Fingerprint Research Articles

Mother and Daughter Technique Using a Low-Profile Microcatheter for Navigating a Complete Radial Artery Loop

AbstractRadial loops are infrequent; however, they are a major cause for failure of radial access for procedure. Interventionists should be familiar with bail-out techniques when a radial loop is encountered to avoid spasm/injury. We describe our experience with two cases with 360 degrees radial loop in which we used low-profile microcatheter system to successfully complete the procedure

IoT Based Smart Attendance Management System

Abstract: This research work has application for attendance system of employer's and students in general. The system will facilitate institutions! organization to make attendance individual in time along with data information thumb impression will be taken as a signature for the system entry. Main design and challenge in this system is the design of database architecture and its business logic. I. AIMS AND OBJECTIVE The aim of this system is to implement in C#.net set of reliable techniques for fingerprint image enhancement and minutiae extraction. The performance of these techniques will be evaluated on a fingerprint data set. In combination with these development techniques, statistical experiments can then be performed on the fingerprint data set. The results from these experiments can be used to help us better understand what is involved in determining the statistical uniqueness of fingerprint minutiae. The main aim that this system would test whether attendance by fingerprint is enough for identification. It is expected that the work in this system will reach the stage of being able to fully test hypothesis. II. BACKGROUND/CONTEXT Fingerprints are the oldest form of biometric identification. Modem fingerprint-based identification is used in forensic science, and in biometric systems such as civilian identification devices. Keywords: the fingerprint data, statistical uniqueness of fingerprint minutiae.

BANK OF PASSWORDS: a secure Android password manager implemented based on specific requirements

Passwords serve as a vital means to safeguard our digital accounts. Many individuals resort to conventional methods like writing down passwords on paper or storing them on cloud services, often overlooking security risks, forgetting, and divulging is the most notable, which leads to loss of access to accounts, or potential breaches. In this paper, we propose the development of an Android application named "BANK OF PASSWORD" to address this issue. Our work focuses on creating a lightweight app equipped with essential functionalities desired by users, including password addition, updating, copying, searching, and deletion. To ensure the security of stored passwords, our approach incorporates various protective measures, such as access restriction through a login process and the utilization of SHA256 hashing and AES256 encryption for password encryption, where stored passwords are securely encrypted and stored as ciphertexts within an SQLite database. A fingerprint authentication was implemented as a second login method. Extensive testing of the application demonstrates the successful functioning of all proposed features and requirements on devices running API level 26 or above.

Finger Print and NFC Base Secure Authentication For Safe Lock

This paper proposes an idea on developing a Near Field Communication (NFC) Smart Lock System that utilizes a smart phone’s on-board NFC chip as a method to unlock a door. Access is regulated using a NFC Smart Card which runs a simple user interface that allows an Administrator to grant or deny entry to any particular user. The goal for this project was to give access to particular user. Access will be given to the user by using NFC Smart Card. Every NFC Smart Card contains Unique Identification (UID) Number, by using UID we grant or deny entry to user.

Metabolomic and chemometrics depict to understand the nutraceutical potential of different flaxseed varieties

Flaxseeds phytochemical and nutraceutical composition is influenced by climatic conditions that possibly impact flaxseed fingerprinting authentication. Therefore, this research aimed to discriminate flaxseeds phytochemical and nutraceutical value among eight different varieties (originating from China and Pakistan). Metabolomic fingerprint and chemometrics revealed discrimination among these varieties due to variations in fatty acids, amino acids, cyclic peptides, tocopherols, carotenoids, phenolics, and volatile compounds composition in flaxseeds. A discrimination model with p-value < 0.05 and VIP score >1 was propounded those different biomarkers such as γ-tocopherol, leutein, C18:3, Thr, Glu, 1-hexanol, 2-decenal, 1-octen-3-ol, and cyclic peptides content contribute to the discrimination of different flaxseeds varieties. Compared to RO and CH flaxseed varieties, HU, MO1, and MO2 primarily have higher total fatty acids, amino acids, tocopherols, carotenoids, and cyclic peptides. The present study significantly contributes to the quality fingerprinting of flaxseeds for food and pharmaceutical applications.

Role of doped ZnO variants for the development of latent fingerprint

Here we are presenting a promising approach for the green synthesis of zinc oxide (ZnO) nanomaterials by using lemon grass with minimal environmental impact. The fabricated zinc oxide (ZnO) doped with different dyes ranging from 25 −100 nm were applied to read the minutiae points of finger prints that can lead for person identification. In this model project, we doped different dyes on ZnO and used for the development of latent finger prints on different surfaces and at time duration (1 h to 24 h). The linkage between nanomaterials and fingerprint residues is among oxide group and amine group. We presented that these designed materials have the ability to develop fingerprints on variety of substrates. We displayed that with the passing of time the chroma index and intensity reduce but still at 24 h we can read the minutiae details. This research opens a new era to enhance and quantifying contrast between surface and applied material.

Dermatoglyphic Phenotype in Patients with Cardiovascular Disease

Introduction. Since the predisposition to develop cardiovascular disease is genetically determined, it can be assumed that there are phenotypic features (in particular, dermatoglyphic) that allow predicting the predisposition to develop acute myocardial infarction (MI).&#x0D; The aim of the study was to determine the dermatoglyphic phenotype in patients with myocardial infarction.&#x0D; Materials and methods. The object of the study was dermatoglyphs of distal phalanges of the fingers obtained from 60 male subjects (30 patients with myocardial infarction and 30 healthy men without cardiovascular pathology as a control group). The dermatoglyphic method and the method of statistical analysis were used.&#x0D; Results. It was found that patients with MI had a higher frequency of curl patterns, but a lower frequency of ulnar and radial loops and arc patterns compared to the control group. The value of the comb count in patients with MI was lower than in the control group (p&gt;0.05). The total comb count of the palmar fields a-b, c-d was higher, and the fields b-c were lower in patients with MI than in the control group. The mean value of the angle Аtd on both hands was higher in patients with MI than in the control group. Palm patterns and folds showed no significant differences between the groups.&#x0D; Conclusions&#x0D; The results of this study can be used to standardize the dermatoglyphic pattern of the Ukrainian population and identify individuals prone to MI.

Synthesis, crystal structure investigation and computational studies binding of (7S,8R)-7-acetyl-8-(4-chlorophenyl)-3-(ethylthio)-1,6-dimethyl-7,8-dihydroisoquinoline-4-carbonitrile with monoamine oxidase B

This work reports the preparation of a new dihydroisoquinoline derivative whose structure was characterized by IR, NMR (1H, 13C), MS and verified through single-crystal X-ray analysis. The mean planes of the acetyl and 4-chlorophenyl groups in the title molecule are nearly perpendicular to that of the pyridine ring. In the crystal, π-stacking and C—H···O hydrogen bond interactions involving the pyridine ring and the nitrile group of an adjacent molecule form the full 3-D structure. Hirshfeld surface (HS) analysis shows the topology of the molecules in the crystal packing. Fingerprint (FP) diagrams show the percentage contribution of several intermolecular interactions where H‧‧‧H interactions have a significant contribution (46%). The DFT study reveals a low HOMO-LUMO gap and significant charge transfer is indicated by the natural bonding orbitals (NBO) and frontier molecular orbital (FMO) analyses. Non-covalent interactions and bond characteristics were investigated using the quantum theory of atom in the molecule (QTAIM) and ELF analysis. FMO analysis was used to calculate the HOMO-LUMO energy gap and orbital energies. Using the DFT method, parameters such as global reactivity were calculated. Using the implicit solvent model, properties such as optical and nonlinear optical (NLO) were characterized in the solvent (water) phase and gas phase. The affinity of the title molecule for Monoamine Oxidase B was examined using molecular docking and molecular dynamics studies and these results showed good binding of the target molecule.

EarSlide

Ear wearables (earables) are emerging platforms that are broadly adopted in various applications. There is an increasing demand for robust earables authentication because of the growing amount of sensitive information and the IoT devices that the earable could access. Traditional authentication methods become less feasible due to the limited input interface of earables. Nevertheless, the rich head-related sensing capabilities of earables can be exploited to capture human biometrics. In this paper, we propose EarSlide, an earable biometric authentication system utilizing the advanced sensing capacities of earables and the distinctive features of acoustic fingerprints when users slide their fingers on the face. It utilizes the inward-facing microphone of the earables and the face-ear channel of the ear canal to reliably capture the acoustic fingerprint. In particular, we study the theory of friction sound and categorize the characteristics of the acoustic fingerprints into three representative classes, pattern-class, ridge-groove-class, and coupling-class. Different from traditional fingerprint authentication only utilizes 2D patterns, we incorporate the 3D information in acoustic fingerprint and indirectly sense the fingerprint for authentication. We then design representative sliding gestures that carry rich information about the acoustic fingerprint while being easy to perform. It then extracts multi-class acoustic fingerprint features to reflect the inherent acoustic fingerprint characteristic for authentication. We also adopt an adaptable authentication model and a user behavior mitigation strategy to effectively authenticate legit users from adversaries. The key advantages of EarSlide are that it is resistant to spoofing attacks and its wide acceptability. Our evaluation of EarSlide in diverse real-world environments with intervals over one year shows that EarSlide achieves an average balanced accuracy rate of 98.37% with only one sliding gesture.

Solar and Dynamo Powered Ev Using Fingerprint Authentication

Nonrenewable energy sources are already interfering with the availability of electricity. Today, the primary emphasis is on the generation of electricity from renewable sources. This proposal proposes a feasible design solution in the shape of a user-friendly three-wheeler. A fingerprint-accessible electric vehicle. This electric vehicle uses solar power and a self-changing dynamo to charge its battery. The battery serves as the vehicle's power source. A microcontroller serves as the system's primary controller. It is connected to a fingerprint module, a relay, the car ignition, and an LCD. The Microcontroller reads the input from the fingerprint module and, if it is legitimate, grants access to the ignition system. The status will be displayed on the LCD. In addition, we're adding three more sensors: speed, temperature, and voltage. Lithium-ion batteries can be harmful if not used within the safety-operated area (SOA). To avoid this, we calculate the temperature of the lithium-ion battery when it exceeds 49.9?. It will make a sound through the buzzer. This can prevent damage to the battery and the person driving the vehicle. Voltage Sensor is designed to monitor battery charging and discharging time, which is displayed on the LCD. A speed sensor is used to determine the speed of the vehicle.

CADFA: A Clock Skew-Based Active Device Fingerprint Authentication Scheme for Class-1 IoT Devices

CADFA: A Clock Skew-Based Active Device Fingerprint Authentication Scheme for Class-1 IoT Devices

Physicochemical characterization, Phytochemical analysis and Anti-microbial activity of Elathy mathirai

Elathy Mathirai is a Siddha herbomineral formulation indicated to cure sori(itching), sirangu(Scabies), suram(fever), vaayu, maandham(gastro intestinal disorder) . The aim of the study is to standardize Elathy Mathirai to ensure its quality, purity and safety through its physicochemical, chromatographic, phytochemical, heavy metal, pesticide residue and aflatoxins analysis and the secondary objective is to evaluate its antimicrobial property. This study determines the physicochemical paramaters that are loss on drying, total ash, acid insoluble ash, water soluble extractive, alcohol soluble extractive and pH as 5.667% , 5%, 0.014 %, 14.93 %, 8.3% and 5.6 respectively denotes purity and quality of the drug. From the study results it is ensured that the test drug Elathy mathirai is free from pesticide toxicity and aflatoxins. Qualitative preliminary phytochemical analysis shows the presence of alkaloids, Flavanoids,steroids, triterpenoids, saponins, coumarins, phenol, tannin, sugar and betacyanin. HPTLC finger printing analysis reveals the presence of seven prominent peaks Rf value ranges from 0.04 to 0.39 corresponds to the presence of seven components present within it. It was observed from the results of In vitro anti microbial assay that the formulation EM reveals significant level of activity against bacteria Klebsiella pneumonia and observed moderate activity against Staphylococcal aureus, Pseudomonas aeruginosa and posess consistent anti fungal activity against Candida albicans and there is no significant effect on Aspergillus niger. The obtained results shows that the EM complies with the regulatory standard and also possess significant anti microbial property against the tested microbes.

Rubik's Encryption Combined with CNN for Biometric Authentication

In response to the rapid evolution of technology, safeguarding user data has become paramount, necessitating a robust solution against diverse cyber threats. This research project proposes a comprehensive approach that integrates biometric authentication, specifically iris and fingerprint recognition, with a sophisticated encryption system based on Rubik's Cube and facilitated by Convolutional Neural Networks (CNNs). Biometric authentication establishes an unassailable link between data records and individuals, ensuring heightened accuracy and security. To counter potential threats, the project incorporates a resilient technique known as zero-bit watermarking, embedding minimal information without compromising the original biometric data's size or quality. The integration of Rubik's Cube-based encryption adds an additional layer of complexity to data protection, employing a dynamic and visually intricate encryption algorithm. The amalgamation of iris and fingerprint authentication leverages the unique biological characteristics of individuals, creating a multi-layered security approach. The CNNs play a pivotal role as the backbone for efficient feature extraction and authentication decision-making, enhancing the overall system's accuracy and reliability. This innovative fusion of cryptographic methods and biometric authentication offers a comprehensive solution for safeguarding sensitive information across diverse applications, from secure data storage to fortified communication channels, addressing the evolving landscape of cybersecurity challenges.

Comparative Analysis of Dermatoglyphic Traits in Albanian and Roma Populations in Kosovo

We examined dermatoglyphics of children in three Albanian and one Roma population sample (collected from 641 individuals from the Albanian populations and 226 individuals from the Roma population of both sexes). We compared Albanian and Roma populations based on four finger (whorl, radial and ulnar loop, and arch) and thirteen palmar traits (pattern frequencies in the Thenar/I interdigital area, II, III, and IV interdigital area, Hypothenar and axial »t« triradius position). The differences between the populations were more evident for palmar traits. In our study the Albanian and the Roma populations showed the best separation when finger and palmar traits are separately analyzed. As expected, the Albanian and the Roma populations separated in statistical analyses of most traits; the main reason for this is the different origins of two ethnic groups. The observed difference also indicates a low level of admixture between the Albanians and the Roma despite them living beside one another for several centuries.

The fourth species of Leptobrachella (Anura, Megophryidae) found at Shiwandashan National Nature Reserve, Guangxi, China.

A new species of the genus Leptobrachella, L.guinanensissp. nov., is described in this study based on morphological, molecular, and bioacoustic data. The species was discovered in the Shiwandashan National Nature Reserve in Shangsi County, Guangxi, China. Phylogenetically, L.guinanensissp. nov. is closely related to L.ventripunctata. However, there are distinct morphological differences between L.guinanensissp. nov. and L.ventripunctata, as well as three other sympatric species (L.shangsiensis, L.shiwandashanensis, and L.sungi). These differences include body size (SVL 30.5-32.5 mm in males; 38.7-41.8 mm in females in the new species vs 25.5-28.0 mm in males, 31.5-35.0 mm in females in L.ventripunctata), the absence of brown spots on the ventral surface (vs chest and belly creamy white with many scattered brown spots in L.ventripunctata), 1/3 toe webbing and wide toe lateral fringes (vs no toe webbing and no lateral fringes in L.ventripunctata), and distinct dermal ridges under toes (vs absent in L.ventripunctata). Furthermore, the dominant vocal frequencies of the new species range from 7.3 to 8.3 kHz, which is unique compared to other Leptobrachella species and represents the highest dominant frequencies ever recorded. The Shiwandashan National Nature Reserve is now home to four known sympatric species of Leptobrachella.

Nudging safety behavior in the steel industry: Evidence from two field studies

The practice of nudging received much attention in different domains of human behaviour (e.g. finance, health, traffic safety and sustainability), but its relevance has not been systematically investigated for safety in the process industry. This study aimed to investigate the effectiveness of nudge interventions in promoting safety behavior in the steel industry through field experiments in a large steel plant, particularly in relation to gas hazards and falling from stairs The results of both experiments showed that the nudge interventions were very effective in promoting safety behavior among workers. An icon reminding of the gas dangers on work jackets effectively increased gas detector compliance, while hand print cues were able to promote workers holding onto handrails. Related organizational implications for a safety nudging approach are discussed. Overall, these findings suggest that nudge interventions can be a cost-effective approach to promote safety behavior in the steel industry. The suggested nudge framework should be implemented as part of a holistic safety approach to promote safety behavior among workers and prevent severe accidents.

Fingerprint Based Blood Group using Deep Learning

Fingerprints are said to be the most accurate means of identifying an individual. In a court of law, fingerprint evidence is by far the most efficient and trustworthy type of evidence. Two key factors that demonstrate the effectiveness of finger prints are that the ridges that form during fetal development remain aligned throughout an individual's life until the skin decomposes, and that no two finger prints—those of the same person or two different people—are ever the same; they always differ in terms of pattern and ridge characteristics. Due to this unique attribute of finger print, it is widely considered as conclusive evidence in the court of law. This study presents an innovative methodology for the identification of blood groups by utilizing fingerprints and advanced machine learning techniques. Fingerprint patterns, renowned for their distinctiveness and enduring nature, serve as a significant biometric identifier. In this investigation, Convolutional Neural Networks (CNNs), a specific category of advanced machine learning, are utilized to extract intricate characteristics from fingerprint images in order to forecast blood groups.

SMA Kosgoro Bogor's Student Attendance Accountability Through Finger Print That Led to Appreciation

SMA Kosgoro Bogor uses fingerprint technology as a tool to improve accountability of student attendance and monitoring. The implementation of fingerprint technology has enabled the school to have detailed and automated information about student attendance. This article aims to explain how the use of the fingerprint system at SMA Kosgoro Bogor can improve student attendance accountability. The method used in this research is a descriptive qualitative method that produces descriptive data in the form of written or oral observations of people and observable behaviour. The data source of this research uses primary data sources and secondary data. The research subjects were all students of SMAS Kosgoro Bogor. One form of appreciation given is the provision of free tuition scholarships at the beginning of each month that meets predetermined criteria, such as consistent daily attendance, recorded in the school attendance system, designated as a nominee by the homeroom teacher, active in extracurricular activities, speaking well, and behaving politely.

Multimodal Biometric Login System Using Face and Signature

Biometrics has developed to be one of the most relevant technologies used in Information Technology (IT) security. Uni-modal biometric systems have a variety of problems which decreases the performance and accuracy of these systems. One way to overcome the limitations of the Unimodal biometric systems is through fusion to form a multimodal biometric system. Hence this process is developed based on Multimodal Biometric system based on Face, Finger print, Signature etc. Multimodal biometric system employing Convolutional Neural Networks (CNNs) for effective feature extraction and classification. The system combines facial and signature biometrics, harnessing the unique advantages of each modality to create a more resilient and accurate authentication framework. Multimodal biometric system with CNN integration holds promise for applications in secure access control, financial transactions, and other domains where reliable authentication is crucial. Its adaptability and scalability make it a viable solution for addressing the evolving challenges in biometric security systems. Key Word: Unimodal biometric system , Multimodal Biometric system , Convolutional Neural Networks (CNNs),deep learning.

The Influence of Organizational Behavior and Finger Print Technology on Employee Work Discipline at The Palopo City Land Office

Purpose: The aim of this research is that researchers want to determine whether organizational behavior and fingerprint technology influence the work discipline at the Palopo City Land Office.&#x0D; Research methodology: Quantitative methods were used in this study. This research was conducted at the Palopo City Land Office between October and November 2023. Data were obtained by distributing questionnaires to 80 respondents. The collected data were tested using multiple linear regression analysis with SPSS statistics application program version 20 to test two or more independent variables against the dependent variable.&#x0D; Results: From the results of the T test, it is proven that the organizational behavior variable has a partial effect on work discipline at the Palopo City Land Office, and that the fingerprint technology variable has a partial effect on work discipline at the Palopo City Land Office. The test results from this research show that fcount &gt; Fiable or 117,552 3.11, with a significance value of 0.001 &lt; 0.05, can be said to be significant because this proves that organizational behavior and fingerprint technology have a positive effect on work discipline.&#x0D; Implementation: Thus, it can be concluded that all independent variables in this research work together or simultaneously on the dependent variable. The coefficient of determination in this study was also 0.753 or 75.3%, which shows that organizational behavior and fingerprint technology can influence changes in work discipline, while the remaining 24.7% is explained by other factors outside of this research.