R. Ani^1,*, O. S. Deepa², B. R. Manju¹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3033-3048, 2023, DOI:10.32604/csse.2023.033807 - 09 November 2023

Abstract The drug development process takes a long time since it requires sorting through a large number of inactive compounds from a large collection of compounds chosen for study and choosing just the most pertinent compounds that can bind to a disease protein. The use of virtual screening in pharmaceutical research is growing in popularity. During the early phases of medication research and development, it is crucial. Chemical compound searches are now more narrowly targeted. Because the databases contain more and more ligands, this method needs to be quick and exact. Neural network fingerprints were created… More >

Hyeon Park¹, SeoYeon Kim², Seok Min Ko¹, TaeGuen Kim^2,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1891-1909, 2023, DOI:10.32604/cmc.2023.039464 - 30 August 2023

Abstract The rapid growth of modern vehicles with advanced technologies requires strong security to ensure customer safety. One key system that needs protection is the passive key entry system (PKES). To prevent attacks aimed at defeating the PKES, we propose a novel radio frequency (RF) fingerprinting method. Our method extracts the cepstral coefficient feature as a fingerprint of a radio frequency signal. This feature is then analyzed using a convolutional neural network (CNN) for device identification. In evaluation, we conducted experiments to determine the effectiveness of different cepstral coefficient features and the convolutional neural network-based model. More >

Amira Tarek Mahmoud^1,*, Wael A. Awad², Gamal Behery², Mohamed Abouhawwash^3,4, Mehedi Masud⁵, Hanan Aljuaid⁶, Ahmed Ismail Ebada⁷

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2007-2023, 2023, DOI:10.32604/iasc.2023.031692 - 05 January 2023

Abstract The accuracy of fingerprint recognition model is extremely important due to its usage in forensic and security fields. Any fingerprint recognition system has particular network architecture whereas many other networks achieve higher accuracy. To solve this problem in a unified model, this paper proposes a model that can automatically specify itself. So, it is called an automatic deep neural network (ADNN). Our algorithm can specify the appropriate architecture of the neural network used and some significant parameters of this network. These parameters are the number of filters, epochs, and iterations. It guarantees the highest accuracy… More >

Yun Fen Yong^1,*, Chee Keong Tan¹, Ian Kim Teck Tan², Su Wei Tan¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1801-1818, 2023, DOI:10.32604/cmc.2023.032710 - 22 September 2022

Abstract A robust radio map is essential in implementing a fingerprint-based indoor positioning system (IPS). However, the offline site survey to manually construct the radio map is time-consuming and labour-intensive. Various interpolation techniques have been proposed to infer the virtual fingerprints to reduce the time and effort required for offline site surveys. This paper presents a novel fingerprint interpolator using a multi-path loss model (M-PLM) to create the virtual fingerprints from the collected sample data based on different signal paths from different access points (APs). Based on the historical signal data, the poor signal paths are… More >

Saif Saad Hameed, Ismail Taha Ahmed^*, Omar Munthir Al Okashi

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 327-340, 2023, DOI:10.32604/cmc.2023.031622 - 22 September 2022

Abstract Biometric recognition refers to the identification of individuals through their unique behavioral features (e.g., fingerprint, face, and iris). We need distinguishing characteristics to identify people, such as fingerprints, which are world-renowned as the most reliable method to identify people. The recognition of fingerprints has become a standard procedure in forensics, and different techniques are available for this purpose. Most current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification models. Therefore, we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and… More >

Edgar Scavino^1,*, Mohd Amiruddin Abd Rahman¹, Zahid Farid²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 379-397, 2023, DOI:10.32604/cmc.2023.023824 - 22 September 2022

Abstract Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting… More >

Zhiguo Lu¹, Yuhong Zheng^1,*, Pengchong Zhang², Boyuan Fan³, Aimin Yu⁴, Li Fu^3,*

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2549-2558, 2022, DOI:10.32604/phyton.2022.021288 - 12 July 2022

Abstract In this communication, we used electrochemical sensor for recording the electrochemical profiles of eleven species of Yulania spp. from leaf extract. Two solvents and two buffer conditions were used for electrochemical fingerprints collection. Their electrochemical fingerprints can be converted to different patterns and consequently for species recognition. The results indicate the pattern recognition is much convenient than that of the recognition of species directly using voltammetric signal. The current information in electrochemical fingerprinting represents the type and amount of electrochemically active molecules, which linked to the genetic differences among the plants. Therefore, the electrochemical fingerprints were More >

Jie Chen¹, Chengsheng Yuan^1,2,*, Chen Cui², Zhihua Xia¹, Xingming Sun^1,3, Thangarajah Akilan⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 719-733, 2022, DOI:10.32604/cmc.2022.027984 - 18 May 2022

Abstract Fingerprint identification systems have been widely deployed in many occasions of our daily life. However, together with many advantages, they are still vulnerable to the presentation attack (PA) by some counterfeit fingerprints. To address challenges from PA, fingerprint liveness detection (FLD) technology has been proposed and gradually attracted people's attention. The vast majority of the FLD methods directly employ convolutional neural network (CNN), and rarely pay attention to the problem of over-parameterization and over-fitting of models, resulting in large calculation force of model deployment and poor model generalization. Aiming at filling this gap, this paper… More >

A. S. Anakath^1,*, S. Ambika², S. Rajakumar³, R. Kannadasan⁴, K. S. Sendhil Kumar⁵

Computer Systems Science and Engineering, Vol.43, No.2, pp. 833-847, 2022, DOI:10.32604/csse.2022.022329 - 20 April 2022

Abstract Cloud computing becomes an important application development platform for processing user data with high security. Service providers are accustomed to providing storage centers outside the trusted location preferred by the data owner. Thus, ensuring the security and confidentiality of the data while processing in the centralized network is very difficult. The secured key transmission between the sender and the receiver in the network is a huge challenge in managing most of the sensitive data transmission among the cloud network. Intruders are very active over the network like real authenticated user to hack the personal sensitive… More >

Yuhao Chen¹, Jiajun Liu¹, Yaxi Peng¹, Ziyi Liu², Zhipeng Yang^1,*

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1501-1516, 2022, DOI:10.32604/iasc.2022.026346 - 24 March 2022

Abstract As a neural fingerprint, functional connectivity networks (FCNs) have been used to identify subjects from group. However, a number of studies have only paid attention to cerebral cortex when constructing the brain FCN. Other areas of the brain also play important roles in brain activities. It is widely accepted that the human brain is composed of many highly complex functional networks of cortex. Moreover, recent studies have confirmed correlations between signals of cortex and white matter (WM) bundles. Therefore, it is difficult to reflect the functional characteristics of the brain through a single-layer FCN. In… More >