Yanyan Han^1,2, Jiangping Yu³, Guangyu Hu⁴, Chenglei Pan⁴, Dingbang Xie⁵, Chao Guo^1,2,6,*, Abdul Waheed⁷

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4789-4802, 2022, DOI:10.32604/cmc.2022.027496

Abstract Verifiable secret sharing mainly solves the cheating behavior between malicious participants and the ground control center in the satellite network. The verification stage can verify the effectiveness of secret shares issued by the ground control center to each participant and verify the effectiveness of secret shares shown by participants. We use a lot of difficult assumptions based on mathematical problems in the verification stage, such as solving the difficult problem of the discrete logarithm, large integer prime factorization, and so on. Compared with other verifiable secret sharing schemes designed for difficult problems under the same security, the verifiable secret sharing… More >

Sha Li^1,2, Qiao Meng^1,*, Irfan Tariq¹, Xi Chen³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6079-6090, 2022, DOI:10.32604/cmc.2022.027404

Abstract This article presents a high speed third-order continuous-time (CT) sigma-delta analog-to-digital converter (SDADC) based on voltage-controlled oscillator (VCO), featuring a digital programmable quantizer structure. To improve the overall performance, not only oversampling technique but also noise-shaping enhancing technique is used to suppress in-band noise. Due to the intrinsic first-order noise-shaping of the VCO quantizer, the proposed third-order SDADC can realize forth-order noise-shaping ideally. As a bright advantage, the proposed programmable VCO quantizer is digital-friendly, which can simplify the design process and improve anti-interference capability of the circuit. A 4-bit programmable VCO quantizer clocked at 2.5 GHz, which is proposed in a… More >

Li Xu^1,2,*, Ruzhen Lou¹, Chuanbin Zhang¹, Bo Lang³, Weiyue Ding⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4489-4507, 2022, DOI:10.32604/cmc.2022.027400

Abstract In the heavy clutter environment, the information capacity is large, the relationships among information are complicated, and track initiation often has a high false alarm rate or missing alarm rate. Obviously, it is a difficult task to get a high-quality track initiation in the limited measurement cycles. This paper studies the multi-target track initiation in heavy clutter. At first, a relaxed logic-based clutter filter algorithm is presented. In the algorithm, the raw measurement is filtered by using the relaxed logic method. We not only design a kind of incremental and adaptive filtering gate, but also add the angle extrapolation based… More >

Jaber S. Alzahrani¹, Reem M. Alshehri², Mohammad Alamgeer³, Anwer Mustafa Hilal^4,*, Abdelwahed Motwakel⁴, Ishfaq Yaseen⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4267-4281, 2022, DOI:10.32604/cmc.2022.027369

Abstract Recently, medical data classification becomes a hot research topic among healthcare professionals and research communities, which assist in the disease diagnosis and decision making process. The latest developments of artificial intelligence (AI) approaches paves a way for the design of effective medical data classification models. At the same time, the existence of numerous features in the medical dataset poses a curse of dimensionality problem. For resolving the issues, this article introduces a novel feature subset selection with artificial intelligence based classification model for biomedical data (FSS-AICBD) technique. The FSS-AICBD technique intends to derive a useful set of features and thereby… More >

Mua’ad Abu-Faraj^1,*, Abeer Al-Hyari², Ziad Alqadi³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5699-5712, 2022, DOI:10.32604/cmc.2022.027364

Abstract Predicting the value of one or more variables using the values of other variables is a very important process in the various engineering experiments that include large data that are difficult to obtain using different measurement processes. Regression is one of the most important types of supervised machine learning, in which labeled data is used to build a prediction model, regression can be classified into three different categories: linear, polynomial, and logistic. In this research paper, different methods will be implemented to solve the linear regression problem, where there is a linear relationship between the target and the predicted output.… More >

Xingjian Xue^1,*, Linjuan Ge², Longxin Zeng², Weiran Li², Rui Song², Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5135-5148, 2022, DOI:10.32604/cmc.2022.027356

Abstract To study riding safety at intersection entrance, video recognition technology is used to build vehicle-bicycle conflict models based on the Bayesian method. It is analyzed the relationship among the width of non-motorized lanes at the entrance lane of the intersection, the vehicle-bicycle soft isolation form of the entrance lane of intersection, the traffic volume of right-turning motor vehicles and straight-going non-motor vehicles, the speed of right-turning motor vehicles, and straight-going non-motor vehicles, and the conflict between right-turning motor vehicles and straight-going non-motor vehicles. Due to the traditional statistical methods, to overcome the discreteness of vehicle-bicycle conflict data and the differences… More >

Mohammed Hadwan^1,2,3,*, Mohammed A. Al-Hagery⁴, Mohammed Al-Sarem⁵, Faisal Saeed^5,6

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4675-4689, 2022, DOI:10.32604/cmc.2022.027311

Abstract Different types of pandemics that have appeared from time to time have changed many aspects of daily life. Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown. The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store. A huge number of reviews are written daily by users to express their opinions, which include significant information to improve these applications. The manual processing and extracting of information from users’ reviews is an… More >

Hatice Jenkins¹, Siamand Hesami^1,*, Fulden Yesiltepe²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6167-6184, 2022, DOI:10.32604/cmc.2022.027293

Abstract This research investigates a broad range of possible factors affecting the adoption of new technology in the banking industry using adaptive LASSO and a standard logit model. The research integrated the adoption of the innovation framework and the technology acceptance theory to develop a conceptual framework for the analysis. Primary data was collected from 400 bank customers in North Cyprus. Risk perception and other customer-specific factors such as perceived risk index and negative attitude toward new technologies index were formulated for the proposed conceptual model. The findings indicated that individuals with a negative attitude toward new technology are least likely… More >

Yangqun Li^1,2,*, Jin Qi^1,2, Lijuan Min^1,2, Hongzhi Yang^1,2, Chenyang Zhou^1,2, Bonan Jin³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5079-5098, 2022, DOI:10.32604/cmc.2022.027281

Abstract Web of Things (WoT) resources are not only numerous, but also have a wide range of applications and deployments. The centralized WoT resource sharing mechanism lacks flexibility and scalability, and hence cannot satisfy requirement of distributed resource sharing in large-scale environment. In response to this problem, a trusted and secure mechanism for WoT resources sharing based on context and blockchain (CWoT-Share) was proposed. Firstly, the mechanism can respond quickly to the changes of the application environment by dynamically determining resource access control rules according to the context. Then, the flexible resource charging strategies, which reduced the fees paid by the… More >

S. Prabha Kumaresan¹, Chee Keong Tan^2,*, Yin Hoe Ng¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6119-6140, 2022, DOI:10.32604/cmc.2022.027223

Abstract Non-orthogonal multiple access (NOMA) has been a key enabling technology for the fifth generation (5G) cellular networks. Based on the NOMA principle, a traditional neural network has been implemented for user clustering (UC) to maximize the NOMA system’s throughput performance by considering that each sample is independent of the prior and the subsequent ones. Consequently, the prediction of UC for the future ones is based on the current clustering information, which is never used again due to the lack of memory of the network. Therefore, to relate the input features of NOMA users and capture the dependency in the clustering… More >