Fingerprint Extraction Research Articles

Automatic equipment fault fingerprint extraction for the fault diagnostic on the batch process data

Equipment condition monitoring in semiconductor manufacturing requires prompt, accurate, and sensitive detection and classification of equipment and process faults. Efficient and effective fault diagnostic is essential to minimizing scrapped wafers, reducing unscheduled equipment downtime, and consequently maintaining high production throughput and product yields. Through analyzing the equipment sensor signals as the batch process data, i.e., process timestamp×sensor×wafer, this paper firstly applies the well-known Support Vector Machine (SVM) classifier to detect the abnormal observations. In the second stage, the normal process dynamics are decomposed into different clusters by K-Means clustering. Each part of the process dynamics is further modelled by Principal Component Analysis (PCA). Fault fingerprints then can be extracted by consolidating the out of control scenarios after projecting the abnormal observations into the PCA models. An empirical study is conducted in collaboration with a local IC maker in France to validate the methodology. The result shows that the proposed approach can effectively detect abnormal observations as well as automatically classify the proper fault fingerprints to give evident guidelines in explaining the known faults.

Dereplication by HPLC-DAD-ESI-MS/MS and Screening for Biological Activities of Byrsonima Species (Malpighiaceae).

Byrsonima species have been used in the treatment of gastrointestinal and gynecological inflammations, skin infections and snakebites. Based on their biological activities, it is important to study other organisms from this genus and to identify their metabolites. To determine the metabolic fingerprinting of methanol and ethyl acetate extracts of four Byrsonima species (B. intermedia, B. coccolobifolia, B. verbascifolia and B. sericea) by HPLC-DAD-ESI-MS/MS and evaluate their in vitro antioxidant, anti-glycation, anti-inflammatory and cytotoxic activities. Antioxidant activity was determined by DPPH˙, ABTS˙+ and ROO˙ scavenging assays. Anti-glycation activity was evaluated by the ability to inhibit the formation of advanced glycation endproducts (AGEs). Anti-inflammatory activity was evaluated using a murine macrophage cell line (RAW 264-7) in the presence of lipopolysaccharide (LPS). Tumour necrosis factor alpha (TNF-α) and nitrite (NO2- ) production were measured by ELISA and the Griess reaction, respectively. The compounds present in the extracts were tentatively identified by HPLC-DAD-ESI-MS/MS. The evaluation of the biological activities showed the potential of the extracts. The activities were assigned to the presence of glycoside flavonoids mainly derived from quercetin, quinic acid derivatives, gallic acid derivatives, galloylquinic acids and proanthocyanidins. Two isomers of sinapic acid-O-hexoside were described for the first time in a Byrsonima species. This research contributes to the study of the genus, it is the first report of the chemical composition of B. sericea and demonstrates the importance of the dereplication process, allowing the identification of known compounds without time-consuming procedures. Copyright © 2017 John Wiley & Sons, Ltd.

TagIt: Tagging Network Flows using Blind Fingerprints

AbstractFlow fingerprinting is a mechanism for linking obfuscated network flows at large scale. In this paper, we introduce the firstblindflow fingerprinting system called TagIt. Our system works by modulating fingerprint signals into the timing patterns of network flows through slightly delaying packets into secret time intervals only known to the fingerprinting parties. We design TagIt to to enable reliable fingerprint extraction by legitimate fingerprinting parties despite natural network noise, but invisible to an adversary who does not possess the secret fingerprinting key. TagIt makes use of randomization to resist various detection attacks such as multi-flow attacks. We evaluate the performance and invisibility of TagIt through theoretical analysis as well as simulations and experimentation on live network flows.

PHARMACOGNOSTIC SCREENING STUDIES OF JUSTICIA GENDARUSSA BURM. LEAVES FOUND IN DEHRADUN DISTRICT OF UTTARAKHAND

Objective: Justicia gendarussa Burm. (family Acanthaceae) commonly known as nilinirgundi, is found in Southern India possesses multifarious biological activities due to large range of phytoconstituents. The present study is designed to evaluate the various pharmacognostic parameters of the leaves of J. gendarussa, found in Dehradun district of Uttarakhand for its authentication.Methods: Fresh leaves were taken for the morphological and microscopical (histology and powder) evaluation. Physicochemical parameters (ash values, extractives values, florescence analysis, microbial contamination, and loss on drying) were also performed. Phytochemical screening and thin-layer chromatographic fingerprinting of extracts were also performed to check the presence of various phytoconstituents.Results: The microscopy of the leaves evinced the presence of anisocytic stomata, cuboidal calcium oxalate crystals, cystoliths, multicellular covering trichomes, starch grains and oil globules. The quantitative estimation of total ash, acid insoluble, and water soluble ash values were 13.8%, 1.2%, and 4.5% w/w, respectively. The alcohol soluble and water soluble extractives were estimated as 11.45% and 15.67% w/w, respectively. Foreign organic matter and loss on drying values obtained were 0.23% and 11.2% w/w. Phytochemical screening of petroleum ether, chloroform, methanol and aqueous extracts ascertained the presence of alkaloids, phenolic compounds, saponins, tannins, carbohydrates, flavonoids, glycosides, steroids and triterpenoids. The thin-layer chromatography (TLC) profiling of different extracts revealed the presence of potential compounds which can be further isolated with the help of high-performance liquid chromatography or high-performance TLC.Conclusion: The results of this study provide suitable standards for the authentication of this plant. In the present study, there are certain variations observed from the evaluations done on the same species by other research groups. The probable reason suggested for such disparity is due to the environmental and geographical differences in the locations of the plant collected.

Metabolomic-Guided Isolation of Bioactive Natural Products from Curvularia sp., an Endophytic Fungus of Terminalia laxiflora.

Endophytic fungi associated with medicinal plants are a potential source of novel chemistry and biology. Metabolomic tools were successfully employed to compare the metabolite fingerprints of solid and liquid culture extracts of endophyte Curvularia sp. isolated from the leaves of Terminalia laxiflora. Natural product databases were used to dereplicate metabolites in order to determine known compounds and the presence of new natural products. Multivariate analysis highlighted the putative metabolites responsible for the bioactivity of the fungal extract and its fractions on NF-κB and the myelogenous leukemia cell line K562. Metabolomic tools and dereplication studies using high-resolution electrospray ionization mass spectrometry directed the fractionation and isolation of the bioactive components from the fungal extracts. This resulted in the isolation of N-acetylphenylalanine (1: ) and two linear peptide congeners of 1: : dipeptide N-acetylphenylalanyl-L-phenylalanine (2: ) and tripeptide N-acetylphenylalanyl-L-phenylalanyl-L-leucine (3: ).

Deep convolutional neural network for latent fingerprint enhancement

In this work, we propose a novel latent fingerprint enhancement method based on FingerNet inspired by recent development of Convolutional Neural Network (CNN). Although CNN is achieving superior performance in many computer vision tasks from low-level image processing to high-level semantic understanding, limited attention has been paid in fingerprint community. The proposed FingerNet has three major parts: one common convolution part shared by two different deconvolution parts, which are the enhancement branch and the orientation branch. The convolution part is to extract fingerprint features particularly for enhancement purpose. The enhancement deconvolution branch is employed to remove structured noise and enhance fingerprints as its task. The orientation deconvolution branch performs the task of guiding enhancement through a multi-task learning strategy. The network is trained in the manner of pixels-to-pixels and end-to-end learning, that can directly enhance latent fingerprint as the output. We also study some implementation details such as single-task learning, multi-task learning, and the residual learning. Experimental results of the FingerNet system on latent fingerprint dataset NIST SD27 demonstrate effectiveness and robustness of the proposed method.

Modulation of cholinergic, monoaminergic, and purinergic enzymes of the brain functions by bitter (Vernonia amygdalina) and water bitter (Struchium sparganophora) leaves extracts: comparison of phenolic constituents versus nootropic potentials

This study investigated the possible neuroprotective properties of two commonly consumed tropical vegetables. The modulatory effects of Vernonia amygdalina (VA) and Struchium sparganophora (SS) on the activities of Na+/K+ ATPase, ecto-5′-nucleotidase, monoamine oxidase (MAO), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and FeSO4-induced oxidative stress in rat brain homogenate were assessed. The result revealed that both vegetables inhibited AChE, BChE, MAO, and ecto-5’nucleotidase activities, but stimulated Na+/K+ ATPase activity in a concentration-dependent manner. The SS had a significantly higher (P ˂ 0.05) inhibitory effect on AChE (IC50 = 4.83 μg/mL), BChE (IC50 = 5.61 μg/mL), MAO (IC50 = 26.11 μg/mL), ecto-5′ nucleotidase (IC50 = 23.04 μg/mL) than VA [AChE (IC50 = 7.53 μg/mL), BChE (IC50 = 7.32 μg/mL), MAO (IC50 = 26.11 μg/mL), and ecto-5′ nucleotidase (IC50 = 42.35 μg/mL)]. Furthermore, SS (IC50 = 28.30 μg/mL) had a significantly higher (P < 0.05) stimulatory effect on Na+/K+ ATPase activity than VA (IC50 = 34.87 μg/mL). Both extracts exhibited a strong antioxidant properties as typified by their radicals (OH and DPPH) scavenging and Fe2+ chelating abilities, as well as inhibition of Fe2+-induced lipid peroxidation in rat brain homogenate. The HPLC fingerprint of VA and SS extracts revealed the presence of catechin, chlorogenic acid, caffeic acid, p-coumaric acid, rutin, orientin, quercitrin quercetin, and luteolin. The stimulation of Na+/K+ ATPase activity, inhibition of 5′-nucleotidase, AChE, BChE, and MAO activities as well as Fe2+-induced oxidative stress could be a possible mechanism through which VA and SS exerts neuroprotective properties.

GC/MS Fingerprinting of Solvent Extracts and Essential Oils Obtained from Liverwort Species

Studies concerning chemical profiling of the volatiles present in the solvent extracts from liverworts help to determine inter- and intraspecific relationships in this plant group. Due to the fact that the liverworts are morphologically very small and it is difficult to collect their sufficient amounts, there are still a few data concerning the chemistry of essential oils. The available data indicate however, that the components present in the essential oils can be used in chemosystematic studies of these spore-forming plants. Compounds occurring in the essential oils constitute a powerful tool for studying chemical differences between or within liverwort species for which the characteristic components are mono- and sesquiterpenoids. Good results were obtained for the liverworts species from the genera Asterella, Conocephalum, Diplophyllum, Jungermannia, Lepidozia, Radula, Reboulia or Scapania.

Fingerprint Image Segmentation: A Review of State of the Art Techniques

In Automatic Fingerprint Identification System (AFIS), pre-processing of the image is a crucial process in deciding the quality and performance of the system. Pre-processing is consists many stages as Segmentation, Enhancement, Binarisation, and Thinning. In this segmentation is one of the steps of pre-processing which differentiate foreground and background region of fingerprint images. Segmentation is the separation of the fingerprint region or extraction of the presence of ridges from the background of the initial image. Segmentation is necessary because it constructs the region of interest from the input image, reduces the processing time, increases the recognition or matching process performance, and reduces the probability of false feature extraction. A 100% accurate segmentation is always very difficult, especially in the very poor quality image or partial image filled with noise such as the presence of latent. Fingerprints are made of Ridge and Valley structure and their features are classified in three levels as Level 1, Level 2, and Level 3. Level 1 Features are singular macro details like ridge pattern and ridge flows. Level 2 is ridge local features like ridge bifurcation and ridge ending or simply minutiae points or ridge orientation. Level 3 is micro details like sweat pores, incipient ridges. This paper provides an overview of the state of the art techniques of fingerprint image segmentation and contribution of other researchers on segmentation. This paper also discusses a different class of segmentation algorithms with its measuring parameters, computational complexity, advantages, limitations, and applications.

Method of Empirical Mode Decomposition in Specific Emitter Identification

RF fingerprint (RFF) extraction is a fundamental issue of specific emitter identification (SEI). In most of current SEI techniques, the extracted RFFs are adversely affected by other components. This paper introduces a novel SEI system for the common communication signals. Empirical mode decomposition (EMD) method is applied in such system to separate components of a signal, which efficiently mitigates the obscurity problem of RFF. The principal component analysis (PCA) is then used to select the critical feature and a support vector machine (SVM) classifier is finally used to realize the emitter classification. In the experiments, the transient signals captured from four mobile phones and the steady signals from four WLAN cards are utilized to evaluate the performance. The experimental results highlight that the proposed method can achieve high accuracy of recognizing to transmitters.

RF fingerprint extraction for GNSS anti-spoofing using axial integrated Wigner bispectrum

Spoofing interference has caused serious security problems in global navigation satellite systems (GNSS), so identifying spoofing signals from genuine signals is the key task of GNSS. For the spoofing detection, a novel feature extraction method using axial integrated Wigner bispectrum (AIWB) is investigated in this paper. Compared with diagonal sliced Wigner bispectrum (SWB), this method not only reduces the dimension of the Wigner bispectrum, but also utilizes much more signal information. We use singular values of AIWB as the feature vector of the signal, and use support vector machine (SVM) to realize the identification of spoofing signals. Compared with SWB and bispectrum, the simulation results demonstrate that AIWB has lower Equal Error Rate (EER), especially in relatively low SNRs, and has better recognition performance due to its lower mean misclassification rate and smaller variation.

Effectiveness of fine root fingerprinting as a tool to identify plants of the Alps: Results of a preliminary study

To identify plants of the Alps through analysis of their roots is currently extremely difficult when using traditional identification methods such as dichotomous keys and/or illustrated atlases. Besides genetic analysis, other analytical methods, such as chromatographic analysis, could also be useful for root identification. Chromatographic fingerprints of root extracts of six species (Betula pendula, Picea abies, Fagus sylvatica, Larix decidua, Fraxinus excelsior and Corylus avellana) were analyzed in order to understand whether these species have a chromatographic fingerprint that identifies them, and hence to ascertain whether they can be identified by applying the method of analysis presented below. One hundred and sixty-two root samples were collected in various areas of the Alps and subjected to high-performance liquid chromatography (HPLC) analysis. Multivariate analysis techniques (e.g. cluster analysis) were employed for statistical analysis of chromatographic fingerprints. This study revealed that the chromatographic fingerprints of birch, spruce and larch samples were similar and that the method can therefore clearly identify the respective species. Instead, chromatographic fingerprint samples of beech, hazel and ash presented greater variability. Research proposals based on the results obtained in this study were also developed in order to implement and facilitate studies regarding plant roots.

Distributed Content Based Video Identification in Peer-to-Peer Networks: Requirements and Solutions

In this paper, we first discuss the essential requirements for a fingerprint (perceptual hash)-based distributed video identification system in peer-to-peer (P2P) networks in comparison with traditional central database implementations of fingerprints. This discussion reveals that first, fingerprint sizes of existing video fingerprint methods are not compatible with the cache sizes of current P2P clients; second, fingerprint extraction durations during a query are not at tolerable levels for a user in the network; third, the repetitive patterns in the extracted fingerprints avoid the uniform distribution of storage and traffic load among the peers; and finally, the existing methods do not provide a solution to synchronize the fingerprint extraction from the shared video and queried video. In order to solve the mentioned requirements, we propose a baseline method using only the difference of video frame means, which decreases the fingerprint sizes to typical cache sizes, by increasing the granularity levels from seconds to minutes. We then develop a novel algorithm which utilizes reference points on one-dimensional frame mean sequence for the synchronization of fingerprint extraction. This algorithm is extended with a hierarchical decoding approach based on Gaussian scales, which only decodes a subset of video frames without needing a full decoding. Finally, an analysis on the effect of design parameters to the fingerprint probability distribution is performed to avoid repetitive patterns. Our ultimate solution reduces the fingerprint sizes into kilobytes, extraction time to seconds, and search duration into milliseconds, and achieves about 90% detection rates with 1–4 min granularities, while enabling a fair distribution of storage load among the peers at the same time.

An On-Chip Technique to Detect Hardware Trojans and Assist Counterfeit Identification

This paper introduces an embedded solution for the detection of hardware trojans (HTs) and counterfeits. The proposed method, which considers that HTs are necessarily inserted on production lots and not on a single device, is based on the fingerprinting of the static distribution of the supply voltage ( $V_{\mathrm{ dd}}$ ) over the whole surface of an integrated circuit. The measurement of this fingerprint is done through an array of sensors sensitive to the local $V_{\mathrm{ dd}}$ value and fingerprint extraction is based on a novel variation model of CMOS logic performance. This model takes into account not only process variations but also the impact of the design (layout, supply routing, and so on). In addition to the fingerprinting process, this paper introduces an adaptive distinguisher to deal with the difficult problem of fixing the p-value on large sets of statistical tests. The efficiency of the whole detection methodology is experimentally demonstrated on a set of 24 FPGA boards.

Preliminary Phytochemical Content and Antidiabetic Potential Investigations of &amp;lt;i&amp;gt;Panda oleosa&amp;lt;/i&amp;gt; (Pierre) Used in Kisangani Areas

Panda oleosa Pierre (POP), a tropical plant tree, has been used in traditional medicine in Kisangani city and around to treat various diseases including diabetes and HIV/AIDs. This study aims to evaluate the chemical composition of POP extracts while setting up chromatographic fingerprints for their quality control, and the anti-hyperglycemic potential of trunk bark aqueous extracts of POP. Common chemical reactions were used for identification of main secondary metabolic groups. Thin layer chromatography was used to set up several chromatographic fingerprints of water and alcoholic extracts while evaluating chemical composition. Oral glucose tolerance test served to induce hyperglycemia in a rabbit model. The extracts were given as 25 mg/kg, 50 mg/kg, and 100 mg/kg body weight, 30 minutes before loading animals with glucose 4 g/kg. Blood samples were collected at various times: just before extracts (T-30), before (T0) and after glucose load (T30, T60, T120, and T180). Blood glucose levels were measured with One Touch Glucometer. The identification tests revealed the presence of saponins (3.58%), tannins (5%); alkaloids, quinones, flavonoids, and terpenes sterols could not be formerly detected by the reagents used. Interesting chromatographic spots were observed whose behaviors are of catechic tannin proanthocyanes. The extract significantly reduced glucose levels in dose dependent manner as compared to control and glibenclamide reference groups. The average of mean percentage of reduction in glucose level at T120 with the extract 100 mg/kg was close to that of glibenclamide 0.25 mg/kg (49% and 40.2%). These findings back the traditional use of the plant to treat diabetic patients and constitute a foundation for an extensive study to find a new antidiabetic phythomedicine.

Comparative study on the phenolic content, antioxidant properties and HPLC fingerprinting of the leaf extracts of Clerodendrum volubile P. Beauv

The present study aimed to investigate the phenolic contents and antioxidant properties of the various leaf extracts (methanol, ethanol, ethyl acetate) of Clerodendrum volubile. In vitro scavenging activities of the extracts were assessed against 1,1-diphenyl-2 picrylhydrazyl (DPPH), 2,2- azinobis (3-ethylbenzo-thiazoline- 6-sulfonate (ABTS) radical scavenging ability (ABTS) radicals. The reducing power ability and high-performance liquid chromatography-diode-array detector (HPLCDAD) of the extracts was also determined. The methanol extract had the highest reducing power, DPPH and ABTS radicals scavenging activities, followed by ethanol and ethyl acetate extracts. The HPLC-DAD results revealed the presence of both phenolic acids (caffeic acid, gallic acid) and flavonoids (catechin, quercetin, rutin, quercitrin, kaempferol, luteolin, apigenin) as its major bioactive polyphenolics. The difference in scavenging potential of the extracts may be due to variation in the phytoconstituents extracted using various solvents. The result suggests that the methanol leaf extract of Clerodendrum volubile could serve as a potential source of antioxidants and can be explored as a therapeutic agent in free radical induced diseases.

Pharmacognostic evaluation of stem bark and leaves of Anogeissus pendula Edgew

Background: Anogeissus pendula Edgew has ethnomedicinal importance in various parts of India. It is used in diarrhoea, dysentery, cough, wound healing, burns, skin diseases and gastric disorder. No attempts have been made regarding pharmacognostic investigation of the plant till date. Aim: The present study aimed to perform the pharmacognostic study of leaf and stem bark of Anogeissus pendula Edgew. Settings and Design: The study was designed in accordance with standard procedures. Materials and Methods: Pharmacognostic studies viz. organoleptic, macroscopic, microscopic, physicochemical and chromatographic fingerprinting on fresh and dried plant parts along with the hydroalcoholic extracts were conducted. Results and Conclusions: A. pendula has dorsiventral oblanceolate to obovate leaves arranged in opposite pairs while the stem bark has rough appearance and ash to greyish white in colour. Leaves have anomocytic type of stomata. The characteristic microscopic features of leaves were observed to be epidermal cells, palisade and spongy parenchyma, vascular bundles, xylem and phloem cells. Stem bark microscopy revealed the presence of periderm, secondary cortex and secondary phloem. Chromatographic fingerprinting of extracts showed the presence of flavonoids (Rutin and Quercetin) and they were quantified. Rutin was found to be 6.23% w/w in leaves and 9.97% w/w in stem bark extract while Quercetin to be 27.29% w/w and 51.62% respectively. The present study evaluated various pharmacognostic parameters which will help in quality control (standardization) of A. pendula Edgew in crude form, in herbal formulations and also aid in the preparation of an herbal monograph for the species.

Radio Frequency Fingerprint Extraction of Radio Emitter Based on I/Q Imbalance

Specific emitter identification use external signal feature called radio frequency fingerprint to identify the different radio transmitter, which does not rely on information content. A radio frequency fingerprint feature extraction approach based on I/Q imbalance of quadrature modulation signal is proposed. A I/Q modulator model is utilized to investigate the sources of radio frequency fingerprint and the effect on signal. A fingerprint features extraction based on signal space is proposed, but the SNR (Signal to Noise Ratio) need to be estimated before. Simulation results demonstrate that the method have superior performance than previous bispectrum-based, Hibert-Huang transform-based approaches.

A robust and low-cost video fingerprint extraction method for copy detection

Video fingerprinting for content-based video identification is a very useful task for the management and monetization of copyrighted content distribution. The main challenges of monitoring and copy detection systems are: a) the effective identification of highly transformed videos (robustness) and b) computational efficiency which may be relevant for some applications. Typically, most video fingerprinting methods focus on robustness leaving aside computational efficiency. However, for real-time applications are necessary low computational cost detection methods, for instance, in illegal content monitoring in video streaming distributions. Therefore, in this paper, we propose a low-cost and effective video fingerprint extraction method based on the combination of content-based features using both acoustic and visual video components. Our method is capable of detecting video copies by using computationally efficient fingerprints while maintaining robustness against the decrease in quality and content preserved distortions, which are frequent but severe attacks.

Chromatographic fingerprinting and free-radical scavenging activity of ethanol extracts of Muntingia calabura L. leaves and stems

ObjectiveTo determine the thin-layer chromatography (TLC) fingerprint profiles and to evaluate the in vitro antioxidant activity of ethanol extracts of Muntingia calabura (M. calabura) leaves and stems. MethodsThe leaves and stems were extracted using ethanol as solvent. The TLC separation of the phytochemical constituents of the leaf and ethanol extracts was carried out in ethyl acetate: n-hexane and chloroform: ethyl acetate mobile phase systems. Distinct spots were visualized under visible light, UV 254 nm, UV 366 nm and after spraying with vanillin-sulfuric acid. The 2,2-diphenyl-1-picrylhydrazyl free-radical scavenging assay was used to evaluate the antioxidant activity of the extracts. ResultsBoth the leaf and stem ethanol extracts at 4 mg/mL exhibited 2,2-diphenyl-1-picrylhydrazyl inhibition of more than 90%, relative to gallic acid. The results of TLC showed that the degree of resolution between the constituent spots was comparable between the two mobile phase systems using the different visualization wavelengths. Under the 254 nm visualization, few spots were observed in leaf and stem extracts. Visualization at 366 nm yielded the greatest number of observable spots of various colors in both leaf and stem extracts. More spots were visualized upon post-derivatization with vanillin-sulfuric acid in the TLC chromatograms using chloroform: ethyl acetate mobile phase, compared to those in ethyl acetate: n-hexane mobile phase. ConclusionsM. calabura exhibited very high antioxidant activity in its leaves and stems ethanol extracts, both of which are used in traditional medicine. The TLC results demonstrated the presence of diverse secondary metabolites in the leaf and stem ethanol extracts, indicating that the antioxidant activity, including other bioactivities may be attributed to these phytochemical constituents. This paper has reported for the first time the TLC fingerprinting of M. calabura using visible light, UV 254 nm, UV 366 and post-derivatization with vanillin-spray to visualize separate spots on TLC plates.