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1
Anshari, Muhammad, Mitra istiar Wardhana, and Dhara Alim Cendekia. "Visual Login Fingerprints Scanner Aplikasi Mobile Banking (BRImo, Jenius, BNI Mobile Banking) berdasarkan Model Kait Nir Eyal." JoLLA: Journal of Language, Literature, and Arts 3, no. 8 (August 31, 2023): 1198–216. http://dx.doi.org/10.17977/um064v3i82023p1198-1216.
Повний текст джерелаАнотація:
Fitur fingerprint scanner cenderung lebih sering digunaakan secara repetitif untuk login pada aplikasi perbankan karena dianggap lebih cepat dan mudah. Anggapan ini juga terlihat dari sedikitnya usaha kognitif pada proses pencarian tombol fingerprint scanner. Tombol fingerprint scanner aplikasi BRImo, BNI Mobile Banking dan Jenius cenderung menjadi kontras serta halaman login didesain untuk mengarahkan pengguna pada fitur tersebut. Berdasarkan kebiasaan repetitif penggunaan fingerprint scanner dan aspek visual yang mengarahkan pengguna ke fingerprint scanner penelitaia ini menggunakan model kait untuk menguraikan cara visual fitur tersebut berefek pada penggunaan yang repetitif ketika. Hasil dari penelitian ini menyebutkan bahawa aplikasi BRImo yang menggunakan kontras visual pada tombol fingerprint scanner yang juga secara implisit memberikan kontras secara fungsi pada tombol disekitarya bila ditinjau berdasarkan model kait bisa memicu pengguna untuk menekan tombol tersebut secara repetitif. Kata kunci: model Kait; aplikasi perbankan; fingerprint scanner Visual Login Fingerprints Scanner for Mobile Banking Applications (BRImo, Jenius, BNI Mobile Banking) based on the Kait Nir Eyal Model The fingerprint scanner feature tends to be used repeatedly to log in to banking applications because it is considered faster and easier. This assumption is also seen from the lack of cognitive effort in the process of searching for the fingerprint scanner button. The fingerprint scanner buttons for the BRImo, BNI Mobile Banking and Jenius applications tend to be in contrast and the login page is designed to direct users to these features. Based on the repetitive habit of using fingerprint scanners and the visual aspects that direct users to the fingerprint scanner, this study uses a hook model to describe how visually these features have an effect on repetitive use. The results of this study indicate that the BRImo application that uses visual contrast on the fingerprint scanner button which also implicitly provides functional contrast to the surrounding buttons when viewed based on the latch model can trigger the user to press the button repeatedly. Keywords: Kait model; internet banking; fingerprint scanner
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Zhang, Huiqing, and Yueqing Li. "LightGBM Indoor Positioning Method Based on Merged Wi-Fi and Image Fingerprints." Sensors 21, no. 11 (May 25, 2021): 3662. http://dx.doi.org/10.3390/s21113662.
Повний текст джерелаАнотація:
Smartphones are increasingly becoming an efficient platform for solving indoor positioning problems. Fingerprint-based positioning methods are popular because of the wide deployment of wireless local area networks in indoor environments and the lack of model propagation paths. However, Wi-Fi fingerprint information is singular, and its positioning accuracy is typically 2–10 m; thus, it struggles to meet the requirements of high-precision indoor positioning. Therefore, this paper proposes a positioning algorithm that combines Wi-Fi fingerprints and visual information to generate fingerprints. The algorithm involves two steps: merged-fingerprint generation and fingerprint positioning. In the merged-fingerprint generation stage, the kernel principal component analysis feature of the Wi-Fi fingerprint and the local binary pattern features of the scene image are fused. In the fingerprint positioning stage, a light gradient boosting machine (LightGBM) is trained with mutually exclusive feature bundling and histogram optimization to obtain an accurate positioning model. The method is tested in an actual environment. The experimental results show that the positioning accuracy of the LightGBM method is 90% within a range of 1.53 m. Compared with the single-fingerprint positioning method, the accuracy is improved by more than 20%, and the performance is improved by more than 15% compared with other methods. The average locating error is 0.78 m.
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Popov, Vladimir. "The Problem of Selection of Fingerprints for Topological Localization." Applied Mechanics and Materials 365-366 (August 2013): 946–49. http://dx.doi.org/10.4028/www.scientific.net/amm.365-366.946.
Повний текст джерелаАнотація:
Visual navigation is extensively used in contemporary robotics. In particular, we can mention different systems of visual landmarks. In this paper, we consider one-dimensional color panoramas. Panoramas can be used for creating fingerprints. Fingerprints give us unique identifiers for visually distinct locations by recovering statistically significant features. Fingerprints can be used as visual landmarks for mobile robot navigation. In this paper, we consider a method for automatic generation of fingerprints. Since a fingerprint is a circular string, different string-matching algorithms can be used for selection of fingerprints. In particular, we consider the problem of finding the consensus of circular strings under the Hamming distance metric.
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Luda, M. P., N. Li Pira, D. Trevisan, and V. Pau. "Evaluation of Antifingerprint Properties of Plastic Surfaces Used in Automotive Components." International Journal of Polymer Science 2018 (November 28, 2018): 1–11. http://dx.doi.org/10.1155/2018/1895683.
Повний текст джерелаАнотація:
The antifingerprint properties of a range of surfaces produced with different technologies (in-mould decoration, in-mould labeling, and painted) were objectively evaluated by depositing on them in standard conditions an artificial fingerprint for direct determination of its visibility. The artificial fingerprint behaves similarly to the real human fingerprints. A classification method is then proposed to classify surfaces on the base of antifingerprint properties by measuring the roughness profile (Ra) and calculating the % variation of gloss (GU 20 and 60°), haze, luminance (L), and diffuse reflectance (R) values after fingerprint deposition. This approach provides an objective and quantitative test method to determine visual antifingerprint properties of coated surfaces, instead of the “easy-to-clean” properties commonly evaluated. The data acquired provides a design guideline for fabricating visually fingerprint-free surfaces by controlling roughness, texture, color, and transparency of surfaces, with the aim of optically masking fingerprints.
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Shams, Haroon, Tariqullah Jan, Amjad Ali Khalil, Naveed Ahmad, Abid Munir, and Ruhul Amin Khalil. "Fingerprint image enhancement using multiple filters." PeerJ Computer Science 9 (January 3, 2023): e1183. http://dx.doi.org/10.7717/peerj-cs.1183.
Повний текст джерелаАнотація:
Biometrics is the measurement of an individual’s distinctive physical and behavioral characteristics. In comparison to traditional token-based or knowledge-based forms of identification, biometrics such as fingerprints, are more reliable. Fingerprint images recorded digitally can be affected by scanner noise, incorrect finger pressure, condition of the finger’s skin (wet, dry, or abraded), or physical material it is scanned from. Image enhancement algorithms applied to fingerprint images remove noise elements while retaining relevant structures (ridges, valleys) and help in the detection of fingerprint features (minutiae). Amongst the most common image enhancement filters is the Gabor filter, however, given their restricted maximum bandwidth as well as limited range of spectral information, it falls short. We put forward a novel method of fingerprint image enhancement using a combination of a diffusion-coherence filter and a 2D log-Gabor filter. The log-Gabor overcomes the limitations of the Gabor filter while Coherence Diffusion mitigates noise elements within fingerprint images. Implementation is done on the FVC image database and assessed via visual comparison with coherence diffusion used disjointedly and with the Gabor filter.
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Zabala-Blanco, David, Marco Mora, Ricardo J. Barrientos, Ruber Hernández-García, and José Naranjo-Torres. "Fingerprint Classification through Standard and Weighted Extreme Learning Machines." Applied Sciences 10, no. 12 (June 15, 2020): 4125. http://dx.doi.org/10.3390/app10124125.
Повний текст джерелаАнотація:
Fingerprint classification is a stage of biometric identification systems that aims to group fingerprints and reduce search times and computational complexity in the databases of fingerprints. The most recent works on this problem propose methods based on deep convolutional neural networks (CNNs) by adopting fingerprint images as inputs. These networks have achieved high classification performances, but with a high computational cost in the network training process, even by using high-performance computing techniques. In this paper, we introduce a novel fingerprint classification approach based on feature extractor models, and basic and modified extreme learning machines (ELMs), being the first time that this approach is adopted. The weighted ELMs naturally address the problem of unbalanced data, such as fingerprint databases. Some of the best and most recent extractors (Capelli02, Hong08, and Liu10), which are based on the most relevant visual characteristics of the fingerprint image, are considered. Considering the unbalanced classes for fingerprint identification schemes, we optimize the ELMs (standard, original weighted, and decay weighted) in terms of the geometric mean by estimating their hyper-parameters (regularization parameter, number of hidden neurons, and decay parameter). At the same time, the classic accuracy and penetration-rate metrics are computed for comparison purposes with the superior CNN-based methods reported in the literature. The experimental results show that weighted ELM with the presence of the golden-ratio in the weighted matrix (W-ELM2) overall outperforms the rest of the ELMs. The combination of the Hong08 extractor and W-ELM2 competes with CNNs in terms of the fingerprint classification efficacy, but the ELMs-based methods have been demonstrated their extremely fast training speeds in any context.
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Makrushin, Andrey, Venkata Srinath Mannam, and Jana Dittmann. "Privacy-Friendly Datasets of Synthetic Fingerprints for Evaluation of Biometric Algorithms." Applied Sciences 13, no. 18 (September 5, 2023): 10000. http://dx.doi.org/10.3390/app131810000.
Повний текст джерелаАнотація:
The datasets of synthetic biometric samples are created having in mind two major objectives: bypassing privacy concerns and compensating for missing sample variability in datasets of real biometric samples. If the purpose of generating samples is the evaluation of biometric systems, the foremost challenge is to generate so-called mated impressions—different fingerprints of the same finger. Note that for fingerprints, the finger’s identity is given by the co-location of minutiae points. The other challenge is to ensure the realism of generated samples. We solve both challenges by reconstructing fingerprints from pseudo-random minutiae making use of the pix2pix network. For controlling the identity of mated impressions, we derive the locations and orientations of minutiae from randomly created non-realistic synthetic fingerprints and slightly modify them in an identity-preserving way. Our previously trained pix2pix models reconstruct fingerprint images from minutiae maps, ensuring that the realistic appearance is transferred from training to synthetic samples. The main contribution of this work lies in creating and making public two synthetic fingerprint datasets of 500 virtual subjects with 8 fingers each and 10 impressions per finger, totaling 40,000 samples in each dataset. Our synthetic datasets are designed to possess characteristics of real biometric datasets. Thus, we believe they can be applied for the privacy-friendly testing of fingerprint recognition systems. In our evaluation, we use NFIQ2 for approving the visual quality and Verifinger SDK for measuring the reconstruction success.
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Yadav, Nisha, Deeksha Mudgal, Amarnath Mishra, Sacheendra Shukla, Tabarak Malik, and Vivek Mishra. "Harnessing fluorescent carbon quantum dots from natural resource for advancing sweat latent fingerprint recognition with machine learning algorithms for enhanced human identification." PLOS ONE 19, no. 1 (January 4, 2024): e0296270. http://dx.doi.org/10.1371/journal.pone.0296270.
Повний текст джерелаАнотація:
Nowadays, it is fascinating to engineer waste biomass into functional valuable nanomaterials. We investigate the production of hetero-atom doped carbon quantum dots (N-S@MCDs) to address the adaptability constraint in green precursors concerning the contents of the green precursors i.e., Tagetes erecta (marigold extract). The successful formation of N-S@MCDs as described has been validated by distinct analytical characterizations. As synthesized N-S@MCDs successfully incorporated on corn-starch powder, providing a nano-carbogenic fingerprint powder composition (N-S@MCDs/corn-starch phosphors). N-S@MCDs imparts astounding color-tunability which enables highly fluorescent fingerprint pattern developed on different non-porous surfaces along with immediate visual enhancement under UV-light, revealing a bright sharp fingerprint, along with long-time preservation of developed fingerprints. The creation and comparison of latent fingerprints (LFPs) are two key research in the recognition and detection of LFPs, respectively. In this work, developed fingerprints are regulated with an artificial intelligence program. The optimum sample has a very high degree of similarity with the standard control, as shown by the program’s good matching score (86.94%) for the optimal sample. Hence, our results far outperform the benchmark attained using the conventional method, making the N-S@MCDs/corn-starch phosphors and the digital processing program suitable for use in real-world scenarios.
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Hasoun, Rajaa, Soukaena Hashem, and Rehab Hasan. "A Proposed Hybrid Fingerprint, Image Fusion and Visual Cryptography Technique for Anti-Phishing." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 1 (October 10, 2021): 328–48. http://dx.doi.org/10.55562/jrucs.v39i1.216.
Повний текст джерелаАнотація:
This paper proposes an anti-phishing web site system it is carried out by the two following stages: Registration phase; the user enters username and password then (his/her) fingerprint, server site selects virtual fingerprint image. The fusion will be applied to fuse real fingerprint with virtual one, fused image will be input to visual cryptography(VC) scheme to produce two shares, one share kept with user in addition to fuse image, and other shares are kept with the server. Authentication phase; in this phase the user enters the password and is asked to enter the fingerprint. Pattern recognition is done to determine if it is hacker or authenticated user, when the server accepts the fingerprint the user will be required to input (his/her) share, so the user share is stacked with server share and generated image is displayed. The user will decide if it’s a phishing site or not depending on the displayed image (after matching it with the image that the server shared through registration phase).From many experimental works conducted on the proposal, we notice the strength is centered in image fusion. Where the fused fingerprint images have higher quality (entropy) than the single fingerprint image, that increases randomness of the VC shares which are extracted from the fused fingerprint.
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Wu, Feng, and Baohua Jiang. "Application of Fluorescent Carbon Nanoelectronic Materials in Combining Partial Differential Equations for Fingerprint Development and Its Image Enhancement." Journal of Nanoelectronics and Optoelectronics 18, no. 9 (September 1, 2023): 1070–77. http://dx.doi.org/10.1166/jno.2023.3496.
Повний текст джерелаАнотація:
Fluorescent developers play a crucial role when dealing with objects with complex patterns or color interference against their background due to their excellent photoluminescent properties. In recent years, fluorescent nanoelectronic materials have emerged as a novel class of fluorescent materials for fingerprint development research. Here, carbon quantum dots (CQDs) are synthesized using an electrochemical method and utilized as fluorescent nanoelectronic materials in combination with gold nanoparticles (AuNPs) to form a composite (Au/CQDs). The photoelectric properties of Au/CQDs are verified, and a precursor solution for Au/CQDs is prepared using the Wessling method. After the addition of a surfactant and subsequent elimination processes, an Au/CQDs fluorescent nanocolloidal solution is obtained. This solution is applied for the development of visible fingerprints and latent fingerprints on adhesive surfaces. The resulting development images are subjected to enhancement processes such as sharpening, smoothing, and noise reduction using partial differential equations to improve their visual quality. In experiments, under light exposure, Au/CQDs exhibit a higher conversion rate with cyclohexane compared to conditions without light. In the Au/NPs system, the fluorescence of CQDs is effectively quenched due to the rapid electron transfer process within the Au/CQDs system. Moreover, the electrode modified with Au/CQDs shows significantly improved efficiency in decomposing H2O2 compared to conditions without light exposure. After the development with Au/CQDs nanoparticle colloid solution, bright fingerprint patterns are visible under ultraviolet light. As the age of the fingerprint increases, the developed fingerprint has a higher resolution than fresh fingerprints. Image enhancement through partial differential equations results in satisfactory sharp edges and smooth contours in the images.
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Cadd, Samuel, Bo Li, Peter Beveridge, William O'Hare, and Meez Islam. "Age Determination of Blood-Stained Fingerprints Using Visible Wavelength Reflectance Hyperspectral Imaging." Journal of Imaging 4, no. 12 (November 29, 2018): 141. http://dx.doi.org/10.3390/jimaging4120141.
Повний текст джерелаАнотація:
The ability to establish the exact time a crime was committed is one of the fundamental aims of forensic science. The analysis of recovered evidence can provide information to assist in age determination, such as blood, which is one of the most commonly encountered types of biological evidence and the most common fingerprint contaminant. There are currently no accepted methods to establish the age of a blood-stained fingerprint, so progress in this area would be of considerable benefit for forensic investigations. A novel application of visible wavelength reflectance, hyperspectral imaging (HSI), is used for the detection and age determination of blood-stained fingerprints on white ceramic tiles. Both identification and age determination are based on the unique visible absorption spectrum of haemoglobin between 400 and 680 nm and the presence of the Soret peak at 415 nm. In this study, blood-stained fingerprints were aged over 30 days and analysed using HSI. False colour aging scales were produced from a 30-day scale and a 24 h scale, allowing for a clear visual method for age estimations for deposited blood-stained fingerprints. Nine blood-stained fingerprints of varying ages deposited on one white ceramic tile were easily distinguishable using the 30-day false colour scale.
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Muhammad, Hussein G., and Zainab A. Khalaf. "Fingerprint Identification System based on VGG, CNN, and ResNet Techniques." Basrah Researches Sciences 50, no. 1 (June 30, 2024): 14. http://dx.doi.org/10.56714/bjrs.50.1.14.
Повний текст джерелаАнотація:
This study compares three different pre-trained deep learning models specifically designed for fingerprint identification. The first model uses Convolutional Neural Network (CNN), the second includes Residual Network (ResNet), and the third employs the Visual Geometry Group (VGG) approach. The subsequent comparative assessment reveals the CNN-based model's superior performance, with an impressive F1 score of 96.5%. In contrast, the ResNet and VGG models achieve F1 scores of 94.3% and 92.11%, respectively. These findings highlight the CNN model's ability to accurately identify fingerprints. Furthermore, a comparative analysis is performed between the obtained results and those reported in recent studies using the same dataset. This analysis evaluates the performance of the proposed models and compares them to previous research, increasing confidence in the results. In conclusion, this study shows that in terms of fingerprint identification, the CNN-based model performs better than the other models.
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Worley, Christopher G., Sara S. Wiltshire, Thomasin C. Miller, George J. Havrilla, and Vahid Majidi. "Detection of visible and latent fingerprints by micro-X-ray fluorescence." Powder Diffraction 21, no. 2 (June 2006): 136–39. http://dx.doi.org/10.1154/1.2204065.
Повний текст джерелаАнотація:
Numerous methods are available to forensic scientists for detecting fingerprints in which the prints are treated with various agents to enhance the visual contrast between the print and the surface. In the present work, the spatial elemental imaging capabilities of micro-X-ray fluorescence (MXRF) were used to visualize fingerprint patterns based on inorganic elements present in the prints. A major advantage of using MXRF is that the prints are left unaltered for other analyses, such as deoxyribonucleic acid extraction or for archiving. Most of the fingerprints which were examined were imaged from the potassium and chlorine present in the print residue. Among the various prints studied, lower count rates were also observed in the elemental maps of Ca, Al, Na, Mg, Si, P, S, and the X-ray source scatter. A sebaceous oily fingerprint left by one subject was successfully imaged by MXRF, but sebaceous prints left by a different person were undetectable, indicating that print elemental composition may be person and/or diet dependent. Prints containing substances that might be found in real-world cases were also visualized including sweat, lotion, saliva, and sunscreen.
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Annappanavar, Sneha Manohar, and Pallavi Vijay Chavan. "Enabling secure authentication using fingerprint and visual cryptography." International Journal of Biometrics 16, no. 6 (2024): 614–39. http://dx.doi.org/10.1504/ijbm.2024.141949.
Повний текст джерела
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Alsaidi, Nadia M. G., Arkan J. Mohammed, and Wael J. Abdulaal. "Fingerprints Authentication Using Grayscale Fractal Dimension." Al-Mustansiriyah Journal of Science 29, no. 3 (March 10, 2019): 106. http://dx.doi.org/10.23851/mjs.v29i3.627.
Повний текст джерелаАнотація:
Characterizing of visual objects is an important role in pattern recognition that can be performed through shape analysis. Several approaches have been introduced to extract relevant information of a shape. The complexity of the shape is the most widely used approach for this purpose where fractal dimension and generalized fractal dimension are methodologies used to estimate the complexity of the shapes. The box counting dimension is one of the methods that used to estimate fractal dimension. It is estimated basically to describe the self-similarity in objects. A lot of objects have the self-similarity; fingerprint is one of those objects where the generalized box counting dimension is used for recognizing of the fingerprints to be utilized for authentication process. A new fractal dimension method is proposed in this paper. It is verified by the experiment on a set of natural texture images to show its efficiency and accuracy, and a satisfactory result is found. It also offers promising performance when it is applied for fingerprint recognition.
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Datcu, Dragos, Jelmer Winkel, and Leon Rothkrantz. "Augmented reality to support parcel handling in last-mile logistics." Acta Polytechnica CTU Proceedings 39 (December 15, 2022): 1–5. http://dx.doi.org/10.14311/app.2022.39.0001.
Повний текст джерелаАнотація:
We have developed an augmented reality (AR) based system which keeps track of events during the parcel handling process for last-mile logistics. The system can retrieve and highlight the location of parcels in large piles with AR on the user's smartphone. A camera array automatically detects the parcels laid down manually by an operator. New parcels are scanned and parcel fingerprints are generated semi-automatically. The system can detect and track the known parcels by fingerprint and can further highlight the location of the parcel using 3D visual clues, directly on the smartphone of the operator.
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Rafika, Ageng Setiani, Mukti Budiarto, and Wahyu Budianto. "APLIKASI MONITORING SISTEM ABSENSI SIDIK JARI SEBAGAI PENDUKUNG PEMBAYARAN BIAYA PEGAWAI TERPUSAT DENGAN SAP." CCIT Journal 8, no. 3 (May 19, 2015): 134–46. http://dx.doi.org/10.33050/ccit.v8i3.332.
Повний текст джерелаАнотація:
Monitoring Data on the presence of Usig Fingerprints is a strategic approach towards improving the discipline of employees, to achieve improved discipline such officials then needed an application monitoring system using Fingerprint time & attendance data are not effectively separated the human, infrastructure and overall management system for centralized employee fee payment process with SAP/ERP as expected and did not experience any delay in payment. Attendance System Monitoring application is capable of helping the PA (Payrool Administration) in favour of an increase in the accuracy of the data centralized employee fee payments with SAP can be realized should be supported by a reliable Technology Informatics infrastructure. Attendance Monitoring System application using the Fingerprint are created in this journal is an application programming examples that use the programming language visual basic 6.0 and SQL Server database, which is expected to help resolve problems existing in HUMAN RESOURCES in General and the ADM. Personnel in particular. The design of monitoring data on the presence of using fingerprints only handles input from someone who has been registered in the database, whereas the output that is displayed showing the reports relating to the attendance reports to be used as the supporter of the accuracy of the data centralized employee fee payments with SAP.
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LOU, MELANIE, and G. BRIAN GOLDING. "fingerprint: visual depiction of variation in multiple sequence alignments." Molecular Ecology Notes 7, no. 6 (November 2007): 908–14. http://dx.doi.org/10.1111/j.1471-8286.2007.01904.x.
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Ouyang, Jian-quan, Hua Nie, Min Zhang, Zezhou li, and Yongzhou Li. "Fusing audio-visual fingerprint to detect TV commercial advertisement." Computers & Electrical Engineering 37, no. 6 (November 2011): 991–1008. http://dx.doi.org/10.1016/j.compeleceng.2011.08.004.
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Tamburro, Gabriella, Patrique Fiedler, David Stone, Jens Haueisen, and Silvia Comani. "A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings." PeerJ 6 (February 23, 2018): e4380. http://dx.doi.org/10.7717/peerj.4380.
Повний текст джерелаАнотація:
Background EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: the need for visual inspection of the separated independent components (subjectivity problem) and, in some cases, for the independent and simultaneous recording of the inspected artefacts to identify the artefactual independent components; a potentially heavy manipulation of the EEG signals; the use of linear classification methods; the use of simulated artefacts to validate the methods; no testing in dry electrode or high-density EEG datasets; applications limited to specific conditions and electrode layouts. Methods Our fingerprint method automatically identifies EEG ICs containing eyeblinks, eye movements, myogenic artefacts and cardiac interference by evaluating 14 temporal, spatial, spectral, and statistical features composing the IC fingerprint. Sixty-two real EEG datasets containing cued artefacts are recorded with wet and dry electrodes (128 wet and 97 dry channels). For each artefact, 10 nonlinear SVM classifiers are trained on fingerprints of expert-classified ICs. Training groups include randomly chosen wet and dry datasets decomposed in 80 ICs. The classifiers are tested on the IC-fingerprints of different datasets decomposed into 20, 50, or 80 ICs. The SVM performance is assessed in terms of accuracy, False Omission Rate (FOR), Hit Rate (HR), False Alarm Rate (FAR), and sensitivity (p). For each artefact, the quality of the artefact-free EEG reconstructed using the classification of the best SVM is assessed by visual inspection and SNR. Results The best SVM classifier for each artefact type achieved average accuracy of 1 (eyeblink), 0.98 (cardiac interference), and 0.97 (eye movement and myogenic artefact). Average classification sensitivity (p) was 1 (eyeblink), 0.997 (myogenic artefact), 0.98 (eye movement), and 0.48 (cardiac interference). Average artefact reduction ranged from a maximum of 82% for eyeblinks to a minimum of 33% for cardiac interference, depending on the effectiveness of the proposed method and the amplitude of the removed artefact. The performance of the SVM classifiers did not depend on the electrode type, whereas it was better for lower decomposition levels (50 and 20 ICs). Discussion Apart from cardiac interference, SVM performance and average artefact reduction indicate that the fingerprint method has an excellent overall performance in the automatic detection of eyeblinks, eye movements and myogenic artefacts, which is comparable to that of existing methods. Being also independent from simultaneous artefact recording, electrode number, type and layout, and decomposition level, the proposed fingerprint method can have useful applications in clinical and experimental EEG settings.
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Growns, Bethany, James D. Dunn, Rebecca K. Helm, Alice Towler, and Jeff Kukucka. "The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices." PLOS ONE 17, no. 8 (August 11, 2022): e0272338. http://dx.doi.org/10.1371/journal.pone.0272338.
Повний текст джерелаАнотація:
The low prevalence effect is a phenomenon whereby target prevalence affects performance in visual search (e.g., baggage screening) and comparison (e.g., fingerprint examination) tasks, such that people more often fail to detect infrequent target stimuli. For example, when exposed to higher base-rates of ‘matching’ (i.e., from the same person) than ‘non-matching’ (i.e., from different people) fingerprint pairs, people more often misjudge ‘non-matching’ pairs as ‘matches’–an error that can falsely implicate an innocent person for a crime they did not commit. In this paper, we investigated whether forensic science training may mitigate the low prevalence effect in fingerprint comparison. Forensic science trainees (n = 111) and untrained novices (n = 114) judged 100 fingerprint pairs as ‘matches’ or ‘non-matches’ where the matching pair occurrence was either high (90%) or equal (50%). Some participants were also asked to use a novel feature-comparison strategy as a potential attenuation technique for the low prevalence effect. Regardless of strategy, both trainees and novices were susceptible to the effect, such that they more often misjudged non-matching pairs as matches when non-matches were rare. These results support the robust nature of the low prevalence effect in visual comparison and have important applied implications for forensic decision-making in the criminal justice system.
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Cahyaningtiyas, Rizqia, Efy Yosrita, and Rakhmat Arianto. "THE AUTOMATIC DOORS INTEGRATED ABSENCE AND USER ACCESS USING FINGERPRINT." Jurnal Ilmiah FIFO 8, no. 2 (November 1, 2016): 147. http://dx.doi.org/10.22441/fifo.v8i2.1309.
Повний текст джерелаАнотація:
This research aims to design Accompanied Door Access System Automation Absence and User Access Rights Using Integrated Fingerprint Database on Basic Computer Lab Informatics STT-PLN. What is meant by "Absent Automation and User Access Rights" among other computerized attendance automatically using fingerprint and right into a room on a predetermined schedule of lectures on computer lab space. System design method used is the method of evolutionary prototype, using MySQL database and coding using Visual C # .NET. These results indicate that the Door Access System Automation Accompanied Absence and User Access Rights Using Integrated Fingerprint Database can help assistants in attendance processing, computer lab room becomes more secure and computerized
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Bhati, Kajol, Divya Bajpai Tripathy, Ashutosh Kumar Dixit, Vignesh Kumaravel, Jamal S. M. Sabir, Irfan A. Rather, and Shruti Shukla. "Waste Biomass Originated Biocompatible Fluorescent Graphene Nano-Sheets for Latent Fingerprints Detection in Versatile Surfaces." Catalysts 13, no. 7 (July 6, 2023): 1077. http://dx.doi.org/10.3390/catal13071077.
Повний текст джерелаАнотація:
In recent years, the application of biocompatible and non-toxic nanomaterials for the detection of fingerprints has become the major interest in the forensic sector and crime investigation. In this study, waste chickpea seeds, as a natural resource, were bioprocessed and utilized for the synthesis of non-toxic graphene nano-sheets (GNSs) with high fluorescence. The graphene GNS were synthesized via pyrolysis at high temperatures and were characterized by TEM, XPS, fluorescence and UV-Vis spectroscopy, and FTIR analysis. The GNS exhibited excitation-independent emission at about 620 nm with a quantum yield of over 10% and showed more distinct blue light under a UV lamp. Biocompatibility of the synthesized GNS in terms of cell viability (88.28% and 74.19%) was observed even at high concentrations (50 and 100 mg/mL), respectively. In addition, the antimicrobial properties of the synthesized GNS-based coatings were tested with the pathogenic strain of Bacillus cereus via live/dead cell counts and a plate counting method confirming their biocompatible and antimicrobial nature for their potential use in safe fingerprint detection. The developed chickpea-originated fluorescent GNS-based spray coatings were tested on different surfaces, including plastic, glass, silicon, steel, and soft plastic for the detection of crime scene fingerprints. Results confirmed that GNS can be used for the detection of latent fingerprints on multiple non-porous surfaces and were easy to detect under a UV lamp at 395 nm. These findings reinforce the suggestion that the developed fluorescent GNS spray coating has a high potential to increase sensitive and stable crime traces for forensic latent fingerprint detection on nonporous surface material. Capitalizing on their color-tunable behavior, the developed chickpea-originated fluorescent GNS-based spray coating is ideal for the visual enhancement of latent fingerprints.
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Bansal, Roli, Priti Sehgal, and Punam Bedi. "Securing Fingerprint Images Through PSO Based Robust Facial Watermarking." International Journal of Information Security and Privacy 6, no. 2 (April 2012): 34–52. http://dx.doi.org/10.4018/jisp.2012040103.
Повний текст джерелаАнотація:
Presented is an efficient watermarking scheme using Particle Swarm Optimization (PSO) to watermark host fingerprint images with their corresponding facial images in the Discrete Cosine Transform (DCT) domain. PSO is used to find the best DCT coefficients’ locations in the host image where the facial image data can be embedded, so that the distortion produced in the host image is minimum. The objective function for PSO is formulated in terms of the Structural Similarity Index (SSIM) and the Orientation Certainty Level Index (OCL) so as to base it on the simple visual effect of the human visual perception capability and correct minutia prediction ability. The results exhibit better watermarked image quality while retaining the feature set of the original fingerprint. Moreover, the proposed technique is robust so that the extraction of watermark is possible even after the watermarked image is exposed to attacks. As a result, at the receiver’s end, the watermarked fingerprint image and the extracted facial image can be verified for a secure and accurate biometric based personal authentication.
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Booth, Mary C., Kenneth L. Hatter, Darlene Miller, Janet Davis, Regis Kowalski, David W. Parke, James Chodosh, et al. "Molecular Epidemiology of Staphylococcus aureus and Enterococcus faecalis in Endophthalmitis." Infection and Immunity 66, no. 1 (January 1, 1998): 356–60. http://dx.doi.org/10.1128/iai.66.1.356-360.1998.
Повний текст джерелаАнотація:
ABSTRACT Genomic DNA fingerprint analysis was performed on 39Staphylococcus aureus and 28 Enterococcus faecalis endophthalmitis isolates collected from multiple clinical centers. Among 21 S. aureus genomic DNA fingerprint patterns identified, five clonotypes were recovered from multiple unrelated patients and accounted for 58.9% (23 of 39) of the isolates analyzed. Compared with strains having unique genomic DNA fingerprint patterns, the S. aureus clonotypes occurring more than once were more likely to result in visual acuities of 20/200 or worse (P = 0.036 [χ2 test]). In contrast to the S. aureus isolates, the E. faecalis endophthalmitis isolates were a clonally diverse population, enriched for the expression of a known toxin, cytolysin, which is plasmid encoded.
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Kovács, András Bálint, Gal Raz, Giancarlo Valente, Michele Svanera, and Sergio Benini. "A Robust Neural Fingerprint of Cinematic Shot-Scale." Projections 13, no. 3 (December 1, 2019): 23–52. http://dx.doi.org/10.3167/proj.2019.130303.
Повний текст джерелаАнотація:
This article provides evidence for the existence of a robust “brainprint” of cinematic shot-scales that generalizes across movies, genres, and viewers. We applied a machine-learning method on a dataset of 234 fMRI scans taken during the viewing of a movie excerpt. Based on a manual annotation of shot-scales in five movies, we generated a computational model that predicts time series of this feature. The model was then applied on fMRI data obtained from new participants who either watched excerpts from the movies or clips from new movies. The predicted shot-scale time series that were based on our model significantly correlated with the original annotation in all nine cases. The spatial structure of the model indicates that the empirical experience of cinematic close-ups correlates with the activation of the ventral visual stream, the centromedial amygdala, and components of the mentalization network, while the experience of long shots correlates with the activation of the dorsal visual pathway and the parahippocampus. The shot-scale brainprint is also in line with the notion that this feature is informed among other factors by perceived apparent distance. Based on related theoretical and empirical findings we suggest that the empirical experience of close and far shots implicates different mental models: concrete and contextualized perception dominated by recognition and visual and semantic memory on the one hand, and action-related processing supporting orientation and movement monitoring on the other.
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Laoudias, Christos, Artyom Nikitin, Panagiotis Karras, Moustafa Youssef, and Demetrios Zeinalipour-Yazti. "Indoor Quality-of-position Visual Assessment Using Crowdsourced Fingerprint Maps." ACM Transactions on Spatial Algorithms and Systems 7, no. 2 (February 2021): 1–32. http://dx.doi.org/10.1145/3433026.
Повний текст джерелаАнотація:
Internet-based Indoor Navigation (IIN) architectures organize signals collected by crowdsourcers in Fingerprint Maps (FMs) to improve localization given that satellite-based technologies do not operate accurately in indoor spaces where people spend 80%–90% of their time. In this article, we study the Quality-of-Position (QoP) assessment problem, which aims to assess in an offline manner the localization accuracy that can be obtained by a user that aims to localize using a FM. Particularly, our proposed ACCES framework uses a generic interpolation method using Gaussian Processes (GP), upon which a navigability score at any location is derived using the Cramer-Rao Lower Bound (CRLB). We derive adaptations of ACCES for both Magnetic and Wi-Fi data and implement a complete visual assessment environment, which has been incorporated in the Anyplace open-source IIN. Our experimental evaluation of ACCES in Anyplace suggests the high qualitative and quantitative benefits of our propositions.
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Olasupo, A. O., O. S. Ademiluyi, M. A. Usman, K. K. A. Abdullah, O. O. Olubanwo, F. E. Ayo, U. H. Ojumadu, E. O. Salami, and T. E. Ibironke. "A FINGERPRINT BASED STUDENTS ATTENDANCE MANAGEMENT SYSTEM FOR OLABISI ONABANJO UNIVERSITY." FUDMA JOURNAL OF SCIENCES 6, no. 1 (April 2, 2022): 253–65. http://dx.doi.org/10.33003/fjs-2022-0601-896.
Повний текст джерелаАнотація:
The development of attendance was motivated by the necessity to keep track of who was there in a certain location at any given moment for future reference. Attendance is defined as the awareness of persons present at a specific location at a specific time for a previously scheduled event. Keeping and managing attendance records efficiently is critical for student evaluation. All formal institutions of learning place a high value on class attendance, which is so important that students who do not reach the class attendance threshold are not allowed to appear for exams. Traditional attendance marking techniques are prone to human error and time demanding for both students and lecturers during class. The old attendance system has various drawbacks, including lost attendance sheets, impersonation, time waste, insecurity, and lack of precision. As a result, by utilizing the unique qualities of fingerprint technology, a smart solution to the challenges connected with the traditional attendance system is required. As a result, the article devised, designed, and deployed a fingerprint-based attendance management system for students. The system's development model was the Software Development Life Cycle (SDLC). To record and verify students' fingerprints, a digital persona fingerprint scanner was utilized, and the Graphical User Interface (GUI) was created using the window forms application of the Visual Studio Integrated Development Environment (IDE). The back-end design was created using the C# programming language and the Structure Query Language (SQL) server. The system's logic was implemented in C#, and the SQL server was utilized as the
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Ashritha Reddy, D. "Implementation of the Optimized Dual Fingerprint Algorithm for Protecting Privacy Information." International Transactions on Electrical Engineering and Computer Science 2, no. 3 (September 30, 2023): 118–27. http://dx.doi.org/10.62760/iteecs.2.3.2023.59.
Повний текст джерелаАнотація:
The electromagnetic spectrum (EM) is made up of a variety of wavelengths, but the only wavelength that can be seen by the human visual system (HVS) is the visible wavelength, which is also referred to as the digital image processing (DIP) wavelength. The visible wavelength is also known as the visible light spectrum (VLS). The DIP is a component of the signal processing, but the HVS is unable to see the other elements of the signal if the DIP is not there. This is because the HVS requires a digital screen in order to see them, which is an application of the DIP. Through the implementation of digitalization applications in a variety of study domains, the DIP transforms the current world into a center for technological innovation. In today's society, security is of the highest importance, and biometrics-based systems have gained appeal over conventional ones because to their simplicity of use, resilience, and accuracy. Biometrics-based systems are becoming more popular. In this research, a unique combinational manner-based security solution is provided by combining the two fingerprints and taking into account their distinct orientations and minute details. This approach is made possible by taking into mind the minutiae involved. The creation of a fingerprint template that is identical to the original fingerprint included taking elements from two separate fingerprints and combining them. The information is protected against theft using the suggested template, which also demonstrates a low error rate (FRR = 0.4% at FAR = 0.1%) when compared to conventional methods (FAR = 0.1%). In conclusion, as compared to traditional approaches, the suggested method possesses a superior virtual identity, which demonstrates positive outcomes when defending against incidental and inadvertent attacks.
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Szulc, Natalia A., Zuzanna Mackiewicz, Janusz M. Bujnicki, and Filip Stefaniak. "fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions." PLOS Computational Biology 18, no. 6 (June 2, 2022): e1009783. http://dx.doi.org/10.1371/journal.pcbi.1009783.
Повний текст джерелаАнотація:
Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.
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Li, Ming, Hua Ren, En Zhang, Wei Wang, Lin Sun, and Di Xiao. "A VQ-Based Joint Fingerprinting and Decryption Scheme for Secure and Efficient Image Distribution." Security and Communication Networks 2018 (August 6, 2018): 1–11. http://dx.doi.org/10.1155/2018/4313769.
Повний текст джерелаАнотація:
The first joint fingerprinting and decryption (JFD) for vector quantization (VQ) images addressed the problem that the decrypted multimedia data may be redistributed from authorized customers to unauthorized customers. The scheme also caused conventional JFD methods to be equipped with a special ability to resist noise interference. Till now, some existing schemes related have been proposed to protect the multimedia content and distribution, but these schemes failed to tackle several problems existing in the original JFD scheme based on VQ image, including high transmission cost and severe fingerprinted image distortion. In this paper, we propose a novel JFD method by combining a weight-sum function with fingerprinting embedding and extraction for VQ images. Under the combination, the visual quality of the fingerprinted image is further improved; also the fingerprint extraction implements a blind extraction process. Experiments and analyses demonstrate the feasibility of the proposed method.
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Yang, Yu, Xing-Lin Huang, Zhong-Min Jiang, Xue-Fang Li, Yan Qi, Jie Yu, Xing-Xin Yang, and Mei Zhang. "Quantification of Chemical Groups and Quantitative HPLC Fingerprint of Poria cocos (Schw.) Wolf." Molecules 27, no. 19 (September 27, 2022): 6383. http://dx.doi.org/10.3390/molecules27196383.
Повний текст джерелаАнотація:
(1)Objective: In this study, a quantitative analysis of chemical groups (the triterpenoids, water-soluble polysaccharides, and acidic polysaccharides) and quantitative high liquid performance chromatography (HPLC) fingerprint of Poria cocos (Schw.) Wolf (PC) for quality control was developed. (2) Methodology: First, three main chemical groups, including triterpenoids, water-soluble polysaccharides, and acidic polysaccharides, in 16 batches of PC were evaluated by ultraviolet spectrophotometry. Afterward, the quantitative fingerprint of PC was established, and the alcohol extract of PC was further evaluated. The method involves establishing 16 batches of PC fingerprints by HPLC, evaluating the similarity of different batches of PC, and identifying eight bioactive components, including poricoic acid B (PAB), dehydrotumulosic acid (DTA), poricoic acid A (PAA), polyporenic acid C (PAC), 3-epidehydrotumulosic acid (EA), dehydropachymic acid (DPA), dehydrotrametenolic acid (DTA-1), and dehydroeburicoic acid (DEA), in PC by comparison with the reference substance. Combined with the quantitative analysis of multi-components by a single marker (QAMS), six bioactive ingredients, including PAB, DTA, PAC, EA, DPA, and DEA, in PC from different places were established. In addition, the multivariate statistical analyses, such as principal component analysis and heatmap hierarchical clustering analysis are more intuitive, and the visual analysis strategy was used to evaluate the content of bioactive components in 16 batches of PC. Finally, the analysis strategy of three main chemical groups in PC was combined with the quantitative fingerprint strategy, which reduced the error caused by the single method. (3) Results: The establishment of a method for the quantification of chemical groups and quantitative HPLC fingerprint of PC was achieved as demonstrated through the quantification of six triterpenes in PC by a single marker. (4) Conclusions: Through qualitative and quantitative chemical characterization, a multi-directional, simple and efficient routine evaluation method of PC quality was established. The results reveal that this strategy can provide an analytical method for the quality evaluation of PC and other Chinese medicinal materials.
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Sedik, Ahmed, Ahmed A. Abd El-Latif, Mohammed El-Affendi, and Hala Mostafa. "A Cancelable Biometric System Based on Deep Style Transfer and Symmetry Check for Double-Phase User Authentication." Symmetry 15, no. 7 (July 15, 2023): 1426. http://dx.doi.org/10.3390/sym15071426.
Повний текст джерелаАнотація:
In recent times, there has been a noticeable increase in the application of human biometrics for user authentication in various domains, such as online banking. However, the use of biometric systems poses security risks and the potential for misuse, primarily due to the storage of original templates in databases. To tackle this issue, the concept of cancelable biometrics has emerged as a reliable method utilizing one-way encryption. Several algorithms have been developed to implement cancelable biometrics, incorporating visual representations of single or multiple biometrics. This research proposes a cancelable biometric system that utilizes deep learning techniques to generate two encrypted modalities, namely text and image, using facial and fingerprint biometrics acquired from a smartphone. The system consists of two main stages: a visual encoder and a text encoder. The visual encoder converts the fingerprint style into a facial representation, creating a cancelable template to ensure the potential for cancelation. The resulting visual template is then processed by the text encoder, which employs hashing techniques to generate a corresponding text template. User authentication is automatically verified by utilizing the generated templates through Siamese networks.
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Platt, D. J., J. S. Chesham, D. J. Brown, C. A. Kraft, and J. Taggart. "Restriction enzyme fingerprinting of enterobacterial plasmids: a simple strategy with wide application." Journal of Hygiene 97, no. 2 (October 1986): 205–10. http://dx.doi.org/10.1017/s0022172400065281.
Повний текст джерелаАнотація:
SummaryRestriction enzyme fingerprints were generated from purified plasmid DNA from 324 clinical isolates that belonged to 7 enterobacterial genera and 88 single plasmids in Escherichia coli K12 according to the following strategy.Purified plasmid DNA was digested with PstI. The number of fragments detected in a 0·8 agarose gel was used to determine which 2 of 6 restriction enzymes including Pstl was most likely to provide a fingerprint comprising sufficient fragments to ensure specificity but sufficiently few to allow easy visual assessment and minimize coincidental matching. When PstI produced > 20 fragments, Eco RI and HindIII were used; when PstI generated < 6 fragments Bsp 1286 and AvaII were used and SmaI was employed when between 6 and 20 fragments were obtained from PstI digests. Using a minimum of 12 fragments from a combination of 2 enzymes as the criterion for characterizing a strain/plasmid, satisfactory 2-enzyme fingerprints were obtained from 87% of the strains and plasmids studied using PstI and no more than two additional enzymes per strain. Of the remaining 54 strains, 51 harboured only small plasmids (< 10 kb) and 3 produced satisfactory fingerprints when digested with a fourth enzyme.
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Castro, Francesco, Donato Impedovo, and Giuseppe Pirlo. "A Medical Image Encryption Scheme for Secure Fingerprint-Based Authenticated Transmission." Applied Sciences 13, no. 10 (May 16, 2023): 6099. http://dx.doi.org/10.3390/app13106099.
Повний текст джерелаАнотація:
Secure transmission of medical images and medical data is essential in healthcare systems, both in telemedicine and AI approaches. The compromise of images and medical data could affect patient privacy and the accuracy of diagnosis. Digital watermarking embeds medical images into a non-significant image before transmission to ensure visual security. However, it is vulnerable to white-box attacks because the embedded medical image can be extracted by an attacker that knows the system’s operation and does not ensure the authenticity of image transmission. A visually secure image encryption scheme for secure fingerprint-based authenticated transmission has been proposed to solve the above issues. The proposed scheme embeds the encrypted medical image, the encrypted physician’s fingerprint, and the patient health record (EHR) into a non-significant image to ensure integrity, authenticity, and confidentiality during the medical image and medical data transmission. A chaotic encryption algorithm based on a permutation key has been used to encrypt the medical image and fingerprint feature vector. A hybrid asymmetric cryptography scheme based on Elliptic Curve Cryptography (ECC) and AES has been implemented to protect the permutation key. Simulations and comparative analysis show that the proposed scheme achieves higher visual security of the encrypted image and higher medical image reconstruction quality than other secure image encryption approaches.
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Xuzhou Li. "An Improved Fingerprint Image Segmentation Algorithm Based on Visual Perception Model." International Journal of Digital Content Technology and its Applications 6, no. 16 (September 30, 2012): 506–13. http://dx.doi.org/10.4156/jdcta.vol6.issue16.61.
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Busey, T., B. Schneider, and D. Wyatte. "Expertise and the width of the visual filter in fingerprint examiners." Journal of Vision 8, no. 6 (March 19, 2010): 178. http://dx.doi.org/10.1167/8.6.178.
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Kominis, Iannis K., and Michail Loulakis. "Quantum advantage in biometric authentication with single photons." Journal of Applied Physics 131, no. 8 (February 28, 2022): 084401. http://dx.doi.org/10.1063/5.0080942.
Повний текст джерелаАнотація:
It was recently proposed to use the human visual system’s ability to perform efficient photon counting in order to devise a new biometric methodology. The relevant biometric “fingerprint” is represented by the optical losses light suffers along several different paths from the cornea to the retina. The “fingerprint” is accessed by interrogating a subject on perceiving or not weak light flashes, containing few tens of photons, so that the subject’s visual system works at the threshold of perception, at which regime optical losses play a significant role. Here, we show that if, instead of weak laser light pulses, we use quantum light sources, in particular, single-photon sources, we obtain a quantum advantage, which translates into a reduction of the interrogation time required to achieve the desired performance. Besides the particular application on biometrics, our work further demonstrates that quantum light sources can provide deeper insights when studying human vision.
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Marcovich, Arie L. "Asymmetrical Corneal Topography in Map-Dot-Fingerprint Dystrophy Resembling Keratoconus." International Journal of Keratoconus and Ectatic Corneal Diseases 1, no. 2 (2012): 131–33. http://dx.doi.org/10.5005/jp-journals-10025-1025.
Повний текст джерелаАнотація:
ABSTRACT Map-dot-fingerprint dystrophy cause painless blurred vision due to irregular astigmatism. Corneal topography may show asymmetry and irregularity and can resemble keratoconus. Two patients with map-dot dystrophy with unilateral blurring of vision are presented that were misdiagnosed as keratoconus due to asymmetric corneal topography. Medical treatment with hypertonic saline and lubrication in one patient and alcohol assisted epithelial delamination in the second patient restored visual acuity and restored normal appearance of corneal topography. How to cite this article Marcovich AL. Asymmetrical Corneal Topography in Map-Dot-Fingerprint Dystrophy Resembling Keratoconus. Int J Kerat Ect Cor Dis 2012;1(2):131-133.
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Ahmad Zainudin and Lutfil Hakim Arif Efendi. "DESAIN SISTEM PENDATAAN KEHADIRAN KARYAWAN TERINTEGRASI FINGERPRINT DENGAN FUNGSI PENGATURAN SHIFT KERJA BERBASIS VISUAL." Elkom : Jurnal Elektronika dan Komputer 12, no. 2 (December 13, 2019): 83–88. http://dx.doi.org/10.51903/elkom.v12i2.452.
Повний текст джерелаАнотація:
Data collection on employee attendance at a company is a must, with the aim of monitoring discipline, calculating employee salaries, and other needs. Data collection on employee attendance at companies that are used today is very diverse, following the development of technology. The United Tronik Semarang office, which employs relatively many employees, currently uses a manual card attendance data collection system that attracts researchers to make the United Tronik Office the object of research.
Fingerprint is one of the hardware used to support employee attendance data collection which is relatively simple and easy to reach, the accuracy and ease of operation make the fingerprint attendance system more and more in demand. One of the human error problems in the attendance data collection system is attendance recording errors, especially for employees with shift work hours. Arrangement of work shifts in programs built with Visual Basic 2010 can minimize attendance recording errors, because it can set the recording time for employees. To support the ease of data access and shift settings, the researcher uses a Client Server database system with SQL Server 2005 Software.
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Ling, Hefei, Lingyu Yan, Fuhao Zou, Cong Liu, and Hui Feng. "Fast image copy detection approach based on local fingerprint defined visual words." Signal Processing 93, no. 8 (August 2013): 2328–38. http://dx.doi.org/10.1016/j.sigpro.2012.08.011.
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Chourasia, Jaishri. "Identification and authentication using visual cryptography based fingerprint watermarking over natural image." CSI Transactions on ICT 1, no. 4 (December 2013): 343–48. http://dx.doi.org/10.1007/s40012-013-0033-1.
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Cahyadi, Decki Noor, Tenia Wahyuningrum, and Irwan Susanto. "Rancang Bangun Sistem Presensi Mahasiswa Berbasis Fingerprint Client Server." JURNAL INFOTEL - Informatika Telekomunikasi Elektronika 6, no. 1 (May 10, 2014): 43. http://dx.doi.org/10.20895/infotel.v6i1.15.
Повний текст джерелаАнотація:
Presensi mahasiswa merupakan salah satu peran penting dalam kegiatan belajar dan mengajar. Sistem Presensi melalui SIMAK di ST3 Telkom memiliki beberapa kekurangan, yaitu memerlukan waktu khusus untuk memanggil mahasiswa satu persatu, juga memiliki celah kecurangan, jika dosen yang bersangkutan tidak mengenali wajah mahasiswa, sehingga ada kemungkinan mahasiswa mengaku sebagai mahasiswa lain. Berdasarkan hasil analisa, ditawarkan sebuah inovasi baru untuk Sistem Presensi menggunakan fingerprint berbasis client server. Dalam pembangunan Sistem Presensi ini menggunakan metode pengembangan sistem waterfall, DBMS Microsoft Access dan Visual Basic 6.0 sebagai bahasa pemrogramannya. Hasil pengujian menunjukkan sistem informasi presensi sudah dapat berjalan dengan baik. Output sesuai dengan rancangan yang telah dibuat.
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Augé, Anaïs. "How visual metaphors can contradict verbal occurrences." Metaphor and the Social World 12, no. 1 (November 1, 2021): 1–22. http://dx.doi.org/10.1075/msw.20001.aug.
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Abstract We investigate the different interpretations related to the metaphorical imprint of climate change in English and French media discourses. This cross-linguistic perspective is motivated by the particularities of both languages which have been assumed to promote different understandings of climate change-related concepts. We focus on the metaphor carbon footprint whose meaning can be compared to another climate change metaphor in English: fingerprint . These two source domains share a highly specific and concrete meaning interpreted from lexical constructions enabled by the English language. In French, however, such a specification cannot be interpreted from the meaning of the metaphor empreinte carbone ( carbon imprint ) which defines a similar concept. We rely on visual representations of these metaphorical expressions in English and French to discuss the characteristics associated with each source domain: we show that visual metaphors can contradict expectations emerging from the interpretations of verbal metaphors.
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Iwan Kooerniawan and Denny Setyawan. "Penerapan Sistem Absensi Fingerprint Dengan Menggunakan Visual Basic 6.0 di CV. MEDIA INOVASI." Jurnal Ilmiah Manajemen, Bisnis dan Kewirausahaan 1, no. 3 (October 15, 2021): 18–27. http://dx.doi.org/10.55606/jurimbik.v1i3.49.
Повний текст джерелаАнотація:
Attendance is an important thing for an agency or company. because it is used in calculating the amount of an employee's salary or wages and from attendance it can also see the discipline of employee attendance. Therefore, in its implementation, the attendance process requires accuracy in its implementation so as not to hinder company performance.This final project is designing an employee attendance system at CV. INNOVATION MEDIA which is useful for providing good attendance information quickly and easily, also through this study is expected to provide convenience to employees of CV. INNOVATION MEDIA in doing attendance. Employee attendance system design at CV. INNOVATION MEDIA was developed using Visual Basic 6.0 software and with Finger Print as a tool. This system records employee attendance in the form of a daily attendance list. It is used to accommodate the data needed to streamline the information system.With this system, it is expected that the data processing process will be more effective and efficient. In searching for data it will be easier. The purpose of this study is to design an employee attendance information system which is expected to help the
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Olumide S., Adewale, Boyinbode Olutayo K., and Salako E. Adekunle. "An Innovative Approach in Electronic Voting System Based on Fingerprint and Visual Semagram." International Journal of Information Engineering and Electronic Business 13, no. 5 (October 8, 2021): 24–37. http://dx.doi.org/10.5815/ijieeb.2021.05.03.
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Kusumawardhani, Octarifia, and Panggih Basuki. "Purwarupa Sistem Kunci Kombinasi Berbasis Sidik Jari dan Sensor Passive Infrared Receiver." Creative Information Technology Journal 2, no. 2 (April 4, 2015): 144. http://dx.doi.org/10.24076/citec.2015v2i2.44.
Повний текст джерелаАнотація:
Purwarupa sistem ini dilatar belakangi karena kurangnya sistem keamanan yang memadai sehingga terjadi tindakan pencurian dan penghuni asrama atau kost membawa teman tanpa seizin pemilik kost. Sistem ini mengimplementasikan pola sidik jari penghuni yang telah terdaftar. Dengan menggunakan satu pola sidik jari dipastikan tidak membawa lebih dari satu orang, sehingga sistem dapat mengizinkan akses masuk kost atau asrama maupun menolak akses masuk karena ada orang lain yang tidak terdaftar.Pengujian sistem dilakukan setiap hari dengan menggunakan beberapa sampel pola sidik jari penghuni yang diambil oleh alat sensor sidik jari Fingerspot U.are.U 4500.Pendeteksian orang menggunakan sensor Passive Infrared Receiver dengan bantuan sensor photodiode untuk menghitung jumlah orang.Untuk mempermudah pendeteksian digunakan sistem minimum ATMega16 dan bahasa pemrograman Bascom AVR.Microsoft Visual Basic 6 digunakan sebagai antarmuka sehingga dapat berinteraksi dengan alat. Data yang telah diambil selanjutnya disimpan dalam basis data menggunakan MySQL dan Microsoft Access 2007.The prototype of this system is due to the lack of adequate security systems in the boarding house that there was a theft and tenants bring their friends without the permission of the owner of the boarding house. This system is based on fingerprint patterns of the tenants who have been registered. By using a fingerprint pattern for security mechanism, a tenant will not be able to bring his/her friends without permission.The system is implemented using Fingerspot U.are.U 4500 as the fingerprint reader. The presence and number of people is detected using Passive Infared Receiver and photodiode. In order to simplify the system, detection of people is implemented using ATMega16 as minimum system and Bascom AVR as programming language. Microsoft Visual Basic 6 is used for interaction with the interface. The data whisch have been taken are stored in Microsoft Access 2007 and MySQL.
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Perczel, Júlia. "Is Structure Context or Content? A Data-Driven Method of Comparing Museum Collections." Život umjetnosti, no. 105 (December 31, 2019): 76–109. http://dx.doi.org/10.31664/zu.2019.105.04.
Повний текст джерелаАнотація:
This paper presents a method which depicts a museum collection as a relational venue structure. This venue structure is constructed from the exhibition history of the artists acquired by the museum, in such a way that it uniquely characterizes the collection. Such a structure can be conceived as a historical fingerprint of a collection. The paper compares such derived historical fingerprints of three canonical museum collections: that of the Tate Collection in the UK, the Centre Pompidou in Paris and the Museum of Modern Art in New York. The goal is to develop the understanding of the way they represent the art of the Central-East European region. The research shows that the representation formed by the three museums on the region relies on specific venues and connections among them. Furthermore, the analysis has identified patterns within these structures that contribute to the formation of the representations in typical ways. As a result, the agency of museums is tackled from a data-driven perspective highlighting the social embeddedness of representations, and a method is introduced that enables comparison of collections built through distinctive acquisition histories.
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Ales, Justin, Thom Carney, and Stanley A. Klein. "The folding fingerprint of visual cortex reveals the timing of human V1 and V2." NeuroImage 49, no. 3 (February 2010): 2494–502. http://dx.doi.org/10.1016/j.neuroimage.2009.09.022.
Повний текст джерела
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Allouche, Mohamed, Tarek Frikha, Mihai Mitrea, Gérard Memmi, and Faten Chaabane. "Lightweight Blockchain Processing. Case Study: Scanned Document Tracking on Tezos Blockchain." Applied Sciences 11, no. 15 (August 3, 2021): 7169. http://dx.doi.org/10.3390/app11157169.
Повний текст джерелаАнотація:
To bridge the current gap between the Blockchain expectancies and their intensive computation constraints, the present paper advances a lightweight processing solution, based on a load-balancing architecture, compatible with the lightweight/embedding processing paradigms. In this way, the execution of complex operations is securely delegated to an off-chain general-purpose computing machine while the intimate Blockchain operations are kept on-chain. The illustrations correspond to an on-chain Tezos configuration and to a multiprocessor ARM embedded platform (integrated into a Raspberry Pi). The performances are assessed in terms of security, execution time, and CPU consumption when achieving a visual document fingerprint task. It is thus demonstrated that the advanced solution makes it possible for a computing intensive application to be deployed under severely constrained computation and memory resources, as set by a Raspberry Pi 3. The experimental results show that up to nine Tezos nodes can be deployed on a single Raspberry Pi 3 and that the limitation is not derived from the memory but from the computation resources. The execution time with a limited number of fingerprints is 40% higher than using a classical PC solution (value computed with 95% relative error lower than 5%).