagged by a part of speech (POS) tagger. To present a more accurate POS tagger for the Persian language, we propose an improved and accurate tagger called IAoM that supports properties of text to speech systems such as Lexical Stress Search, Homograph words Disambiguation, Break Phrase Detection, and main aspects of Persian morphology. IAoM uses Maximum Likelihood Estimation (MLE) to determine the tags of unknown words. In addition, it uses a few defined rules for the sake More >

Vankamamidi S. Naresh^1,∗,†, Suryateja S. Pericherla^2,‡, Pilla Sita Rama Murty^3,§, Sivaranjani Reddi^4,¶

Computer Systems Science and Engineering, Vol.35, No.6, pp. 411-421, 2020, DOI:10.32604/csse.2020.35.411

Abstract Healthcare, the largest global industry, is undergoing significant transformations with the genesis of a new technology known as the Internet of Things (IoT). Many healthcare leaders are investing more money for transforming their services to harness the benefits provided by IoT, thereby paving the way for the Internet of Medical Things (IoMT), an extensive collection of medical sensors and associated infrastructure. IoMT has many benefits like providing remote healthcare by monitoring health vitals of patients at a distant place, providing healthcare services to elderly people, and monitoring a large group of people in a region More >

Hai Yang Zhu^1,∗,†, Xiaobo Yin^1,∗,‡, Shunxiang Zhang^1,∗,§, Zhongliang Wei^1,¶, Guangli Zhu^1,II, Meng-Yen Hsieh^2,*,**

Computer Systems Science and Engineering, Vol.35, No.6, pp. 399-410, 2020, DOI:10.32604/csse.2020.35.399

Abstract A large number of new words in product reviews generated by mobile terminals are valuable indicators of the privacy preferences of customers. By clustering these privacy preferences, sufficient information can be collected to characterize users and provide a data basis for the research issues of privacy protection. The widespread use of mobile clients shortens the string length of the comment corpus generated by product reviews, resulting in a high repetition rate. Therefore, the effective and accurate recognition of new words is a problem that requires an urgent solution. Hence, in this paper, we propose a… More >

G. Ravikanth^1,∗, K. V. N. Sunitha^2,†, B. Eswara Reddy³

Computer Systems Science and Engineering, Vol.35, No.5, pp. 385-393, 2020

Abstract Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and single GPU. The errand… More >