43 CFR 423.25 - Vandalism, tampering, and theft.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Vandalism, tampering, and theft. 423.25 Section 423.25 Public Lands: Interior Regulations Relating to Public Lands BUREAU OF RECLAMATION... of Conduct § 423.25 Vandalism, tampering, and theft. (a) You must not tamper or attempt to tamper...

Tamper indicating bolt

DOEpatents

Blagin, Sergei V.; Barkanov, Boris P.

2004-09-14

A tamper-indicating fastener has a cylindrical body with threads extending from one end along a portion of the body, and a tamper indicating having a transducer for converting physical properties of the body into electronic data; electronics for recording the electronic data; and means for communicating the recorded information to a remote location from said fastener. The electronics includes a capacitor that varies as a function of force applied by the fastener, and non-volatile memory for recording instances when the capacitance varies, providing an indication of unauthorized access.

Evidence of tampering in watermark identification

NASA Astrophysics Data System (ADS)

McLauchlan, Lifford; Mehrübeoglu, Mehrübe

2009-08-01

In this work, watermarks are embedded in digital images in the discrete wavelet transform (DWT) domain. Principal component analysis (PCA) is performed on the DWT coefficients. Next higher order statistics based on the principal components and the eigenvalues are determined for different sets of images. Feature sets are analyzed for different types of attacks in m dimensional space. The results demonstrate the separability of the features for the tampered digital copies. Different feature sets are studied to determine more effective tamper evident feature sets. The digital forensics, the probable manipulation(s) or modification(s) performed on the digital information can be identified using the described technique.

Tamper to delay motion and decrease ionization of a sample during short pulse x-ray imaging

DOEpatents

London, Richard A [Orinda, CA; Szoke,; Abraham, Hau-Riege [Fremont, CA; Stefan P. , Chapman; Henry, N [Livermore, CA

2007-06-26

A system for x-ray imaging of a small sample comprising positioning a tamper so that it is operatively connected to the sample, directing short intense x-ray pulses onto the tamper and the sample, and detecting an image from the sample. The tamper delays the explosive motion of the sample during irradiation by the short intense x-ray pulses, thereby extending the time to obtain an x-ray image of the original structure of the sample.

40 CFR 205.58-2 - Tampering.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Tampering. 205.58-2 Section 205.58-2 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS TRANSPORTATION EQUIPMENT NOISE EMISSION CONTROLS Medium and Heavy Trucks § 205.58-2 Tampering. (a) For each configuration...

Integrated optical tamper sensor with planar waveguide

DOEpatents

Carson, Richard F.; Casalnuovo, Stephen A.

1993-01-01

A monolithic optical tamper sensor, comprising an optical emitter and detector, connected by an optical waveguide and placed into the critical entry plane of an enclosed sensitive region, the tamper sensor having a myriad of scraps of a material optically absorbent at the wavelength of interest, such that when the absorbent material is in place on the waveguide, an unique optical signature can be recorded, but when entry is attempted into the enclosed sensitive region, the scraps of absorbent material will be displaced and the optical/electrical signature of the tamper sensor will change and that change can be recorded.

Integrated optical tamper sensor with planar waveguide

DOEpatents

Carson, R.F.; Casalnuovo, S.A.

1993-01-05

A monolithic optical tamper sensor, comprising an optical emitter and detector, connected by an optical waveguide and placed into the critical entry plane of an enclosed sensitive region, the tamper sensor having a myriad of scraps of a material optically absorbent at the wavelength of interest, such that when the absorbent material is in place on the waveguide, an unique optical signature can be recorded, but when entry is attempted into the enclosed sensitive region, the scraps of absorbent material will be displaced and the optical/electrical signature of the tamper sensor will change and that change can be recorded.

Tamper indicating gold nanocup plasmonic films

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeVetter, Brent M.; Bernacki, Bruce E.; Bennett, Wendy D.

The spectral signature of nanoplasmonic films are both robust and tailorable with optical responses ranging from the visible to the near-infrared. We present the development of flexible, elastomeric nanoplasmonic films consisting of periodic arrays of gold nanocups as tamper indicating films. Gold nanocups have polarization-sensitive optical properties that may be manufactured into films that offer unique advantages for tamper indication. These flexible films can be made quickly and at low-cost using commercially available monodisperse polystyrene nanospheres through self-assembly followed by plasma etching, metal deposition, and lift-off from a sacrificial substrate. Polarization- and angle-dependent optical spectroscopic measurements were performed to characterizemore » the fabricated films. Furthermore, using polarization-sensitive hyperspectral imaging, we demonstrate how these films can be applied to tamper indication and counterfeit resistance applications.« less

Tamper indicating gold nanocup plasmonic films

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeVetter, Brent M.; Bernacki, Bruce E.; Bennett, Wendy D.

2017-02-13

The spectral signature of nanoplasmonic films are both robust and tailorable with optical responses ranging from the visible to the near-infrared. We present the development of flexible, elastomeric nanoplasmonic films consisting of periodic arrays of gold nanocups as tamper indicating films. Gold nanocups have polarization-sensitive optical properties that may be manufactured into films that offer unique advantages for tamper indication. These flexible films can be made quickly and at low-cost using commercially available monodisperse polystyrene nanospheres through self-assembly followed by plasma etching, metal deposition, and lift-off from a sacrificial substrate. Polarization- and angle-dependent optical spectroscopic measurements were performed to characterizemore » the fabricated films. Using polarization-sensitive hyperspectral imaging, we demonstrate how these films can be applied to tamper indication and counterfeit resistance applications.« less

Enhanced tamper indicator

DOEpatents

Garcia, Anthony R.; Johnston, Roger G.

2003-07-08

The present invention provides an apparatus and method whereby the reliability and tamper-resistance of tamper indicators can be improved. A flexible connector may be routed through a latch for an enclosure such as a door or container, and the free ends of the flexible connector may be passed through a first locking member and firmly attached to an insert through the use of one or more attachment members such as set screws. A second locking member may then be assembled in interlocking relation with the first locking member to form an interlocked assembly around the insert. The insert may have one or more sharp projections extending toward the first or second locking member so that any compressive force applied in an attempt to disassemble the interlocked assembly results in permanent, visible damage to the first or second locking member.

36 CFR 2.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 36 Parks, Forests, and Public Property 1 2014-07-01 2014-07-01 false Trespassing, tampering and... INTERIOR RESOURCE PROTECTION, PUBLIC USE AND RECREATION § 2.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property...

36 CFR 2.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 36 Parks, Forests, and Public Property 1 2013-07-01 2013-07-01 false Trespassing, tampering and... INTERIOR RESOURCE PROTECTION, PUBLIC USE AND RECREATION § 2.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property...

36 CFR 2.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 36 Parks, Forests, and Public Property 1 2011-07-01 2011-07-01 false Trespassing, tampering and... INTERIOR RESOURCE PROTECTION, PUBLIC USE AND RECREATION § 2.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property...

36 CFR 2.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 36 Parks, Forests, and Public Property 1 2012-07-01 2012-07-01 false Trespassing, tampering and... INTERIOR RESOURCE PROTECTION, PUBLIC USE AND RECREATION § 2.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property...

36 CFR 2.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Trespassing, tampering and... INTERIOR RESOURCE PROTECTION, PUBLIC USE AND RECREATION § 2.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property...

36 CFR 1002.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 36 Parks, Forests, and Public Property 3 2011-07-01 2011-07-01 false Trespassing, tampering and..., PUBLIC USE AND RECREATION § 1002.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property or real property not open...

36 CFR 1002.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 36 Parks, Forests, and Public Property 3 2012-07-01 2012-07-01 false Trespassing, tampering and..., PUBLIC USE AND RECREATION § 1002.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property or real property not open...

36 CFR 1002.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 36 Parks, Forests, and Public Property 3 2014-07-01 2014-07-01 false Trespassing, tampering and..., PUBLIC USE AND RECREATION § 1002.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property or real property not open...

36 CFR 1002.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Trespassing, tampering and..., PUBLIC USE AND RECREATION § 1002.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property or real property not open...

A Secure and Robust Approach to Software Tamper Resistance

NASA Astrophysics Data System (ADS)

Ghosh, Sudeep; Hiser, Jason D.; Davidson, Jack W.

Software tamper-resistance mechanisms have increasingly assumed significance as a technique to prevent unintended uses of software. Closely related to anti-tampering techniques are obfuscation techniques, which make code difficult to understand or analyze and therefore, challenging to modify meaningfully. This paper describes a secure and robust approach to software tamper resistance and obfuscation using process-level virtualization. The proposed techniques involve novel uses of software check summing guards and encryption to protect an application. In particular, a virtual machine (VM) is assembled with the application at software build time such that the application cannot run without the VM. The VM provides just-in-time decryption of the program and dynamism for the application's code. The application's code is used to protect the VM to ensure a level of circular protection. Finally, to prevent the attacker from obtaining an analyzable snapshot of the code, the VM periodically discards all decrypted code. We describe a prototype implementation of these techniques and evaluate the run-time performance of applications using our system. We also discuss how our system provides stronger protection against tampering attacks than previously described tamper-resistance approaches.

An Efficient Semi-fragile Watermarking Scheme for Tamper Localization and Recovery

NASA Astrophysics Data System (ADS)

Hou, Xiang; Yang, Hui; Min, Lianquan

2018-03-01

To solve the problem that remote sensing images are vulnerable to be tampered, a semi-fragile watermarking scheme was proposed. Binary random matrix was used as the authentication watermark, which was embedded by quantizing the maximum absolute value of directional sub-bands coefficients. The average gray level of every non-overlapping 4×4 block was adopted as the recovery watermark, which was embedded in the least significant bit. Watermarking detection could be done directly without resorting to the original images. Experimental results showed our method was robust against rational distortions to a certain extent. At the same time, it was fragile to malicious manipulation, and realized accurate localization and approximate recovery of the tampered regions. Therefore, this scheme can protect the security of remote sensing image effectively.

Triboluminescent tamper-indicating device

DOEpatents

Johnston, Roger G.; Garcia, Anthony R. E.

2002-01-01

A tamper-indicating device is described. The device has a transparent or translucent cylindrical body that includes triboluminescent material, and an outer opaque layer that prevents ambient light from entering. A chamber in the body holds an undeveloped piece of photographic film bearing an image. The device is assembled from two body members. One of the body members includes a recess for storing film and an optical assembly that can be adjusted to prevent light from passing through the assembly and exposing the film. To use the device with a hasp, the body members are positioned on opposite sides of a hasp, inserted through the hasp, and attached. The optical assembly is then manipulated to allow any light generated from the triboluminescent materials during a tampering activity that damages the device to reach the film and destroy the image on the film.

Ranking of sabotage/tampering avoidance technology alternatives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, W.B.; Tabatabai, A.S.; Powers, T.B.

1986-01-01

Pacific Northwest Laboratory conducted a study to evaluate alternatives to the design and operation of nuclear power plants, emphasizing a reduction of their vulnerability to sabotage. Estimates of core melt accident frequency during normal operations and from sabotage/tampering events were used to rank the alternatives. Core melt frequency for normal operations was estimated using sensitivity analysis of results of probabilistic risk assessments. Core melt frequency for sabotage/tampering was estimated by developing a model based on probabilistic risk analyses, historic data, engineering judgment, and safeguards analyses of plant locations where core melt events could be initiated. Results indicate the most effectivemore » alternatives focus on large areas of the plant, increase safety system redundancy, and reduce reliance on single locations for mitigation of transients. Less effective options focus on specific areas of the plant, reduce reliance on some plant areas for safe shutdown, and focus on less vulnerable targets.« less

Reversible Data Hiding in FTIR Microspectroscopy Images with Tamper Indication and Payload Error Correction

PubMed Central

Seppänen, Tapio

2017-01-01

Fourier transform infrared (FTIR) microspectroscopy images contain information from the whole infrared spectrum used for microspectroscopic analyses. In combination with the FTIR image, visible light images are used to depict the area from which the FTIR spectral image was sampled. These two images are traditionally acquired as separate files. This paper proposes a histogram shifting-based data hiding technique to embed visible light images in FTIR spectral images producing single entities. The primary objective is to improve data management efficiency. Secondary objectives are confidentiality, availability, and reliability. Since the integrity of biomedical data is vital, the proposed method applies reversible data hiding. After extraction of the embedded data, the FTIR image is reversed to its original state. Furthermore, the proposed method applies authentication tags generated with keyed Hash-Based Message Authentication Codes (HMAC) to detect tampered or corrupted areas of FTIR images. The experimental results show that the FTIR spectral images carrying the payload maintain good perceptual fidelity and the payload can be reliably recovered even after bit flipping or cropping attacks. It has been also shown that extraction successfully removes all modifications caused by the payload. Finally, authentication tags successfully indicated tampered FTIR image areas. PMID:29259987

Ephemeral profiles of prescription drug and formulation tampering: evolving pseudoscience on the Internet.

PubMed

Cone, Edward J

2006-06-01

The magnitude of non-therapeutic use, or misuse of prescription pharmaceuticals now rivals that of illicit drug abuse. Drug and formulation tampering enables misusers to administer higher doses by intended and non-intended routes. Perceived motives appear to be a combination of interests in achieving a faster onset and enhancing psychoactive effects. Narcotic analgesics, stimulants, and depressants are widely sought, examined, and tampered with for recreational use. This review examines tampering methods reported on the Internet for selected pharmaceutical products. The Internet provides broad and varied guidance on tampering methods that are specific to drug classes and unique formulations. Instructions are available on crushing, separating, purifying and chemically altering specific formulations to allow changes in dosage, route of administration, and time course of effects. Many pharmaceutical formulations contain features that serve as "barriers" to tampering. The nature and effectiveness of formulation barriers vary widely with many being overcome by adventurous misusers. Examples of successes and failures in tampering attempts are frequently described on Internet sites that support recreational drug use. Successful tampering methods that have widespread appeal evolve into recipes and become archived on multiple websites. Examples of tampering methods include: (1) how to separate narcotic drugs (codeine, hydrocodone, oxycodone) from excipients and non-desirable actives (aspirin, acetaminophen, ibuprofen); (2) overcoming time-release formulations (beads, layers, matrices); (3) removal of active drug from high-dose formulations (patches, pills); (4) alteration of dosage forms for alternate routes of administration. The development of successful formulations that inhibit or prevent drug/formulation tampering with drugs of abuse should take into consideration the scope and practice of tampering methods available to recreational drug users on the Internet.

36 CFR § 1002.31 - Trespassing, tampering and vandalism.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 36 Parks, Forests, and Public Property 3 2013-07-01 2012-07-01 true Trespassing, tampering and... PROTECTION, PUBLIC USE AND RECREATION § 1002.31 Trespassing, tampering and vandalism. (a) The following are prohibited: (1) Trespassing. Trespassing, entering or remaining in or upon property or real property not open...

50 CFR 27.65 - Tampering with vehicles and equipment.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 50 Wildlife and Fisheries 8 2011-10-01 2011-10-01 false Tampering with vehicles and equipment. 27.65 Section 27.65 Wildlife and Fisheries UNITED STATES FISH AND WILDLIFE SERVICE, DEPARTMENT OF THE INTERIOR (CONTINUED) THE NATIONAL WILDLIFE REFUGE SYSTEM PROHIBITED ACTS Disturbing Violations: Against Nonwildlife Property § 27.65 Tampering with...

50 CFR 27.65 - Tampering with vehicles and equipment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 50 Wildlife and Fisheries 9 2012-10-01 2012-10-01 false Tampering with vehicles and equipment. 27.65 Section 27.65 Wildlife and Fisheries UNITED STATES FISH AND WILDLIFE SERVICE, DEPARTMENT OF THE INTERIOR (CONTINUED) THE NATIONAL WILDLIFE REFUGE SYSTEM PROHIBITED ACTS Disturbing Violations: Against Nonwildlife Property § 27.65 Tampering with...

25 CFR 11.440 - Tampering with or fabricating physical evidence.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 1 2014-04-01 2014-04-01 false Tampering with or fabricating physical evidence. 11.440 Section 11.440 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAW AND ORDER COURTS OF INDIAN OFFENSES AND LAW AND ORDER CODE Criminal Offenses § 11.440 Tampering with or fabricating physical evidence...

25 CFR 11.440 - Tampering with or fabricating physical evidence.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 1 2011-04-01 2011-04-01 false Tampering with or fabricating physical evidence. 11.440 Section 11.440 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAW AND ORDER COURTS OF INDIAN OFFENSES AND LAW AND ORDER CODE Criminal Offenses § 11.440 Tampering with or fabricating physical evidence...

Secure RFID tag or sensor with self-destruction mechanism upon tampering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nekoogar, Faranak; Dowla, Farid; Twogood, Richard

A circuit board anti-tamper mechanism comprises a circuit board having a frangible portion, a trigger having a trigger spring, a trigger arming mechanism actuated by the trigger wherein the trigger arming mechanism is initially non-actuated, a force producing mechanism, a latch providing mechanical communication between the trigger arming mechanism and the force producing mechanism, wherein the latch initially retains the force producing mechanism in a refracted position. Arming pressure applied to the trigger sufficient to overcome the trigger spring force will actuate the trigger arming mechanism, causing the anti-tamper mechanism to be armed. Subsequent tampering with the anti-tamper mechanism resultsmore » in a decrease of pressure on the trigger below the trigger spring force, thereby causing the trigger arming mechanism to actuate the latch, thereby releasing the force producing mechanism to apply force to the frangible portion of the circuit board, thereby breaking the circuit board.« less

Towards the development of tamper-resistant, ground-based mobile sensor nodes

NASA Astrophysics Data System (ADS)

Mascarenas, David; Stull, Christopher; Farrar, Charles

2011-11-01

Mobile sensor nodes hold great potential for collecting field data using fewer resources than human operators would require and potentially requiring fewer sensors than a fixed-position sensor array. It would be very beneficial to allow these mobile sensor nodes to operate unattended with a minimum of human intervention. In order to allow mobile sensor nodes to operate unattended in a field environment, it is imperative that they be capable of identifying and responding to external agents that may attempt to tamper with, damage or steal the mobile sensor nodes, while still performing their data collection mission. Potentially hostile external agents could include animals, other mobile sensor nodes, or humans. This work will focus on developing control policies to help enable a mobile sensor node to identify and avoid capture by a hostile un-mounted human. The work is developed in a simulation environment, and demonstrated using a non-holonomic, ground-based mobile sensor node. This work will be a preliminary step toward ensuring the cyber-physical security of ground-based mobile sensor nodes that operate unattended in potentially unfriendly environments.

DEVELOPMENT OF A CERAMIC TAMPER INDICATING SEAL: SRNL CONTRIBUTIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krementz, D.; Brinkman, K.; Martinez-Rodriguez, M.

2013-06-03

Savannah River National Laboratory (SRNL) and Sandia National Laboratories (SNL) are collaborating on development of a Ceramic Seal, also sometimes designated the Intrinsically Tamper Indicating Ceramic Seal (ITICS), which is a tamper indicating seal for international safeguards applications. The Ceramic Seal is designed to be a replacement for metal loop seals that are currently used by the IAEA and other safeguards organizations. The Ceramic Seal has numerous features that enhance the security of the seal, including a frangible ceramic body, protective and tamper indicating coatings, an intrinsic unique identifier using Laser Surface Authentication, electronics incorporated into the seal that providemore » cryptographic seal authentication, and user-friendly seal wire capture. A second generation prototype of the seal is currently under development whose seal body is of Low Temperature Co-fired Ceramic (LTCC) construction. SRNL has developed the mechanical design of the seal in an iterative process incorporating comments from the SNL vulnerability review team. SRNL is developing fluorescent tamper indicating coatings, with recent development focusing on optimizing the durability of the coatings and working with a vendor to develop a method to apply coatings on a 3-D surface. SRNL performed a study on the effects of radiation on the electronics of the seal and possible radiation shielding techniques to minimize the effects. SRNL is also investigating implementation of Laser Surface Authentication (LSA) as a means of unique identification of each seal and the effects of the surface coatings on the LSA signature.« less

Tamper-Resistant Mobile Health Using Blockchain Technology

PubMed Central

2017-01-01

Background Digital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials. Objective The aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network. Methods We developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults. Results Electronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network. Conclusions Blockchain serves as a tamperproof system for m

Tamper-Resistant Mobile Health Using Blockchain Technology.

PubMed

Ichikawa, Daisuke; Kashiyama, Makiko; Ueno, Taro

2017-07-26

Digital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials. The aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network. We developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults. Electronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network. Blockchain serves as a tamperproof system for mHealth. Combining mHealth with blockchain technology may

40 CFR 205.173-2 - Tampering.

Code of Federal Regulations, 2010 CFR

2010-07-01

... removal or puncturing the muffler, baffles, header pipes, or any other component which conducts exhaust... EQUIPMENT NOISE EMISSION CONTROLS Motorcycle Exhaust Systems § 205.173-2 Tampering. The manufacturer must... exhaust system which causes the motorcycle to exceed the Federal noise standard. Use of the motorcycle...

The indirect detection of bleach (sodium hypochlorite) in beverages as evidence of product tampering.

PubMed

Jackson, David S; Crockett, David F; Wolnik, Karen A

2006-07-01

Bleach (sodium hypochlorite) has been identified as the adulterant in a relatively large number of product tamperings that have been investigated by the Forensic Chemistry Center (FCC) of the U.S. Food and Drug Administration. In this work, household bleach was added to 23 different beverages at each of three levels. The impact of sodium hypochlorite on these beverages over a 13-day study period was evaluated using the following techniques: diphenylamine spot test for oxidizing agents, potassium iodide-starch test paper for oxidizing agents, pH, iodometric titration for quantitating hypochlorite, ion chromatography for chloride and chlorate quantitation, automated headspace sampling with gas chromatography-flame ionization detection (GC-FID) for determination of chloroform, and visual and organoleptic observations. This study has shown that hypochlorite is fragile when added to most common beverages and typically breaks down either partially or completely over time. In cases where a beverage is suspected of being adulterated with bleach but tests for hypochlorite are negative, it is still possible to characterize the product to demonstrate that the results are consistent with the addition of bleach. An adulterated product will give a positive test for oxidizing agents using the diphenylamine spot test. It is likely that the pH of the adulterated product will be higher than a control of that product. Ion chromatographic analysis shows elevated chloride and chlorate as compared with a control. And, chloroform may also be detected by GC-FID especially if the beverage that was adulterated contains citric acid.

Detection of shifted double JPEG compression by an adaptive DCT coefficient model

NASA Astrophysics Data System (ADS)

Wang, Shi-Lin; Liew, Alan Wee-Chung; Li, Sheng-Hong; Zhang, Yu-Jin; Li, Jian-Hua

2014-12-01

In many JPEG image splicing forgeries, the tampered image patch has been JPEG-compressed twice with different block alignments. Such phenomenon in JPEG image forgeries is called the shifted double JPEG (SDJPEG) compression effect. Detection of SDJPEG-compressed patches could help in detecting and locating the tampered region. However, the current SDJPEG detection methods do not provide satisfactory results especially when the tampered region is small. In this paper, we propose a new SDJPEG detection method based on an adaptive discrete cosine transform (DCT) coefficient model. DCT coefficient distributions for SDJPEG and non-SDJPEG patches have been analyzed and a discriminative feature has been proposed to perform the two-class classification. An adaptive approach is employed to select the most discriminative DCT modes for SDJPEG detection. The experimental results show that the proposed approach can achieve much better results compared with some existing approaches in SDJPEG patch detection especially when the patch size is small.

Internet pseudoscience: Testing opioid containing formulations with tampering potential.

PubMed

Pascali, Jennifer P; Fais, Paolo; Vaiano, Fabio; Pigaiani, Nicola; D'Errico, Stefano; Furlanetto, Sandra; Palumbo, Diego; Bertol, Elisabetta

2018-05-10

Drug tampering practices, with the aim to increase availability of drug delivery and/or enhance drug effects, are accessible on Internet and are practiced by some portion of recreational drug users. Not rarely, recreational misuse may result in toxic and even fatal results. The aim of the present study was to assess the tampering risk of medicaments containing different formulations of an opioid in combination with paracetamol or dexketoprofen, following the procedures reported in dedicated forums on the web. Tablets and suppositories containing codeine, tramadol and oxycodone were extracted following the reported "Cold water extraction"; dextromethorphan was extracted from cough syrup following the procedure reported as "Acid/base extraction" and fentanyl was extracted from transdermal patches according the procedure reported in Internet. The tampered products and opportunely prepared calibrators in water were analysed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The separation of the analytes was carried on Agilent ZORBAX Eclipse Plus C18 (RRHT 2.1 mm × 50 mm, 1.8 μm) by the gradient elution of 0.01% formic acid in water and 0.01% formic acid in methanol. Acquisition was by MRM mode considering at least two transitions for compound. Declared recoveries for these home-made extractions claimed to exceed 99% for the opioid and to complete remove paracetamol, often associated to liver toxicity and thus to obtain a "safer" preparation. In this study, the authors demonstrated that rarely the recoveries for the opioid reached 90% and that up to 60% of the paracetamol amount remained in solution. Thus, high risks for health remained both for the potential lethality of the opioid content, but also for the sub-lethal chronic use of these mixtures, which contained still uncontrolled, ignored, but often important amounts of paracetamol. Copyright © 2018 Elsevier B.V. All rights reserved.

49 CFR Appendix C to Part 218 - Statement of Agency Enforcement Policy on Tampering

Code of Federal Regulations, 2014 CFR

2014-10-01

... Tampering C Appendix C to Part 218 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Pt. 218, App. C Appendix C to Part 218—Statement of Agency Enforcement Policy on Tampering The Rail Safety Improvement Act...

49 CFR Appendix C to Part 218 - Statement of Agency Enforcement Policy on Tampering

Code of Federal Regulations, 2013 CFR

2013-10-01

... Tampering C Appendix C to Part 218 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Pt. 218, App. C Appendix C to Part 218—Statement of Agency Enforcement Policy on Tampering The Rail Safety Improvement Act...

49 CFR Appendix C to Part 218 - Statement of Agency Enforcement Policy on Tampering

Code of Federal Regulations, 2010 CFR

2010-10-01

... Tampering C Appendix C to Part 218 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RAILROAD OPERATING PRACTICES Pt. 218, App. C Appendix C to Part 218—Statement of Agency Enforcement Policy on Tampering The Rail Safety Improvement Act...

Optically resonant subwavelength films for tamper-indicating tags and seals

NASA Astrophysics Data System (ADS)

Alvine, Kyle J.; Suter, Jonathan D.; Bernacki, Bruce E.; Bennett, Wendy D.

2015-05-01

We present the design, modeling and performance of a proof-of-concept tamper indicating approach that exploits newlydeveloped subwavelength-patterned films. These films have a nanostructure-dependent resonant optical reflection that is wavelength, angle, and polarization dependent. As such, they can be tailored to fabricate overlay transparent films for tamper indication and authentication of sensitive or controlled materials not possible with currently-known technologies. An additional advantage is that the unique optical signature is dictated by the geometry and fabrication process of the nanostructures in the film, rather than on the material used. The essential structure unit in the subwavelength resonant coating is a nanoscale Open-Ring Resonator (ORR). This building block is fabricated by coating a dielectric nanoscale template with metal to form a hemispherical shell-like structure. This curved metallic shell structure has a cross-section with an intrinsic capacitance and inductance and is thus the optical equivalent to the well-known "LC" circuit where the capacitance and inductance are determined by the nanoshell dimensions. For structures with sub 100 nm scale, this resonance occurs in the visible electromagnetic spectrum, and in the IR for larger shells. Tampering of the film would be visible though misalignment of the angle-sensitive features in the film. It is additionally possible to add in intrinsic oxidation and strain sensitive matrix materials to further complicate tamper repair and counterfeiting. Cursory standoff readout would be relatively simple using a combination of a near-infrared (or visible) LED flashlight and polarizer or passively using room lighting illumination and a dispersive detector.

Active Time Domain Reflectometry for Tamper Indication in Unattended Safeguards Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheen, David M.; Smith, Leon E.; Tedeschi, Jonathan R.

2015-07-14

The International Atomic Energy Agency (IAEA) continues to expand its use of unattended measurement systems. An increasing number of systems and an expanding family of instruments create challenges in terms of deployment efficiency and the implementation of data authentication measures. In collaboration with the IAEA, tamper-indicating measures to address data-transmission authentication challenges with unattended safeguards systems are under investigation. Pacific Northwest National Laboratory is studying the viability of active time-domain reflectometry (TDR) along two parallel but interconnected paths: (1) swept-frequency TDR as the highly flexible, laboratory gold standard to which field-deployable options can be compared, and (2) a low-cost commerciallymore » available spread-spectrum TDR technology as one option for field implementation. This paper describes the TDR methods under investigation and the associated benchtop test-bed, tampering scenarios of interest,, and viability measurement results to date (e.g., comparison of relative sensitivity to tamper scenarios).« less

Adolescent pedometer protocols: examining reactivity, tampering and participants' perceptions.

PubMed

Scott, Joseph John; Morgan, Philip James; Plotnikoff, Ronald Cyril; Trost, Stewart Graeme; Lubans, David Revalds

2014-01-01

The aim of this study was to investigate adolescents' potential reactivity and tampering while wearing pedometers by comparing different monitoring protocols to accelerometer output. The sample included adolescents (N = 123, age range = 14-15 years) from three secondary schools in New South Wales, Australia. Schools were randomised to one of the three pedometer monitoring protocols: (i) daily sealed (DS) pedometer group, (ii) unsealed (US) pedometer group or (iii) weekly sealed (WS) pedometer group. Participants wore pedometers (Yamax Digi-Walker CW700, Yamax Corporation, Kumamoto City, Japan) and accelerometers (Actigraph GT3X+, Pensacola, USA) simultaneously for seven days. Repeated measures analysis of variance was used to examine potential reactivity. Bivariate correlations between step counts and accelerometer output were calculated to explore potential tampering. The correlation between accelerometer output and pedometer steps/day was strongest among participants in the WS group (r = 0.82, P ≤ 0.001), compared to the US (r = 0.63, P ≤ 0.001) and DS (r = 0.16, P = 0.324) groups. The DS (P ≤ 0.001) and US (P = 0.003), but not the WS (P = 0.891), groups showed evidence of reactivity. The results suggest that reactivity and tampering does occur in adolescents and contrary to existing research, pedometer monitoring protocols may influence participant behaviour.

21 CFR 211.132 - Tamper-evident packaging requirements for over-the-counter (OTC) human drug products.

Code of Federal Regulations, 2014 CFR

2014-04-01

... dermatological, dentifrice, insulin, or lozenge product) for retail sale that is not packaged in a tamper..., dentifrice, insulin, or lozenge product) for retail sale shall package the product in a tamper-evident...

21 CFR 211.132 - Tamper-evident packaging requirements for over-the-counter (OTC) human drug products.

Code of Federal Regulations, 2012 CFR

2012-04-01

... dermatological, dentifrice, insulin, or lozenge product) for retail sale that is not packaged in a tamper..., dentifrice, insulin, or lozenge product) for retail sale shall package the product in a tamper-evident...

21 CFR 211.132 - Tamper-evident packaging requirements for over-the-counter (OTC) human drug products.

Code of Federal Regulations, 2013 CFR

2013-04-01

... dermatological, dentifrice, insulin, or lozenge product) for retail sale that is not packaged in a tamper..., dentifrice, insulin, or lozenge product) for retail sale shall package the product in a tamper-evident...

21 CFR 211.132 - Tamper-evident packaging requirements for over-the-counter (OTC) human drug products.

Code of Federal Regulations, 2010 CFR

2010-04-01

... dermatological, dentifrice, insulin, or lozenge product) for retail sale that is not packaged in a tamper..., dentifrice, insulin, or lozenge product) for retail sale shall package the product in a tamper-evident...

21 CFR 211.132 - Tamper-evident packaging requirements for over-the-counter (OTC) human drug products.

Code of Federal Regulations, 2011 CFR

2011-04-01

... dermatological, dentifrice, insulin, or lozenge product) for retail sale that is not packaged in a tamper..., dentifrice, insulin, or lozenge product) for retail sale shall package the product in a tamper-evident...

Test-Tampering Found Rampant in Atlanta System

ERIC Educational Resources Information Center

Samuels, Christina A.

2011-01-01

The author reports on a state investigation into Atlanta's impressive gains on state tests which finds that test-tampering was rampant in the much-praised school system. The report unveiled by the Georgia governor's office states that Atlanta teachers and principals for years methodically altered answer sheets for students taking state tests,…

Using Focus Groups to Study Consumer Understanding and Experiences with Tamper-Evident Packaging Devices

ERIC Educational Resources Information Center

Pascall, Melvin A.; Lee, Ken; Fraser, Angela; Halim, Linna

2009-01-01

A focus group with an educational component was used to help initiate a new research hypothesis. Early-stage development of a new tamper-evident invention was improved with input from a consumer focus group. The focus group comprised consumers who were shown several tamper-evident devices, including a new color-changing cap under active…

Reusable, tamper-indicating seal

DOEpatents

Ryan, Michael J.

1978-01-01

A reusable, tamper-indicating seal comprises a drum confined within a fixed body and rotatable in one direction therewithin, the top of the drum constituting a tray carrying a large number of small balls of several different colors. The fixed body contains parallel holes for looping a seal wire therethrough. The base of the drums carries cams adapted to coact with cam followers to lock the wire within the seal at one angular position of the drum. A channel in the fixed body -- visible from outside the seal -- adjacent the tray constitutes a segregated location for a small plurality of the colored balls. A spring in the tray forces colored balls into the segregated location at one angular position of the drum, further rotation securing the balls in position and the wires in the seal. A wedge-shaped plough removes the balls from the segregated location, at a different angular position of the drum, the wire being unlocked at the same position. A new pattern of colored balls will appear in the segregated location when the seal is relocked.

A comparison among tapentadol tamper-resistant formulations (TRF) and OxyContin® (non-TRF) in prescription opioid abusers

PubMed Central

Vosburg, Suzanne K.; Jones, Jermaine D.; Manubay, Jeanne M.; Ashworth, Judy B.; Shapiro, Douglas Y.; Comer, Sandra D.

2013-01-01

Aims To examine whether tamper-resistant formulations (TRFs) of tapentadol hydrochloride ER 50 mg (TAP50) and tapentadol hydrochloride 250 mg (TAP250) could be converted into forms amenable to intranasal (Study 1) or intravenous abuse (Study 2). Design Randomized, repeated-measures study designs were employed. A non-TRF of OxyContin® 40 mg (OXY40) served as a positive control. No drug was taken in either study. Setting The studies took place in an outpatient setting in New York, NY. Participants 25 experienced, healthy extended-release oxycodone abusers participated in each study. Measurements The primary outcome for Study 1 was percentage of participants who indicated they would snort the tampered tablets, while the primary outcome for Study 2 was percent yield of active drug in solution. Other descriptive variables such as time spent manipulating the tablets were also examined to better characterize tampering behaviors. Findings Tampered TRF tablets were less desirable than the tampered OXY40 tablets. Few individuals were willing to snort the TRF particles (TAP50: 24%, TAP250: 16%; OXY40: 100% p<.001). There was less drug extracted from the TAP50 tablet than from the OXY40 tablet (3.5% vs. 37.0%, p=.008), and no samples from the TAP250 tablets contained analyzable solutions of the drug. It took participants longer to tamper with the TAPs (Study 1: TAP50 vs. OXY40, p<.01; TAP250 vs. OXY40, p<.01; Study 2: TAP250 vs. OXY40, p<05). Conclusions Taptentadol TRF tablets were not well-liked by individuals who regularly tampered with extended-release oxycodone tablets. Employing tamper resistant technology may be a promising approach towards reducing the abuse potential of tapentadol ER. PMID:23316699

Reusable tamper-indicating security seal

DOEpatents

Ryan, Michael J.

1983-01-01

The invention teaches means for detecting unauthorized tampering or substitutions of a device, and has particular utility when applied on a "seal" device used to secure a location or thing. The seal has a transparent body wall, and a first indicia, viz., a label identification is formed on the inside surface of this wall. Second and third indicia are formed on the outside surface of the transparent wall, and each of these indicia is transparent to allow the parallax angled viewing of the first indicia through these indicia. The second indicia is in the form of a broadly uniform pattern, viz, many small spaced dots; while the third indicia is in the form of easily memorized objects, such as human faces, made on a substrate by means of halftone printing. The substrate is lapped over the outside surface of the transparent wall. A thin cocoon of a transparent material, generally of the same material as the substrate such as plastic, is formed over the seal body and specifically over the transparent wall and the second and third indicia formed thereon. This cocoon is seamless and has walls of nonuniform thickness. Both the genuineness of the seal and whether anyone has attempted to compromise the seal can thus be visually determined upon inspection.

Digital image modification detection using color information and its histograms.

PubMed

Zhou, Haoyu; Shen, Yue; Zhu, Xinghui; Liu, Bo; Fu, Zigang; Fan, Na

2016-09-01

The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. Copyright © 2016. Published by Elsevier Ireland Ltd.

50 CFR 27.65 - Tampering with vehicles and equipment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... INTERIOR (CONTINUED) THE NATIONAL WILDLIFE REFUGE SYSTEM PROHIBITED ACTS Disturbing Violations: Against... motor vehicle, boat, equipment or machinery or attempting to tamper with, enter, or start any motor vehicle, boat, equipment or machinery on any national wildlife refuge without proper authorization is...

Detection of inter-frame forgeries in digital videos.

PubMed

K, Sitara; Mehtre, B M

2018-05-26

Videos are acceptable as evidence in the court of law, provided its authenticity and integrity are scientifically validated. Videos recorded by surveillance systems are susceptible to malicious alterations of visual content by perpetrators locally or remotely. Such malicious alterations of video contents (called video forgeries) are categorized into inter-frame and intra-frame forgeries. In this paper, we propose inter-frame forgery detection techniques using tamper traces from spatio-temporal and compressed domains. Pristine videos containing frames that are recorded during sudden camera zooming event, may get wrongly classified as tampered videos leading to an increase in false positives. To address this issue, we propose a method for zooming detection and it is incorporated in video tampering detection. Frame shuffling detection, which was not explored so far is also addressed in our work. Our method is capable of differentiating various inter-frame tamper events and its localization in the temporal domain. The proposed system is tested on 23,586 videos of which 2346 are pristine and rest of them are candidates of inter-frame forged videos. Experimental results show that we have successfully detected frame shuffling with encouraging accuracy rates. We have achieved improved accuracy on forgery detection in frame insertion, frame deletion and frame duplication. Copyright © 2018. Published by Elsevier B.V.

A Theorem and its Application to Finite Tampers

DOE R&D Accomplishments Database

Feynman, R. P.

1946-08-15

A theorem is derived which is useful in the analysis of neutron problems in which all neutrons have the same velocity. It is applied to determine extrapolated end-points, the asymptotic amplitude from a point source, and the neutron density at the surface of a medium. Formulas fro the effect of finite tampers are derived by its aid, and their accuracy discussed.

Security inspection in ports by anomaly detection using hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Rivera, Javier; Valverde, Fernando; Saldaña, Manuel; Manian, Vidya

2013-05-01

Applying hyperspectral imaging technology in port security is crucial for the detection of possible threats or illegal activities. One of the most common problems that cargo suffers is tampering. This represents a danger to society because it creates a channel to smuggle illegal and hazardous products. If a cargo is altered, security inspections on that cargo should contain anomalies that reveal the nature of the tampering. Hyperspectral images can detect anomalies by gathering information through multiple electromagnetic bands. The spectrums extracted from these bands can be used to detect surface anomalies from different materials. Based on this technology, a scenario was built in which a hyperspectral camera was used to inspect the cargo for any surface anomalies and a user interface shows the results. The spectrum of items, altered by different materials that can be used to conceal illegal products, is analyzed and classified in order to provide information about the tampered cargo. The image is analyzed with a variety of techniques such as multiple features extracting algorithms, autonomous anomaly detection, and target spectrum detection. The results will be exported to a workstation or mobile device in order to show them in an easy -to-use interface. This process could enhance the current capabilities of security systems that are already implemented, providing a more complete approach to detect threats and illegal cargo.

"Old Age and Loneliness: Cross-Sectional and Longitudinal Analyses in the Tampere Longitudinal Study on Aging"

ERIC Educational Resources Information Center

Jylha, Marja

2004-01-01

The purpose of this study was to examine whether older age is associated with increasing loneliness in people aged 60 and over. Data came from TamELSA, a population-based prospective longitudinal study in Tampere, Finland. The followup time was 20 years. Loneliness was measured by a single question--"Do you feel lonely?"--with the…

Efficiency of extraction and conversion of pseudoephedrine to methamphetamine from tamper-resistant and non-tamper-resistant formulations.

PubMed

Presley, Brandon; Bianchi, Bob; Coleman, John; Diamond, Fran; McNally, Gerry

2018-07-15

Clandestine chemists have demonstrated an ability to convert commercially available pseudoephedrine formulations to methamphetamine. Some of these formulations have properties that manufacturers claim limit or block the extraction of pseudoephedrine and its direct conversion to methamphetamine. In this study, 3 commercially available pseudoephedrine formulations were evaluated for ease of extraction and conversion to methamphetamine using a common chemistry technique called the one-pot method that is frequently employed by clandestine chemists. Two marketed pseudoephedrine formulations with claimed tamper-resistant properties - Zephrex-D ® and Nexafed ® - were compared to Sunmark ® , a comparator formulation of pseudoephedrine without tamper-resistant properties. Particle size reduction was conducted using 8 readily available tools; solubility was assessed using 2 common aqueous solutions and various reaction conditions (e.g., temperature, stirring); extractability was evaluated using 8 common organic solvents. The one-pot (single vessel) method commonly used in clandestine processes was employed; chemicals and equipment were purchased locally on the open market. Quantities and addition times of the chemicals used to carry out the procedure and the duration of the reaction were varied to determine the effect on methamphetamine yield. The procedure was appropriately scaled and conducted in a controlled environment to reduce risk and maximize yields. Pseudoephedrine and methamphetamine were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Standard quantitative procedures were used to determine the quantities of pseudoephedrine and methamphetamine recovered and produced, respectively. Particle size reduction resulted in some loss of material of each pseudoephedrine formulation; Zephrex-D tablets were broken down to a coarse material; Nexafed and Sunmark tablets were reduced to a fine powder. The solubility rates of intact and ground

Method and apparatus for active tamper indicating device using optical time-domain reflectometry

DOEpatents

Smith, D. Barton; Muhs, Jeffrey D.; Pickett, Chris A.; Earl, D. Duncan

1999-01-01

An optical time-domain reflectometer (OTDR) launches pulses of light into a link or a system of multiplexed links and records the waveform of pulses reflected by the seals in the link(s). If a seal is opened, the link of cables will become a discontinuous transmitter of the light pulses and the OTDR can immediately detect that a seal has been opened. By analyzing the waveform, the OTDR can also quickly determine which seal(s) were opened. In this way the invention functions as a system of active seals. The invention is intended for applications that require long-term surveillance of a large number of closures. It provides immediate tamper detection, allows for periodic access to secured closures, and can be configured for many different distributions of closures. It can monitor closures in indoor and outdoor locations and it can monitor containers or groups of containers located many kilometers apart.

21 CFR 700.25 - Tamper-resistant packaging requirements for cosmetic products.

Code of Federal Regulations, 2014 CFR

2014-04-01

... cosmetic products. 700.25 Section 700.25 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS GENERAL Requirements for Specific Cosmetic Products § 700.25 Tamper-resistant packaging requirements for cosmetic products. (a) General. Because most cosmetic liquid...

21 CFR 700.25 - Tamper-resistant packaging requirements for cosmetic products.

Code of Federal Regulations, 2013 CFR

2013-04-01

... cosmetic products. 700.25 Section 700.25 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS GENERAL Requirements for Specific Cosmetic Products § 700.25 Tamper-resistant packaging requirements for cosmetic products. (a) General. Because most cosmetic liquid...

21 CFR 700.25 - Tamper-resistant packaging requirements for cosmetic products.

Code of Federal Regulations, 2012 CFR

2012-04-01

... cosmetic products. 700.25 Section 700.25 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS GENERAL Requirements for Specific Cosmetic Products § 700.25 Tamper-resistant packaging requirements for cosmetic products. (a) General. Because most cosmetic liquid...

21 CFR 700.25 - Tamper-resistant packaging requirements for cosmetic products.

Code of Federal Regulations, 2011 CFR

2011-04-01

... cosmetic products. 700.25 Section 700.25 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) COSMETICS GENERAL Requirements for Specific Cosmetic Products § 700.25 Tamper-resistant packaging requirements for cosmetic products. (a) General. Because most cosmetic liquid...

21 CFR 700.25 - Tamper-resistant packaging requirements for cosmetic products.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 7 2010-04-01 2010-04-01 false Tamper-resistant packaging requirements for cosmetic products. 700.25 Section 700.25 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH... of cosmetic product packages. The Food and Drug Administration has the authority and responsibility...

Tamper Indicating Device: Initial Training, Course 50112

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bonner, Stephen Ray; Sandoval, Dana M.

Tamper Indicating Device (TID): Initial Training, course #50112, covers Los Alamos National Laboratory (LANL) Material Control & Accountability (MC&A) TID Program procedures for the application and removal of TIDs. LANL’s policy is to comply with Department of Energy (DOE) requirements for the use of TIDs consistent with the graded safeguards described in DOE Manual DOE O 474.2, Nuclear Material Control and Accountability. When you have completed this course, you will: recognize standard practices and procedures of the LANL TID Program; have hands-on experience in the application and removal of LANL TIDs, and; verify the application and removal of LANL TIDs.

Fiber Optic Tamper Indicating Enclosure (TIE); A Case Study in Authentication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anheier, Norman C.; Benz, Jacob M.; Tanner, Jennifer E.

2015-07-15

A robust fiber optic-based tamper-indicating enclosure (TIE) has been developed by PNNL through funding by the National Nuclear Security Administration Office of Nuclear Verification over the past few years. The objective of this work is to allow monitors to have confidence in both the authenticity and integrity of the TIE and the monitoring equipment inside, throughout the time it may be located at a host facility. Incorporating authentication features into the design were the focus of fiscal year 2014 development efforts. Throughout the development process, modifications have been made to the physical TIE design based on lessons learned via exercisesmore » and expert elicitation. The end result is a robust and passive TIE which can be utilized to protect monitoring party equipment left in a host facility.« less

21 CFR 800.12 - Contact lens solutions and tablets; tamper-resistant packaging.

Code of Federal Regulations, 2010 CFR

2010-04-01

...-resistant retail packages, there is the opportunity for the malicious adulteration of these products with... confidence in the security of the packages of over-the-counter (OTC) health care products. The Food and Drug... used to make such a solution for retail sale that is not packaged in a tamper-resistant package and...

21 CFR 800.12 - Contact lens solutions and tablets; tamper-resistant packaging.

Code of Federal Regulations, 2011 CFR

2011-04-01

...-resistant retail packages, there is the opportunity for the malicious adulteration of these products with... confidence in the security of the packages of over-the-counter (OTC) health care products. The Food and Drug... used to make such a solution for retail sale that is not packaged in a tamper-resistant package and...

21 CFR 800.12 - Contact lens solutions and tablets; tamper-resistant packaging.

Code of Federal Regulations, 2012 CFR

2012-04-01

...-resistant retail packages, there is the opportunity for the malicious adulteration of these products with... confidence in the security of the packages of over-the-counter (OTC) health care products. The Food and Drug... used to make such a solution for retail sale that is not packaged in a tamper-resistant package and...

21 CFR 800.12 - Contact lens solutions and tablets; tamper-resistant packaging.

Code of Federal Regulations, 2013 CFR

2013-04-01

...-resistant retail packages, there is the opportunity for the malicious adulteration of these products with... confidence in the security of the packages of over-the-counter (OTC) health care products. The Food and Drug... used to make such a solution for retail sale that is not packaged in a tamper-resistant package and...

21 CFR 800.12 - Contact lens solutions and tablets; tamper-resistant packaging.

Code of Federal Regulations, 2014 CFR

2014-04-01

...-resistant retail packages, there is the opportunity for the malicious adulteration of these products with... confidence in the security of the packages of over-the-counter (OTC) health care products. The Food and Drug... used to make such a solution for retail sale that is not packaged in a tamper-resistant package and...

Authenticity examination of compressed audio recordings using detection of multiple compression and encoders' identification.

PubMed

Korycki, Rafal

2014-05-01

Since the appearance of digital audio recordings, audio authentication has been becoming increasingly difficult. The currently available technologies and free editing software allow a forger to cut or paste any single word without audible artifacts. Nowadays, the only method referring to digital audio files commonly approved by forensic experts is the ENF criterion. It consists in fluctuation analysis of the mains frequency induced in electronic circuits of recording devices. Therefore, its effectiveness is strictly dependent on the presence of mains signal in the recording, which is a rare occurrence. Recently, much attention has been paid to authenticity analysis of compressed multimedia files and several solutions were proposed for detection of double compression in both digital video and digital audio. This paper addresses the problem of tampering detection in compressed audio files and discusses new methods that can be used for authenticity analysis of digital recordings. Presented approaches consist in evaluation of statistical features extracted from the MDCT coefficients as well as other parameters that may be obtained from compressed audio files. Calculated feature vectors are used for training selected machine learning algorithms. The detection of multiple compression covers up tampering activities as well as identification of traces of montage in digital audio recordings. To enhance the methods' robustness an encoder identification algorithm was developed and applied based on analysis of inherent parameters of compression. The effectiveness of tampering detection algorithms is tested on a predefined large music database consisting of nearly one million of compressed audio files. The influence of compression algorithms' parameters on the classification performance is discussed, based on the results of the current study. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Uniquely identifiable tamper-evident device using coupling between subwavelength gratings

NASA Astrophysics Data System (ADS)

Fievre, Ange Marie Patricia

Reliability and sensitive information protection are critical aspects of integrated circuits. A novel technique using near-field evanescent wave coupling from two subwavelength gratings (SWGs), with the input laser source delivered through an optical fiber is presented for tamper evidence of electronic components. The first grating of the pair of coupled subwavelength gratings (CSWGs) was milled directly on the output facet of the silica fiber using focused ion beam (FIB) etching. The second grating was patterned using e-beam lithography and etched into a glass substrate using reactive ion etching (RIE). The slightest intrusion attempt would separate the CSWGs and eliminate near-field coupling between the gratings. Tampering, therefore, would become evident. Computer simulations guided the design for optimal operation of the security solution. The physical dimensions of the SWGs, i.e. period and thickness, were optimized, for a 650 nm illuminating wavelength. The optimal dimensions resulted in a 560 nm grating period for the first grating etched in the silica optical fiber and 420 nm for the second grating etched in borosilicate glass. The incident light beam had a half-width at half-maximum (HWHM) of at least 7 microm to allow discernible higher transmission orders, and a HWHM of 28 microm for minimum noise. The minimum number of individual grating lines present on the optical fiber facet was identified as 15 lines. Grating rotation due to the cylindrical geometry of the fiber resulted in a rotation of the far-field pattern, corresponding to the rotation angle of moire fringes. With the goal of later adding authentication to tamper evidence, the concept of CSWGs signature was also modeled by introducing random and planned variations in the glass grating. The fiber was placed on a stage supported by a nanomanipulator, which permitted three-dimensional displacement while maintaining the fiber tip normal to the surface of the glass substrate. A 650 nm diode laser was

Behavior Knowledge Space-Based Fusion for Copy-Move Forgery Detection.

PubMed

Ferreira, Anselmo; Felipussi, Siovani C; Alfaro, Carlos; Fonseca, Pablo; Vargas-Munoz, John E; Dos Santos, Jefersson A; Rocha, Anderson

2016-07-20

The detection of copy-move image tampering is of paramount importance nowadays, mainly due to its potential use for misleading the opinion forming process of the general public. In this paper, we go beyond traditional forgery detectors and aim at combining different properties of copy-move detection approaches by modeling the problem on a multiscale behavior knowledge space, which encodes the output combinations of different techniques as a priori probabilities considering multiple scales of the training data. Afterwards, the conditional probabilities missing entries are properly estimated through generative models applied on the existing training data. Finally, we propose different techniques that exploit the multi-directionality of the data to generate the final outcome detection map in a machine learning decision-making fashion. Experimental results on complex datasets, comparing the proposed techniques with a gamut of copy-move detection approaches and other fusion methodologies in the literature show the effectiveness of the proposed method and its suitability for real-world applications.

Effect of source tampering in the security of quantum cryptography

NASA Astrophysics Data System (ADS)

Sun, Shi-Hai; Xu, Feihu; Jiang, Mu-Sheng; Ma, Xiang-Chun; Lo, Hoi-Kwong; Liang, Lin-Mei

2015-08-01

The security of source has become an increasingly important issue in quantum cryptography. Based on the framework of measurement-device-independent quantum key distribution (MDI-QKD), the source becomes the only region exploitable by a potential eavesdropper (Eve). Phase randomization is a cornerstone assumption in most discrete-variable (DV) quantum communication protocols (e.g., QKD, quantum coin tossing, weak-coherent-state blind quantum computing, and so on), and the violation of such an assumption is thus fatal to the security of those protocols. In this paper, we show a simple quantum hacking strategy, with commercial and homemade pulsed lasers, by Eve that allows her to actively tamper with the source and violate such an assumption, without leaving a trace afterwards. Furthermore, our attack may also be valid for continuous-variable (CV) QKD, which is another main class of QKD protocol, since, excepting the phase random assumption, other parameters (e.g., intensity) could also be changed, which directly determine the security of CV-QKD.

Changes in the dispensing of opioid medications in Canada following the introduction of a tamper-deterrent formulation of long-acting oxycodone: a time series analysis.

PubMed

Gomes, Tara; Mastorakos, Andrea; Paterson, J Michael; Sketris, Ingrid; Caetano, Patricia; Greaves, Simon; Henry, David

2017-11-22

In February 2012, a reformulated tamper-deterrent form of long-acting oxycodone, OxyNeo, was introduced in Canada. We investigated the impact of the introduction of OxyNeo on patterns of opioid prescribing. We conducted population-based, cross-sectional analyses of opioid dispensing in Canada between 2008 and 2016. We estimated monthly community pharmacy dispensing of oral formulations of codeine, morphine, hydromorphone and oxycodone, and a transdermal formulation of fentanyl, and converted quantities to milligrams of morphine equivalents (MMEs) per 1000 population. We used time series analysis to evaluate the effect of the introduction of OxyNeo on these trends. National dispensing of long-acting opioids fell by 14.9% between February 2012 and April 2016, from 36 098 MMEs to 30 716 MMEs per 1000 population ( p < 0.01). This effect varied across Canada and was largest in Ontario (reduction of 22.8%) ( p = 0.01) and British Columbia (reduction of 30.0%) ( p = 0.01). The national rate of oxycodone dispensing fell by 46.4% after the introduction of OxyNeo ( p < 0.001); this was partially offset by an increase of 47.8% in hydromorphone dispensing ( p < 0.001). Although dispensing of immediate-release opioids was a substantial contributor to overall population opioid exposure across Canada, it was unaffected by the introduction of OxyNeo ( p > 0.05 in all provinces). The findings suggest that the introduction of a tamper-deterrent formulation of long-acting oxycodone in Canada, against a background of changing public drug benefits, was associated with sustained changes in selection of long-acting opioids but only small changes in the quantity of long-acting opioids dispensed. This illustrates the limited effect a tamper-deterrent formulation and associated coverage policy can have when other, non-tamper-deterrent alternatives are readily available. Copyright 2017, Joule Inc. or its licensors.

Detection and localization of copy-paste forgeries in digital videos.

PubMed

Singh, Raahat Devender; Aggarwal, Naveen

2017-12-01

Amidst the continual march of technology, we find ourselves relying on digital videos to proffer visual evidence in several highly sensitive areas such as journalism, politics, civil and criminal litigation, and military and intelligence operations. However, despite being an indispensable source of information with high evidentiary value, digital videos are also extremely vulnerable to conscious manipulations. Therefore, in a situation where dependence on video evidence is unavoidable, it becomes crucial to authenticate the contents of this evidence before accepting them as an accurate depiction of reality. Digital videos can suffer from several kinds of manipulations, but perhaps, one of the most consequential forgeries is copy-paste forgery, which involves insertion/removal of objects into/from video frames. Copy-paste forgeries alter the information presented by the video scene, which has a direct effect on our basic understanding of what that scene represents, and so, from a forensic standpoint, the challenge of detecting such forgeries is especially significant. In this paper, we propose a sensor pattern noise based copy-paste detection scheme, which is an improved and forensically stronger version of an existing noise-residue based technique. We also study a demosaicing artifact based image forensic scheme to estimate the extent of its viability in the domain of video forensics. Furthermore, we suggest a simplistic clustering technique for the detection of copy-paste forgeries, and determine if it possess the capabilities desired of a viable and efficacious video forensic scheme. Finally, we validate these schemes on a set of realistically tampered MJPEG, MPEG-2, MPEG-4, and H.264/AVC encoded videos in a diverse experimental set-up by varying the strength of post-production re-compressions and transcodings, bitrates, and sizes of the tampered regions. Such an experimental set-up is representative of a neutral testing platform and simulates a real

The feasibility study based on e-commerce instructions-focuses on detection and deletion of illegal content

NASA Astrophysics Data System (ADS)

Guo, Tianze; Bi, Siyu; Liu, Jiaming

2018-04-01

This essay legally restrains the illegal content based on the e-commerce directive and introduces that the European countries detect and notify illegal content through the instructions of competent authorities, notification of credible flaggers, user reports and technical tools. The illegal content should be deleted through the service terms and transparency report basing on prevent excessive deletions system. At the same time, use filters to detect and filter to against the recurrence of illegal content. By analyzing the advantages of China under the environment of cracking down on illegal content, this essay concludes that the success of China in cracking down on illegal content lies in all-round collaborative management model of countries, governments, enterprises and individuals. At the end of the essay, one is to build a training corpus that can automatically update the ability to identify the illegal content. And it proposes an optimization scheme that establish a complete set of address resolution procedures and classify IP address data according to big data analysis and DNS protection module to prevent hackers from spreading illegal content by tampering with DNS segments.

Idaho National Laboratory Supervisory Control and Data Acquisition Intrusion Detection System (SCADA IDS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jared Verba; Michael Milvich

2008-05-01

Current Intrusion Detection System (IDS) technology is not suited to be widely deployed inside a Supervisory, Control and Data Acquisition (SCADA) environment. Anomaly- and signature-based IDS technologies have developed methods to cover information technology-based networks activity and protocols effectively. However, these IDS technologies do not include the fine protocol granularity required to ensure network security inside an environment with weak protocols lacking authentication and encryption. By implementing a more specific and more intelligent packet inspection mechanism, tailored traffic flow analysis, and unique packet tampering detection, IDS technology developed specifically for SCADA environments can be deployed with confidence in detecting maliciousmore » activity.« less

The Social Construction of the Urban Use of Information Technology: The Case of Tampere, Finland

ERIC Educational Resources Information Center

Inkinen, Tommi

2006-01-01

This paper explores the social use of information and communication technologies (ICTs) in the city of Tampere, Finland. It focuses on two essential elements: the city (as the location with national context) and citizens (as members of the "local" information society). The paper also examines the question of building social networks via…

DEVELOPMENT OF A TAMPER RESISTANT/INDICATING AEROSOL COLLECTION SYSTEM FOR ENVIRONMENTAL SAMPLING AT BULK HANDLING FACILITIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sexton, L.

2012-06-06

Environmental sampling has become a key component of International Atomic Energy Agency (IAEA) safeguards approaches since its approval for use in 1996. Environmental sampling supports the IAEA's mission of drawing conclusions concerning the absence of undeclared nuclear material or nuclear activities in a Nation State. Swipe sampling is the most commonly used method for the collection of environmental samples from bulk handling facilities. However, augmenting swipe samples with an air monitoring system, which could continuously draw samples from the environment of bulk handling facilities, could improve the possibility of the detection of undeclared activities. Continuous sampling offers the opportunity tomore » collect airborne materials before they settle onto surfaces which can be decontaminated, taken into existing duct work, filtered by plant ventilation, or escape via alternate pathways (i.e. drains, doors). Researchers at the Savannah River National Laboratory and Oak Ridge National Laboratory have been working to further develop an aerosol collection technology that could be installed at IAEA safeguarded bulk handling facilities. The addition of this technology may reduce the number of IAEA inspector visits required to effectively collect samples. The principal sample collection device is a patented Aerosol Contaminant Extractor (ACE) which utilizes electrostatic precipitation principles to deposit particulates onto selected substrates. Recent work has focused on comparing traditional swipe sampling to samples collected via an ACE system, and incorporating tamper resistant and tamper indicating (TRI) technologies into the ACE system. Development of a TRI-ACE system would allow collection of samples at uranium/plutonium bulk handling facilities in a manner that ensures sample integrity and could be an important addition to the international nuclear safeguards inspector's toolkit. This work was supported by the Next Generation Safeguards Initiative (NGSI

"Tampering to Death": A Fatal Codeine Intoxication Due to a Homemade Purification of a Medical Formulation.

PubMed

Fais, Paolo; Pigaiani, Nicola; Cecchetto, Giovanni; Montisci, Massimo; Gottardo, Rossella; Viel, Guido; Pascali, Jennifer Paola; Tagliaro, Franco

2017-11-01

Many homemade tamper processes of medical codeine formulations are available on selected "forums" on the Internet, where recreational codeine users claim to be able to purify codeine by removing additives, such as acetaminophen, to avoid or limit adverse effects. In this work, it is reported and discussed a fatal case of codeine intoxication. The findings of objects such as jars, filters, and tablets, and amounts of unknown liquid material at the death scene investigation suggested a fatal codeine intoxication after the tampering procedure called "cold water extraction." Toxicological results obtained from the analysis of both the nonbiological material and the body fluids of the decedent integrated with the information collected at the death scene investigation confirmed the above-mentioned hypothesis. This report underlines the importance of a tight interconnection between criminalistics and legal medicine to strengthen the identification of the cause of death and the reconstruction of the event. © 2017 American Academy of Forensic Sciences.

Tamper asymmetry and its effect on transmission for x-ray driven opacity simulations

DOE PAGES

Morris, H. E.; Tregillis, I. L.; Hoffman, N. M.; ...

2017-08-01

This paper reports on synthetic transmission results from Lasnex [1] radiation-hydrodynamics simulations of opacity experiments carried out at Sandia National Laboratories' recently upgraded ZR facility. The focus is on experiments utilizing disk targets composed of a half-moon Fe/Mg mixture tamped on either end with 10- m CH and an additional 35- m beryllium tamper accessory on the end facing the spectrometer. Five x-ray sources with peak power ranging from 10 to 24 TW were used in the simulations to heat and backlight the opacity target. The dominant effect is that the beryllium behind the Fe/Mg mixture is denser and moremore » opaque than the beryllium unshielded by metal during the times of greatest importance for the transmission measurement for all drives. This causes the simulated transmission to be lower than expected, and this is most pronounced for the case using the lowest drive power. While beryllium has a low opacity, its areal density is sufficiently high such that the expected reduction of the measured transmission is significant. This situation leads to an overestimate of iron opacity by 10-215% for a photon energy range of 975- 1775 eV for the 10-TW case. It is shown that if the tamper conditions are known, the transmission through each component of the target can be calculated and the resulting opacity can be corrected.« less

Planar ultra thin glass seals with optical fiber interface for monitoring tamper attacks on security eminent components

NASA Astrophysics Data System (ADS)

Thiel, M.; Flachenecker, G.; Schade, W.; Gorecki, C.; Thoma, A.; Rathje, R.

2017-11-01

Optical seals consisting of waveguide Bragg grating sensor structures in ultra thin glass transparencies have been developed to cover security relevant objects for detection of unauthorized access. For generation of optical signature in the seals, femtosecond laser pulses were used. The optical seals were connected with an optical fiber to enable external read out of the seal. Different attack scenarios for getting undetected access to the object, covered by the seal, were proven and evaluated. The results presented here, verify a very high level of security. An unauthorized detaching and subsequent replacement by original or copy of the seals for tampering would be accompanied with a very high technological effort, posing a substantial barrier towards an attacker. Additionally, environmental influences like temperature effects have a strong but reproducible influence on signature, which in context of a temperature reference database increases the level of security significantly.

Tamper asymmetry and its effect on transmission for x-ray driven opacity simulations

NASA Astrophysics Data System (ADS)

Morris, H. E.; Tregillis, I. L.; Hoffman, N. M.; Sherrill, M. E.; Fontes, C. J.; Marshall, A. J.; Urbatsch, T. J.; Bradley, P. A.

2017-09-01

This paper reports on synthetic transmission results from Lasnex [Zimmerman and Kruer, Comments Plasma Phys. 2, 51 (1975)] radiation-hydrodynamics simulations of opacity experiments carried out at Sandia National Laboratories' recently upgraded ZR facility. The focus is on experiments utilizing disk targets composed of a half-moon Fe/Mg mixture tamped on either end with 10-μm CH and an additional 35-μm beryllium tamper accessory on the end facing the spectrometer. Five x-ray sources with peak power ranging from 10 to 24 TW were used in the simulations to heat and backlight the opacity target. The dominant effect is that the beryllium behind the Fe/Mg mixture is denser and more opaque than the beryllium unshielded by metal during the times of greatest importance for the transmission measurement for all drives. This causes the simulated transmission to be lower than expected, and this is most pronounced for the case using the lowest drive power. While beryllium has a low opacity, its areal density is sufficiently high such that the expected reduction of the measured transmission is significant. This situation leads to an overestimate of iron opacity by 10%-215% for a photon energy range of 975-1775 eV for the 10-TW case. It is shown that if the tamper conditions are known, the transmission through each component of the target can be calculated and the resulting opacity can be corrected.

Child-resistant and tamper-resistant packaging: A systematic review to inform tobacco packaging regulation.

PubMed

Jo, Catherine L; Ambs, Anita; Dresler, Carolyn M; Backinger, Cathy L

2017-02-01

We aimed to investigate the effects of special packaging (child-resistant, adult-friendly) and tamper-resistant packaging on health and behavioral outcomes in order to identify research gaps and implications for packaging standards for tobacco products. We searched seven databases for keywords related to special and tamper-resistant packaging, consulted experts, and reviewed citations of potentially relevant studies. 733 unique papers were identified. Two coders independently screened each title and abstract for eligibility. They then reviewed the full text of the remaining papers for a second round of eligibility screening. Included studies investigated a causal relationship between type of packaging or packaging regulation and behavioral or health outcomes and had a study population composed of consumers. Studies were excluded on the basis of publication type, if they were not peer-reviewed, and if they had low external validity. Two reviewers independently coded each paper for study and methodological characteristics and limitations. Discrepancies were discussed and resolved. The review included eight studies: four assessing people's ability to access the contents of different packaging types and four evaluating the impact of packaging requirements on health-related outcomes. Child-resistant packaging was generally more difficult to open than non-child-resistant packaging. Child-resistant packaging requirements have been associated with reductions in child mortality. Child-resistant packaging holds the expectation to reduce tobacco product poisonings among children under six. Published by Elsevier Inc.

Self-recovery fragile watermarking algorithm based on SPHIT

NASA Astrophysics Data System (ADS)

Xin, Li Ping

2015-12-01

A fragile watermark algorithm is proposed, based on SPIHT coding, which can recover the primary image itself. The novelty of the algorithm is that it can tamper location and Self-restoration. The recovery has been very good effect. The first, utilizing the zero-tree structure, the algorithm compresses and encodes the image itself, and then gained self correlative watermark data, so as to greatly reduce the quantity of embedding watermark. Then the watermark data is encoded by error correcting code, and the check bits and watermark bits are scrambled and embedded to enhance the recovery ability. At the same time, by embedding watermark into the latter two bit place of gray level image's bit-plane code, the image after embedded watermark can gain nicer visual effect. The experiment results show that the proposed algorithm may not only detect various processing such as noise adding, cropping, and filtering, but also recover tampered image and realize blind-detection. Peak signal-to-noise ratios of the watermark image were higher than other similar algorithm. The attack capability of the algorithm was enhanced.

Child-resistant and tamper-resistant packaging: A systematic review to inform tobacco packaging regulation

PubMed Central

Jo, Catherine L.; Ambs, Anita; Dresler, Carolyn M.; Backinger, Cathy L.

2017-01-01

Objective We aimed to investigate the effects of special packaging (child-resistant, adult-friendly) and tamper-resistant packaging on health and behavioral outcomes in order to identify research gaps and implications for packaging standards for tobacco products. Methods We searched seven databases for keywords related to special and tamper-resistant packaging, consulted experts, and reviewed citations of potentially relevant studies. 733 unique papers were identified. Two coders independently screened each title and abstract for eligibility. They then reviewed the full text of the remaining papers for a second round of eligibility screening. Included studies investigated a causal relationship between type of packaging or packaging regulation and behavioral or health outcomes and had a study population composed of consumers. Studies were excluded on the basis of publication type, if they were not peer-reviewed, and if they had low external validity. Two reviewers independently coded each paper for study and methodological characteristics and limitations. Discrepancies were discussed and resolved. Results The review included eight studies: four assessing people’s ability to access the contents of different packaging types and four evaluating the impact of packaging requirements on health-related outcomes. Child-resistant packaging was generally more difficult to open than non-child-resistant packaging. Child-resistant packaging requirements have been associated with reductions in child mortality. Conclusions Child-resistant packaging holds the expectation to reduce tobacco product poisonings among children under six. PMID:27939602

2007 Beyond SBIR Phase II: Bringing Technology Edge to the Warfighter

DTIC Science & Technology

2007-08-23

Systems Trade-Off Analysis and Optimization Verification and Validation On-Board Diagnostics and Self - healing Security and Anti-Tampering Rapid...verification; Safety and reliability analysis of flight and mission critical systems On-Board Diagnostics and Self - Healing Model-based monitoring and... self - healing On-board diagnostics and self - healing ; Autonomic computing; Network intrusion detection and prevention Anti-Tampering and Trust

Operator agency in process intervention: tampering versus application of tacit knowledge

NASA Astrophysics Data System (ADS)

Van Gestel, P.; Pons, D. J.; Pulakanam, V.

2015-09-01

Statistical process control (SPC) theory takes a negative view of adjustment of process settings, which is termed tampering. In contrast, quality and lean programmes actively encourage operators to acts of intervention and personal agency in the improvement of production outcomes. This creates a conflict that requires operator judgement: How does one differentiate between unnecessary tampering and needful intervention? Also, difficult is that operators apply tacit knowledge to such judgements. There is a need to determine where in a given production process the operators are applying tacit knowledge, and whether this is hindering or aiding quality outcomes. The work involved the conjoint application of systems engineering, statistics, and knowledge management principles, in the context of a case study. Systems engineering was used to create a functional model of a real plant. Actual plant data were analysed with the statistical methods of ANOVA, feature selection, and link analysis. This identified the variables to which the output quality was most sensitive. These key variables were mapped back to the functional model. Fieldwork was then directed to those areas to prospect for operator judgement activities. A natural conversational approach was used to determine where and how operators were applying judgement. This contrasts to the interrogative approach of conventional knowledge management. Data are presented for a case study of a meat rendering plant. The results identify specific areas where operators' tacit knowledge and mental model contribute to quality outcomes and untangles the motivations behind their agency. Also evident is how novice and expert operators apply their knowledge differently. Novices were focussed on meeting throughput objectives, and their incomplete understanding of the plant characteristics led them to inadvertently sacrifice quality in the pursuit of productivity in certain situations. Operators' responses to the plant are affected by

Watermarking of ultrasound medical images in teleradiology using compressed watermark

PubMed Central

Badshah, Gran; Liew, Siau-Chuin; Zain, Jasni Mohamad; Ali, Mushtaq

2016-01-01

Abstract. The open accessibility of Internet-based medical images in teleradialogy face security threats due to the nonsecured communication media. This paper discusses the spatial domain watermarking of ultrasound medical images for content authentication, tamper detection, and lossless recovery. For this purpose, the image is divided into two main parts, the region of interest (ROI) and region of noninterest (RONI). The defined ROI and its hash value are combined as watermark, lossless compressed, and embedded into the RONI part of images at pixel’s least significant bits (LSBs). The watermark lossless compression and embedding at pixel’s LSBs preserve image diagnostic and perceptual qualities. Different lossless compression techniques including Lempel-Ziv-Welch (LZW) were tested for watermark compression. The performances of these techniques were compared based on more bit reduction and compression ratio. LZW was found better than others and used in tamper detection and recovery watermarking of medical images (TDARWMI) scheme development to be used for ROI authentication, tamper detection, localization, and lossless recovery. TDARWMI performance was compared and found to be better than other watermarking schemes. PMID:26839914

On the designing of a tamper resistant prescription RFID access control system.

PubMed

Safkhani, Masoumeh; Bagheri, Nasour; Naderi, Majid

2012-12-01

Recently, Chen et al. have proposed a novel tamper resistant prescription RFID access control system, published in the Journal of Medical Systems. In this paper we consider the security of the proposed protocol and identify some existing weaknesses. The main attack is a reader impersonation attack which allows an active adversary to impersonate a legitimate doctor, e.g. the patient's doctor, to access the patient's tag and change the patient prescription. The presented attack is quite efficient. To impersonate a doctor, the adversary should eavesdrop one session between the doctor and the patient's tag and then she can impersonate the doctor with the success probability of '1'. In addition, we present efficient reader-tag to back-end database impersonation, de-synchronization and traceability attacks against the protocol. Finally, we propose an improved version of protocol which is more efficient compared to the original protocol while provides the desired security against the presented attacks.

Time-Domain Reflectometry for Tamper Indication in Unattended Monitoring Systems for Safeguards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tedeschi, Jonathan R.; Smith, Leon E.; Moore, David E.

2014-12-01

The International Atomic Energy Agency (IAEA) continues to expand its use of unattended, remotely monitored measurement systems. An increasing number of systems and an expanding family of instruments create challenges in terms of deployment efficiency and the implementation of data authentication measures. Pacific Northwest National Laboratory (PNNL) leads a collaboration that is exploring various tamper-indicating (TI) measures that could help to address some of the long-standing detector and data-transmission authentication challenges with IAEA’s unattended systems. PNNL is investigating the viability of active time-domain reflectometry (TDR) along two parallel but interconnected paths: (1) swept-frequency TDR as the highly flexible, laboratory goldmore » standard to which field-deployable options can be compared, and (2) a low-cost commercially available spread-spectrum TDR technology as one option for field implementation. This report describes PNNL’s progress and preliminary findings from the first year of the study, and describes the path forward.« less

StegoWall: blind statistical detection of hidden data

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav V.; Herrigel, Alexander; Rytsar, Yuri B.; Pun, Thierry

2002-04-01

Novel functional possibilities, provided by recent data hiding technologies, carry out the danger of uncontrolled (unauthorized) and unlimited information exchange that might be used by people with unfriendly interests. The multimedia industry as well as the research community recognize the urgent necessity for network security and copyright protection, or rather the lack of adequate law for digital multimedia protection. This paper advocates the need for detecting hidden data in digital and analog media as well as in electronic transmissions, and for attempting to identify the underlying hidden data. Solving this problem calls for the development of an architecture for blind stochastic hidden data detection in order to prevent unauthorized data exchange. The proposed architecture is called StegoWall; its key aspects are the solid investigation, the deep understanding, and the prediction of possible tendencies in the development of advanced data hiding technologies. The basic idea of our complex approach is to exploit all information about hidden data statistics to perform its detection based on a stochastic framework. The StegoWall system will be used for four main applications: robust watermarking, secret communications, integrity control and tamper proofing, and internet/network security.

Detecting Copy Move Forgery In Digital Images

NASA Astrophysics Data System (ADS)

Gupta, Ashima; Saxena, Nisheeth; Vasistha, S. K.

2012-03-01

In today's world several image manipulation software's are available. Manipulation of digital images has become a serious problem nowadays. There are many areas like medical imaging, digital forensics, journalism, scientific publications, etc, where image forgery can be done very easily. To determine whether a digital image is original or doctored is a big challenge. To find the marks of tampering in a digital image is a challenging task. The detection methods can be very useful in image forensics which can be used as a proof for the authenticity of a digital image. In this paper we propose the method to detect region duplication forgery by dividing the image into overlapping block and then perform searching to find out the duplicated region in the image.

A source-channel coding approach to digital image protection and self-recovery.

PubMed

Sarreshtedari, Saeed; Akhaee, Mohammad Ali

2015-07-01

Watermarking algorithms have been widely applied to the field of image forensics recently. One of these very forensic applications is the protection of images against tampering. For this purpose, we need to design a watermarking algorithm fulfilling two purposes in case of image tampering: 1) detecting the tampered area of the received image and 2) recovering the lost information in the tampered zones. State-of-the-art techniques accomplish these tasks using watermarks consisting of check bits and reference bits. Check bits are used for tampering detection, whereas reference bits carry information about the whole image. The problem of recovering the lost reference bits still stands. This paper is aimed at showing that having the tampering location known, image tampering can be modeled and dealt with as an erasure error. Therefore, an appropriate design of channel code can protect the reference bits against tampering. In the present proposed method, the total watermark bit-budget is dedicated to three groups: 1) source encoder output bits; 2) channel code parity bits; and 3) check bits. In watermark embedding phase, the original image is source coded and the output bit stream is protected using appropriate channel encoder. For image recovery, erasure locations detected by check bits help channel erasure decoder to retrieve the original source encoded image. Experimental results show that our proposed scheme significantly outperforms recent techniques in terms of image quality for both watermarked and recovered image. The watermarked image quality gain is achieved through spending less bit-budget on watermark, while image recovery quality is considerably improved as a consequence of consistent performance of designed source and channel codes.

Detecting double compressed MPEG videos with the same quantization matrix and synchronized group of pictures structure

NASA Astrophysics Data System (ADS)

Aghamaleki, Javad Abbasi; Behrad, Alireza

2018-01-01

Double compression detection is a crucial stage in digital image and video forensics. However, the detection of double compressed videos is challenging when the video forger uses the same quantization matrix and synchronized group of pictures (GOP) structure during the recompression history to conceal tampering effects. A passive approach is proposed for detecting double compressed MPEG videos with the same quantization matrix and synchronized GOP structure. To devise the proposed algorithm, the effects of recompression on P frames are mathematically studied. Then, based on the obtained guidelines, a feature vector is proposed to detect double compressed frames on the GOP level. Subsequently, sparse representations of the feature vectors are used for dimensionality reduction and enrich the traces of recompression. Finally, a support vector machine classifier is employed to detect and localize double compression in temporal domain. The experimental results show that the proposed algorithm achieves the accuracy of more than 95%. In addition, the comparisons of the results of the proposed method with those of other methods reveal the efficiency of the proposed algorithm.

Privacy protection in surveillance systems based on JPEG DCT baseline compression and spectral domain watermarking

NASA Astrophysics Data System (ADS)

Sablik, Thomas; Velten, Jörg; Kummert, Anton

2015-03-01

An novel system for automatic privacy protection in digital media based on spectral domain watermarking and JPEG compression is described in the present paper. In a first step private areas are detected. Therefore a detection method is presented. The implemented method uses Haar cascades to detects faces. Integral images are used to speed up calculations and the detection. Multiple detections of one face are combined. Succeeding steps comprise embedding the data into the image as part of JPEG compression using spectral domain methods and protecting the area of privacy. The embedding process is integrated into and adapted to JPEG compression. A Spread Spectrum Watermarking method is used to embed the size and position of the private areas into the cover image. Different methods for embedding regarding their robustness are compared. Moreover the performance of the method concerning tampered images is presented.

Forensic detection of noise addition in digital images

NASA Astrophysics Data System (ADS)

Cao, Gang; Zhao, Yao; Ni, Rongrong; Ou, Bo; Wang, Yongbin

2014-03-01

We proposed a technique to detect the global addition of noise to a digital image. As an anti-forensics tool, noise addition is typically used to disguise the visual traces of image tampering or to remove the statistical artifacts left behind by other operations. As such, the blind detection of noise addition has become imperative as well as beneficial to authenticate the image content and recover the image processing history, which is the goal of general forensics techniques. Specifically, the special image blocks, including constant and strip ones, are used to construct the features for identifying noise addition manipulation. The influence of noising on blockwise pixel value distribution is formulated and analyzed formally. The methodology of detectability recognition followed by binary decision is proposed to ensure the applicability and reliability of noising detection. Extensive experimental results demonstrate the efficacy of our proposed noising detector.

Process design and control of a twin screw hot melt extrusion for continuous pharmaceutical tamper-resistant tablet production.

PubMed

Baronsky-Probst, J; Möltgen, C-V; Kessler, W; Kessler, R W

2016-05-25

Hot melt extrusion (HME) is a well-known process within the plastic and food industries that has been utilized for the past several decades and is increasingly accepted by the pharmaceutical industry for continuous manufacturing. For tamper-resistant formulations of e.g. opioids, HME is the most efficient production technique. The focus of this study is thus to evaluate the manufacturability of the HME process for tamper-resistant formulations. Parameters such as the specific mechanical energy (SME), as well as the melt pressure and its standard deviation, are important and will be discussed in this study. In the first step, the existing process data are analyzed by means of multivariate data analysis. Key critical process parameters such as feed rate, screw speed, and the concentration of the API in the polymers are identified, and critical quality parameters of the tablet are defined. In the second step, a relationship between the critical material, product and process quality attributes are established by means of Design of Experiments (DoEs). The resulting SME and the temperature at the die are essential data points needed to indirectly qualify the degradation of the API, which should be minimal. NIR-spectroscopy is used to monitor the material during the extrusion process. In contrast to most applications in which the probe is directly integrated into the die, the optical sensor is integrated into the cooling line of the strands. This saves costs in the probe design and maintenance and increases the robustness of the chemometric models. Finally, a process measurement system is installed to monitor and control all of the critical attributes in real-time by means of first principles, DoE models, soft sensor models, and spectroscopic information. Overall, the process is very robust as long as the screw speed is kept low. Copyright © 2015 Elsevier B.V. All rights reserved.

Three New Methods for Analysis of Answer Changes

ERIC Educational Resources Information Center

Sinharay, Sandip; Johnson, Matthew S.

2017-01-01

In a pioneering research article, Wollack and colleagues suggested the "erasure detection index" (EDI) to detect test tampering. The EDI can be used with or without a continuity correction and is assumed to follow the standard normal distribution under the null hypothesis of no test tampering. When used without a continuity correction,…

Passive forensics for copy-move image forgery using a method based on DCT and SVD.

PubMed

Zhao, Jie; Guo, Jichang

2013-12-10

As powerful image editing tools are widely used, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the tampering techniques which are frequently used. Most existing techniques to expose this forgery need to improve the robustness for common post-processing operations and fail to precisely locate the tampering region especially when there are large similar or flat regions in the image. In this paper, a robust method based on DCT and SVD is proposed to detect this specific artifact. Firstly, the suspicious image is divided into fixed-size overlapping blocks and 2D-DCT is applied to each block, then the DCT coefficients are quantized by a quantization matrix to obtain a more robust representation of each block. Secondly, each quantized block is divided non-overlapping sub-blocks and SVD is applied to each sub-block, then features are extracted to reduce the dimension of each block using its largest singular value. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by predefined shift frequency threshold. Experiment results demonstrate that our proposed method can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, AWGN, JPEG compression and their mixed operations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Characterizing and Implementing Efficient Primitives for Privacy-Preserving Computation

DTIC Science & Technology

2015-07-01

the mobile device. From this, the mobile will detect any tampering from the malicious party by a discrepancy in these returned values, eliminating...the need for an output MAC. If no tampering is detected , the mobile device then decrypts the output of computation. APPROVED FOR PUBLIC RELEASE...useful error messages when the compiler detects a problem with an application, making debugging the application significantly easier than with other

An Enhanced Secure Identity-Based Certificateless Public Key Authentication Scheme for Vehicular Sensor Networks

PubMed Central

Li, Congcong; Zhang, Xi; Wang, Haiping; Li, Dongfeng

2018-01-01

Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes. PMID:29324719

An Enhanced Secure Identity-Based Certificateless Public Key Authentication Scheme for Vehicular Sensor Networks.

PubMed

Li, Congcong; Zhang, Xi; Wang, Haiping; Li, Dongfeng

2018-01-11

Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes.

Copy-move forgery detection through stationary wavelets and local binary pattern variance for forensic analysis in digital images.

PubMed

Mahmood, Toqeer; Irtaza, Aun; Mehmood, Zahid; Tariq Mahmood, Muhammad

2017-10-01

The most common image tampering often for malicious purposes is to copy a region of the same image and paste to hide some other region. As both regions usually have same texture properties, therefore, this artifact is invisible for the viewers, and credibility of the image becomes questionable in proof centered applications. Hence, means are required to validate the integrity of the image and identify the tampered regions. Therefore, this study presents an efficient way of copy-move forgery detection (CMFD) through local binary pattern variance (LBPV) over the low approximation components of the stationary wavelets. CMFD technique presented in this paper is applied over the circular regions to address the possible post processing operations in a better way. The proposed technique is evaluated on CoMoFoD and Kodak lossless true color image (KLTCI) datasets in the presence of translation, flipping, blurring, rotation, scaling, color reduction, brightness change and multiple forged regions in an image. The evaluation reveals the prominence of the proposed technique compared to state of the arts. Consequently, the proposed technique can reliably be applied to detect the modified regions and the benefits can be obtained in journalism, law enforcement, judiciary, and other proof critical domains. Copyright © 2017 Elsevier B.V. All rights reserved.

Image authentication by means of fragile CGH watermarking

NASA Astrophysics Data System (ADS)

Schirripa Spagnolo, Giuseppe; Simonetti, Carla; Cozzella, Lorenzo

2005-09-01

In this paper we propose a fragile marking system based on Computer Generated Hologram coding techniques, which is able to detect malicious tampering while tolerating some incidental distortions. A fragile watermark is a mark that is readily altered or destroyed when the host image is modified through a linear or nonlinear transformation. A fragile watermark monitors the integrity of the content of the image but not its numerical representation. Therefore the watermark is designed so that the integrity is proven if the content of the image has not been tampered. Since digital images can be altered or manipulated with ease, the ability to detect changes to digital images is very important for many applications such as news reporting, medical archiving, or legal usages. The proposed technique could be applied to Color Images as well as to Gray Scale ones. Using Computer Generated Hologram watermarking, the embedded mark could be easily recovered by means of a Fourier Transform. Due to this fact host image can be tampered and watermarked with the same holographic pattern. To avoid this possibility we have introduced an encryption method using a asymmetric Cryptography. The proposed schema is based on the knowledge of original mark from the Authentication

DNA-based random number generation in security circuitry.

PubMed

Gearheart, Christy M; Arazi, Benjamin; Rouchka, Eric C

2010-06-01

DNA-based circuit design is an area of research in which traditional silicon-based technologies are replaced by naturally occurring phenomena taken from biochemistry and molecular biology. This research focuses on further developing DNA-based methodologies to mimic digital data manipulation. While exhibiting fundamental principles, this work was done in conjunction with the vision that DNA-based circuitry, when the technology matures, will form the basis for a tamper-proof security module, revolutionizing the meaning and concept of tamper-proofing and possibly preventing it altogether based on accurate scientific observations. A paramount part of such a solution would be self-generation of random numbers. A novel prototype schema employs solid phase synthesis of oligonucleotides for random construction of DNA sequences; temporary storage and retrieval is achieved through plasmid vectors. A discussion of how to evaluate sequence randomness is included, as well as how these techniques are applied to a simulation of the random number generation circuitry. Simulation results show generated sequences successfully pass three selected NIST random number generation tests specified for security applications.

Distributed clone detection in static wireless sensor networks: random walk with network division.

PubMed

Khan, Wazir Zada; Aalsalem, Mohammed Y; Saad, N M

2015-01-01

Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads.

Distributed Clone Detection in Static Wireless Sensor Networks: Random Walk with Network Division

PubMed Central

Khan, Wazir Zada; Aalsalem, Mohammed Y.; Saad, N. M.

2015-01-01

Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads. PMID:25992913

Content fragile watermarking for H.264/AVC video authentication

NASA Astrophysics Data System (ADS)

Ait Sadi, K.; Guessoum, A.; Bouridane, A.; Khelifi, F.

2017-04-01

Discrete cosine transform is exploited in this work to generate the authentication data that are treated as a fragile watermark. This watermark is embedded in the motion vectors. The advances in multimedia technologies and digital processing tools have brought with them new challenges for the source and content authentication. To ensure the integrity of the H.264/AVC video stream, we introduce an approach based on a content fragile video watermarking method using an independent authentication of each group of pictures (GOPs) within the video. This technique uses robust visual features extracted from the video pertaining to the set of selected macroblocs (MBs) which hold the best partition mode in a tree-structured motion compensation process. An additional security degree is offered by the proposed method through using a more secured keyed function HMAC-SHA-256 and randomly choosing candidates from already selected MBs. In here, the watermark detection and verification processes are blind, whereas the tampered frames detection is not since it needs the original frames within the tampered GOPs. The proposed scheme achieves an accurate authentication technique with a high fragility and fidelity whilst maintaining the original bitrate and the perceptual quality. Furthermore, its ability to detect the tampered frames in case of spatial, temporal and colour manipulations is confirmed.

Opioid use following the introduction of an extended-release oxycodone formulation with tamper-resistant properties: Prospective historical chart review in methadone-maintained patients.

PubMed

Sankey, Christopher; Setnik, Beatrice; Harsanyi, Zoltan; Michalko, Ken; Yang, Zejiang; Geoffroy, Pierre

2016-01-01

Emerging data are demonstrating that tamper-resistant opioids may play an important role in changing prescription opioid abuse behaviors. This study was a chart review to examine if the reformulation of OxyContin® into a version with tamper-resistant properties (OxyNEO®) had an impact on oxycodone-positive urine drug screens (UDSs) in opioid-dependent patients receiving methadone maintenance therapy (MMT). The historical element of this study examined 250 eligible charts from patients on MMT who had data during the time periods when only OxyContin was available (baseline period), during the transition to OxyNEO, and when only OxyNEO was available. The prospective element included an exploratory questionnaire regarding retrospective opioid use. The study was conducted at three methadone clinics, in Oshawa, Peterborough, and Scarborough in Ontario, Canada. Male and female patients were eligible if they had a diagnosis of opioid dependency, received MMT, and had at least one oxycodone-positive UDS during the baseline period. This was a noninterventional study. The main outcome was the number of oxycodonepositive UDSs. The results demonstrated a marked reduction in oxycodone-positive UDSs that showed stepwise, statistically significant decreases during the transition and post-OxyContin periods relative to baseline. While the oxycodone-positive UDS results were decreasing, morphine-related-positive UDSs remained relatively stable during the same periods. There were no significant gender differences noted. The introduction of OxyNEO was associated with a statistically significant reduction in oxycodone exposure in a population of methadone-maintained patients.

An Outbreak of Norovirus Infections Among Lunch Customers at a Restaurant, Tampere, Finland, 2015.

PubMed

Vo, Thuan Huu; Okasha, Omar; Al-Hello, Haider; Polkowska, Aleksandra; Räsänen, Sirpa; Bojang, Merja; Nuorti, J Pekka; Jalava, Katri

2016-09-01

On January 29, 2015, the city of Tampere environmental health officers were informed of a possible foodborne outbreak among customers who had eaten lunch in restaurant X. Employees of electric companies A and B had a sudden onset of gastrointestinal symptoms. We conducted a retrospective cohort study to identify the vehicle, source, and causative agent of the outbreak. A case was defined as an employee of companies A or B with diarrhea and/or vomiting who ate lunch at Restaurant X on January 26, 2015. All employees of the companies attending the implicated lunch were invited to participate in the cohort study. Environmental investigation was conducted. Twenty-one responders were included in statistical analysis, of which 11 met with the case definition. Of the 15 food items consumed by participants, four food items were associated with gastroenteritis. Of four kitchen staff, three tested positive for norovirus GIP7, the strain was found earlier in the community. No patient samples were obtained. Level of hygiene in the kitchen was inadequate. Infected kitchen staff probably transmitted norovirus by inadequate hygiene practices. No new cases associated with Restaurant X were reported after the hygiene practices were improved.

Tampering detection system using quantum-mechanical systems

DOEpatents

Humble, Travis S [Knoxville, TN; Bennink, Ryan S [Knoxville, TN; Grice, Warren P [Oak Ridge, TN

2011-12-13

The use of quantum-mechanically entangled photons for monitoring the integrity of a physical border or a communication link is described. The no-cloning principle of quantum information science is used as protection against an intruder's ability to spoof a sensor receiver using a `classical` intercept-resend attack. Correlated measurement outcomes from polarization-entangled photons are used to protect against quantum intercept-resend attacks, i.e., attacks using quantum teleportation.

Machine Learning Based Malware Detection

DTIC Science & Technology

2015-05-18

A TRIDENT SCHOLAR PROJECT REPORT NO. 440 Machine Learning Based Malware Detection by Midshipman 1/C Zane A. Markel, USN...COVERED (From - To) 4. TITLE AND SUBTITLE Machine Learning Based Malware Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...suitably be projected into realistic performance. This work explores several aspects of machine learning based malware detection . First, we

Active Time-Domain Reflectometry for Unattended Safeguards Systems: FY16 Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tedeschi, Jonathan R.; Smith, Leon E.; Conrad, Ryan C.

2016-10-21

The International Atomic Energy Agency (IAEA) continues to expand its use of unattended measurement systems. An increasing number of systems and an expanding family of instruments create challenges in terms of deployment efficiency and the implementation of data authentication measures. Traditional data security measures, for example tamper-indicating (TI) conduit, are impractical for the long separation distances (often 100 meters or more) between unattended monitoring system (UMS) components. Pacific Northwest National Laboratory (PNNL) is studying the viability of active time-domain reflectometry (TDR) for the detection of cable tampering in unattended radiation detection systems. The instrument concept under investigation would allow formore » unmanned cable integrity measurements, remote surveillance reporting and locating of cable faults and/or tampers. This report describes PNNL’s FY16 progress and includes: an overview of the TDR methods under investigation; description of the TDR evaluation testbed developed by PNNL; development and testing of advanced signal processing algorithms to extract weak signals from relatively high noise levels; and initial testing of a laboratory prototype intended for IAEA UMS applications and based on a commercially available TDR module. Preliminary viability findings and recommendations for the next stage of development and testing are provided.« less

Unattended wireless proximity sensor networks for counterterrorism, force protection, littoral environments, PHM, and tamper monitoring ground applications

NASA Astrophysics Data System (ADS)

Forcier, Bob

2003-09-01

This paper describes a digital-ultrasonic ground network, which forms an unique "unattended mote sensor system" for monitoring the environment, personnel, facilities, vehicles, power generation systems or aircraft in Counter-Terrorism, Force Protection, Prognostic Health Monitoring (PHM) and other ground applications. Unattended wireless smart sensor/tags continuously monitor the environment and provide alerts upon changes or disruptions to the environment. These wireless smart sensor/tags are networked utilizing ultrasonic wireless motes, hybrid RF/Ultrasonic Network Nodes and Base Stations. The network is monitored continuously with a 24/7 remote and secure monitoring system. This system utilizes physical objects such as a vehicle"s structure or a building to provide the media for two way secure communication of key metrics and sensor data and eliminates the "blind spots" that are common in RF solutions because of structural elements of buildings, etc. The digital-ultrasonic sensors have networking capability and a 32-bit identifier, which provide a platform for a robust data acquisition (DAQ) for a large amount of sensors. In addition, the network applies a unique "signature" of the environment by comparing sensor-to-sensor data to pick up on minute changes, which would signal an invasion of unknown elements or signal a potential tampering in equipment or facilities. The system accommodates satellite and other secure network uplinks in either RF or UWB protocols. The wireless sensors can be dispersed by ground or air maneuvers. In addition, the sensors can be incorporated into the structure or surfaces of vehicles, buildings, or clothing of field personnel.

Agents Based e-Commerce and Securing Exchanged Information

NASA Astrophysics Data System (ADS)

Al-Jaljouli, Raja; Abawajy, Jemal

Mobile agents have been implemented in e-Commerce to search and filter information of interest from electronic markets. When the information is very sensitive and critical, it is important to develop a novel security protocol that can efficiently protect the information from malicious tampering as well as unauthorized disclosure or at least detect any malicious act of intruders. In this chapter, we describe robust security techniques that ensure a sound security of information gathered throughout agent’s itinerary against various security attacks, as well as truncation attacks. A sound security protocol is described, which implements the various security techniques that would jointly prevent or at least detect any malicious act of intruders. We reason about the soundness of the protocol usingSymbolic Trace Analyzer (STA), a formal verification tool that is based on symbolic techniques. We analyze the protocol in key configurations and show that it is free of flaws. We also show that the protocol fulfils the various security requirements of exchanged information in MAS, including data-integrity, data-confidentiality, data-authenticity, origin confidentiality and data non-repudiability.

Data based abnormality detection

NASA Astrophysics Data System (ADS)

Purwar, Yashasvi

Data based abnormality detection is a growing research field focussed on extracting information from feature rich data. They are considered to be non-intrusive and non-destructive in nature which gives them a clear advantage over conventional methods. In this study, we explore different streams of data based anomalies detection. We propose extension and revisions to existing valve stiction detection algorithm supported with industrial case study. We also explored the area of image analysis and proposed a complete solution for Malaria diagnosis. The proposed method is tested over images provided by pathology laboratory at Alberta Health Service. We also address the robustness and practicality of the solution proposed.

Memory Detection 2.0: The First Web-Based Memory Detection Test

PubMed Central

Kleinberg, Bennett; Verschuere, Bruno

2015-01-01

There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research. PMID:25874966

[A study on the thermographic diagnosis of vibration disease of tie-tamper operators in the Japanese National Railways].

PubMed

Hirahata, H

1984-01-01

There have been many studies of thermographic diagnosis of vibration disease, but few of them seem to have discussed tie-tamping machines as a cause. This study focuses on thermographic diagnosis of vibration disease in tie-tamper operators of the Japanese National Railways. In the diagnosis the subject's both hands were immersed in water at 10 degrees C for 3 minutes before being examined. Variables such as season, age, type of vibration tool used and total operating time were considered. These were selected as outside variables and thermographic results as dependent variables, in Quantification Method II. Season and confirmation of vibration disease were found to have a relationship to thermographic scaling, but no such relationship was found for age, type of vibration tool used, or total operating time. A cross-analysis of variables confirmed the relationship with season, and revealed that there were fewer confirmed cases of vibration disease in spring and summer than in fall and winter. It was finally concluded that thermographic analysis is more reliable in colder weather.

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Authenticity screening of seized whiskey samples using electrophoresis microchips coupled with contactless conductivity detection.

PubMed

Rezende, Kariolanda C A; Moreira, Roger Cardoso; Logrado, Lucio Paulo Lima; Talhavini, Márcio; Coltro, Wendell K T

2016-10-01

This report describes for the first time the use of microchip electrophoresis (ME) devices integrated with capacitively coupled contactless conductivity detection (C 4 D) to investigate the authenticity of seized whiskey samples, which were probably adulterated by simple dilution with tap water. The proposed microfluidic platform was explored for the monitoring of anionic species (Cl - and F - ) in both original and tampered samples. The best separations were achieved within 70 s using a running buffer composed of lactic acid and histidine (pH = 5.9). ME-C 4 D devices were used to analyze samples from three different brands (five samples each). Based on the presence of inorganic anions like Cl - , F - , SO 4 2- and NO 2 - in different amounts, the authenticity of seized whiskeys was compared to original samples. According to the reported data, the proposed microfluidic platform can be useful to help regulatory authorities in the investigation and monitoring of authenticity of commercialized whiskey beverages. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A complete passive blind image copy-move forensics scheme based on compound statistics features.

PubMed

Peng, Fei; Nie, Yun-ying; Long, Min

2011-10-10

Since most sensor pattern noise based image copy-move forensics methods require a known reference sensor pattern noise, it generally results in non-blinded passive forensics, which significantly confines the application circumstances. In view of this, a novel passive-blind image copy-move forensics scheme is proposed in this paper. Firstly, a color image is transformed into a grayscale one, and wavelet transform based de-noising filter is used to extract the sensor pattern noise, then the variance of the pattern noise, the signal noise ratio between the de-noised image and the pattern noise, the information entropy and the average energy gradient of the original grayscale image are chosen as features, non-overlapping sliding window operations are done to the images to divide them into different sub-blocks. Finally, the tampered areas are detected by analyzing the correlation of the features between the sub-blocks and the whole image. Experimental results and analysis show that the proposed scheme is completely passive-blind, has a good detection rate, and is robust against JPEG compression, noise, rotation, scaling and blurring. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Standoff laser-based spectroscopy for explosives detection

NASA Astrophysics Data System (ADS)

Gaft, M.; Nagli, L.

2007-10-01

Real time detection and identification of explosives at a standoff distance is a major issue in efforts to develop defense against so-called Improvised Explosive Devices (IED). It is recognized that the only technique, which is potentially capable to standoff detection of minimal amounts of explosives is laser-based spectroscopy. LDS activity is based on a combination of laser-based spectroscopic methods with orthogonal capabilities. Our technique belongs to trace detection, namely to its micro-particles variety. It is based on commonly held belief that surface contamination was very difficult to avoid and could be exploited for standoff detection. We has applied optical techniques including gated Raman and time-resolved luminescence spectroscopy for detection of main explosive materials, both factory and homemade. We developed and tested a Raman system for the field remote detection and identification of minimal amounts of explosives on relevant surfaces at a distance of up to 30 meters.

Ladar-based IED detection

NASA Astrophysics Data System (ADS)

Engström, Philip; Larsson, Hâkan; Letalick, Dietmar

2014-05-01

An improvised explosive device (IED) is a bomb constructed and deployed in a non-standard manor. Improvised means that the bomb maker took whatever he could get his hands on, making it very hard to predict and detect. Nevertheless, the matters in which the IED's are deployed and used, for example as roadside bombs, follow certain patterns. One possible approach for early warning is to record the surroundings when it is safe and use this as reference data for change detection. In this paper a LADAR-based system for IED detection is presented. The idea is to measure the area in front of the vehicle when driving and comparing this to the previously recorded reference data. By detecting new, missing or changed objects the system can make the driver aware of probable threats.

Vision Based Obstacle Detection in Uav Imaging

NASA Astrophysics Data System (ADS)

Badrloo, S.; Varshosaz, M.

2017-08-01

Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

Microcontroller based driver alertness detection systems to detect drowsiness

NASA Astrophysics Data System (ADS)

Adenin, Hasibah; Zahari, Rahimi; Lim, Tiong Hoo

2018-04-01

The advancement of embedded system for detecting and preventing drowsiness in a vehicle is a major challenge for road traffic accident systems. To prevent drowsiness while driving, it is necessary to have an alert system that can detect a decline in driver concentration and send a signal to the driver. Studies have shown that traffc accidents usually occur when the driver is distracted while driving. In this paper, we have reviewed a number of detection systems to monitor the concentration of a car driver and propose a portable Driver Alertness Detection System (DADS) to determine the level of concentration of the driver based on pixelated coloration detection technique using facial recognition. A portable camera will be placed at the front visor to capture facial expression and the eye activities. We evaluate DADS using 26 participants and have achieved 100% detection rate with good lighting condition and a low detection rate at night.

Immunity-Based Aircraft Fault Detection System

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

A Targeted Attack For Enhancing Resiliency of Intelligent Intrusion Detection Modules in Energy Cyber Physical Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Youssef, Tarek; El Hariri, Mohammad; Habib, Hani

Abstract— Secure high-speed communication is required to ensure proper operation of complex power grid systems and prevent malicious tampering activities. In this paper, artificial neural networks with temporal dependency are introduced for false data identification and mitigation for broadcasted IEC 61850 SMV messages. The fast responses of such intelligent modules in intrusion detection make them suitable for time- critical applications, such as protection. However, care must be taken in selecting the appropriate intelligence model and decision criteria. As such, this paper presents a customizable malware script to sniff and manipulate SMV messages and demonstrates the ability of the malware tomore » trigger false positives in the neural network’s response. The malware developed is intended to be as a vaccine to harden the intrusion detection system against data manipulation attacks by enhancing the neural network’s ability to learn and adapt to these attacks.« less

Occupational exposure to electric and magnetic fields during work tasks at 110 kV substations in the Tampere region.

PubMed

Korpinen, Leena H; Pääkkönen, Rauno J

2010-04-01

The occupational exposure to electric and magnetic fields during various work tasks at seven 110 kV substations in Finland's Tampere region was studied. The aim was to investigate if the action values (10 kV/m for the E-field and 500 microT for the B-field) of the EU Directive 2004/40/EC were exceeded. Electric and magnetic fields were measured during the following work tasks: (1) walking or operating devices on the ground; (2) working from a service platform; (3) working around the power transformer on the ground or using a ladder; and (4) changing a bulb from a man hoist. In work task 2 "working from a service platform" the measured electric field (maximum value 16.6 kV/m) exceeded 10 kV/m in three cases. In the future it is important to study if the limit value (10 mA/m(2)) of Directive 2004/40/EC is exceeded at 110 kV substations. The occupational 500 microT action value of the magnetic flux density field (B-field) was not exceeded in any working situation.

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

On event-based optical flow detection

PubMed Central

Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

2015-01-01

Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

Daytime Water Detection Based on Sky Reflections

NASA Technical Reports Server (NTRS)

Rankin, Arturo; Matthies, Larry; Bellutta, Paolo

2011-01-01

A water body s surface can be modeled as a horizontal mirror. Water detection based on sky reflections and color variation are complementary. A reflection coefficient model suggests sky reflections dominate the color of water at ranges > 12 meters. Water detection based on sky reflections: (1) geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground (2) predicts if the ground pixel is water based on color similarity and local terrain features. Water detection has been integrated on XUVs.

Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

PubMed

Housh, Mashor; Ohar, Ziv

2017-03-01

The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Vision-based vehicle detection and tracking algorithm design

NASA Astrophysics Data System (ADS)

Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

2009-12-01

The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

Laser-based detection of chemical contraband

NASA Astrophysics Data System (ADS)

Clemmer, Robert G.; Kelly, James F.; Martin, Steven W.; Mong, Gary M.; Sharpe, Steven W.

1997-02-01

The goal of our work is tow fold; 1) develop a portable and rapid laser based air sampler for detection of specific chemical contraband and 2) compile a spectral data base in both the near- and mid-IR of sufficiently high quality to be useful for gas phase spectroscopic identification of chemical contraband. During the synthesis or 'cooking' of many illicit chemical substances, relatively high concentrations of volatile solvents, chemical precursors and byproducts are unavoidably released to the atmosphere. In some instances, the final product may have sufficient vapor pressure to be detectable in the surrounding air. The detection of a single high-value effluent or the simultaneous detection of two or more low-value effluents can be used as reliable indicators of a nearby clandestine cooking operation. The designation of high- versus low-value effluent reflects both the commercial availability and legitimate usage of a specific chemical. This paper will describe PNNL's progress and efforts towards the development of a portable laser based air sampling system for the detection of clandestine manufacturing of methamphetamine. Although our current efforts ar focused on methamphetamine, we see no fundamental limitations on detection of other forms of chemical contraband manufacturing. This also includes the synthesis of certain classes of chemical weapons that have recently been deployed by terrorist groups.

Transistor-based particle detection systems and methods

DOEpatents

Jain, Ankit; Nair, Pradeep R.; Alam, Muhammad Ashraful

2015-06-09

Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

10 CFR 73.25 - Performance capabilities for physical protection of strategic special nuclear material in transit.

Code of Federal Regulations, 2012 CFR

2012-01-01

... tampering with transports and cargo containers; and (iii) Surveillance subsystems and procedures to detect... to establish activities for transferring cargo in emergency situations; and (iii) Removal controls...

10 CFR 73.25 - Performance capabilities for physical protection of strategic special nuclear material in transit.

Code of Federal Regulations, 2011 CFR

2011-01-01

... tampering with transports and cargo containers; and (iii) Surveillance subsystems and procedures to detect... to establish activities for transferring cargo in emergency situations; and (iii) Removal controls...

Median filtering detection using variation of neighboring line pairs for image forensics

NASA Astrophysics Data System (ADS)

Rhee, Kang Hyeon

2016-09-01

Attention to tampering by median filtering (MF) has recently increased in digital image forensics. For the MF detection (MFD), this paper presents a feature vector that is extracted from two kinds of variations between the neighboring line pairs: the row and column directions. Of these variations in the proposed method, one is defined by a gradient difference of the intensity values between the neighboring line pairs, and the other is defined by a coefficient difference of the Fourier transform (FT) between the neighboring line pairs. Subsequently, the constructed 19-dimensional feature vector is composed of these two parts. One is the extracted 9-dimensional from the space domain of an image and the other is the 10-dimensional from the frequency domain of an image. The feature vector is trained in a support vector machine classifier for MFD in the altered images. As a result, in the measured performances of the experimental items, the area under the receiver operating characteristic curve (AUC, ROC) by the sensitivity (PTP: the true positive rate) and 1-specificity (PFP: the false-positive rate) are above 0.985 and the classification ratios are also above 0.979. Pe (a minimal average decision error) ranges from 0 to 0.024, and PTP at PFP=0.01 ranges from 0.965 to 0.996. It is confirmed that the grade evaluation of the proposed variation-based MF detection method is rated as "Excellent (A)" by AUC is above 0.9.

Detection of Capsule Tampering by Near-Infrared Reflectance Analysis.

DTIC Science & Technology

1987-08-01

22b. TELEPHONE (Include Area Code) I 22c OFFICE SYM "!f Gar H. HieftJe (812) 335-2189 DO FORM 1473,84 MAR 83 APR edition may be used until exhausted...500 to S0 mg of KCN, and the KCN consisted of fairly large crystals while the analgesic was a powder of small particle size (4,12). Potassium cyanide...10) usually necessary, so NIRA instruments are relatively inexpensive. Little or no ample preparation is required in NIRA, and powders can be directly

Source Camera Identification and Blind Tamper Detections for Images

DTIC Science & Technology

2007-04-24

measures and image quality measures in camera identification problem was studied using conjunction with a KNN classifier to identify the feature sets...shots varying from nature scenes .-.. motorala to close-ups of people. We experimented with the KNN *~. * ny classifier (K=5) as well SVM algorithm of...on Acoustic, Speech and Signal Processing (ICASSP), France, May 2006, vol. 5, pp. 401-404. [9] H. Farid and S. Lyu, "Higher-order wavelet statistics

10 CFR 73.51 - Requirements for the physical protection of stored spent nuclear fuel and high-level radioactive...

Code of Federal Regulations, 2014 CFR

2014-01-01

... security organization must include sufficient personnel per shift to provide for monitoring of detection... authorization and visually searched for explosives before entry. (10) Written response procedures must be... termination of the license. (11) All detection systems and supporting subsystems must be tamper indicating...

10 CFR 73.51 - Requirements for the physical protection of stored spent nuclear fuel and high-level radioactive...

Code of Federal Regulations, 2011 CFR

2011-01-01

... security organization must include sufficient personnel per shift to provide for monitoring of detection... authorization and visually searched for explosives before entry. (10) Written response procedures must be... termination of the license. (11) All detection systems and supporting subsystems must be tamper indicating...

10 CFR 73.51 - Requirements for the physical protection of stored spent nuclear fuel and high-level radioactive...

Code of Federal Regulations, 2012 CFR

2012-01-01

... security organization must include sufficient personnel per shift to provide for monitoring of detection... authorization and visually searched for explosives before entry. (10) Written response procedures must be... termination of the license. (11) All detection systems and supporting subsystems must be tamper indicating...

10 CFR 73.51 - Requirements for the physical protection of stored spent nuclear fuel and high-level radioactive...

Code of Federal Regulations, 2013 CFR

2013-01-01

... security organization must include sufficient personnel per shift to provide for monitoring of detection... authorization and visually searched for explosives before entry. (10) Written response procedures must be... termination of the license. (11) All detection systems and supporting subsystems must be tamper indicating...

Automatic background updating for video-based vehicle detection

NASA Astrophysics Data System (ADS)

Hu, Chunhai; Li, Dongmei; Liu, Jichuan

2008-03-01

Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.

A universal DNA-based protein detection system.

PubMed

Tran, Thua N N; Cui, Jinhui; Hartman, Mark R; Peng, Songming; Funabashi, Hisakage; Duan, Faping; Yang, Dayong; March, John C; Lis, John T; Cui, Haixin; Luo, Dan

2013-09-25

Protein immune detection requires secondary antibodies which must be carefully selected in order to avoid interspecies cross-reactivity, and is therefore restricted by the limited availability of primary/secondary antibody pairs. Here we present a versatile DNA-based protein detection system using a universal adapter to interface between IgG antibodies and DNA-modified reporter molecules. As a demonstration of this capability, we successfully used DNA nano-barcodes, quantum dots, and horseradish peroxidase enzyme to detect multiple proteins using our DNA-based labeling system. Our system not only eliminates secondary antibodies but also serves as a novel method platform for protein detection with modularity, high capacity, and multiplexed capability.

A Universal DNA-Based Protein Detection System

PubMed Central

Tran, Thua N. N.; Cui, Jinhui; Hartman, Mark R.; Peng, Songming; Funabashi, Hisakage; Duan, Faping; Yang, Dayong; March, John C.; Lis, John T.; Cui, Haixin; Luo, Dan

2014-01-01

Protein immune detection requires secondary antibodies which must be carefully selected in order to avoid interspecies cross-reactivity, and is therefore restricted by the limited availability of primary/secondary antibody pairs. Here we present a versatile DNA-based protein detection system using a universal adapter to interface between IgG antibodies and DNA-modified reporter molecules. As a demonstration of this capability, we successfully used DNA nano-barcodes, quantum dots, and horseradish peroxidase enzyme to detect multiple proteins using our DNA-based labeling system. Our system not only eliminates secondary antibodies but also serves as a novel method platform for protein detection with modularity, high capacity, and multiplexed capability. PMID:23978265

High-performance combination method of electric network frequency and phase for audio forgery detection in battery-powered devices.

PubMed

Savari, Maryam; Abdul Wahab, Ainuddin Wahid; Anuar, Nor Badrul

2016-09-01

Audio forgery is any act of tampering, illegal copy and fake quality in the audio in a criminal way. In the last decade, there has been increasing attention to the audio forgery detection due to a significant increase in the number of forge in different type of audio. There are a number of methods for forgery detection, which electric network frequency (ENF) is one of the powerful methods in this area for forgery detection in terms of accuracy. In spite of suitable accuracy of ENF in a majority of plug-in powered devices, the weak accuracy of ENF in audio forgery detection for battery-powered devices, especially in laptop and mobile phone, can be consider as one of the main obstacles of the ENF. To solve the ENF problem in terms of accuracy in battery-powered devices, a combination method of ENF and phase feature is proposed. From experiment conducted, ENF alone give 50% and 60% accuracy for forgery detection in mobile phone and laptop respectively, while the proposed method shows 88% and 92% accuracy respectively, for forgery detection in battery-powered devices. The results lead to higher accuracy for forgery detection with the combination of ENF and phase feature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Faint Debris Detection by Particle Based Track-Before-Detect Method

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired

Fire flame detection based on GICA and target tracking

NASA Astrophysics Data System (ADS)

Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

2013-04-01

To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

An immunity-based anomaly detection system with sensor agents.

PubMed

Okamoto, Takeshi; Ishida, Yoshiteru

2009-01-01

This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.

2001-09-01

This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerablemore » preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.« less

Attribute and topology based change detection in a constellation of previously detected objects

DOEpatents

Paglieroni, David W.; Beer, Reginald N.

2016-01-19

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

Research of detection depth for graphene-based optical sensor

NASA Astrophysics Data System (ADS)

Yang, Yong; Sun, Jialve; Liu, Lu; Zhu, Siwei; Yuan, Xiaocong

2018-03-01

Graphene-based optical sensors have been developed for research into the biological intercellular refractive index (RI) because they offer greater detection depths than those provided by the surface plasmon resonance technique. In this Letter, we propose an experimental approach for measurement of the detection depth in a graphene-based optical sensor system that uses transparent polydimethylsiloxane layers with different thicknesses. The experimental results show that detection depths of 2.5 μm and 3 μm can be achieved at wavelengths of 532 nm and 633 nm, respectively. These results prove that graphene-based optical sensors can realize long-range RI detection and are thus promising for use as tools in the biological cell detection field. Additionally, we analyze the factors that influence the detection depth and provide a feasible approach for detection depth control based on adjustment of the wavelength and the angle of incidence. We believe that this approach will be useful in RI tomography applications.

Signal Detection Theory-Based Information Processing for the Detection of Breast Cancer at Microwave Frequencies

DTIC Science & Technology

2002-08-01

the measurement noise, as well as the physical model of the forward scattered electric field. The Bayesian algorithms for the Uncertain Permittivity...received at multiple sensors. In this research project a tissue- model -based signal-detection theory approach for the detection of mammary tumors in the...oriented information processors. In this research project a tissue- model - based signal detection theory approach for the detection of mammary tumors in the

Daytime Water Detection Based on Sky Reflections

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Matthies, Larry H.; Bellutta, Paolo

2011-01-01

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide-open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies. One of the properties of water useful for detecting it is that its surface acts as a horizontal mirror at large incidence angles. Water bodies can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. The Jet Propulsion Laboratory (JPL) has implemented a water detector based on sky reflections that geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground and predicts if the ground pixel is water based on color similarity and local terrain features. This software detects water bodies in wide-open areas on cross-country terrain at mid- to far-range using imagery acquired from a forward-looking stereo pair of color cameras mounted on a terrestrial UGV. In three test sequences approaching a pond under a clear, overcast, and cloudy sky, the true positive detection rate was 100% when the UGV was beyond 7 meters of the water's leading edge and the largest false positive detection rate was 0.58%. The sky reflection based water detector has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA, USA.

Point pattern match-based change detection in a constellation of previously detected objects

DOEpatents

Paglieroni, David W.

2016-06-07

A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

Bacteriophage-Based Pathogen Detection

NASA Astrophysics Data System (ADS)

Ripp, Steven

Considered the most abundant organism on Earth, at a population approaching 1031, bacteriophage, or phage for short, mediate interactions with myriad bacterial hosts that has for decades been exploited in phage typing schemes for signature identification of clinical, food-borne, and water-borne pathogens. With over 5,000 phage being morphologically characterized and grouped as to susceptible host, there exists an enormous cache of bacterial-specific sensors that has more recently been incorporated into novel bio-recognition assays with heightened sensitivity, specificity, and speed. These assays take many forms, ranging from straightforward visualization of labeled phage as they attach to their specific bacterial hosts to reporter phage that genetically deposit trackable signals within their bacterial hosts to the detection of progeny phage or other uniquely identifiable elements released from infected host cells. A comprehensive review of these and other phage-based detection assays, as directed towards the detection and monitoring of bacterial pathogens, will be provided in this chapter.

Conductive fabric seal

DOEpatents

Livesay, Ronald Jason; Mason, Brandon William; Kuhn, Michael Joseph; Rowe, Nathan Carl

2017-04-04

Disclosed are several examples of a system and method for detecting if an article is being tampered with. Included is a covering made of a substrate that is coated with a layer of an electrically conductive material that forms an electrically conductive surface having an electrical resistance. The covering is configured to at least partially encapsulate the article such that the article cannot be tampered with, without modifying the electrical resistance of the electrically conductive surface of the covering. A sensing device is affixed to the electrically conductive surface of the covering and the sensing device monitors the condition of the covering by producing a signal that is indicative of the electrical resistance of the electrically conductive surface of the covering. A measured electrical resistance that differs from a nominal electrical resistance is indicative of a covering that is being tampered with and an alert is communicated to an observer.

Conductive fabric seal

DOEpatents

Livesay, Ronald Jason; Mason, Brandon William; Kuhn, Michael Joseph; Rowe, Nathan Carl

2015-10-13

Disclosed are several examples of a system and method for detecting if an article is being tampered with. Included is a covering made of a substrate that is coated with a layer of an electrically conductive material that forms an electrically conductive surface having an electrical resistance. The covering is configured to at least partially encapsulate the article such that the article cannot be tampered with, without modifying the electrical resistance of the electrically conductive surface of the covering. A sensing device is affixed to the electrically conductive surface of the covering and the sensing device monitors the condition of the covering by producing a signal that is indicative of the electrical resistance of the electrically conductive surface of the covering. A measured electrical resistance that differs from a nominal electrical resistance is indicative of a covering that is being tampered with and an alert is communicated to an observer.

Remotely Monitored Sealing Array Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

2012-09-12

The Remotely Monitored Sealing Array (RMSA) utilizes the Secure Sensor Platform (SSP) framework to establish the fundamental operating capabilities for communication, security, power management, and cryptography. In addition to the SSP framework the RMSA software has unique capabilities to support monitoring a fiber optic seal. Fiber monitoring includes open and closed as well as parametric monitoring to detect tampering attacks. The fiber monitoring techniques, using the SSP power management processes, allow the seals to last for years while maintaining the security requirements of the monitoring application. The seal is enclosed in a tamper resistant housing with software to support activemore » tamper monitoring. New features include LED notification of fiber closure, the ability to retrieve the entire fiber optic history via translator command, separate memory storage for fiber optic events, and a more robust method for tracking and resending failed messages.« less

Train integrity detection risk analysis based on PRISM

NASA Astrophysics Data System (ADS)

Wen, Yuan

2018-04-01

GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

Current-based detection of nonlocal spin transport in graphene for spin-based logic applications

NASA Astrophysics Data System (ADS)

Wen, Hua; Zhu, Tiancong; Luo, Yunqiu Kelly; Amamou, Walid; Kawakami, Roland K.

2014-05-01

Graphene has been proposed for novel spintronic devices due to its robust and efficient spin transport properties at room temperature. Some of the most promising proposals require current-based readout for integration purposes, but the current-based detection of spin accumulation has not yet been developed. In this work, we demonstrate current-based detection of spin transport in graphene using a modified nonlocal geometry. By adding a variable shunt resistor in parallel to the nonlocal voltmeter, we are able to systematically cross over from the conventional voltage-based detection to current-based detection. As the shunt resistor is reduced, the output current from the spin accumulation increases as the shunt resistance drops below a characteristic value R*. We analyze this behavior using a one-dimensional drift-diffusion model, which accounts well for the observed behavior. These results provide the experimental and theoretical foundation for current-based detection of nonlocal spin transport.

Detection of cat-eye effect echo based on unit APD

NASA Astrophysics Data System (ADS)

Wu, Dong-Sheng; Zhang, Peng; Hu, Wen-Gang; Ying, Jia-Ju; Liu, Jie

2016-10-01

The cat-eye effect echo of optical system can be detected based on CCD, but the detection range is limited within several kilometers. In order to achieve long-range even ultra-long-range detection, it ought to select APD as detector because of the high sensitivity of APD. The detection system of cat-eye effect echo based on unit APD is designed in paper. The implementation scheme and key technology of the detection system is presented. The detection performances of the detection system including detection range, detection probability and false alarm probability are modeled. Based on the model, the performances of the detection system are analyzed using typical parameters. The results of numerical calculation show that the echo signal-to-noise ratio is greater than six, the detection probability is greater than 99.9% and the false alarm probability is less tan 0.1% within 20 km detection range. In order to verify the detection effect, we built the experimental platform of detection system according to the design scheme and carry out the field experiments. The experimental results agree well with the results of numerical calculation, which prove that the detection system based on the unit APD is feasible to realize remote detection for cat-eye effect echo.

Water Detection Based on Object Reflections

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Matthies, Larry H.

2012-01-01

Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

Saliency detection algorithm based on LSC-RC

NASA Astrophysics Data System (ADS)

Wu, Wei; Tian, Weiye; Wang, Ding; Luo, Xin; Wu, Yingfei; Zhang, Yu

2018-02-01

Image prominence is the most important region in an image, which can cause the visual attention and response of human beings. Preferentially allocating the computer resources for the image analysis and synthesis by the significant region is of great significance to improve the image area detecting. As a preprocessing of other disciplines in image processing field, the image prominence has widely applications in image retrieval and image segmentation. Among these applications, the super-pixel segmentation significance detection algorithm based on linear spectral clustering (LSC) has achieved good results. The significance detection algorithm proposed in this paper is better than the regional contrast ratio by replacing the method of regional formation in the latter with the linear spectral clustering image is super-pixel block. After combining with the latest depth learning method, the accuracy of the significant region detecting has a great promotion. At last, the superiority and feasibility of the super-pixel segmentation detection algorithm based on linear spectral clustering are proved by the comparative test.

Security of fragile authentication watermarks with localization

NASA Astrophysics Data System (ADS)

Fridrich, Jessica

2002-04-01

In this paper, we study the security of fragile image authentication watermarks that can localize tampered areas. We start by comparing the goals, capabilities, and advantages of image authentication based on watermarking and cryptography. Then we point out some common security problems of current fragile authentication watermarks with localization and classify attacks on authentication watermarks into five categories. By investigating the attacks and vulnerabilities of current schemes, we propose a variation of the Wong scheme18 that is fast, simple, cryptographically secure, and resistant to all known attacks, including the Holliman-Memon attack9. In the new scheme, a special symmetry structure in the logo is used to authenticate the block content, while the logo itself carries information about the block origin (block index, the image index or time stamp, author ID, etc.). Because the authentication of the content and its origin are separated, it is possible to easily identify swapped blocks between images and accurately detect cropped areas, while being able to accurately localize tampered pixels.

Water Detection Based on Sky Reflections

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.; Matthies, Larry H.

2010-01-01

This software has been designed to detect water bodies that are out in the open on cross-country terrain at mid- to far-range (approximately 20 100 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). Non-traversable water bodies, such as large puddles, ponds, and lakes, are indirectly detected by detecting reflections of the sky below the horizon in color imagery. The appearance of water bodies in color imagery largely depends on the ratio of light reflected off the water surface to the light coming out of the water body. When a water body is far away, the angle of incidence is large, and the light reflected off the water surface dominates. We have exploited this behavior to detect water bodies out in the open at mid- to far-range. When a water body is detected at far range, a UGV s path planner can begin to look for alternate routes to the goal position sooner, rather than later. As a result, detecting water hazards at far range generally reduces the time required to reach a goal position during autonomous navigation. This software implements a new water detector based on sky reflections that geometrically locates the exact pixel in the sky that is reflecting on a candidate water pixel on the ground, and predicts if the ground pixel is water based on color similarity and local terrain features

Change detection from remotely sensed images: From pixel-based to object-based approaches

NASA Astrophysics Data System (ADS)

Hussain, Masroor; Chen, Dongmei; Cheng, Angela; Wei, Hui; Stanley, David

2013-06-01

The appetite for up-to-date information about earth's surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection.

Passive detection of copy-move forgery in digital images: state-of-the-art.

PubMed

Al-Qershi, Osamah M; Khoo, Bee Ee

2013-09-10

Currently, digital images and videos have high importance because they have become the main carriers of information. However, the relative ease of tampering with images and videos makes their authenticity untrustful. Digital image forensics addresses the problem of the authentication of images or their origins. One main branch of image forensics is passive image forgery detection. Images could be forged using different techniques, and the most common forgery is the copy-move, in which a region of an image is duplicated and placed elsewhere in the same image. Active techniques, such as watermarking, have been proposed to solve the image authenticity problem, but those techniques have limitations because they require human intervention or specially equipped cameras. To overcome these limitations, several passive authentication methods have been proposed. In contrast to active methods, passive methods do not require any previous information about the image, and they take advantage of specific detectable changes that forgeries can bring into the image. In this paper, we describe the current state-of-the-art of passive copy-move forgery detection methods. The key current issues in developing a robust copy-move forgery detector are then identified, and the trends of tackling those issues are addressed. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

[Detecting fire smoke based on the multispectral image].

PubMed

Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei

2010-04-01

Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.

Rate based failure detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or datamore » paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.« less

Abuse-deterrent formulations: part 1 - development of a formulation-based classification system.

PubMed

Mastropietro, David J; Omidian, Hossein

2015-02-01

Strategies have been implemented to decrease the large proportion of individuals misusing abusable prescription medications. Abuse-deterrent formulations (ADFs) have been grown to incorporate many different technologies that still lack a systematic naming and organizational nomenclature. Without a proper classification system, it has been challenging to properly identify ADFs, study and determine common traits or characteristics and simplify communication within the field. This article introduces a classification system for all ADF approaches and examines the physical, chemical and pharmacological characteristics of a formulation by placing them into primary, secondary and tertiary categories. Primary approaches block tampering done directly to the product. Secondary approaches work in vivo after the product is administered. Tertiary approaches use materials that discourage abuse but do not stop tampering. Part 2 of this article discusses proprietary technologies, patents and products utilizing primary approaches. Drug products using opioid antagonists and aversive agents have been seen over the past few decades to discourage primarily overuse and injection. However, innovation in formulation development has introduced products capable of deterring multiple forms of tampering and abuse. Often, this is accomplished using known excipients and manufacturing methods that are repurposed to prevent crushing, extraction and syringeability.

DNA aptamer-based colorimetric detection platform for Salmonella Enteritidis.

PubMed

Bayraç, Ceren; Eyidoğan, Füsun; Avni Öktem, Hüseyin

2017-12-15

Food safety is a major issue to protect public health and a key challenge is to find detection methods for identification of hazards in food. Food borne infections affects millions of people each year and among pathogens, Salmonella Enteritidis is most widely found bacteria causing food borne diseases. Therefore, simple, rapid, and specific detection methods are needed for food safety. In this study, we demonstrated the selection of DNA aptamers with high affinity and specificity against S. Enteritidis via Cell Systematic Evolution of Ligands by Exponential Enrichment (Cell-SELEX) and development of sandwich type aptamer-based colorimetric platforms for its detection. Two highly specific aptamers, crn-1 and crn-2, were developed through 12 rounds of selection with K d of 0.971µM and 0.309µM, respectively. Both aptamers were used to construct sandwich type capillary detection platforms. With the detection limit of 10 3 CFU/mL, crn-1 and crn-2 based platforms detected target bacteria specifically based on color change. This platform is also suitable for detection of S. Enteritidis in complex food matrix. Thus, this is the first to demonstrate use of Salmonella aptamers for development of the colorimetric aptamer-based detection platform in its identification and detection with naked eye in point-of-care. Copyright © 2017 Elsevier B.V. All rights reserved.

An FPGA-Based People Detection System

NASA Astrophysics Data System (ADS)

Nair, Vinod; Laprise, Pierre-Olivier; Clark, James J.

2005-12-01

This paper presents an FPGA-based system for detecting people from video. The system is designed to use JPEG-compressed frames from a network camera. Unlike previous approaches that use techniques such as background subtraction and motion detection, we use a machine-learning-based approach to train an accurate detector. We address the hardware design challenges involved in implementing such a detector, along with JPEG decompression, on an FPGA. We also present an algorithm that efficiently combines JPEG decompression with the detection process. This algorithm carries out the inverse DCT step of JPEG decompression only partially. Therefore, it is computationally more efficient and simpler to implement, and it takes up less space on the chip than the full inverse DCT algorithm. The system is demonstrated on an automated video surveillance application and the performance of both hardware and software implementations is analyzed. The results show that the system can detect people accurately at a rate of about[InlineEquation not available: see fulltext.] frames per second on a Virtex-II 2V1000 using a MicroBlaze processor running at[InlineEquation not available: see fulltext.], communicating with dedicated hardware over FSL links.

Wavelet based detection of manatee vocalizations

NASA Astrophysics Data System (ADS)

Gur, Berke M.; Niezrecki, Christopher

2005-04-01

The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. Several boater warning systems, based upon manatee vocalizations, have been proposed to reduce the number of collisions. Three detection methods based on the Fourier transform (threshold, harmonic content and autocorrelation methods) were previously suggested and tested. In the last decade, the wavelet transform has emerged as an alternative to the Fourier transform and has been successfully applied in various fields of science and engineering including the acoustic detection of dolphin vocalizations. As of yet, no prior research has been conducted in analyzing manatee vocalizations using the wavelet transform. Within this study, the wavelet transform is used as an alternative to the Fourier transform in detecting manatee vocalizations. The wavelet coefficients are analyzed and tested against a specified criterion to determine the existence of a manatee call. The performance of the method presented is tested on the same data previously used in the prior studies, and the results are compared. Preliminary results indicate that using the wavelet transform as a signal processing technique to detect manatee vocalizations shows great promise.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

Detection of heavy metal by paper-based microfluidics.

PubMed

Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

2016-09-15

Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Arduino-based noise robust online heart-rate detection.

PubMed

Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

2017-04-01

This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

A Hybrid Digital-Signature and Zero-Watermarking Approach for Authentication and Protection of Sensitive Electronic Documents

PubMed Central

Kabir, Muhammad N.; Alginahi, Yasser M.

2014-01-01

This paper addresses the problems and threats associated with verification of integrity, proof of authenticity, tamper detection, and copyright protection for digital-text content. Such issues were largely addressed in the literature for images, audio, and video, with only a few papers addressing the challenge of sensitive plain-text media under known constraints. Specifically, with text as the predominant online communication medium, it becomes crucial that techniques are deployed to protect such information. A number of digital-signature, hashing, and watermarking schemes have been proposed that essentially bind source data or embed invisible data in a cover media to achieve its goal. While many such complex schemes with resource redundancies are sufficient in offline and less-sensitive texts, this paper proposes a hybrid approach based on zero-watermarking and digital-signature-like manipulations for sensitive text documents in order to achieve content originality and integrity verification without physically modifying the cover text in anyway. The proposed algorithm was implemented and shown to be robust against undetected content modifications and is capable of confirming proof of originality whilst detecting and locating deliberate/nondeliberate tampering. Additionally, enhancements in resource utilisation and reduced redundancies were achieved in comparison to traditional encryption-based approaches. Finally, analysis and remarks are made about the current state of the art, and future research issues are discussed under the given constraints. PMID:25254247

Stand-off imaging Raman spectroscopy for forensic analysis of post-blast scenes: trace detection of ammonium nitrate and 2,4,6-trinitrotoluene

NASA Astrophysics Data System (ADS)

Ceco, Ema; Önnerud, Hans; Menning, Dennis; Gilljam, John L.; Bââth, Petra; Östmark, Henric

2014-05-01

The following paper presents a realistic forensic capability test of an imaging Raman spectroscopy based demonstrator system, developed at FOI, the Swedish Defence Research Agency. The system uses a 532 nm laser to irradiate a surface of 25×25mm. The backscattered radiation from the surface is collected by an 8" telescope with subsequent optical system, and is finally imaged onto an ICCD camera. We present here an explosives trace analysis study of samples collected from a realistic scenario after a detonation. A left-behind 5 kg IED, based on ammonium nitrate with a TNT (2,4,6-trinitrotoluene) booster, was detonated in a plastic garbage bin. Aluminum sample plates were mounted vertically on a holder approximately 6 m from the point of detonation. Minutes after the detonation, the samples were analyzed with stand-off imaging Raman spectroscopy from a distance of 10 m. Trace amounts could be detected from the secondary explosive (ammonium nitrate with an analysis time of 1 min. Measurement results also indicated detection of residues from the booster (TNT). The sample plates were subsequently swabbed and analyzed with HPLC and GC-MS analyses to confirm the results from the stand-off imaging Raman system. The presented findings indicate that it is possible to determine the type of explosive used in an IED from a distance, within minutes after the attack, and without tampering with physical evidence at the crime scene.

Design of fire detection equipment based on ultraviolet detection technology

NASA Astrophysics Data System (ADS)

Liu, Zhenji; Liu, Jin; Chu, Sheng; Ping, Chao; Yuan, Xiaobing

2015-03-01

Utilized the feature of wide bandgap semiconductor of MgZnO, researched and developed a kind of Mid-Ultraviolet-Band(MUV) ultraviolet detector which has passed the simulation experiment in the sun circumstance. Based on the ultraviolet detector, it gives out a design scheme of gun-shot detection device, which is composed of twelve ultraviolet detectors, signal amplifier, processor, annunciator , azimuth indicator and the bracket. Through Analysing the feature of solar blind, ultraviolet responsivity, fire feature of gunshots and detection distance, the feasibility of this design scheme is proved.

Automatic food intake detection based on swallowing sounds.

PubMed

Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

2012-11-01

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions.

Automatic food intake detection based on swallowing sounds

PubMed Central

Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

2012-01-01

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions. PMID:23125873

Laser-based standoff detection of explosives: a critical review.

PubMed

Wallin, Sara; Pettersson, Anna; Ostmark, Henric; Hobro, Alison

2009-09-01

A review of standoff detection technologies for explosives has been made. The review is focused on trace detection methods (methods aiming to detect traces from handling explosives or the vapours surrounding an explosive charge due to the vapour pressure of the explosive) rather than bulk detection methods (methods aiming to detect the bulk explosive charge). The requirements for standoff detection technologies are discussed. The technologies discussed are mostly laser-based trace detection technologies, such as laser-induced-breakdown spectroscopy, Raman spectroscopy, laser-induced-fluorescence spectroscopy and IR spectroscopy but the bulk detection technologies millimetre wave imaging and terahertz spectroscopy are also discussed as a complement to the laser-based methods. The review includes novel techniques, not yet tested in realistic environments, more mature technologies which have been tested outdoors in realistic environments as well as the most mature millimetre wave imaging technique.

Aptamer-based SERRS Sensor for Thrombin Detection

PubMed Central

Cho, Hansang; Baker, Brian R.; Wachsmann-Hogiu, Sebastian; Pagba, Cynthia V.; Laurence, Ted A.; Lane, Stephen M.; Lee, Luke P.; Tok, Jeffrey B.-H.

2012-01-01

We describe an aptamer-based Surface Enhanced Resonance Raman Scattering (SERRS) sensor with high sensitivity, specificity, and stability for the detection of a coagulation protein, human α-thrombin. The sensor achieves high sensitivity and a limit of detection of 100 pM by monitoring the SERRS signal change upon the single step of thrombin binding to immobilized thrombin binding aptamer. The selectivity of the sensor is demonstrated by the specific discrimination of thrombin from other protein analytes. The specific recognition and binding of thrombin by the thrombin binding aptamer is essential to the mechanism of the aptamer-based sensor, as shown through measurements using negative control oligonucleotides. In addition, the sensor can detect 1 nM thrombin in the presence of complex biofluids, such as 10% fetal calf serum, demonstrating that the immobilized, 5'-capped, 3'-capped aptamer is sufficiently robust for clinical diagnostic applications. Furthermore, the proposed sensor may be implemented for multiplexed detection using different aptamer-Raman probe complexes. PMID:19367849

Shadow-Based Vehicle Detection in Urban Traffic

PubMed Central

Ibarra-Arenado, Manuel; Tjahjadi, Tardi; Pérez-Oria, Juan; Robla-Gómez, Sandra; Jiménez-Avello, Agustín

2017-01-01

Vehicle detection is a fundamental task in Forward Collision Avoiding Systems (FACS). Generally, vision-based vehicle detection methods consist of two stages: hypotheses generation and hypotheses verification. In this paper, we focus on the former, presenting a feature-based method for on-road vehicle detection in urban traffic. Hypotheses for vehicle candidates are generated according to the shadow under the vehicles by comparing pixel properties across the vertical intensity gradients caused by shadows on the road, and followed by intensity thresholding and morphological discrimination. Unlike methods that identify the shadow under a vehicle as a road region with intensity smaller than a coarse lower bound of the intensity for road, the thresholding strategy we propose determines a coarse upper bound of the intensity for shadow which reduces false positives rates. The experimental results are promising in terms of detection performance and robustness in day time under different weather conditions and cluttered scenarios to enable validation for the first stage of a complete FACS. PMID:28448465

Magnetic wire trap arrays for biomarker-based molecular detection

NASA Astrophysics Data System (ADS)

Vieira, Gregory; Mahajan, Kalpesh; Ruan, Gang; Winter, Jessica; Sooryakumar, R.

2012-02-01

Submicrometer-scale magnetic devices built on chip-based platforms have recently been shown to present opportunities for new particle trapping and manipulation technologies. Meanwhile, advances in nanoparticle fabrication allow for the building of custom-made particles with precise control of their size, composition, and other properties such as magnetism, fluorescence, and surface biomarker characteristics. In particular, carefully tailored surface biomarkers facilitate precise binding to targeted molecules, self-actuated construction of hybrid structures, and fluorescence-based detection schemes. Based on these progresses, we present an on-chip detection mechanism for molecules with known surface markers. Hybrid nanostructures consisting of micelle nanoparticles, fluorescent quantum dots, and superparamagnetic iron oxide nanoparticles are used to detect proteins or DNA molecules. The target is detected by the magnetic and fluorescent functionalities of the composite nanostructure, whereas in the absence of the target these signals are not present. Underlying this approach is the simultaneous manipulation via ferromagnetic zigzag nanowire arrays and imaging via quantum dot excitation. This chip-based detection technique could provide a powerful, low cost tool for ultrasensitive molecule detection with ramifications in healthcare diagnostics and small-scale chemical synthesis.

Human visual system-based smoking event detection

NASA Astrophysics Data System (ADS)

Odetallah, Amjad D.; Agaian, Sos S.

2012-06-01

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

Detection limit of a VCO based detection chain dedicated to particles recognition and tracking

NASA Astrophysics Data System (ADS)

Coulié, K.; Rahajandraibe, W.; Aziza, H.; Micolau, G.; Vauché, R.

2018-01-01

A particle detection chain based on CMOS-SOI VCO circuit is presented. The solution is used for the recognition and the tracking of a given particle at circuit level. TCAD simulation of the detector has been performed on a 3×3 matrix of diodes based detector for particles recognition and tracking. The current response of the detector has been used for a case study in order to determine the ability of the chain to recognize an alpha particle crossing a 3×3 detection cell. The detection limit of the proposed solution is investigated and discussed in this paper.

Salient object detection method based on multiple semantic features

NASA Astrophysics Data System (ADS)

Wang, Chunyang; Yu, Chunyan; Song, Meiping; Wang, Yulei

2018-04-01

The existing salient object detection model can only detect the approximate location of salient object, or highlight the background, to resolve the above problem, a salient object detection method was proposed based on image semantic features. First of all, three novel salient features were presented in this paper, including object edge density feature (EF), object semantic feature based on the convex hull (CF) and object lightness contrast feature (LF). Secondly, the multiple salient features were trained with random detection windows. Thirdly, Naive Bayesian model was used for combine these features for salient detection. The results on public datasets showed that our method performed well, the location of salient object can be fixed and the salient object can be accurately detected and marked by the specific window.

Infrared small target detection based on Danger Theory

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Yang, Xiao

2009-11-01

To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

Water Detection Based on Color Variation

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.

2012-01-01

This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

Underwater electric field detection system based on weakly electric fish

NASA Astrophysics Data System (ADS)

Xue, Wei; Wang, Tianyu; Wang, Qi

2018-04-01

Weakly electric fish sense their surroundings in complete darkness by their active electric field detection system. However, due to the insufficient detection capacity of the electric field, the detection distance is not enough, and the detection accuracy is not high. In this paper, a method of underwater detection based on rotating current field theory is proposed to improve the performance of underwater electric field detection system. First of all, we built underwater detection system based on the theory of the spin current field mathematical model with the help of the results of previous researchers. Then we completed the principle prototype and finished the metal objects in the water environment detection experiments, laid the foundation for the further experiments.

The design method and research status of vehicle detection system based on geomagnetic detection principle

NASA Astrophysics Data System (ADS)

Lin, Y. H.; Bai, R.; Qian, Z. H.

2018-03-01

Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.

Satellite-Based EMI Detection, Identification, and Mitigation

NASA Astrophysics Data System (ADS)

Stottler, R.; Bowman, C.

2016-09-01

Commanding, controlling, and maintaining the health of satellites requires a clear operating spectrum for communications. Electro Magnetic Interference (EMI) from other satellites can interfere with these communications. Determining which satellite is at fault improves space situational awareness and can be used to avoid the problem in the future. The Rfi detection And Prediction Tool, Optimizing Resources (RAPTOR) monitors the satellite communication antenna signals to detect EMI (also called RFI for Radio Frequency Interference) using a neural network trained on past cases of both normal communications and EMI events. RAPTOR maintains a database of satellites that have violated the reserved spectrum in the past. When satellite-based EMI is detected, RAPTOR first checks this list to determine if any are angularly close to the satellite being communicated with. Additionally, RAPTOR checks the Space Catalog to see if any of its active satellites are angularly close. RAPTOR also consults on-line databases to determine if the described operating frequencies of the satellites match the detected EMI and recommends candidates to be added to the known offenders database, accordingly. Based on detected EMI and predicted orbits and frequencies, RAPTOR automatically reschedules satellite communications to avoid current and future satellite-based EMI. It also includes an intuitive display for a global network of satellite communications antennas and their statuses including the status of their EM spectrum. RAPTOR has been prototyped and tested with real data (amplitudes versus frequency over time) for both satellite communication signals and is currently undergoing full-scale development. This paper describes the RAPTOR technologies and results of testing.

Two-Layer Fragile Watermarking Method Secured with Chaotic Map for Authentication of Digital Holy Quran

PubMed Central

Khalil, Mohammed S.; Khan, Muhammad Khurram; Alginahi, Yasser M.

2014-01-01

This paper presents a novel watermarking method to facilitate the authentication and detection of the image forgery on the Quran images. Two layers of embedding scheme on wavelet and spatial domain are introduced to enhance the sensitivity of fragile watermarking and defend the attacks. Discrete wavelet transforms are applied to decompose the host image into wavelet prior to embedding the watermark in the wavelet domain. The watermarked wavelet coefficient is inverted back to spatial domain then the least significant bits is utilized to hide another watermark. A chaotic map is utilized to blur the watermark to make it secure against the local attack. The proposed method allows high watermark payloads, while preserving good image quality. Experiment results confirm that the proposed methods are fragile and have superior tampering detection even though the tampered area is very small. PMID:25028681

Two-layer fragile watermarking method secured with chaotic map for authentication of digital Holy Quran.

PubMed

Khalil, Mohammed S; Kurniawan, Fajri; Khan, Muhammad Khurram; Alginahi, Yasser M

2014-01-01

This paper presents a novel watermarking method to facilitate the authentication and detection of the image forgery on the Quran images. Two layers of embedding scheme on wavelet and spatial domain are introduced to enhance the sensitivity of fragile watermarking and defend the attacks. Discrete wavelet transforms are applied to decompose the host image into wavelet prior to embedding the watermark in the wavelet domain. The watermarked wavelet coefficient is inverted back to spatial domain then the least significant bits is utilized to hide another watermark. A chaotic map is utilized to blur the watermark to make it secure against the local attack. The proposed method allows high watermark payloads, while preserving good image quality. Experiment results confirm that the proposed methods are fragile and have superior tampering detection even though the tampered area is very small.

Identifying Threats Using Graph-based Anomaly Detection

NASA Astrophysics Data System (ADS)

Eberle, William; Holder, Lawrence; Cook, Diane

Much of the data collected during the monitoring of cyber and other infrastructures is structural in nature, consisting of various types of entities and relationships between them. The detection of threatening anomalies in such data is crucial to protecting these infrastructures. We present an approach to detecting anomalies in a graph-based representation of such data that explicitly represents these entities and relationships. The approach consists of first finding normative patterns in the data using graph-based data mining and then searching for small, unexpected deviations to these normative patterns, assuming illicit behavior tries to mimic legitimate, normative behavior. The approach is evaluated using several synthetic and real-world datasets. Results show that the approach has high truepositive rates, low false-positive rates, and is capable of detecting complex structural anomalies in real-world domains including email communications, cellphone calls and network traffic.

Engineering nanomaterials-based biosensors for food safety detection.

PubMed

Lv, Man; Liu, Yang; Geng, Jinhui; Kou, Xiaohong; Xin, Zhihong; Yang, Dayong

2018-05-30

Food safety always remains a grand global challenge to human health, especially in developing countries. To solve food safety pertained problems, numerous strategies have been developed to detect biological and chemical contaminants in food. Among these approaches, nanomaterials-based biosensors provide opportunity to realize rapid, sensitive, efficient and portable detection, overcoming the restrictions and limitations of traditional methods such as complicated sample pretreatment, long detection time, and relying on expensive instruments and well-trained personnel. In this review article, we provide a cross-disciplinary perspective to review the progress of nanomaterials-based biosensors for the detection of food contaminants. The review article is organized by the category of food contaminants including pathogens/toxins, heavy metals, pesticides, veterinary drugs and illegal additives. In each category of food contaminant, the biosensing strategies are summarized including optical, colorimetric, fluorescent, electrochemical, and immune- biosensors; the relevant analytes, nanomaterials and biosensors are analyzed comprehensively. Future perspectives and challenges are also discussed briefly. We envision that our review could bridge the gap between the fields of food science and nanotechnology, providing implications for the scientists or engineers in both areas to collaborate and promote the development of nanomaterials-based biosensors for food safety detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

Analysis of Tyman green detection system based on polarization interference

NASA Astrophysics Data System (ADS)

Huang, Yaolin; Wang, Min; Shao, Xiaoping; Kou, Yuanfeng

2018-02-01

The optical surface deviation of the lens can directly affect the quality of the optical system.In order to effectively and accurately detect the surface shape, an optical surface on-line detection system based on polarization interference technology is designed and developed. The system is based on Tyman-Green interference optical path, join the polarization interference measuring technology. Based on the theoretical derivation of the optical path and the ZEMAX software simulation, the experimental optical path is constructed. The parallel light is used to detect the concave lens. The parallel light is used as the light source, the size of the polarization splitting prism, detection radius of curvature, the relations between and among the size of the lens aperture, a detection range is given.

COTD: Reference-free Hardware Trojan Detection in Gate-level Netlist

DTIC Science & Technology

2017-03-01

modern designs , the constraint of time- to-market window, and the cost restriction of final product highly drive the horizontal design process. The...third-party intellectual properties (3PIPs) are widely used while they expose a design to hardware Trojans (HTs) that may tamper with the design and...activated. Some work have investigated hardware Trojans in early design stages and several techniques have been proposed to study the switching

Label-free electrical detection using carbon nanotube-based biosensors.

PubMed

Maehashi, Kenzo; Matsumoto, Kazuhiko

2009-01-01

Label-free detections of biomolecules have attracted great attention in a lot of life science fields such as genomics, clinical diagnosis and practical pharmacy. In this article, we reviewed amperometric and potentiometric biosensors based on carbon nanotubes (CNTs). In amperometric detections, CNT-modified electrodes were used as working electrodes to significantly enhance electroactive surface area. In contrast, the potentiometric biosensors were based on aptamer-modified CNT field-effect transistors (CNTFETs). Since aptamers are artificial oligonucleotides and thus are smaller than the Debye length, proteins can be detected with high sensitivity. In this review, we discussed on the technology, characteristics and developments for commercialization in label-free CNT-based biosensors.

Vision-Based People Detection System for Heavy Machine Applications

PubMed Central

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-01

This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

Vision-Based People Detection System for Heavy Machine Applications.

PubMed

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-20

This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance.

Distributed intrusion detection system based on grid security model

NASA Astrophysics Data System (ADS)

Su, Jie; Liu, Yahui

2008-03-01

Grid computing has developed rapidly with the development of network technology and it can solve the problem of large-scale complex computing by sharing large-scale computing resource. In grid environment, we can realize a distributed and load balance intrusion detection system. This paper first discusses the security mechanism in grid computing and the function of PKI/CA in the grid security system, then gives the application of grid computing character in the distributed intrusion detection system (IDS) based on Artificial Immune System. Finally, it gives a distributed intrusion detection system based on grid security system that can reduce the processing delay and assure the detection rates.

Sensitivity Comparison of Vapor Trace Detection of Explosives Based on Chemo-Mechanical Sensing with Optical Detection and Capacitive Sensing with Electronic Detection

PubMed Central

Strle, Drago; Štefane, Bogdan; Zupanič, Erik; Trifkovič, Mario; Maček, Marijan; Jakša, Gregor; Kvasič, Ivan; Muševič, Igor

2014-01-01

The article offers a comparison of the sensitivities for vapour trace detection of Trinitrotoluene (TNT) explosives of two different sensor systems: a chemo-mechanical sensor based on chemically modified Atomic Force Microscope (AFM) cantilevers based on Micro Electro Mechanical System (MEMS) technology with optical detection (CMO), and a miniature system based on capacitive detection of chemically functionalized planar capacitors with interdigitated electrodes with a comb-like structure with electronic detection (CE). In both cases (either CMO or CE), the sensor surfaces are chemically functionalized with a layer of APhS (trimethoxyphenylsilane) molecules, which give the strongest sensor response for TNT. The construction and calibration of a vapour generator is also presented. The measurements of the sensor response to TNT are performed under equal conditions for both systems, and the results show that CE system with ultrasensitive electronics is far superior to optical detection using MEMS. Using CMO system, we can detect 300 molecules of TNT in 10+12 molecules of N2 carrier gas, whereas the CE system can detect three molecules of TNT in 10+12 molecules of carrier N2. PMID:24977388

Microcontroller-based real-time QRS detection.

PubMed

Sun, Y; Suppappola, S; Wrublewski, T A

1992-01-01

The authors describe the design of a system for real-time detection of QRS complexes in the electrocardiogram based on a single-chip microcontroller (Motorola 68HC811). A systematic analysis of the instrumentation requirements for QRS detection and of the various design techniques is also given. Detection algorithms using different nonlinear transforms for the enhancement of QRS complexes are evaluated by using the ECG database of the American Heart Association. The results show that the nonlinear transform involving multiplication of three adjacent, sign-consistent differences in the time domain gives a good performance and a quick response. When implemented with an appropriate sampling rate, this algorithm is also capable of rejecting pacemaker spikes. The eight-bit single-chip microcontroller provides sufficient throughput and shows a satisfactory performance. Implementation of multiple detection algorithms in the same system improves flexibility and reliability. The low chip count in the design also favors maintainability and cost-effectiveness.

Fabric defect detection based on faster R-CNN

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Liu, Xianghui; Li, Chunlei; Li, Bicao; Wang, Baorui

2018-04-01

In order to effectively detect the defects for fabric image with complex texture, this paper proposed a novel detection algorithm based on an end-to-end convolutional neural network. First, the proposal regions are generated by RPN (regional proposal Network). Then, Fast Region-based Convolutional Network method (Fast R-CNN) is adopted to determine whether the proposal regions extracted by RPN is a defect or not. Finally, Soft-NMS (non-maximum suppression) and data augmentation strategies are utilized to improve the detection precision. Experimental results demonstrate that the proposed method can locate the fabric defect region with higher accuracy compared with the state-of- art, and has better adaptability to all kinds of the fabric image.

Paper-based Platform for Urinary Creatinine Detection.

PubMed

Sittiwong, Jarinya; Unob, Fuangfa

2016-01-01

A new paper platform was developed for the colorimetric detection of creatinine. The filter paper was coated with 3-propylsulfonic acid trimethoxysilane and used as the platform. Creatinine in a cationic form was extracted onto the paper via an ion-exchange mechanism and detected through the Jaffé reaction, resulting in a yellow-orange color complex. The color change on the paper could be observed visually, and the quantitative detection of creatinine was achieved through monitoring the color intensity change. The color intensity of creatinine complexes on the paper platform as a function of the creatinine concentration provided a linear range for creatinine detection in the range of 10 - 60 mg L(-1) and a detection limit of 4.2 mg L(-1). The accuracy of the proposed paper-based method was comparable to the conventional standard Jaffé method. This paper platform could be applied for simple and rapid detection of creatinine in human urine samples with a low consumption of reagent.

Self-recovery reversible image watermarking algorithm

PubMed Central

Sun, He; Gao, Shangbing; Jin, Shenghua

2018-01-01

The integrity of image content is essential, although most watermarking algorithms can achieve image authentication but not automatically repair damaged areas or restore the original image. In this paper, a self-recovery reversible image watermarking algorithm is proposed to recover the tampered areas effectively. First of all, the original image is divided into homogeneous blocks and non-homogeneous blocks through multi-scale decomposition, and the feature information of each block is calculated as the recovery watermark. Then, the original image is divided into 4×4 non-overlapping blocks classified into smooth blocks and texture blocks according to image textures. Finally, the recovery watermark generated by homogeneous blocks and error-correcting codes is embedded into the corresponding smooth block by mapping; watermark information generated by non-homogeneous blocks and error-correcting codes is embedded into the corresponding non-embedded smooth block and the texture block via mapping. The correlation attack is detected by invariant moments when the watermarked image is attacked. To determine whether a sub-block has been tampered with, its feature is calculated and the recovery watermark is extracted from the corresponding block. If the image has been tampered with, it can be recovered. The experimental results show that the proposed algorithm can effectively recover the tampered areas with high accuracy and high quality. The algorithm is characterized by sound visual quality and excellent image restoration. PMID:29920528

The detection of bulk explosives using nuclear-based techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morgado, R.E.; Gozani, T.; Seher, C.C.

1988-01-01

In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals;more » new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.« less

Authentication via wavefront-shaped optical responses

NASA Astrophysics Data System (ADS)

Eilers, Hergen; Anderson, Benjamin R.; Gunawidjaja, Ray

2018-02-01

Authentication/tamper-indication is required in a wide range of applications, including nuclear materials management and product counterfeit detection. State-of-the-art techniques include reflective particle tags, laser speckle authentication, and birefringent seals. Each of these passive techniques has its own advantages and disadvantages, including the need for complex image comparisons, limited flexibility, sensitivity to environmental conditions, limited functionality, etc. We have developed a new active approach to address some of these short-comings. The use of an active characterization technique adds more flexibility and additional layers of security over current techniques. Our approach uses randomly-distributed nanoparticles embedded in a polymer matrix (tag/seal) which is attached to the item to be secured. A spatial light modulator is used to adjust the wavefront of a laser which interacts with the tag/seal, and a detector is used to monitor this interaction. The interaction can occur in various ways, including transmittance, reflectance, fluorescence, random lasing, etc. For example, at the time of origination, the wavefront-shaped reflectance from a tag/seal can be adjusted to result in a specific pattern (symbol, words, etc.) Any tampering with the tag/seal would results in a disturbance of the random orientation of the nanoparticles and thus distort the reflectance pattern. A holographic waveplate could be inserted into the laser beam for verification. The absence/distortion of the original pattern would then indicate that tampering has occurred. We have tested the tag/seal's and authentication method's tamper-indicating ability using various attack methods, including mechanical, thermal, and chemical attacks, and have verified our material/method's robust tamper-indicating ability.

An Android malware detection system based on machine learning

NASA Astrophysics Data System (ADS)

Wen, Long; Yu, Haiyang

2017-08-01

The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

Development of a HIV-1 Virus Detection System Based on Nanotechnology.

PubMed

Lee, Jin-Ho; Oh, Byung-Keun; Choi, Jeong-Woo

2015-04-27

Development of a sensitive and selective detection system for pathogenic viral agents is essential for medical healthcare from diagnostics to therapeutics. However, conventional detection systems are time consuming, resource-intensive and tedious to perform. Hence, the demand for sensitive and selective detection system for virus are highly increasing. To attain this aim, different aspects and techniques have been applied to develop virus sensor with improved sensitivity and selectivity. Here, among those aspects and techniques, this article reviews HIV virus particle detection systems incorporated with nanotechnology to enhance the sensitivity. This review mainly focused on four different detection system including vertically configured electrical detection based on scanning tunneling microscopy (STM), electrochemical detection based on direct electron transfer in virus, optical detection system based on localized surface plasmon resonance (LSPR) and surface enhanced Raman spectroscopy (SERS) using plasmonic nanoparticle.

Reproducibility and quantitation of amplicon sequencing-based detection

PubMed Central

Zhou, Jizhong; Wu, Liyou; Deng, Ye; Zhi, Xiaoyang; Jiang, Yi-Huei; Tu, Qichao; Xie, Jianping; Van Nostrand, Joy D; He, Zhili; Yang, Yunfeng

2011-01-01

To determine the reproducibility and quantitation of the amplicon sequencing-based detection approach for analyzing microbial community structure, a total of 24 microbial communities from a long-term global change experimental site were examined. Genomic DNA obtained from each community was used to amplify 16S rRNA genes with two or three barcode tags as technical replicates in the presence of a small quantity (0.1% wt/wt) of genomic DNA from Shewanella oneidensis MR-1 as the control. The technical reproducibility of the amplicon sequencing-based detection approach is quite low, with an average operational taxonomic unit (OTU) overlap of 17.2%±2.3% between two technical replicates, and 8.2%±2.3% among three technical replicates, which is most likely due to problems associated with random sampling processes. Such variations in technical replicates could have substantial effects on estimating β-diversity but less on α-diversity. A high variation was also observed in the control across different samples (for example, 66.7-fold for the forward primer), suggesting that the amplicon sequencing-based detection approach could not be quantitative. In addition, various strategies were examined to improve the comparability of amplicon sequencing data, such as increasing biological replicates, and removing singleton sequences and less-representative OTUs across biological replicates. Finally, as expected, various statistical analyses with preprocessed experimental data revealed clear differences in the composition and structure of microbial communities between warming and non-warming, or between clipping and non-clipping. Taken together, these results suggest that amplicon sequencing-based detection is useful in analyzing microbial community structure even though it is not reproducible and quantitative. However, great caution should be taken in experimental design and data interpretation when the amplicon sequencing-based detection approach is used for quantitative

Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

PubMed

Ganapathy, S; Yogesh, P; Kannan, A

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

PubMed Central

Ganapathy, S.; Yogesh, P.; Kannan, A.

2012-01-01

Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

Image Registration-Based Bolt Loosening Detection of Steel Joints

PubMed Central

2018-01-01

Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts. PMID:29597264

Image Registration-Based Bolt Loosening Detection of Steel Joints.

PubMed

Kong, Xiangxiong; Li, Jian

2018-03-28

Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts.

Gear-box fault detection using time-frequency based methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected.more » Two different time-frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen-Loeve basis. Both of them detects the gear-box fault with an acceptable detection delay.« less

Raman spectroscopy-based detection of chemical contaminants in food powders

NASA Astrophysics Data System (ADS)

Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

2016-05-01

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

PubMed

Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

2016-12-01

In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving average (EWMA) monitoring scheme to detect a potential fall in the accelerometric data. We used an EWMA to identify features that correspond with a particular type of fall allowing us to classify falls. Only features corresponding with detected falls were used in the classification phase. A benefit of using a subset of the original data to design classification models minimizes training time and simplifies models. Based on features corresponding to detected falls, we used the support vector machine (SVM) algorithm to distinguish between true falls and fall-like events. We apply this strategy to the publicly available fall detection databases from the university of Rzeszow's. Results indicated that our strategy accurately detected and classified fall events, suggesting its potential application to early alert mechanisms in the event of fall situations and its capability for classification of detected falls. Comparison of the classification results using the EWMA-based SVM classifier method with those achieved using three commonly used machine learning classifiers, neural network, K-nearest neighbor and naïve Bayes, proved our model superior.

Regional Principal Color Based Saliency Detection

PubMed Central

Lou, Jing; Ren, Mingwu; Wang, Huan

2014-01-01

Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms. PMID:25379960

Plant Ethylene Detection Using Laser-Based Photo-Acoustic Spectroscopy.

PubMed

Van de Poel, Bram; Van Der Straeten, Dominique

2017-01-01

Analytical detection of the plant hormone ethylene is an important prerequisite in physiological studies. Real-time and super sensitive detection of trace amounts of ethylene gas is possible using laser-based photo-acoustic spectroscopy. This Chapter will provide some background on the technique, compare it with conventional gas chromatography, and provide a detailed user-friendly hand-out on how to operate the machine and the software. In addition, this Chapter provides some tips and tricks for designing and performing physiological experiments suited for ethylene detection with laser-based photo-acoustic spectroscopy.

The performance of spatially offset Raman spectroscopy for liquid explosive detection

NASA Astrophysics Data System (ADS)

Loeffen, Paul W.; Maskall, Guy; Bonthron, Stuart; Bloomfield, Matthew; Tombling, Craig; Matousek, Pavel

2016-10-01

Aviation security requirements adopted in 2014 require liquids to be screened at most airports throughout Europe, North America and Australia. Cobalt's unique Spatially Offset Raman Spectroscopy (SORS™) technology has proven extremely effective at screening liquids, aerosols and gels (LAGS) with extremely low false alarm rates. SORS is compatible with a wide range of containers, including coloured, opaque or clear plastics, glass and paper, as well as duty-free bottles in STEBs (secure tamper-evident bags). Our award-winning Insight range has been specially developed for table-top screening at security checkpoints. Insight systems use our patented SORS technology for rapid and accurate chemical analysis of substances in unopened non-metallic containers. Insight100M™ and the latest member of the range - Insight200M™ - also screen metallic containers. Our unique systems screen liquids, aerosols and gels with the highest detection capability and lowest false alarm rates of any ECAC-approved scanner, with several hundred units already in use at airports including eight of the top ten European hubs. This paper presents an analysis of real performance data for these systems.

Unsupervised malaria parasite detection based on phase spectrum.

PubMed

Fang, Yuming; Xiong, Wei; Lin, Weisi; Chen, Zhenzhong

2011-01-01

In this paper, we propose a novel method for malaria parasite detection based on phase spectrum. The method first obtains the amplitude spectrum and phase spectrum for blood smear images through Quaternion Fourier Transform (QFT). Then it gets the reconstructed image based on Inverse Quaternion Fourier transform (IQFT) on a constant amplitude spectrum and the original phase spectrum. The malaria parasite areas can be detected easily from the reconstructed blood smear images. Extensive experiments have demonstrated the effectiveness of this novel method.

Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

PubMed

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-05-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU.

Vision based speed breaker detection for autonomous vehicle

NASA Astrophysics Data System (ADS)

C. S., Arvind; Mishra, Ritesh; Vishal, Kumar; Gundimeda, Venugopal

2018-04-01

In this paper, we are presenting a robust and real-time, vision-based approach to detect speed breaker in urban environments for autonomous vehicle. Our method is designed to detect the speed breaker using visual inputs obtained from a camera mounted on top of a vehicle. The method performs inverse perspective mapping to generate top view of the road and segment out region of interest based on difference of Gaussian and median filter images. Furthermore, the algorithm performs RANSAC line fitting to identify the possible speed breaker candidate region. This initial guessed region via RANSAC, is validated using support vector machine. Our algorithm can detect different categories of speed breakers on cement, asphalt and interlock roads at various conditions and have achieved a recall of 0.98.

Stratification-Based Outlier Detection over the Deep Web.

PubMed

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

Stratification-Based Outlier Detection over the Deep Web

PubMed Central

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

Oligonucleotide-based biosensors for in vitro diagnostics and environmental hazard detection.

PubMed

Jung, Il Young; Lee, Eun Hee; Suh, Ah Young; Lee, Seung Jin; Lee, Hyukjin

2016-04-01

Oligonucleotide-based biosensors have drawn much attention because of their broad applications in in vitro diagnostics and environmental hazard detection. They are particularly of interest to many researchers because of their high specificity as well as excellent sensitivity. Recently, oligonucleotide-based biosensors have been used to achieve not only genetic detection of targets but also the detection of small molecules, peptides, and proteins. This has further broadened the applications of these sensors in the medical and health care industry. In this review, we highlight various examples of oligonucleotide-based biosensors for the detection of diseases, drugs, and environmentally hazardous chemicals. Each example is provided with detailed schematics of the detection mechanism in addition to the supporting experimental results. Furthermore, future perspectives and new challenges in oligonucleotide-based biosensors are discussed.

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

QRS detection based ECG quality assessment.

PubMed

Hayn, Dieter; Jammerbund, Bernhard; Schreier, Günter

2012-09-01

Although immediate feedback concerning ECG signal quality during recording is useful, up to now not much literature describing quality measures is available. We have implemented and evaluated four ECG quality measures. Empty lead criterion (A), spike detection criterion (B) and lead crossing point criterion (C) were calculated from basic signal properties. Measure D quantified the robustness of QRS detection when applied to the signal. An advanced Matlab-based algorithm combining all four measures and a simplified algorithm for Android platforms, excluding measure D, were developed. Both algorithms were evaluated by taking part in the Computing in Cardiology Challenge 2011. Each measure's accuracy and computing time was evaluated separately. During the challenge, the advanced algorithm correctly classified 93.3% of the ECGs in the training-set and 91.6 % in the test-set. Scores for the simplified algorithm were 0.834 in event 2 and 0.873 in event 3. Computing time for measure D was almost five times higher than for other measures. Required accuracy levels depend on the application and are related to computing time. While our simplified algorithm may be accurate for real-time feedback during ECG self-recordings, QRS detection based measures can further increase the performance if sufficient computing power is available.

Land-based infrared imagery for marine mammal detection

NASA Astrophysics Data System (ADS)

Graber, Joseph; Thomson, Jim; Polagye, Brian; Jessup, Andrew

2011-09-01

A land-based infrared (IR) camera is used to detect endangered Southern Resident killer whales in Puget Sound, Washington, USA. The observations are motivated by a proposed tidal energy pilot project, which will be required to monitor for environmental effects. Potential monitoring methods also include visual observation, passive acoustics, and active acoustics. The effectiveness of observations in the infrared spectrum is compared to observations in the visible spectrum to assess the viability of infrared imagery for cetacean detection and classification. Imagery was obtained at Lime Kiln Park, Washington from 7/6/10-7/9/10 using a FLIR Thermovision A40M infrared camera (7.5-14μm, 37°HFOV, 320x240 pixels) under ideal atmospheric conditions (clear skies, calm seas, and wind speed 0-4 m/s). Whales were detected during both day (9 detections) and night (75 detections) at distances ranging from 42 to 162 m. The temperature contrast between dorsal fins and the sea surface ranged from 0.5 to 4.6 °C. Differences in emissivity from sea surface to dorsal fin are shown to aid detection at high incidence angles (near grazing). A comparison to theory is presented, and observed deviations from theory are investigated. A guide for infrared camera selection based on site geometry and desired target size is presented, with specific considerations regarding marine mammal detection. Atmospheric conditions required to use visible and infrared cameras for marine mammal detection are established and compared with 2008 meteorological data for the proposed tidal energy site. Using conservative assumptions, infrared observations are predicted to provide a 74% increase in hours of possible detection, compared with visual observations.

Moiré deflectometry-based position detection for optical tweezers.

PubMed

Khorshad, Ali Akbar; Reihani, S Nader S; Tavassoly, Mohammad Taghi

2017-09-01

Optical tweezers have proven to be indispensable tools for pico-Newton range force spectroscopy. A quadrant photodiode (QPD) positioned at the back focal plane of an optical tweezers' condenser is commonly used for locating the trapped object. In this Letter, for the first time, to the best of our knowledge, we introduce a moiré pattern-based detection method for optical tweezers. We show, both theoretically and experimentally, that this detection method could provide considerably better position sensitivity compared to the commonly used detection systems. For instance, position sensitivity for a trapped 2.17 μm polystyrene bead is shown to be 71% better than the commonly used QPD-based detection method. Our theoretical and experimental results are in good agreement.

Advances in neutron based bulk explosive detection

NASA Astrophysics Data System (ADS)

Gozani, Tsahi; Strellis, Dan

2007-08-01

Neutron based explosive inspection systems can detect a wide variety of national security threats. The inspection is founded on the detection of characteristic gamma rays emitted as the result of neutron interactions with materials. Generally these are gamma rays resulting from thermal neutron capture and inelastic scattering reactions in most materials and fast and thermal neutron fission in fissile (e.g.235U and 239Pu) and fertile (e.g.238U) materials. Cars or trucks laden with explosives, drugs, chemical agents and hazardous materials can be detected. Cargo material classification via its main elements and nuclear materials detection can also be accomplished with such neutron based platforms, when appropriate neutron sources, gamma ray spectroscopy, neutron detectors and suitable decision algorithms are employed. Neutron based techniques can be used in a variety of scenarios and operational modes. They can be used as stand alones for complete scan of objects such as vehicles, or for spot-checks to clear (or validate) alarms indicated by another inspection system such as X-ray radiography. The technologies developed over the last two decades are now being implemented with good results. Further advances have been made over the last few years that increase the sensitivity, applicability and robustness of these systems. The advances range from the synchronous inspection of two sides of vehicles, increasing throughput and sensitivity and reducing imparted dose to the inspected object and its occupants (if any), to taking advantage of the neutron kinetic behavior of cargo to remove systematic errors, reducing background effects and improving fast neutron signals.

Gold Nanoparticles-Based Barcode Analysis for Detection of Norepinephrine.

PubMed

An, Jeung Hee; Lee, Kwon-Jai; Choi, Jeong-Woo

2016-02-01

Nanotechnology-based bio-barcode amplification analysis offers an innovative approach for detecting neurotransmitters. We evaluated the efficacy of this method for detecting norepinephrine in normal and oxidative-stress damaged dopaminergic cells. Our approach use a combination of DNA barcodes and bead-based immunoassays for detecting neurotransmitters with surface-enhanced Raman spectroscopy (SERS), and provides polymerase chain reaction (PCR)-like sensitivity. This method relies on magnetic Dynabeads containing antibodies and nanoparticles that are loaded both with DNA barcords and with antibodies that can sandwich the target protein captured by the Dynabead-bound antibodies. The aggregate sandwich structures are magnetically separated from the solution and treated to remove the conjugated barcode DNA. The DNA barcodes are then identified by SERS and PCR analysis. The concentration of norepinephrine in dopaminergic cells can be readily detected using the bio-barcode assay, which is a rapid, high-throughput screening tool for detecting neurotransmitters.

Video-Based Affect Detection in Noninteractive Learning Environments

ERIC Educational Resources Information Center

Chen, Yuxuan; Bosch, Nigel; D'Mello, Sidney

2015-01-01

The current paper explores possible solutions to the problem of detecting affective states from facial expressions during text/diagram comprehension, a context devoid of interactive events that can be used to infer affect. These data present an interesting challenge for face-based affect detection because likely locations of affective facial…

Retinal hemorrhage detection by rule-based and machine learning approach.

PubMed

Di Xiao; Shuang Yu; Vignarajan, Janardhan; Dong An; Mei-Ling Tay-Kearney; Kanagasingam, Yogi

2017-07-01

Robust detection of hemorrhages (HMs) in color fundus image is important in an automatic diabetic retinopathy grading system. Detection of the hemorrhages that are close to or connected with retinal blood vessels was found to be challenge. However, most methods didn't put research on it, even some of them mentioned this issue. In this paper, we proposed a novel hemorrhage detection method based on rule-based and machine learning methods. We focused on the improvement of detection of the hemorrhages that are close to or connected with retinal blood vessels, besides detecting the independent hemorrhage regions. A preliminary test for detecting HM presence was conducted on the images from two databases. We achieved sensitivity and specificity of 93.3% and 88% as well as 91.9% and 85.6% on the two datasets.

Microbial Fuels Cell-Based Biosensor for Toxicity Detection: A Review

PubMed Central

Zhou, Tuoyu; Han, Huawen; Liu, Pu; Xiong, Jian; Tian, Fake; Li, Xiangkai

2017-01-01

With the unprecedented deterioration of environmental quality, rapid recognition of toxic compounds is paramount for performing in situ real-time monitoring. Although several analytical techniques based on electrochemistry or biosensors have been developed for the detection of toxic compounds, most of them are time-consuming, inaccurate, or cumbersome for practical applications. More recently, microbial fuel cell (MFC)-based biosensors have drawn increasing interest due to their sustainability and cost-effectiveness, with applications ranging from the monitoring of anaerobic digestion process parameters (VFA) to water quality detection (e.g., COD, BOD). When a MFC runs under correct conditions, the voltage generated is correlated with the amount of a given substrate. Based on this linear relationship, several studies have demonstrated that MFC-based biosensors could detect heavy metals such as copper, chromium, or zinc, as well as organic compounds, including p-nitrophenol (PNP), formaldehyde and levofloxacin. Both bacterial consortia and single strains can be used to develop MFC-based biosensors. Biosensors with single strains show several advantages over systems integrating bacterial consortia, such as selectivity and stability. One of the limitations of such sensors is that the detection range usually exceeds the actual pollution level. Therefore, improving their sensitivity is the most important for widespread application. Nonetheless, MFC-based biosensors represent a promising approach towards single pollutant detection. PMID:28956857

Microbial Fuels Cell-Based Biosensor for Toxicity Detection: A Review.

PubMed

Zhou, Tuoyu; Han, Huawen; Liu, Pu; Xiong, Jian; Tian, Fake; Li, Xiangkai

2017-09-28

With the unprecedented deterioration of environmental quality, rapid recognition of toxic compounds is paramount for performing in situ real-time monitoring. Although several analytical techniques based on electrochemistry or biosensors have been developed for the detection of toxic compounds, most of them are time-consuming, inaccurate, or cumbersome for practical applications. More recently, microbial fuel cell (MFC)-based biosensors have drawn increasing interest due to their sustainability and cost-effectiveness, with applications ranging from the monitoring of anaerobic digestion process parameters (VFA) to water quality detection (e.g., COD, BOD). When a MFC runs under correct conditions, the voltage generated is correlated with the amount of a given substrate. Based on this linear relationship, several studies have demonstrated that MFC-based biosensors could detect heavy metals such as copper, chromium, or zinc, as well as organic compounds, including p -nitrophenol (PNP), formaldehyde and levofloxacin. Both bacterial consortia and single strains can be used to develop MFC-based biosensors. Biosensors with single strains show several advantages over systems integrating bacterial consortia, such as selectivity and stability. One of the limitations of such sensors is that the detection range usually exceeds the actual pollution level. Therefore, improving their sensitivity is the most important for widespread application. Nonetheless, MFC-based biosensors represent a promising approach towards single pollutant detection.

An experimental validation of a statistical-based damage detection approach.

DOT National Transportation Integrated Search

2011-01-01

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to : autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and : predicted beha...

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors

PubMed Central

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-01-01

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms. PMID:27240382

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors.

PubMed

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-05-28

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

Enhancing Community Detection By Affinity-based Edge Weighting Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, Andy; Sanders, Geoffrey; Henson, Van

Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is idealmore » for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.« less

Efficient method of image edge detection based on FSVM

NASA Astrophysics Data System (ADS)

Cai, Aiping; Xiong, Xiaomei

2013-07-01

For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

Evaluation of Two Outlier-Detection-Based Methods for Detecting Tissue-Selective Genes from Microarray Data

PubMed Central

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-01-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU. PMID:19936074

Person-level changes in oxycodone use after the introduction of a tamper-resistant formulation in Australia.

PubMed

Schaffer, Andrea L; Buckley, Nicholas A; Degenhardt, Louisa; Larance, Briony; Cairns, Rose; Dobbins, Timothy A; Pearson, Sallie-Anne

2018-03-26

Australia introduced tamper-resistant controlled-release (CR) oxycodone in April 2014. We quantified the impact of the reformulation on dispensing, switching and poisonings. We performed interrupted time-series analyses using population-representative national dispensing data from 2012 to 2016. We measured dispensing of oxycodone CR (≥ 10 mg), discontinuation of use of strong opioids and switching to other strong opioids after the reformulation compared with a historical control period. Similarly, we compared calls about intentional opioid poisoning using data from a regional poisons information centre. After the reformulation, dispensing decreased for 10-30 mg (total level shift -11.1%, 95% confidence interval [CI], -17.2% to -4.6%) and 40-80 mg oxycodone CR (total level shift -31.5%, 95% CI -37.5% to -24.9%) in participants less than 65 years of age but was unchanged in people 65 years of age or older. Compared with the previous year, discontinuation of use of strong opioids did not increase (adjusted hazard ratio [HR] 0.95, 95% CI 0.91 to 1.00), but switching to oxycodone/naloxone did increase (adjusted HR 1.54, 95% CI 1.32 to 1.79). Switching to morphine varied by age ( p < 0.001), and the greatest increase was in participants less than 45 years of age (adjusted HR 4.33, 95% CI 2.13 to 8.80). Participants switching after the reformulation were more likely to be dispensed a tablet strength of 40 mg or more (adjusted odds ratio [OR] 1.40, 95% CI 1.09 to 1.79). Calls for intentional poisoning that involved oxycodone taken orally increased immediately after the reformulation (incidence rate ratio (IRR) 1.31, 95% CI 1.05-1.64), but there was no change for injected oxycodone. The reformulation had a greater impact on opioid access patterns of people less than 65 years of age who were using higher strengths of oxycodone CR. This group has been identified as having an increased risk of problematic opioid use and warrants closer monitoring in clinical practice. �

A New Intrusion Detection Method Based on Antibody Concentration

NASA Astrophysics Data System (ADS)

Zeng, Jie; Li, Tao; Li, Guiyang; Li, Haibo

Antibody is one kind of protein that fights against the harmful antigen in human immune system. In modern medical examination, the health status of a human body can be diagnosed by detecting the intrusion intensity of a specific antigen and the concentration indicator of corresponding antibody from human body’s serum. In this paper, inspired by the principle of antigen-antibody reactions, we present a New Intrusion Detection Method Based on Antibody Concentration (NIDMBAC) to reduce false alarm rate without affecting detection rate. In our proposed method, the basic definitions of self, nonself, antigen and detector in the intrusion detection domain are given. Then, according to the antigen intrusion intensity, the change of antibody number is recorded from the process of clone proliferation for detectors based on the antigen classified recognition. Finally, building upon the above works, a probabilistic calculation method for the intrusion alarm production, which is based on the correlation between the antigen intrusion intensity and the antibody concen-tration, is proposed. Our theoretical analysis and experimental results show that our proposed method has a better performance than traditional methods.

Text image authenticating algorithm based on MD5-hash function and Henon map

NASA Astrophysics Data System (ADS)

Wei, Jinqiao; Wang, Ying; Ma, Xiaoxue

2017-07-01

In order to cater to the evidentiary requirements of the text image, this paper proposes a fragile watermarking algorithm based on Hash function and Henon map. The algorithm is to divide a text image into parts, get flippable pixels and nonflippable pixels of every lump according to PSD, generate watermark of non-flippable pixels with MD5-Hash, encrypt watermark with Henon map and select embedded blocks. The simulation results show that the algorithm with a good ability in tampering localization can be used to authenticate and forensics the authenticity and integrity of text images

Sea-Based Infrared Scene Interpretation by Background Type Classification and Coastal Region Detection for Small Target Detection

PubMed Central

Kim, Sungho

2015-01-01

Sea-based infrared search and track (IRST) is important for homeland security by detecting missiles and asymmetric boats. This paper proposes a novel scheme to interpret various infrared scenes by classifying the infrared background types and detecting the coastal regions in omni-directional images. The background type or region-selective small infrared target detector should be deployed to maximize the detection rate and to minimize the number of false alarms. A spatial filter-based small target detector is suitable for identifying stationary incoming targets in remote sea areas with sky only. Many false detections can occur if there is an image sector containing a coastal region, due to ground clutter and the difficulty in finding true targets using the same spatial filter-based detector. A temporal filter-based detector was used to handle these problems. Therefore, the scene type and coastal region information is critical to the success of IRST in real-world applications. In this paper, the infrared scene type was determined using the relationships between the sensor line-of-sight (LOS) and a horizontal line in an image. The proposed coastal region detector can be activated if the background type of the probing sector is determined to be a coastal region. Coastal regions can be detected by fusing the region map and curve map. The experimental results on real infrared images highlight the feasibility of the proposed sea-based scene interpretation. In addition, the effects of the proposed scheme were analyzed further by applying region-adaptive small target detection. PMID:26404308

An FPGA-Based Rapid Wheezing Detection System

PubMed Central

Lin, Bor-Shing; Yen, Tian-Shiue

2014-01-01

Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. PMID:24481034

Driver fatigue detection based on eye state.

PubMed

Lin, Lizong; Huang, Chao; Ni, Xiaopeng; Wang, Jiawen; Zhang, Hao; Li, Xiao; Qian, Zhiqin

2015-01-01

Nowadays, more and more traffic accidents occur because of driver fatigue. In order to reduce and prevent it, in this study, a calculation method using PERCLOS (percentage of eye closure time) parameter characteristics based on machine vision was developed. It determined whether a driver's eyes were in a fatigue state according to the PERCLOS value. The overall workflow solutions included face detection and tracking, detection and location of the human eye, human eye tracking, eye state recognition, and driver fatigue testing. The key aspects of the detection system incorporated the detection and location of human eyes and driver fatigue testing. The simplified method of measuring the PERCLOS value of the driver was to calculate the ratio of the eyes being open and closed with the total number of frames for a given period. If the eyes were closed more than the set threshold in the total number of frames, the system would alert the driver. Through many experiments, it was shown that besides the simple detection algorithm, the rapid computing speed, and the high detection and recognition accuracies of the system, the system was demonstrated to be in accord with the real-time requirements of a driver fatigue detection system.

Distribution System Audits, Leak Detection, and Repair: Kirtland Air Force Base Leak Detection and Repair Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Water Best Management Practice #3 Fact Seet: Outlines how a leak detection and repair program helped Kirtland Air Force Base perform distribution system audits, leak detection, and repair to conserve water site-wide.

Pedestrian detection based on redundant wavelet transform

NASA Astrophysics Data System (ADS)

Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

2016-10-01

Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

"Dip-and-read" paper-based analytical devices using distance-based detection with color screening.

PubMed

Yamada, Kentaro; Citterio, Daniel; Henry, Charles S

2018-05-15

An improved paper-based analytical device (PAD) using color screening to enhance device performance is described. Current detection methods for PADs relying on the distance-based signalling motif can be slow due to the assay time being limited by capillary flow rates that wick fluid through the detection zone. For traditional distance-based detection motifs, analysis can take up to 45 min for a channel length of 5 cm. By using a color screening method, quantification with a distance-based PAD can be achieved in minutes through a "dip-and-read" approach. A colorimetric indicator line deposited onto a paper substrate using inkjet-printing undergoes a concentration-dependent colorimetric response for a given analyte. This color intensity-based response has been converted to a distance-based signal by overlaying a color filter with a continuous color intensity gradient matching the color of the developed indicator line. As a proof-of-concept, Ni quantification in welding fume was performed as a model assay. The results of multiple independent user testing gave mean absolute percentage error and average relative standard deviations of 10.5% and 11.2% respectively, which were an improvement over analysis based on simple visual color comparison with a read guide (12.2%, 14.9%). In addition to the analytical performance comparison, an interference study and a shelf life investigation were performed to further demonstrate practical utility. The developed system demonstrates an alternative detection approach for distance-based PADs enabling fast (∼10 min), quantitative, and straightforward assays.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks.

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed. PMID:29186756

Ensemble method: Community detection based on game theory

NASA Astrophysics Data System (ADS)

Zhang, Xia; Xia, Zhengyou; Xu, Shengwu; Wang, J. D.

2014-08-01

Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

Detection of sea otters in boat-based surveys of Prince William Sound, Alaska

USGS Publications Warehouse

Udevitz, Mark S.; Bodkin, James L.; Costa, Daniel P.

1995-01-01

Boat-based surveys have been commonly used to monitor sea otter populations, but there has been little quantitative work to evaluate detection biases that may affect these surveys. We used ground-based observers to investigate sea otter detection probabilities in a boat-based survey of Prince William Sound, Alaska. We estimated that 30% of the otters present on surveyed transects were not detected by boat crews. Approximately half (53%) of the undetected otters were missed because the otters left the transects, apparently in response to the approaching boat. Unbiased estimates of detection probabilities will be required for obtaining unbiased population estimates from boat-based surveys of sea otters. Therefore, boat-based surveys should include methods to estimate sea otter detection probabilities under the conditions specific to each survey. Unbiased estimation of detection probabilities with ground-based observers requires either that the ground crews detect all of the otters in observed subunits, or that there are no errors in determining which crews saw each detected otter. Ground-based observer methods may be appropriate in areas where nearly all of the sea otter habitat is potentially visible from ground-based vantage points.

Sparsity based target detection for compressive spectral imagery

NASA Astrophysics Data System (ADS)

Boada, David Alberto; Arguello Fuentes, Henry

2016-09-01

Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

Research on manufacturing service behavior modeling based on block chain theory

NASA Astrophysics Data System (ADS)

Zhao, Gang; Zhang, Guangli; Liu, Ming; Yu, Shuqin; Liu, Yali; Zhang, Xu

2018-04-01

According to the attribute characteristics of processing craft, the manufacturing service behavior is divided into service attribute, basic attribute, process attribute, resource attribute. The attribute information model of manufacturing service is established. The manufacturing service behavior information is successfully divided into public and private domain. Additionally, the block chain technology is introduced, and the information model of manufacturing service based on block chain principle is established, which solves the problem of sharing and secreting information of processing behavior, and ensures that data is not tampered with. Based on the key pairing verification relationship, the selective publishing mechanism for manufacturing information is established, achieving the traceability of product data, guarantying the quality of processing quality.

Rear-end vision-based collision detection system for motorcyclists

NASA Astrophysics Data System (ADS)

Muzammel, Muhammad; Yusoff, Mohd Zuki; Meriaudeau, Fabrice

2017-05-01

In many countries, the motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. To increase the safety of motorcyclists and minimize their road fatalities, this paper introduces a vision-based rear-end collision detection system. The binary road detection scheme contributes significantly to reduce the negative false detections and helps to achieve reliable results even though shadows and different lane markers are present on the road. The methodology is based on Harris corner detection and Hough transform. To validate this methodology, two types of dataset are used: (1) self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and (2) online datasets (recorded by placing a camera at the front of a car). This method achieved 95.1% accuracy for the self-recorded dataset and gives reliable results for the rear-end vehicle detections under different road scenarios. This technique also performs better for the online car datasets. The proposed technique's high detection accuracy using a monocular vision camera coupled with its low computational complexity makes it a suitable candidate for a motorbike rear-end collision detection system.

A dynamic bead-based microarray for parallel DNA detection

NASA Astrophysics Data System (ADS)

Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

2011-05-01

A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

Radioactive threat detection using scintillant-based detectors

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2004-09-01

An update to the performance of AS&E's Radioactive Threat Detection sensor technology. A model is presented detailing the components of the scintillant-based RTD system employed in AS&E products aimed at detecting radiological WMD. An overview of recent improvements in the sensors, electrical subsystems and software algorithms are presented. The resulting improvements in performance are described and sample results shown from existing systems. Advanced and future capabilities are described with an assessment of their feasibility and their application to Homeland Defense.

Small threat and contraband detection with TNA-based systems.

PubMed

Shaw, T J; Brown, D; D'Arcy, J; Liu, F; Shea, P; Sivakumar, M; Gozani, T

2005-01-01

The detection of small threats, such as explosives, drugs, and chemical weapons, concealed or encased in surrounding material, is a major concern in areas from security checkpoints to UneXploded Ordnance (UXO) clearance. Techniques such as X-ray and trace detection are often ineffectual in these applications. Thermal neutron analysis (TNA) provides an effective method for detecting concealed threats. This paper shows the effectiveness of Ancore's SPEDS, based on TNA, in detecting concealed liquid threats and differentiating live from inert mortar shells.

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

Tensor-based spatiotemporal saliency detection

NASA Astrophysics Data System (ADS)

Dou, Hao; Li, Bin; Deng, Qianqian; Zhang, LiRui; Pan, Zhihong; Tian, Jinwen

2018-03-01

This paper proposes an effective tensor-based spatiotemporal saliency computation model for saliency detection in videos. First, we construct the tensor representation of video frames. Then, the spatiotemporal saliency can be directly computed by the tensor distance between different tensors, which can preserve the complete temporal and spatial structure information of object in the spatiotemporal domain. Experimental results demonstrate that our method can achieve encouraging performance in comparison with the state-of-the-art methods.

75 FR 27318 - Notice of Intent To Grant an Exclusive License; FIXMO U.S. INC.

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-14

..., license to practice the following Government-Owned invention as described in U.S. Patent Application Serial No.11/999,050 entitled: ``Method of Tamper Detection for Digital Device,'' which was allowed by... above-mentioned invention is assigned to the United States Government as represented by the National...

Raman spectroscopy-based detection of chemical contaminants in food powders

USDA-ARS?s Scientific Manuscript database

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary sp...

Android malware detection based on evolutionary super-network

NASA Astrophysics Data System (ADS)

Yan, Haisheng; Peng, Lingling

2018-04-01

In the paper, an android malware detection method based on evolutionary super-network is proposed in order to improve the precision of android malware detection. Chi square statistics method is used for selecting characteristics on the basis of analyzing android authority. Boolean weighting is utilized for calculating characteristic weight. Processed characteristic vector is regarded as the system training set and test set; hyper edge alternative strategy is used for training super-network classification model, thereby classifying test set characteristic vectors, and it is compared with traditional classification algorithm. The results show that the detection method proposed in the paper is close to or better than traditional classification algorithm. The proposed method belongs to an effective Android malware detection means.

Home Camera-Based Fall Detection System for the Elderly.

PubMed

de Miguel, Koldo; Brunete, Alberto; Hernando, Miguel; Gambao, Ernesto

2017-12-09

Falls are the leading cause of injury and death in elderly individuals. Unfortunately, fall detectors are typically based on wearable devices, and the elderly often forget to wear them. In addition, fall detectors based on artificial vision are not yet available on the market. In this paper, we present a new low-cost fall detector for smart homes based on artificial vision algorithms. Our detector combines several algorithms (background subtraction, Kalman filtering and optical flow) as input to a machine learning algorithm with high detection accuracy. Tests conducted on over 50 different fall videos have shown a detection ratio of greater than 96%.

Microbial detection method based on sensing molecular hydrogen

NASA Technical Reports Server (NTRS)

Wilkins, J. R.; Stoner, G. E.; Boykin, E. H.

1974-01-01

A simple method for detecting bacteria, based on the time of hydrogen evolution, was developed and tested against various members of the Enterobacteriaceae group. The test system consisted of (1) two electrodes, platinum and a reference electrode, (2) a buffer amplifier, and (3) a strip-chart recorder. Hydrogen evolution was measured by an increase in voltage in the negative (cathodic) direction. A linear relationship was established between inoculum size and the time hydrogen was detected (lag period). Lag times ranged from 1 h for 1 million cells/ml to 7 h for 1 cell/ml. For each 10-fold decrease in inoculum, length of the lag period increased 60 to 70 min. Based on the linear relationship between inoculum and lag period, these results indicate the potential application of the hydrogen-sensing method for rapidly detecting coliforms and other gas-producing microorganisms in a variety of clinical, food, and other samples.

SERS-based pesticide detection by using nanofinger sensors

NASA Astrophysics Data System (ADS)

Kim, Ansoon; Barcelo, Steven J.; Li, Zhiyong

2015-01-01

Simple, sensitive, and rapid detection of trace levels of extensively used and highly toxic pesticides are in urgent demand for public health. Surface-enhanced Raman scattering (SERS)-based sensor was designed to achieve ultrasensitive and simple pesticide sensing. We developed a portable sensor system composed of high performance and reliable gold nanofinger sensor strips and a custom-built portable Raman spectrometer. Compared to the general procedure and previously reported studies that are limited to laboratory settings, our analytical method is simple, sensitive, rapid, and cost-effective. Based on the SERS results, the chemical interaction of two pesticides, chlorpyrifos (CPF) and thiabendazole (TBZ), with gold nanofingers was studied to determine a fingerprint for each pesticide. The portable SERS-sensor system was successfully demonstrated to detect CPF and TBZ pesticides within 15 min with a detection limit of 35 ppt in drinking water and 7 ppb on apple skin, respectively.

Smartphone-based low light detection for bioluminescence application

USDA-ARS?s Scientific Manuscript database

We report a smartphone-based device and associated imaging-processing algorithm to maximize the sensitivity of standard smartphone cameras, that can detect the presence of single-digit pW of radiant flux intensity. The proposed hardware and software, called bioluminescent-based analyte quantitation ...

A Cell-Based Approach to Early Pancreatic Cancer Detection

DTIC Science & Technology

2016-10-01

Award Number: W81XWH-15-1-0457 TITLE: A Cell -Based Approach to Early Pancreatic Cancer Detection PRINCIPAL INVESTIGATOR: Dr. Ben Stanger...SUBTITLE 5a. CONTRACT NUMBER A Cell -Based Approach to Early Pancreatic Cancer Detection 5b. GRANT NUMBER W81XWH-15-1-0457 5c. PROGRAM ELEMENT NUMBER 6...tumor cells from mouse blood by depleting the sample of white blood cells (WBCs). Furthermore, the RNA profile of these cells can be assessed by

Family-Based Benchmarking of Copy Number Variation Detection Software.

PubMed

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

DNAzyme based gap-LCR detection of single-nucleotide polymorphism.

PubMed

Zhou, Li; Du, Feng; Zhao, Yongyun; Yameen, Afshan; Chen, Haodong; Tang, Zhuo

2013-07-15

Fast and accurate detection of single-nucleotide polymorphism (SNP) is thought more and more important for understanding of human physiology and elucidating the molecular based diseases. A great deal of effort has been devoted to developing accurate, rapid, and cost-effective technologies for SNP analysis. However most of those methods developed to date incorporate complicated probe labeling and depend on advanced equipment. The DNAzyme based Gap-LCR detection method averts any chemical modification on probes and circumvents those problems by incorporating a short functional DNA sequence into one of LCR primers. Two kinds of exonuclease are utilized in our strategy to digest all the unreacted probes and release the DNAzymes embedded in the LCR product. The DNAzyme applied in our method is a versatile tool to report the result of SNP detection in colorimetric or fluorometric ways for different detection purposes. Copyright © 2013 Elsevier B.V. All rights reserved.

Low-cost EEG-based sleep detection.

PubMed

Van Hal, Bryan; Rhodes, Samhita; Dunne, Bruce; Bossemeyer, Robert

2014-01-01

A real-time stage 1 sleep detection system using a low-cost single dry-sensor EEG headset is described. This device issues an auditory warning at the onset of stage 1 sleep using the "NeuroSky Mindset," an inexpensive commercial entertainment-based headset. The EEG signal is filtered into low/high alpha and low/high beta frequency bands which are analyzed to indicate the onset of sleep. Preliminary results indicate an 81% effective rate of detecting sleep with all failures being false positives of sleep onset. This device was able to predict and respond to the onset of drowsiness preceding stage 1 sleep allowing for earlier warnings with the result of fewer sleep-related accidents.

Infrared dim target detection based on visual attention

NASA Astrophysics Data System (ADS)

Wang, Xin; Lv, Guofang; Xu, Lizhong

2012-11-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Trained neurons-based motion detection in optical camera communications

NASA Astrophysics Data System (ADS)

Teli, Shivani; Cahyadi, Willy Anugrah; Chung, Yeon Ho

2018-04-01

A concept of trained neurons-based motion detection (TNMD) in optical camera communications (OCC) is proposed. The proposed TNMD is based on neurons present in a neural network that perform repetitive analysis in order to provide efficient and reliable motion detection in OCC. This efficient motion detection can be considered another functionality of OCC in addition to two traditional functionalities of illumination and communication. To verify the proposed TNMD, the experiments were conducted in an indoor static downlink OCC, where a mobile phone front camera is employed as the receiver and an 8 × 8 red, green, and blue (RGB) light-emitting diode array as the transmitter. The motion is detected by observing the user's finger movement in the form of centroid through the OCC link via a camera. Unlike conventional trained neurons approaches, the proposed TNMD is trained not with motion itself but with centroid data samples, thus providing more accurate detection and far less complex detection algorithm. The experiment results demonstrate that the TNMD can detect all considered motions accurately with acceptable bit error rate (BER) performances at a transmission distance of up to 175 cm. In addition, while the TNMD is performed, a maximum data rate of 3.759 kbps over the OCC link is obtained. The OCC with the proposed TNMD combined can be considered an efficient indoor OCC system that provides illumination, communication, and motion detection in a convenient smart home environment.

Micromotor-based on-off fluorescence detection of sarin and soman simulants.

PubMed

Singh, Virendra V; Kaufmann, Kevin; Orozco, Jahir; Li, Jinxing; Galarnyk, Michael; Arya, Gaurav; Wang, Joseph

2015-06-30

Self-propelled micromotor-based fluorescent "On-Off" detection of nerve agents is described. The motion-based assay utilizes Si/Pt Janus micromotors coated with fluoresceinamine toward real-time "on-the-fly" field detection of sarin and soman simulants.

Polymer-based sensor array for phytochemical detection

NASA Astrophysics Data System (ADS)

Weerakoon, Kanchana A.; Hiremath, Nitilaksha; Chin, Bryan A.

2012-05-01

Monitoring for the appearance of volatile organic compounds emitted by plants which correspond to time of first insect attack can be used to detect the early stages of insect infestation. This paper reports a chemical sensor array consisting of polymer based chemiresistor sensors that could detect insect infestation effectively. The sensor array consists of sensors with micro electronically fabricated interdigitated electrodes, and twelve different types of electro active polymer layers. The sensor array was cheap, easy to fabricate, and could be used easily in agricultural fields. The polymer array was found to be sensitive to a variety of volatile organic compounds emitted by plants including γ-terpinene α-pinene, pcymene, farnesene, limonene and cis-hexenyl acetate. The sensor array was not only able to detect but also distinguish between these compounds. The twelve sensors produced a resistance change for each of the analytes detected, and each of these responses together produced a unique fingerprint, enabling to distinguish among these chemicals.

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

Adaptive 4d Psi-Based Change Detection

NASA Astrophysics Data System (ADS)

Yang, Chia-Hsiang; Soergel, Uwe

2018-04-01

In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.

An Invisible Text Watermarking Algorithm using Image Watermark

NASA Astrophysics Data System (ADS)

Jalil, Zunera; Mirza, Anwar M.

Copyright protection of digital contents is very necessary in today's digital world with efficient communication mediums as internet. Text is the dominant part of the internet contents and there are very limited techniques available for text protection. This paper presents a novel algorithm for protection of plain text, which embeds the logo image of the copyright owner in the text and this logo can be extracted from the text later to prove ownership. The algorithm is robust against content-preserving modifications and at the same time, is capable of detecting malicious tampering. Experimental results demonstrate the effectiveness of the algorithm against tampering attacks by calculating normalized hamming distances. The results are also compared with a recent work in this domain

Analysis of Android Device-Based Solutions for Fall Detection

PubMed Central

Casilari, Eduardo; Luque, Rafael; Morón, María-José

2015-01-01

Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions. PMID:26213928

Analysis of Android Device-Based Solutions for Fall Detection.

PubMed

Casilari, Eduardo; Luque, Rafael; Morón, María-José

2015-07-23

Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions.

A portable cell-based optical detection device for rapid detection of Listeria and Bacillus toxins

NASA Astrophysics Data System (ADS)

Banerjee, Pratik; Banada, Padmapriya P.; Rickus, Jenna L.; Morgan, Mark T.; Bhunia, Arun K.

2005-11-01

A mammalian cell-based optical biosensor was built to detect pathogenic Listeria and Bacillus species. This sensor measures the ability of the pathogens to infect and induce cytotoxicity on hybrid lymphocyte cell line (Ped-2E9) resulting in the release of alkaline phosphatase (ALP) that can be detected optically using a portable spectrophotometer. The Ped-2E9 cells were encapsulated in collagen gel matrices and grown in 48-well plates or in specially designed filtration tube units. Toxin preparations or bacterial cells were introduced and ALP release was assayed after 3-5 h. Pathogenic L. monocytogenes strains or the listeriolysin toxins preparation showed cytotoxicity ranging from 55% - 92%. Toxin preparations (~20 μg/ml) from B. cereus strains showed 24 - 98% cytotoxicity. In contrast, a non-pathogenic L. innocua (F4247) and a B. substilis induced only 2% and 8% cytotoxicity, respectively. This cell-based detection device demonstrates its ability to detect the presence of pathogenic Listeria and Bacillus species and can potentially be used onsite for food safety or in biosecurity application.

Fiber-Optic Based Compact Gas Leak Detection System

NASA Technical Reports Server (NTRS)

deGroot, Wim A.

1995-01-01

A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

Video-based real-time on-street parking occupancy detection system

NASA Astrophysics Data System (ADS)

Bulan, Orhan; Loce, Robert P.; Wu, Wencheng; Wang, YaoRong; Bernal, Edgar A.; Fan, Zhigang

2013-10-01

Urban parking management is receiving significant attention due to its potential to reduce traffic congestion, fuel consumption, and emissions. Real-time parking occupancy detection is a critical component of on-street parking management systems, where occupancy information is relayed to drivers via smart phone apps, radio, Internet, on-road signs, or global positioning system auxiliary signals. Video-based parking occupancy detection systems can provide a cost-effective solution to the sensing task while providing additional functionality for traffic law enforcement and surveillance. We present a video-based on-street parking occupancy detection system that can operate in real time. Our system accounts for the inherent challenges that exist in on-street parking settings, including illumination changes, rain, shadows, occlusions, and camera motion. Our method utilizes several components from video processing and computer vision for motion detection, background subtraction, and vehicle detection. We also present three traffic law enforcement applications: parking angle violation detection, parking boundary violation detection, and exclusion zone violation detection, which can be integrated into the parking occupancy cameras as a value-added option. Our experimental results show that the proposed parking occupancy detection method performs in real-time at 5 frames/s and achieves better than 90% detection accuracy across several days of videos captured in a busy street block under various weather conditions such as sunny, cloudy, and rainy, among others.

Direct Detection and Sequencing of Damaged DNA Bases

PubMed Central

2011-01-01

Products of various forms of DNA damage have been implicated in a variety of important biological processes, such as aging, neurodegenerative diseases, and cancer. Therefore, there exists great interest to develop methods for interrogating damaged DNA in the context of sequencing. Here, we demonstrate that single-molecule, real-time (SMRT®) DNA sequencing can directly detect damaged DNA bases in the DNA template - as a by-product of the sequencing method - through an analysis of the DNA polymerase kinetics that are altered by the presence of a modified base. We demonstrate the sequencing of several DNA templates containing products of DNA damage, including 8-oxoguanine, 8-oxoadenine, O6-methylguanine, 1-methyladenine, O4-methylthymine, 5-hydroxycytosine, 5-hydroxyuracil, 5-hydroxymethyluracil, or thymine dimers, and show that these base modifications can be readily detected with single-modification resolution and DNA strand specificity. We characterize the distinct kinetic signatures generated by these DNA base modifications. PMID:22185597

Direct detection and sequencing of damaged DNA bases.

PubMed

Clark, Tyson A; Spittle, Kristi E; Turner, Stephen W; Korlach, Jonas

2011-12-20

Products of various forms of DNA damage have been implicated in a variety of important biological processes, such as aging, neurodegenerative diseases, and cancer. Therefore, there exists great interest to develop methods for interrogating damaged DNA in the context of sequencing. Here, we demonstrate that single-molecule, real-time (SMRT®) DNA sequencing can directly detect damaged DNA bases in the DNA template - as a by-product of the sequencing method - through an analysis of the DNA polymerase kinetics that are altered by the presence of a modified base. We demonstrate the sequencing of several DNA templates containing products of DNA damage, including 8-oxoguanine, 8-oxoadenine, O6-methylguanine, 1-methyladenine, O4-methylthymine, 5-hydroxycytosine, 5-hydroxyuracil, 5-hydroxymethyluracil, or thymine dimers, and show that these base modifications can be readily detected with single-modification resolution and DNA strand specificity. We characterize the distinct kinetic signatures generated by these DNA base modifications.

Transmission Line Security Monitor

ScienceCinema

None

2017-12-09

The Transmission Line Security Monitor is a multi-sensor monitor that mounts directly on high-voltage transmission lines to detect, characterize and communicate terrorist activity, human tampering and threatening conditions around support towers. For more information about INL's critical infrastructure protection research, visit http://www.facebook.com/idahonationallaboratory.

Home Camera-Based Fall Detection System for the Elderly

PubMed Central

de Miguel, Koldo

2017-01-01

Falls are the leading cause of injury and death in elderly individuals. Unfortunately, fall detectors are typically based on wearable devices, and the elderly often forget to wear them. In addition, fall detectors based on artificial vision are not yet available on the market. In this paper, we present a new low-cost fall detector for smart homes based on artificial vision algorithms. Our detector combines several algorithms (background subtraction, Kalman filtering and optical flow) as input to a machine learning algorithm with high detection accuracy. Tests conducted on over 50 different fall videos have shown a detection ratio of greater than 96%. PMID:29232846

Live face detection based on the analysis of Fourier spectra

NASA Astrophysics Data System (ADS)

Li, Jiangwei; Wang, Yunhong; Tan, Tieniu; Jain, Anil K.

2004-08-01

Biometrics is a rapidly developing technology that is to identify a person based on his or her physiological or behavioral characteristics. To ensure the correction of authentication, the biometric system must be able to detect and reject the use of a copy of a biometric instead of the live biometric. This function is usually termed "liveness detection". This paper describes a new method for live face detection. Using structure and movement information of live face, an effective live face detection algorithm is presented. Compared to existing approaches, which concentrate on the measurement of 3D depth information, this method is based on the analysis of Fourier spectra of a single face image or face image sequences. Experimental results show that the proposed method has an encouraging performance.

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

PubMed

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

Cosmic string detection with tree-based machine learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-07-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9'-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Cosmic String Detection with Tree-Based Machine Learning

NASA Astrophysics Data System (ADS)

Vafaei Sadr, A.; Farhang, M.; Movahed, S. M. S.; Bassett, B.; Kunz, M.

2018-05-01

We explore the use of random forest and gradient boosting, two powerful tree-based machine learning algorithms, for the detection of cosmic strings in maps of the cosmic microwave background (CMB), through their unique Gott-Kaiser-Stebbins effect on the temperature anisotropies. The information in the maps is compressed into feature vectors before being passed to the learning units. The feature vectors contain various statistical measures of the processed CMB maps that boost cosmic string detectability. Our proposed classifiers, after training, give results similar to or better than claimed detectability levels from other methods for string tension, Gμ. They can make 3σ detection of strings with Gμ ≳ 2.1 × 10-10 for noise-free, 0.9΄-resolution CMB observations. The minimum detectable tension increases to Gμ ≳ 3.0 × 10-8 for a more realistic, CMB S4-like (II) strategy, improving over previous results.

Towards Accurate Node-Based Detection of P2P Botnets

PubMed Central

2014-01-01

Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node's flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches. PMID:25089287

Integrated signal probe based aptasensor for dual-analyte detection.

PubMed

Xiang, Juan; Pi, Xiaomei; Chen, Xiaoqing; Xiang, Lei; Yang, Minghui; Ren, Hao; Shen, Xiaojuan; Qi, Ning; Deng, Chunyan

2017-10-15

For the multi-analyte detection, although the sensitivity has commonly met the practical requirements, the reliability, reproducibility and stability need to be further improved. In this work, two different aptamer probes labeled with redox tags were used as signal probe1 (sP1) and signal probe2 (sP2), which were integrated into one unity DNA architecture to develop the integrated signal probe (ISP). Comparing with the conventional independent signal probes for the simultaneous multi-analyte detection, the proposed ISP was more reproducible and accurate. This can be due to that ISP in one DNA structure can ensure the completely same modification condition and an equal stoichiometric ratio between sP1 and sP2, and furthermore the cross interference between sP1 and sP2 can be successfully prevented by regulating the complementary position of sP1 and sP2. The ISP-based assay system would be a great progress for the dual-analyte detection. Combining with gold nanoparticles (AuNPs) signal amplification, the ISP/AuNPs-based aptasensor for the sensitive dual-analyte detection was explored. Based on DNA structural switching induced by targets binding to aptamer, the simultaneous dual-analyte detection was simply achieved by monitoring the electrochemical responses of methylene blue (MB) and ferrocene (Fc) This proposed detection system possesses such advantages as simplicity in design, easy operation, good reproducibility and accuracy, high sensitivity and selectivity, which indicates the excellent application of this aptasensor in the field of clinical diagnosis or other molecular sensors. Copyright © 2017 Elsevier B.V. All rights reserved.

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Continuous Tamper-proof Logging using TPM2.0

DTIC Science & Technology

2014-06-16

process each log entry. Additional hardware support could mitigate this problem. Tradeoffs between performance and security guarantees Disk write...becomes weaker as the block size increases. This problem is mitigated in protocol B by allowing offline recovery from a power failure and detection of...M.K., Isozaki, H.: Flicker : An execution infrastructure for TCB minimization. ACM SIGOPS Operating Systems Review 42(4) (2008) 315–328 24. Parno, B

Rhythm-based heartbeat duration normalization for atrial fibrillation detection.

PubMed

Islam, Md Saiful; Ammour, Nassim; Alajlan, Naif; Aboalsamh, Hatim

2016-05-01

Screening of atrial fibrillation (AF) for high-risk patients including all patients aged 65 years and older is important for prevention of risk of stroke. Different technologies such as modified blood pressure monitor, single lead ECG-based finger-probe, and smart phone using plethysmogram signal have been emerging for this purpose. All these technologies use irregularity of heartbeat duration as a feature for AF detection. We have investigated a normalization method of heartbeat duration for improved AF detection. AF is an arrhythmia in which heartbeat duration generally becomes irregularly irregular. From a window of heartbeat duration, we estimate the possible rhythm of the majority of heartbeats and normalize duration of all heartbeats in the window based on the rhythm so that we can measure the irregularity of heartbeats for both AF and non-AF rhythms in the same scale. Irregularity is measured by the entropy of distribution of the normalized duration. Then we classify a window of heartbeats as AF or non-AF by thresholding the measured irregularity. The effect of this normalization is evaluated by comparing AF detection performances using duration with the normalization, without normalization, and with other existing normalizations. Sensitivity and specificity of AF detection using normalized heartbeat duration were tested on two landmark databases available online and compared with results of other methods (with/without normalization) by receiver operating characteristic (ROC) curves. ROC analysis showed that the normalization was able to improve the performance of AF detection and it was consistent for a wide range of sensitivity and specificity for use of different thresholds. Detection accuracy was also computed for equal rates of sensitivity and specificity for different methods. Using normalized heartbeat duration, we obtained 96.38% accuracy which is more than 4% improvement compared to AF detection without normalization. The proposed normalization

Qualitative and quantitative detection of T7 bacteriophages using paper based sandwich ELISA.

PubMed

Khan, Mohidus Samad; Pande, Tripti; van de Ven, Theo G M

2015-08-01

Viruses cause many infectious diseases and consequently epidemic health threats. Paper based diagnostics and filters can offer attractive options for detecting and deactivating pathogens. However, due to their infectious characteristics, virus detection using paper diagnostics is more challenging compared to the detection of bacteria, enzymes, DNA or antigens. The major objective of this study was to prepare reliable, degradable and low cost paper diagnostics to detect viruses, without using sophisticated optical or microfluidic analytical instruments. T7 bacteriophage was used as a model virus. A paper based sandwich ELISA technique was developed to detect and quantify the T7 phages in solution. The paper based sandwich ELISA detected T7 phage concentrations as low as 100 pfu/mL to as high as 10(9) pfu/mL. The compatibility of paper based sandwich ELISA with the conventional titre count was tested using T7 phage solutions of unknown concentrations. The paper based sandwich ELISA technique is faster and economical compared to the traditional detection techniques. Therefore, with proper calibration and right reagents, and by following the biosafety regulations, the paper based technique can be said to be compatible and economical to the sophisticated laboratory diagnostic techniques applied to detect pathogenic viruses and other microorganisms. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimized feature-detection for on-board vision-based surveillance

NASA Astrophysics Data System (ADS)

Gond, Laetitia; Monnin, David; Schneider, Armin

2012-06-01

The detection and matching of robust features in images is an important step in many computer vision applications. In this paper, the importance of the keypoint detection algorithms and their inherent parameters in the particular context of an image-based change detection system for IED detection is studied. Through extensive application-oriented experiments, we draw an evaluation and comparison of the most popular feature detectors proposed by the computer vision community. We analyze how to automatically adjust these algorithms to changing imaging conditions and suggest improvements in order to achieve more exibility and robustness in their practical implementation.

Single-channel EEG-based mental fatigue detection based on deep belief network.

PubMed

Pinyi Li; Wenhui Jiang; Fei Su

2016-08-01

Mental fatigue has a pernicious influence on road and work place safety as well as a negative symptom of many acute and chronic illnesses, since the ability of concentrating, responding and judging quickly decreases during the fatigue or drowsiness stage. Electroencephalography (EEG) has been proven to be a robust physiological indicator of human cognitive state over the last few decades. But most existing EEG-based fatigue detection methods have poor performance in accuracy. This paper proposed a single-channel EEG-based mental fatigue detection method based on Deep Belief Network (DBN). The fused nonliear features from specified sub-bands and dynamic analysis, a total of 21 features are extracted as the input of the DBN to discriminate three classes of mental state including alert, slight fatigue and severe fatigue. Experimental results show the good performance of the proposed model comparing with those state-of-art methods.

Rapid detection of tuberculosis using droplet-based microfluidics

NASA Astrophysics Data System (ADS)

Rosenfeld, Liat; Cheng, Yunfeng; Rao, Jianghong; Tang, Sindy K. Y.

2014-03-01

Tuberculosis is one of the most deadly diseases that kills over one million people each year and infects one-third of the world's population. The disease is spread by infection with Mycobacterium tuberculosis (Mtb). Owing to its airborne transmission, early diagnosis is critical to the prevention and control of TB. Standard diagnostic methods, acid-fast smear from sputum, often do not become positive until after transmission occurs, which allows the spread of the disease. Culture-based techniques are more sensitive, but take weeks to obtain results because of the extremely slow growth rate of Mtb. In this study a new method to detect indicator enzyme based on the isolation of tubercle bacillus in a large number of picoliter droplets combined with a fluorescent probe has been developed. We use BlaC (an enzyme naturally expressed/secreted by tubercle bacilli) as a marker and a designed BlaC-specific fluorogenic substrates as probes for Mtb detection. We present here a new method to detect the indicator enzyme based on the isolation, digitization and concentration of bacteria samples in a large number of picoliter drops. We show that by controlling the size of the droplets we can control the rate of conversion. Hence rapid increase in signal has been observed as the size of the drops has been decreased. Our vision is that this tool will be able to detect tubercle bacilli in a sensitive, rapid, specific and quantitative manner in vitro at a low cost, particularly in resource limited settings where TB is the most prevalent.

The parameterization of microchannel-plate-based detection systems

NASA Astrophysics Data System (ADS)

Gershman, Daniel J.; Gliese, Ulrik; Dorelli, John C.; Avanov, Levon A.; Barrie, Alexander C.; Chornay, Dennis J.; MacDonald, Elizabeth A.; Holland, Matthew P.; Giles, Barbara L.; Pollock, Craig J.

2016-10-01

The most common instrument for low-energy plasmas consists of a top-hat electrostatic analyzer (ESA) geometry coupled with a microchannel-plate-based (MCP-based) detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Here we develop a comprehensive mathematical description of particle detection systems. As a function of instrument azimuthal angle, we parameterize (1) particle scattering within the ESA and at the surface of the MCP, (2) the probability distribution of MCP gain for an incident particle, (3) electron charge cloud spreading between the MCP and anode board, and (4) capacitive coupling between adjacent discrete anodes. Using the Dual Electron Spectrometers on the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission as an example, we demonstrate a method for extracting these fundamental detection system parameters from laboratory calibration. We further show that parameters that will evolve in flight, namely, MCP gain, can be determined through application of this model to specifically tailored in-flight calibration activities. This methodology provides a robust characterization of sensor suite performance throughout mission lifetime. The model developed in this work is not only applicable to existing sensors but also can be used as an analytical design tool for future particle instrumentation.

Automated image based prominent nucleoli detection

PubMed Central

Yap, Choon K.; Kalaw, Emarene M.; Singh, Malay; Chong, Kian T.; Giron, Danilo M.; Huang, Chao-Hui; Cheng, Li; Law, Yan N.; Lee, Hwee Kuan

2015-01-01

Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings. PMID:26167383

Automated image based prominent nucleoli detection.

PubMed

Yap, Choon K; Kalaw, Emarene M; Singh, Malay; Chong, Kian T; Giron, Danilo M; Huang, Chao-Hui; Cheng, Li; Law, Yan N; Lee, Hwee Kuan

2015-01-01

Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

Infrared video based gas leak detection method using modified FAST features

NASA Astrophysics Data System (ADS)

Wang, Min; Hong, Hanyu; Huang, Likun

2018-03-01

In order to detect the invisible leaking gas that is usually dangerous and easily leads to fire or explosion in time, many new technologies have arisen in the recent years, among which the infrared video based gas leak detection is widely recognized as a viable tool. However, all the moving regions of a video frame can be detected as leaking gas regions by the existing infrared video based gas leak detection methods, without discriminating the property of each detected region, e.g., a walking person in a video frame may be also detected as gas by the current gas leak detection methods.To solve this problem, we propose a novel infrared video based gas leak detection method in this paper, which is able to effectively suppress strong motion disturbances.Firstly, the Gaussian mixture model(GMM) is used to establish the background model.Then due to the observation that the shapes of gas regions are different from most rigid moving objects, we modify the Features From Accelerated Segment Test (FAST) algorithm and use the modified FAST (mFAST) features to describe each connected component. In view of the fact that the statistical property of the mFAST features extracted from gas regions is different from that of other motion regions, we propose the Pixel-Per-Points (PPP) condition to further select candidate connected components.Experimental results show that the algorithm is able to effectively suppress most strong motion disturbances and achieve real-time leaking gas detection.

A Survey on Anomaly Based Host Intrusion Detection System

NASA Astrophysics Data System (ADS)

Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

2018-04-01

An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

Biosensor-based microRNA detection: techniques, design, performance, and challenges.

PubMed

Johnson, Blake N; Mutharasan, Raj

2014-04-07

The current state of biosensor-based techniques for amplification-free microRNA (miRNA) detection is critically reviewed. Comparison with non-sensor and amplification-based molecular techniques (MTs), such as polymerase-based methods, is made in terms of transduction mechanism, associated protocol, and sensitivity. Challenges associated with miRNA hybridization thermodynamics which affect assay selectivity and amplification bias are briefly discussed. Electrochemical, electromechanical, and optical classes of miRNA biosensors are reviewed in terms of transduction mechanism, limit of detection (LOD), time-to-results (TTR), multiplexing potential, and measurement robustness. Current trends suggest that biosensor-based techniques (BTs) for miRNA assay will complement MTs due to the advantages of amplification-free detection, LOD being femtomolar (fM)-attomolar (aM), short TTR, multiplexing capability, and minimal sample preparation requirement. Areas of future importance in miRNA BT development are presented which include focus on achieving high measurement confidence and multiplexing capabilities.

Light Scattering based detection of food pathogens

USDA-ARS?s Scientific Manuscript database

The current methods for detecting foodborne pathogens are mostly destructive (i.e., samples need to be pretreated), and require time, personnel, and laboratories for analyses. Optical methods including light scattering based techniques have gained a lot of attention recently due to its their rapid a...

Object detection in natural scenes: Independent effects of spatial and category-based attention.

PubMed

Stein, Timo; Peelen, Marius V

2017-04-01

Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.

Research about Memory Detection Based on the Embedded Platform

NASA Astrophysics Data System (ADS)

Sun, Hao; Chu, Jian

As is known to us all, the resources of memory detection of the embedded systems are very limited. Taking the Linux-based embedded arm as platform, this article puts forward two efficient memory detection technologies according to the characteristics of the embedded software. Especially for the programs which need specific libraries, the article puts forwards portable memory detection methods to help program designers to reduce human errors,improve programming quality and therefore make better use of the valuable embedded memory resource.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Quartz crystal microbalance detection of DNA single-base mutation based on monobase-coded cadmium tellurium nanoprobe.

PubMed

Zhang, Yuqin; Lin, Fanbo; Zhang, Youyu; Li, Haitao; Zeng, Yue; Tang, Hao; Yao, Shouzhuo

2011-01-01

A new method for the detection of point mutation in DNA based on the monobase-coded cadmium tellurium nanoprobes and the quartz crystal microbalance (QCM) technique was reported. A point mutation (single-base, adenine, thymine, cytosine, and guanine, namely, A, T, C and G, mutation in DNA strand, respectively) DNA QCM sensor was fabricated by immobilizing single-base mutation DNA modified magnetic beads onto the electrode surface with an external magnetic field near the electrode. The DNA-modified magnetic beads were obtained from the biotin-avidin affinity reaction of biotinylated DNA and streptavidin-functionalized core/shell Fe(3)O(4)/Au magnetic nanoparticles, followed by a DNA hybridization reaction. Single-base coded CdTe nanoprobes (A-CdTe, T-CdTe, C-CdTe and G-CdTe, respectively) were used as the detection probes. The mutation site in DNA was distinguished by detecting the decreases of the resonance frequency of the piezoelectric quartz crystal when the coded nanoprobe was added to the test system. This proposed detection strategy for point mutation in DNA is proved to be sensitive, simple, repeatable and low-cost, consequently, it has a great potential for single nucleotide polymorphism (SNP) detection. 2011 © The Japan Society for Analytical Chemistry

A saliency-based approach to detection of infrared target

NASA Astrophysics Data System (ADS)

Chen, Yanfei; Sang, Nong; Dan, Zhiping

2013-10-01

Automatic target detection in infrared images is a hot research field of national defense technology. We propose a new saliency-based infrared target detection model in this paper, which is based on the fact that human focus of attention is directed towards the relevant target to interpret the most promising information. For a given image, the convolution of the image log amplitude spectrum with a low-pass Gaussian kernel of an appropriate scale is equivalent to an image saliency detector in the frequency domain. At the same time, orientation and shape features extracted are combined into a saliency map in the spatial domain. Our proposed model decides salient targets based on a final saliency map, which is generated by integration of the saliency maps in the frequency and spatial domain. At last, the size of each salient target is obtained by maximizing entropy of the final saliency map. Experimental results show that the proposed model can highlight both small and large salient regions in infrared image, as well as inhibit repeated distractors in cluttered image. In addition, its detecting efficiency has improved significantly.

Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

PubMed

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

Visual saliency detection based on in-depth analysis of sparse representation

NASA Astrophysics Data System (ADS)

Wang, Xin; Shen, Siqiu; Ning, Chen

2018-03-01

Visual saliency detection has been receiving great attention in recent years since it can facilitate a wide range of applications in computer vision. A variety of saliency models have been proposed based on different assumptions within which saliency detection via sparse representation is one of the newly arisen approaches. However, most existing sparse representation-based saliency detection methods utilize partial characteristics of sparse representation, lacking of in-depth analysis. Thus, they may have limited detection performance. Motivated by this, this paper proposes an algorithm for detecting visual saliency based on in-depth analysis of sparse representation. A number of discriminative dictionaries are first learned with randomly sampled image patches by means of inner product-based dictionary atom classification. Then, the input image is partitioned into many image patches, and these patches are classified into salient and nonsalient ones based on the in-depth analysis of sparse coding coefficients. Afterward, sparse reconstruction errors are calculated for the salient and nonsalient patch sets. By investigating the sparse reconstruction errors, the most salient atoms, which tend to be from the most salient region, are screened out and taken away from the discriminative dictionaries. Finally, an effective method is exploited for saliency map generation with the reduced dictionaries. Comprehensive evaluations on publicly available datasets and comparisons with some state-of-the-art approaches demonstrate the effectiveness of the proposed algorithm.

A stereo vision-based obstacle detection system in vehicles

NASA Astrophysics Data System (ADS)

Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

2008-02-01

Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

Tactile sensor of hardness recognition based on magnetic anomaly detection

NASA Astrophysics Data System (ADS)

Xue, Lingyun; Zhang, Dongfang; Chen, Qingguang; Rao, Huanle; Xu, Ping

2018-03-01

Hardness, as one kind of tactile sensing, plays an important role in the field of intelligent robot application such as gripping, agricultural harvesting, prosthetic hand and so on. Recently, with the rapid development of magnetic field sensing technology with high performance, a number of magnetic sensors have been developed for intelligent application. The tunnel Magnetoresistance(TMR) based on magnetoresistance principal works as the sensitive element to detect the magnetic field and it has proven its excellent ability of weak magnetic detection. In the paper, a new method based on magnetic anomaly detection was proposed to detect the hardness in the tactile way. The sensor is composed of elastic body, ferrous probe, TMR element, permanent magnet. When the elastic body embedded with ferrous probe touches the object under the certain size of force, deformation of elastic body will produce. Correspondingly, the ferrous probe will be forced to displace and the background magnetic field will be distorted. The distorted magnetic field was detected by TMR elements and the output signal at different time can be sampled. The slope of magnetic signal with the sampling time is different for object with different hardness. The result indicated that the magnetic anomaly sensor can recognize the hardness rapidly within 150ms after the tactile moment. The hardness sensor based on magnetic anomaly detection principal proposed in the paper has the advantages of simple structure, low cost, rapid response and it has shown great application potential in the field of intelligent robot.

Real-time detection of deoxyribonucleic acid bases via their negative differential conductance signature.

PubMed

Dragoman, D; Dragoman, M

2009-08-01

In this Brief Report, we present a method for the real-time detection of the bases of the deoxyribonucleic acid using their signatures in negative differential conductance measurements. The present methods of electronic detection of deoxyribonucleic acid bases are based on a statistical analysis because the electrical currents of the four bases are weak and do not differ significantly from one base to another. In contrast, we analyze a device that combines the accumulated knowledge in nanopore and scanning tunneling detection and which is able to provide very distinctive electronic signatures for the four bases.

Coarse-to-fine wavelet-based airport detection

NASA Astrophysics Data System (ADS)

Li, Cheng; Wang, Shuigen; Pang, Zhaofeng; Zhao, Baojun

2015-10-01

Airport detection on optical remote sensing images has attracted great interest in the applications of military optics scout and traffic control. However, most of the popular techniques for airport detection from optical remote sensing images have three weaknesses: 1) Due to the characteristics of optical images, the detection results are often affected by imaging conditions, like weather situation and imaging distortion; and 2) optical images contain comprehensive information of targets, so that it is difficult for extracting robust features (e.g., intensity and textural information) to represent airport area; 3) the high resolution results in large data volume, which makes real-time processing limited. Most of the previous works mainly focus on solving one of those problems, and thus, the previous methods cannot achieve the balance of performance and complexity. In this paper, we propose a novel coarse-to-fine airport detection framework to solve aforementioned three issues using wavelet coefficients. The framework includes two stages: 1) an efficient wavelet-based feature extraction is adopted for multi-scale textural feature representation, and support vector machine(SVM) is exploited for classifying and coarsely deciding airport candidate region; and then 2) refined line segment detection is used to obtain runway and landing field of airport. Finally, airport recognition is achieved by applying the fine runway positioning to the candidate regions. Experimental results show that the proposed approach outperforms the existing algorithms in terms of detection accuracy and processing efficiency.

Person-level changes in oxycodone use after the introduction of a tamper-resistant formulation in Australia

PubMed Central

Buckley, Nicholas A.; Degenhardt, Louisa; Larance, Briony; Cairns, Rose; Dobbins, Timothy A.; Pearson, Sallie-Anne

2018-01-01

BACKGROUND: Australia introduced tamper-resistant controlled-release (CR) oxycodone in April 2014. We quantified the impact of the reformulation on dispensing, switching and poisonings. METHODS: We performed interrupted time-series analyses using population-representative national dispensing data from 2012 to 2016. We measured dispensing of oxycodone CR (≥ 10 mg), discontinuation of use of strong opioids and switching to other strong opioids after the reformulation compared with a historical control period. Similarly, we compared calls about intentional opioid poisoning using data from a regional poisons information centre. RESULTS: After the reformulation, dispensing decreased for 10–30 mg (total level shift −11.1%, 95% confidence interval [CI], −17.2% to −4.6%) and 40–80 mg oxycodone CR (total level shift −31.5%, 95% CI −37.5% to −24.9%) in participants less than 65 years of age but was unchanged in people 65 years of age or older. Compared with the previous year, discontinuation of use of strong opioids did not increase (adjusted hazard ratio [HR] 0.95, 95% CI 0.91 to 1.00), but switching to oxycodone/naloxone did increase (adjusted HR 1.54, 95% CI 1.32 to 1.79). Switching to morphine varied by age (p < 0.001), and the greatest increase was in participants less than 45 years of age (adjusted HR 4.33, 95% CI 2.13 to 8.80). Participants switching after the reformulation were more likely to be dispensed a tablet strength of 40 mg or more (adjusted odds ratio [OR] 1.40, 95% CI 1.09 to 1.79). Calls for intentional poisoning that involved oxycodone taken orally increased immediately after the reformulation (incidence rate ratio (IRR) 1.31, 95% CI 1.05–1.64), but there was no change for injected oxycodone. INTERPRETATION: The reformulation had a greater impact on opioid access patterns of people less than 65 years of age who were using higher strengths of oxycodone CR. This group has been identified as having an increased risk of problematic opioid

PCA-HOG symmetrical feature based diseased cell detection

NASA Astrophysics Data System (ADS)

Wan, Min-jie

2016-04-01

A histogram of oriented gradient (HOG) feature is applied to the field of diseased cell detection, which can detect diseased cells in high resolution tissue images rapidly, accurately and efficiently. Firstly, motivated by symmetrical cellular forms, a new HOG symmetrical feature based on the traditional HOG feature is proposed to meet the condition of cell detection. Secondly, considering the high feature dimension of traditional HOG feature leads to plenty of memory resources and long runtime in practical applications, a classical dimension reduction method called principal component analysis (PCA) is used to reduce the dimension of high-dimensional HOG descriptor. Because of that, computational speed is increased greatly, and the accuracy of detection can be controlled in a proper range at the same time. Thirdly, support vector machine (SVM) classifier is trained with PCA-HOG symmetrical features proposed above. At last, practical tissue images is detected and analyzed by SVM classifier. In order to verify the effectiveness of this new algorithm, it is practically applied to conduct diseased cell detection which takes 200 pieces of H&E (hematoxylin & eosin) high resolution staining histopathological images collected from 20 breast cancer patients as a sample. The experiment shows that the average processing rate can be 25 frames per second and the detection accuracy can be 92.1%.

A Novel Distributed Privacy Paradigm for Visual Sensor Networks Based on Sharing Dynamical Systems

NASA Astrophysics Data System (ADS)

Luh, William; Kundur, Deepa; Zourntos, Takis

2006-12-01

Visual sensor networks (VSNs) provide surveillance images/video which must be protected from eavesdropping and tampering en route to the base station. In the spirit of sensor networks, we propose a novel paradigm for securing privacy and confidentiality in a distributed manner. Our paradigm is based on the control of dynamical systems, which we show is well suited for VSNs due to its low complexity in terms of processing and communication, while achieving robustness to both unintentional noise and intentional attacks as long as a small subset of nodes are affected. We also present a low complexity algorithm called TANGRAM to demonstrate the feasibility of applying our novel paradigm to VSNs. We present and discuss simulation results of TANGRAM.

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

PDE based scheme for multi-modal medical image watermarking.

PubMed

Aherrahrou, N; Tairi, H

2015-11-25

This work deals with copyright protection of digital images, an issue that needs protection of intellectual property rights. It is an important issue with a large number of medical images interchanged on the Internet every day. So, it is a challenging task to ensure the integrity of received images as well as authenticity. Digital watermarking techniques have been proposed as valid solution for this problem. It is worth mentioning that the Region Of Interest (ROI)/Region Of Non Interest (RONI) selection can be seen as a significant limitation from which suffers most of ROI/RONI based watermarking schemes and that in turn affects and limit their applicability in an effective way. Generally, the ROI/RONI is defined by a radiologist or a computer-aided selection tool. And thus, this will not be efficient for an institute or health care system, where one has to process a large number of images. Therefore, developing an automatic ROI/RONI selection is a challenge task. The major aim of this work is to develop an automatic selection algorithm of embedding region based on the so called Partial Differential Equation (PDE) method. Thus avoiding ROI/RONI selection problems including: (1) computational overhead, (2) time consuming, and (3) modality dependent selection. The algorithm is evaluated in terms of imperceptibility, robustness, tamper localization and recovery using MRI, Ultrasound, CT and X-ray grey scale medical images. From experimental results that we have conducted on a database of 100 medical images of four modalities, it can be inferred that our method can achieve high imperceptibility, while showing good robustness against attacks. Furthermore, the experiment results confirm the effectiveness of the proposed algorithm in detecting and recovering the various types of tampering. The highest PSNR value reached over the 100 images is 94,746 dB, while the lowest PSNR value is 60,1272 dB, which demonstrates the higher imperceptibility nature of the proposed

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rule-based expert system for maritime anomaly detection

NASA Astrophysics Data System (ADS)

Roy, Jean

2010-04-01

Maritime domain operators/analysts have a mandate to be aware of all that is happening within their areas of responsibility. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc., and it has become more challenging in the past decade, as commercial shipping turned into a potential threat. In particular, a huge portion of the data and information made available to the operators/analysts is mundane, from maritime platforms going about normal, legitimate activities, and it is very challenging for them to detect and identify the non-mundane. To achieve such anomaly detection, they must establish numerous relevant situational facts from a variety of sensor data streams. Unfortunately, many of the facts of interest just cannot be observed; the operators/analysts thus use their knowledge of the maritime domain and their reasoning faculties to infer these facts. As they are often overwhelmed by the large amount of data and information, automated reasoning tools could be used to support them by inferring the necessary facts, ultimately providing indications and warning on a small number of anomalous events worthy of their attention. Along this line of thought, this paper describes a proof-of-concept prototype of a rule-based expert system implementing automated rule-based reasoning in support of maritime anomaly detection.

Performance of PCR-based and Bioluminescent assays for mycoplasma detection.

PubMed

Falagan-Lotsch, Priscila; Lopes, Talíria Silva; Ferreira, Nívea; Balthazar, Nathália; Monteiro, Antônio M; Borojevic, Radovan; Granjeiro, José Mauro

2015-11-01

Contaminated eukaryotic cell cultures are frequently responsible for unreliable results. Regulatory entities request that cell cultures must be mycoplasma-free. Mycoplasma contamination remains a significant problem for cell cultures and may have an impact on biological analysis since they affect many cell parameters. The gold standard microbiological assay for mycoplasma detection involves laborious and time-consuming protocols. PCR-based and Bioluminescent assays have been considered for routine cell culture screening in research laboratories since they are fast, easy and sensitive. Thus, the aim of this work is to compare the performance of two popular commercial assays, PCR-based and Bioluminescent assays, by assessing the level of mycoplasma contamination in cell cultures from Rio de Janeiro Cell Bank (RJCB) and also from customers' laboratories. The results obtained by both performed assays were confirmed by scanning electron microscopy. In addition, we evaluated the limit of detection of the PCR kit under our laboratory conditions and the storage effects on mycoplasma detection in frozen cell culture supernatants. The performance of both assays for mycoplasma detection was not significantly different and they showed very good agreement. The Bioluminescent assay for mycoplasma detection was slightly more dependable than PCR-based due to the lack of inconclusive results produced by the first technique, especially considering the ability to detect mycoplasma contamination in frozen cell culture supernatants. However, cell lines should be precultured for four days or more without antibiotics to obtain safe results. On the other hand, a false negative result was obtained by using this biochemical approach. The implementation of fast and reliable mycoplasma testing methods is an important technical and regulatory issue and PCR-based and Bioluminescent assays may be good candidates. However, validation studies are needed. Copyright © 2015 Elsevier B.V. All rights

RNA-templated single-base mutation detection based on T4 DNA ligase and reverse molecular beacon.

PubMed

Tang, Hongxing; Yang, Xiaohai; Wang, Kemin; Tan, Weihong; Li, Huimin; He, Lifang; Liu, Bin

2008-06-15

A novel RNA-templated single-base mutation detection method based on T4 DNA ligase and reverse molecular beacon (rMB) has been developed and successfully applied to identification of single-base mutation in codon 273 of the p53 gene. The discrimination was carried out using allele-specific primers, which flanked the variable position in the target RNA and was ligated using T4 DNA ligase only when the primers perfectly matched the RNA template. The allele-specific primers also carried complementary stem structures with end-labels (fluorophore TAMRA, quencher DABCYL), which formed a molecular beacon after RNase H digestion. One-base mismatch can be discriminated by analyzing the change of fluorescence intensity before and after RNase H digestion. This method has several advantages for practical applications, such as direct discrimination of single-base mismatch of the RNA extracted from cell; no requirement of PCR amplification; performance of homogeneous detection; and easily design of detection probes.

Dim target detection method based on salient graph fusion

NASA Astrophysics Data System (ADS)

Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

2018-02-01

Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

Cloud-based MOTIFSIM: Detecting Similarity in Large DNA Motif Data Sets.

PubMed

Tran, Ngoc Tam L; Huang, Chun-Hsi

2017-05-01

We developed the cloud-based MOTIFSIM on Amazon Web Services (AWS) cloud. The tool is an extended version from our web-based tool version 2.0, which was developed based on a novel algorithm for detecting similarity in multiple DNA motif data sets. This cloud-based version further allows researchers to exploit the computing resources available from AWS to detect similarity in multiple large-scale DNA motif data sets resulting from the next-generation sequencing technology. The tool is highly scalable with expandable AWS.

Implementing and testing a fiber-optic polarization-based intrusion detection system

NASA Astrophysics Data System (ADS)

Hajj, Rasha El; MacDonald, Gregory; Verma, Pramode; Huck, Robert

2015-09-01

We describe a layer-1-based intrusion detection system for fiber-optic-based networks. Layer-1-based intrusion detection represents a significant elevation in security as it prohibits an adversary from obtaining information in the first place (no cryptanalysis is possible). We describe the experimental setup of the intrusion detection system, which is based on monitoring the behavior of certain attributes of light both in unperturbed and perturbed optical fiber links. The system was tested with optical fiber links of various lengths and types, under different environmental conditions, and under changes in fiber geometry similar to what is experienced during tapping activity. Comparison of the results for perturbed and unperturbed links has shown that the state of polarization is more sensitive to intrusion activity than the degree of polarization or power of the received light. The testing was conducted in a simulated telecommunication network environment that included both underground and aerial links. The links were monitored for intrusion activity. Attempts to tap the link were easily detected with no apparent degradation in the visual quality of the real-time surveillance video.

Capacitor-based detection of nuclear magnetization: nuclear quadrupole resonance of surfaces.

PubMed

Gregorovič, Alan; Apih, Tomaž; Kvasić, Ivan; Lužnik, Janko; Pirnat, Janez; Trontelj, Zvonko; Strle, Drago; Muševič, Igor

2011-03-01

We demonstrate excitation and detection of nuclear magnetization in a nuclear quadrupole resonance (NQR) experiment with a parallel plate capacitor, where the sample is located between the two capacitor plates and not in a coil as usually. While the sensitivity of this capacitor-based detection is found lower compared to an optimal coil-based detection of the same amount of sample, it becomes comparable in the case of very thin samples and even advantageous in the proximity of conducting bodies. This capacitor-based setup may find its application in acquisition of NQR signals from the surface layers on conducting bodies or in a portable tightly integrated nuclear magnetic resonance sensor. Copyright © 2010 Elsevier Inc. All rights reserved.

Statistics and Machine Learning based Outlier Detection Techniques for Exoplanets

NASA Astrophysics Data System (ADS)

Goel, Amit; Montgomery, Michele

2015-08-01

Architectures of planetary systems are observable snapshots in time that can indicate formation and dynamic evolution of planets. The observable key parameters that we consider are planetary mass and orbital period. If planet masses are significantly less than their host star masses, then Keplerian Motion is defined as P^2 = a^3 where P is the orbital period in units of years and a is the orbital period in units of Astronomical Units (AU). Keplerian motion works on small scales such as the size of the Solar System but not on large scales such as the size of the Milky Way Galaxy. In this work, for confirmed exoplanets of known stellar mass, planetary mass, orbital period, and stellar age, we analyze Keplerian motion of systems based on stellar age to seek if Keplerian motion has an age dependency and to identify outliers. For detecting outliers, we apply several techniques based on statistical and machine learning methods such as probabilistic, linear, and proximity based models. In probabilistic and statistical models of outliers, the parameters of a closed form probability distributions are learned in order to detect the outliers. Linear models use regression analysis based techniques for detecting outliers. Proximity based models use distance based algorithms such as k-nearest neighbour, clustering algorithms such as k-means, or density based algorithms such as kernel density estimation. In this work, we will use unsupervised learning algorithms with only the proximity based models. In addition, we explore the relative strengths and weaknesses of the various techniques by validating the outliers. The validation criteria for the outliers is if the ratio of planetary mass to stellar mass is less than 0.001. In this work, we present our statistical analysis of the outliers thus detected.

A novel line segment detection algorithm based on graph search

NASA Astrophysics Data System (ADS)

Zhao, Hong-dan; Liu, Guo-ying; Song, Xu

2018-02-01

To overcome the problem of extracting line segment from an image, a method of line segment detection was proposed based on the graph search algorithm. After obtaining the edge detection result of the image, the candidate straight line segments are obtained in four directions. For the candidate straight line segments, their adjacency relationships are depicted by a graph model, based on which the depth-first search algorithm is employed to determine how many adjacent line segments need to be merged. Finally we use the least squares method to fit the detected straight lines. The comparative experimental results verify that the proposed algorithm has achieved better results than the line segment detector (LSD).

Capacitance-based damage detection sensing for aerospace structural composites

NASA Astrophysics Data System (ADS)

Bahrami, P.; Yamamoto, N.; Chen, Y.; Manohara, H.

2014-04-01

Damage detection technology needs improvement for aerospace engineering application because detection within complex composite structures is difficult yet critical to avoid catastrophic failure. Damage detection is challenging in aerospace structures because not all the damage detection technology can cover the various defect types (delamination, fiber fracture, matrix crack etc.), or conditions (visibility, crack length size, etc.). These defect states are expected to become even more complex with future introduction of novel composites including nano-/microparticle reinforcement. Currently, non-destructive evaluation (NDE) methods with X-ray, ultrasound, or eddy current have good resolutions (< 0.1 mm), but their detection capabilities is limited by defect locations and orientations and require massive inspection devices. System health monitoring (SHM) methods are often paired with NDE technologies to signal out sensed damage, but their data collection and analysis currently requires excessive wiring and complex signal analysis. Here, we present a capacitance sensor-based, structural defect detection technology with improved sensing capability. Thin dielectric polymer layer is integrated as part of the structure; the defect in the structure directly alters the sensing layer's capacitance, allowing full-coverage sensing capability independent of defect size, orientation or location. In this work, capacitance-based sensing capability was experimentally demonstrated with a 2D sensing layer consisting of a dielectric layer sandwiched by electrodes. These sensing layers were applied on substrate surfaces. Surface indentation damage (~1mm diameter) and its location were detected through measured capacitance changes: 1 to 250 % depending on the substrates. The damage detection sensors are light weight, and they can be conformably coated and can be part of the composite structure. Therefore it is suitable for aerospace structures such as cryogenic tanks and rocket

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with

Metamaterial split ring resonator as a sensitive mechanical vibration sensor

NASA Astrophysics Data System (ADS)

Sikha Simon, K.; Chakyar, Sreedevi P.; Andrews, Jolly; Joseph V., P.

2017-06-01

This paper introduces a sensitive vibration sensor based on microwave metamaterial Split Ring Resonator (SRR) capable of detecting any ground vibration. The experimental setup consists of single Broad-side Coupled SRR (BCSRR) unit fixed on a cantilever capable of sensitive vibrations. It is arranged between transmitting and receiving probes of a microwave measurement system. The absorption level variations at the resonant frequency due to the displacement from the reference plane of SRR, which is a function of the strength of external mechanical vibration, is analyzed. This portable and cost effective sensor working on a single frequency is observed to be capable of detecting even very weak vibrations. This may find potential applications in the field of tamper-proofing, mining, quarrying and earthquake sensing.

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Wilson, Edward; Lages, Chris; Mah, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Fengli; Li, Qinghua

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Networkmore » and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.« less

LUSH-based SPR sensor for the detection of alcohols and pheromone

NASA Astrophysics Data System (ADS)

Lau, Hui-Chong; Lee, Yeon-Kyung; Kwon, Jae-Young; Sohn, Young-Soo; Lim, Jeong Ok

2013-05-01

Protein is a widely used sensing substrate in the biosensing technology. In the study conducted here, we used odorant binding protein, LUSH from Drosophila as a biosensing substrate in a miniaturized surface plasmon resonance (SPR) sensor. LUSH contains the specific alcohols binding sites, which mediates the detection of alcohols and pheromone. We first modified the surface of the gold sensor chip using the self assembled monolayer in the chloroform solution. The saturated concentration was determined prior to the detection of alcohols and pheromone at various concentrations. The results showed that the LUSH was saturated at 1000 μg/ml on the gold sensor chip. The detection response of LUSH was significant at higher concentration of alcohols. LUSH detected ethanol at concentration >=50% propanol was detected at >=25% whereas pheromone was detected at >=1.25 μg/μl. The results provide some fundamental information on the potential use of LUSH-based SPR as a simple and easy protein-based sensor in the near future.

Ground-based deep-space LADAR for satellite detection: A parametric study

NASA Astrophysics Data System (ADS)

Davey, Kevin F.

1989-12-01

The minimum performance requirements are determined of a ground based infrared LADAR designed to detect deep space satellites, and a candidate sensor design is presented based on current technology. The research examines LADAR techniques and detection methods to determine the optimum LADAR configuration, and then assesses the effects of atmospheric transmission, background radiance, and turbulence across the infrared region to find the optimum laser wavelengths. Diffraction theory is then used in a parametric analysis of the transmitted laser beam and received signal, using a Cassegrainian telescope design and heterodyne detection. The effects of beam truncation and obscuration, heterodyne misalignment, off-boresight detection, and image-pixel geometry are also included in the analysis. The derived equations are then used to assess the feasibility of several candidate designs under a wide range of detection conditions including daylight operation through cirrus. The results show that successful detection is theoretically possible under most conditions by transmitting a high power frequency modulated pulse train from an isotopic 13CO2 laser radiating at 11.17 micrometers, and utilizing post-detection integration and pulse compression techniques.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

Development of bacteria-based bioassays for arsenic detection in natural waters.

PubMed

Diesel, Elizabeth; Schreiber, Madeline; van der Meer, Jan Roelof

2009-06-01

Arsenic contamination of natural waters is a worldwide concern, as the drinking water supplies for large populations can have high concentrations of arsenic. Traditional techniques to detect arsenic in natural water samples can be costly and time-consuming; therefore, robust and inexpensive methods to detect arsenic in water are highly desirable. Additionally, methods for detecting arsenic in the field have been greatly sought after. This article focuses on the use of bacteria-based assays as an emerging method that is both robust and inexpensive for the detection of arsenic in groundwater both in the field and in the laboratory. The arsenic detection elements in bacteria-based bioassays are biosensor-reporter strains; genetically modified strains of, e.g., Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Rhodopseudomonas palustris. In response to the presence of arsenic, such bacteria produce a reporter protein, the amount or activity of which is measured in the bioassay. Some of these bacterial biosensor-reporters have been successfully utilized for comparative in-field analyses through the use of simple solution-based assays, but future methods may concentrate on miniaturization using fiberoptics or microfluidics platforms. Additionally, there are other potential emerging bioassays for the detection of arsenic in natural waters including nematodes and clams.

Detection of honeycomb cell walls from measurement data based on Harris corner detection algorithm

NASA Astrophysics Data System (ADS)

Qin, Yan; Dong, Zhigang; Kang, Renke; Yang, Jie; Ayinde, Babajide O.

2018-06-01

A honeycomb core is a discontinuous material with a thin-wall structure—a characteristic that makes accurate surface measurement difficult. This paper presents a cell wall detection method based on the Harris corner detection algorithm using laser measurement data. The vertexes of honeycomb cores are recognized with two different methods: one method is the reduction of data density, and the other is the optimization of the threshold of the Harris corner detection algorithm. Each cell wall is then identified in accordance with the neighboring relationships of its vertexes. Experiments were carried out for different types and surface shapes of honeycomb cores, where the proposed method was proved effective in dealing with noise due to burrs and/or deformation of cell walls.

An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

PubMed Central

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-01-01

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio. PMID:24776937

An uncertainty-based distributed fault detection mechanism for wireless sensor networks.

PubMed

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-04-25

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio.

Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues

PubMed Central

Habib, Mohammad Ashfak; Mohktar, Mas S.; Kamaruzzaman, Shahrul Bahyah; Lim, Kheng Seang; Pin, Tan Maw; Ibrahim, Fatimah

2014-01-01

This paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers' interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems. PMID:24759116

Power System Transient Diagnostics Based on Novel Traveling Wave Detection

NASA Astrophysics Data System (ADS)

Hamidi, Reza Jalilzadeh

Modern electrical power systems demand novel diagnostic approaches to enhancing the system resiliency by improving the state-of-the-art algorithms. The proliferation of high-voltage optical transducers and high time-resolution measurements provide opportunities to develop novel diagnostic methods of very fast transients in power systems. At the same time, emerging complex configuration, such as multi-terminal hybrid transmission systems, limits the applications of the traditional diagnostic methods, especially in fault location and health monitoring. The impedance-based fault-location methods are inefficient for cross-bounded cables, which are widely used for connection of offshore wind farms to the main grid. Thus, this dissertation first presents a novel traveling wave-based fault-location method for hybrid multi-terminal transmission systems. The proposed method utilizes time-synchronized high-sampling voltage measurements. The traveling wave arrival times (ATs) are detected by observation of the squares of wavelet transformation coefficients. Using the ATs, an over-determined set of linear equations are developed for noise reduction, and consequently, the faulty segment is determined based on the characteristics of the provided equation set. Then, the fault location is estimated. The accuracy and capabilities of the proposed fault location method are evaluated and also compared to the existing traveling-wave-based method for a wide range of fault parameters. In order to improve power systems stability, auto-reclosing (AR), single-phase auto-reclosing (SPAR), and adaptive single-phase auto-reclosing (ASPAR) methods have been developed with the final objectives of distinguishing between the transient and permanent faults to clear the transient faults without de-energization of the solid phases. However, the features of the electrical arcs (transient faults) are severely influenced by a number of random parameters, including the convection of the air and plasma

Method for oil pipeline leak detection based on distributed fiber optic technology

NASA Astrophysics Data System (ADS)

Chen, Huabo; Tu, Yaqing; Luo, Ting

1998-08-01

Pipeline leak detection is a difficult problem to solve up to now. Some traditional leak detection methods have such problems as high rate of false alarm or missing detection, low location estimate capability. For the problems given above, a method for oil pipeline leak detection based on distributed optical fiber sensor with special coating is presented. The fiber's coating interacts with hydrocarbon molecules in oil, which alters the refractive indexed of the coating. Therefore the light-guiding properties of the fiber are modified. Thus pipeline leak location can be determined by OTDR. Oil pipeline lead detection system is designed based on the principle. The system has some features like real time, multi-point detection at the same time and high location accuracy. In the end, some factors that probably influence detection are analyzed and primary improving actions are given.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

Nanomaterial-Based Biosensors for Detection of Pesticides and Explosives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jun; Lin, Yuehe

2009-01-01

In this chapter, we describe nanomaterial-based biosensors for detecting OP pesticides and explosives. CNTs and functionalized silica nanoparticles have been chosen for this study. The biosensors were combined with the flow-injection system, providing great advantages for onsite, real-time, and continuous detection of environmental pollutants such as OPs and TNT. The sensors take advantage of the electrocatalytic properties of CNTs, which makes it feasible to achieve a sensitive electrochemical detection of the products from enzymatic reactions at low potential. This approach uses a large aspect ratio of silica nanoparticles, which can be used as a carrier for loading a large amountmore » of electroactive species, such as poly(guanine), for amplified detection of explosives. These methods offer a new environmental monitoring tool for rapid, inexpensive, and highly sensitive detection of OPs or TNT compounds.« less

Detecting Chemically Modified DNA Bases Using Surface Enhanced Raman Spectroscopy

PubMed Central

Barhoumi, Aoune; Halas, Naomi J.

2013-01-01

Post-translational modifications of DNA- changes in the chemical structure of individual bases that occur without changes in the DNA sequence- are known to alter gene expression. They are believed to result in frequently deleterious phenotypic changes, such as cancer. Methylation of adenine, methylation and hydroxymethylation of cytosine, and guanine oxidation are the primary DNA base modifications identified to date. Here we show it is possible to use surface enhanced Raman spectroscopy (SERS) to detect these primary DNA base modifications. SERS detection of modified DNA bases is label-free and requires minimal additional sample preparation, reducing the possibility of additional chemical modifications induced prior to measurement. This approach shows the feasibility of DNA base modification assessment as a potentially routine analysis that may be further developed for clinical diagnostics. PMID:24427449

Detecting Chemically Modified DNA Bases Using Surface Enhanced Raman Spectroscopy.

PubMed

Barhoumi, Aoune; Halas, Naomi J

2011-12-15

Post-translational modifications of DNA- changes in the chemical structure of individual bases that occur without changes in the DNA sequence- are known to alter gene expression. They are believed to result in frequently deleterious phenotypic changes, such as cancer. Methylation of adenine, methylation and hydroxymethylation of cytosine, and guanine oxidation are the primary DNA base modifications identified to date. Here we show it is possible to use surface enhanced Raman spectroscopy (SERS) to detect these primary DNA base modifications. SERS detection of modified DNA bases is label-free and requires minimal additional sample preparation, reducing the possibility of additional chemical modifications induced prior to measurement. This approach shows the feasibility of DNA base modification assessment as a potentially routine analysis that may be further developed for clinical diagnostics.

Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

PubMed

Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

2016-05-01

Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

Single Nanochannel-Aptamer-Based Biosensor for Ultrasensitive and Selective Cocaine Detection.

PubMed

Wang, Jian; Hou, Jue; Zhang, Huacheng; Tian, Ye; Jiang, Lei

2018-01-17

Ultrasensitive and selective detection of molecules at nano or sub-nanomolar level is very important for many areas such as early diagnosis and drug testing. Herein, we report a high-sensitive cocaine sensor based on a single nanochannel coupled with DNA aptamers. The single nanochannel-aptamer-based biosensor can recognize cocaine molecules with an excellent sensitivity and good selectivity. A linear relationship between target cocaine concentration and output ionic current is obtained in a wide concentration range of cocaine from 1 nM to 10 μM. The cocaine sensor also shows a detection limit down to 1 nM. This study provides a new avenue to develop new nanochannel-aptamer-based biosensors for rapid and ultratrace detection of a variety of illicit drugs.

Screening and Biosensor-Based Approaches for Lung Cancer Detection

PubMed Central

Wang, Lulu

2017-01-01

Early diagnosis of lung cancer helps to reduce the cancer death rate significantly. Over the years, investigators worldwide have extensively investigated many screening modalities for lung cancer detection, including computerized tomography, chest X-ray, positron emission tomography, sputum cytology, magnetic resonance imaging and biopsy. However, these techniques are not suitable for patients with other pathologies. Developing a rapid and sensitive technique for early diagnosis of lung cancer is urgently needed. Biosensor-based techniques have been recently recommended as a rapid and cost-effective tool for early diagnosis of lung tumor markers. This paper reviews the recent development in screening and biosensor-based techniques for early lung cancer detection. PMID:29065541

Output-Based Structural Damage Detection by Using Correlation Analysis Together with Transmissibility

PubMed Central

Cao, Hongyou; Liu, Quanmin; Wahab, Magd Abdel

2017-01-01

Output-based structural damage detection is becoming increasingly appealing due to its potential in real engineering applications without any restriction regarding excitation measurements. A new transmissibility-based damage detection approach is presented in this study by combining transmissibility with correlation analysis in order to strengthen its performance in discriminating damaged from undamaged scenarios. From this perspective, damage detection strategies are hereafter established by constructing damage-sensitive indicators from a derived transmissibility. A cantilever beam is numerically analyzed to verify the feasibility of the proposed damage detection procedure, and an ASCE (American Society of Civil Engineers) benchmark is henceforth used in the validation for its application in engineering structures. The results of both studies reveal a good performance of the proposed methodology in identifying damaged states from intact states. The comparison between the proposed indicator and the existing indicator also affirms its applicability in damage detection, which might be adopted in further structural health monitoring systems as a discrimination criterion. This study contributed an alternative criterion for transmissibility-based damage detection in addition to the conventional ones. PMID:28773218

Epileptic seizure onset detection based on EEG and ECG data fusion.

PubMed

Qaraqe, Marwa; Ismail, Muhammad; Serpedin, Erchin; Zulfi, Haneef

2016-05-01

This paper presents a novel method for seizure onset detection using fused information extracted from multichannel electroencephalogram (EEG) and single-channel electrocardiogram (ECG). In existing seizure detectors, the analysis of the nonlinear and nonstationary ECG signal is limited to the time-domain or frequency-domain. In this work, heart rate variability (HRV) extracted from ECG is analyzed using a Matching-Pursuit (MP) and Wigner-Ville Distribution (WVD) algorithm in order to effectively extract meaningful HRV features representative of seizure and nonseizure states. The EEG analysis relies on a common spatial pattern (CSP) based feature enhancement stage that enables better discrimination between seizure and nonseizure features. The EEG-based detector uses logical operators to pool SVM seizure onset detections made independently across different EEG spectral bands. Two fusion systems are adopted. In the first system, EEG-based and ECG-based decisions are directly fused to obtain a final decision. The second fusion system adopts an override option that allows for the EEG-based decision to override the fusion-based decision in the event that the detector observes a string of EEG-based seizure decisions. The proposed detectors exhibit an improved performance, with respect to sensitivity and detection latency, compared with the state-of-the-art detectors. Experimental results demonstrate that the second detector achieves a sensitivity of 100%, detection latency of 2.6s, and a specificity of 99.91% for the MAJ fusion case. Copyright © 2016 Elsevier Inc. All rights reserved.

Liquid crystal based biosensors for bile acid detection

NASA Astrophysics Data System (ADS)

He, Sihui; Liang, Wenlang; Tanner, Colleen; Fang, Jiyu; Wu, Shin-Tson

2013-03-01

The concentration level of bile acids is a useful indicator for early diagnosis of liver diseases. The prevalent measurement method in detecting bile acids is the chromatography coupled with mass spectrometry, which is precise yet expensive. Here we present a biosensor platform based on liquid crystal (LC) films for the detection of cholic acid (CA). This platform has the advantage of low cost, label-free, solution phase detection and simple analysis. In this platform, LC film of 4-Cyano-4'-pentylbiphenyl (5CB) was hosted by a copper grid supported with a polyimide-coated glass substrate. By immersing into sodium dodecyl sulfate (SDS) solution, the LC film was coated with SDS which induced a homeotropic anchoring of 5CB. Addition of CA introduced competitive adsorption between CA and SDS at the interface, triggering a transition from homeotropic to homogeneous anchoring. The detection limit can be tuned by changing the pH value of the solution from 12uM to 170uM.

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

A reduced graphene oxide based electrochemical biosensor for tyrosine detection

NASA Astrophysics Data System (ADS)

Wei, Junhua; Qiu, Jingjing; Li, Li; Ren, Liqiang; Zhang, Xianwen; Chaudhuri, Jharna; Wang, Shiren

2012-08-01

In this paper, a ‘green’ and safe hydrothermal method has been used to reduce graphene oxide and produce hemin modified graphene nanosheet (HGN) based electrochemical biosensors for the determination of l-tyrosine levels. The as-fabricated HGN biosensors were characterized by UV-visible absorption spectra, fluorescence spectra, Fourier transform infrared spectroscopy (FTIR) spectra and thermogravimetric analysis (TGA). The experimental results indicated that hemin was successfully immobilized on the reduced graphene oxide nanosheet (rGO) through π-π interaction. TEM images and EDX results further confirmed the attachment of hemin on the rGO nanosheet. Cyclic voltammetry tests were carried out for the bare glass carbon electrode (GCE), the rGO electrode (rGO/GCE), and the hemin-rGO electrode (HGN/GCE). The HGN/GCE based biosensor exhibits a tyrosine detection linear range from 5 × 10-7 M to 2 × 10-5 M with a detection limitation of 7.5 × 10-8 M at a signal-to-noise ratio of 3. The sensitivity of this biosensor is 133 times higher than that of the bare GCE. In comparison with other works, electroactive biosensors are easily fabricated, easily controlled and cost-effective. Moreover, the hemin-rGO based biosensors demonstrate higher stability, a broader detection linear range and better detection sensitivity. Study of the oxidation scheme reveals that the rGO enhances the electron transfer between the electrode and the hemin, and the existence of hemin groups effectively electrocatalyzes the oxidation of tyrosine. This study contributes to a widespread clinical application of nanomaterial based biosensor devices with a broader detection linear range, improved stability, enhanced sensitivity and reduced costs.

Co-detection: ultra-reliable nanoparticle-based electrical detection of biomolecules in the presence of large background interference.

PubMed

Liu, Yang; Gu, Ming; Alocilja, Evangelyn C; Chakrabartty, Shantanu

2010-11-15

An ultra-reliable technique for detecting trace quantities of biomolecules is reported. The technique called "co-detection" exploits the non-linear redundancy amongst synthetically patterned biomolecular logic circuits for deciphering the presence or absence of target biomolecules in a sample. In this paper, we verify the "co-detection" principle on gold-nanoparticle-based conductimetric soft-logic circuits which use a silver-enhancement technique for signal amplification. Using co-detection, we have been able to demonstrate a great improvement in the reliability of detecting mouse IgG at concentration levels that are 10(5) lower than the concentration of rabbit IgG which serves as background interference. Copyright © 2010 Elsevier B.V. All rights reserved.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Variable selection based cotton bollworm odor spectroscopic detection

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Gai, Shasha; Luo, Min; Zhao, Bo

2016-10-01

Aiming at rapid automatic pest detection based efficient and targeting pesticide application and shooting the trouble of reflectance spectral signal covered and attenuated by the solid plant, the possibility of near infrared spectroscopy (NIRS) detection on cotton bollworm odor is studied. Three cotton bollworm odor samples and 3 blank air gas samples were prepared. Different concentrations of cotton bollworm odor were prepared by mixing the above gas samples, resulting a calibration group of 62 samples and a validation group of 31 samples. Spectral collection system includes light source, optical fiber, sample chamber, spectrometer. Spectra were pretreated by baseline correction, modeled with partial least squares (PLS), and optimized by genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS). Minor counts differences are found among spectra of different cotton bollworm odor concentrations. PLS model of all the variables was built presenting RMSEV of 14 and RV2 of 0.89, its theory basis is insect volatilizes specific odor, including pheromone and allelochemics, which are used for intra-specific and inter-specific communication and could be detected by NIR spectroscopy. 28 sensitive variables are selected by GA, presenting the model performance of RMSEV of 14 and RV2 of 0.90. Comparably, 8 sensitive variables are selected by CARS, presenting the model performance of RMSEV of 13 and RV2 of 0.92. CARS model employs only 1.5% variables presenting smaller error than that of all variable. Odor gas based NIR technique shows the potential for cotton bollworm detection.

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

PubMed Central

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-01-01

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

PubMed

Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

2016-07-19

Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

Photonic crystal waveguide-based biosensor for detection of diseases

NASA Astrophysics Data System (ADS)

Chopra, Harshita; Kaler, Rajinder S.; Painam, Balveer

2016-07-01

A biosensor is a device that is used to detect the analytes or molecules of a sample by means of a binding mechanism. A two-dimensional photonic crystal waveguide-based biosensor is designed with a diamond-shaped ring resonator and two waveguides: a bus waveguide and a drop waveguide. The sensing mechanism is based on change in refractive index of the analytes, leading to a shift in the peak resonant wavelength. This mechanism can be used in the field of biomedical treatment where different body fluids such as blood, tears, saliva, or urine can be used as the analyte in which different components of the fluid can be detected. It can also be used to differentiate between the cell lines of a normal and an unhealthy human being. Average value of quality factor for this device comes out to be 1082.2063. For different analytes used, the device exhibits enhanced sensitivity and, hence, it is useful for the detection of diseases.

Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis

PubMed Central

Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq

2015-01-01

Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim’ based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks. PMID:26222882

A fuzzy pattern matching method based on graph kernel for lithography hotspot detection

NASA Astrophysics Data System (ADS)

Nitta, Izumi; Kanazawa, Yuzi; Ishida, Tsutomu; Banno, Koji

2017-03-01

In advanced technology nodes, lithography hotspot detection has become one of the most significant issues in design for manufacturability. Recently, machine learning based lithography hotspot detection has been widely investigated, but it has trade-off between detection accuracy and false alarm. To apply machine learning based technique to the physical verification phase, designers require minimizing undetected hotspots to avoid yield degradation. They also need a ranking of similar known patterns with a detected hotspot to prioritize layout pattern to be corrected. To achieve high detection accuracy and to prioritize detected hotspots, we propose a novel lithography hotspot detection method using Delaunay triangulation and graph kernel based machine learning. Delaunay triangulation extracts features of hotspot patterns where polygons locate irregularly and closely one another, and graph kernel expresses inner structure of graphs. Additionally, our method provides similarity between two patterns and creates a list of similar training patterns with a detected hotspot. Experiments results on ICCAD 2012 benchmarks show that our method achieves high accuracy with allowable range of false alarm. We also show the ranking of the similar known patterns with a detected hotspot.

Research on Daily Objects Detection Based on Deep Neural Network

NASA Astrophysics Data System (ADS)

Ding, Sheng; Zhao, Kun

2018-03-01

With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

Evaluation of three read-depth based CNV detection tools using whole-exome sequencing data.

PubMed

Yao, Ruen; Zhang, Cheng; Yu, Tingting; Li, Niu; Hu, Xuyun; Wang, Xiumin; Wang, Jian; Shen, Yiping

2017-01-01

Whole exome sequencing (WES) has been widely accepted as a robust and cost-effective approach for clinical genetic testing of small sequence variants. Detection of copy number variants (CNV) within WES data have become possible through the development of various algorithms and software programs that utilize read-depth as the main information. The aim of this study was to evaluate three commonly used, WES read-depth based CNV detection programs using high-resolution chromosomal microarray analysis (CMA) as a standard. Paired CMA and WES data were acquired for 45 samples. A total of 219 CNVs (size ranged from 2.3 kb - 35 mb) identified on three CMA platforms (Affymetrix, Agilent and Illumina) were used as standards. CNVs were called from WES data using XHMM, CoNIFER, and CNVnator with modified settings. All three software packages detected an elevated proportion of small variants (< 20 kb) compared to CMA. XHMM and CoNIFER had poor detection sensitivity (22.2 and 14.6%), which correlated with the number of capturing probes involved. CNVnator detected most variants and had better sensitivity (87.7%); however, suffered from an overwhelming detection of small CNVs below 20 kb, which required further confirmation. Size estimation of variants was exaggerated by CNVnator and understated by XHMM and CoNIFER. Low concordances of CNV, detected by three different read-depth based programs, indicate the immature status of WES-based CNV detection. Low sensitivity and uncertain specificity of WES-based CNV detection in comparison with CMA based CNV detection suggests that CMA will continue to play an important role in detecting clinical grade CNV in the NGS era, which is largely based on WES.

Whisker Contact Detection of Rodents Based on Slow and Fast Mechanical Inputs

PubMed Central

Claverie, Laure N.; Boubenec, Yves; Debrégeas, Georges; Prevost, Alexis M.; Wandersman, Elie

2017-01-01

Rodents use their whiskers to locate nearby objects with an extreme precision. To perform such tasks, they need to detect whisker/object contacts with a high temporal accuracy. This contact detection is conveyed by classes of mechanoreceptors whose neural activity is sensitive to either slow or fast time varying mechanical stresses acting at the base of the whiskers. We developed a biomimetic approach to separate and characterize slow quasi-static and fast vibrational stress signals acting on a whisker base in realistic exploratory phases, using experiments on both real and artificial whiskers. Both slow and fast mechanical inputs are successfully captured using a mechanical model of the whisker. We present and discuss consequences of the whisking process in purely mechanical terms and hypothesize that free whisking in air sets a mechanical threshold for contact detection. The time resolution and robustness of the contact detection strategies based on either slow or fast stress signals are determined. Contact detection based on the vibrational signal is faster and more robust to exploratory conditions than the slow quasi-static component, although both slow/fast components allow localizing the object. PMID:28119582

From Signature-Based Towards Behaviour-Based Anomaly Detection (Extended Abstract)

DTIC Science & Technology

2010-11-01

data acquisition can serve as sensors. De- facto standard for IP flow monitoring is NetFlow format. Although NetFlow was originally developed by Cisco...packets with some common properties that pass through a network device. These collected flows are exported to an external device, the NetFlow ...Thanks to the network-based approach using NetFlow data, the detection algorithm is host independent and highly scalable. Deep Packet Inspection

Identification of chemical warfare agents using a portable microchip-based detection device

NASA Astrophysics Data System (ADS)

Petkovic-Duran, K.; Swallow, A.; Sexton, B. A.; Glenn, F.; Zhu, Y.

2011-12-01

Analysis of chemical warfare agents (CWAs) and their degradation products is an important verification component in support of the Chemical Weapons Convention and urgently demanding rapid and reliable analytical methods. A portable microchip electrophoresis (ME) device with contactless conductivity (CCD) detection was developed for the in situ identification of CWA and their degradation products. A 10mM MES/His, 0.4mM CTAB - based separation electrolyte accomplished the analysis of Sarin (GB), Tabun( GA) and Soman (GD) in less than 1 min, which is the fastest screening of nerve agents achieved with portable ME and CCD based detection methods to date. Reproducibility of detection was successfully demonstrated on simultaneous detection of GB (200ppm) and GA (278ppm). Reasonable agreement for the four consecutive runs was achieved with the mean peak time for Sarin of 29.15s, and the standard error of 0.58s or 2%. GD and GA were simultaneously detected with their degradation products methylphosphonic acid (MPA), pinacolyl methylphosphonic acid (PMPA) and O-Ethyl Phosphorocyanidate (GAHP and GAHP1) respectively. The detection limit for Sarin was around 35ppb. To the best of our knowledge this is the best result achieved in microchip electrophoresis and contactless conductivity based detection to date.

Density-based parallel skin lesion border detection with webCL

PubMed Central

2015-01-01

Background Dermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate borders through a hand drawn representation based upon visual inspection. Due to the subjective nature of this technique, intra- and inter-observer variations are common. Because of this, the automated assessment of lesion borders in dermoscopic images has become an important area of study. Methods Fast density based skin lesion border detection method has been implemented in parallel with a new parallel technology called WebCL. WebCL utilizes client side computing capabilities to use available hardware resources such as multi cores and GPUs. Developed WebCL-parallel density based skin lesion border detection method runs efficiently from internet browsers. Results Previous research indicates that one of the highest accuracy rates can be achieved using density based clustering techniques for skin lesion border detection. While these algorithms do have unfavorable time complexities, this effect could be mitigated when implemented in parallel. In this study, density based clustering technique for skin lesion border detection is parallelized and redesigned to run very efficiently on the heterogeneous platforms (e.g. tablets, SmartPhones, multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units) by transforming the technique into a series of independent concurrent operations. Heterogeneous computing is adopted to support accessibility, portability and multi-device use in the clinical settings. For this, we used WebCL, an emerging technology that enables a HTML5 Web browser to execute code in parallel for heterogeneous platforms. We depicted WebCL and our parallel algorithm design. In

Density-based parallel skin lesion border detection with webCL.

PubMed

Lemon, James; Kockara, Sinan; Halic, Tansel; Mete, Mutlu

2015-01-01

Dermoscopy is a highly effective and noninvasive imaging technique used in diagnosis of melanoma and other pigmented skin lesions. Many aspects of the lesion under consideration are defined in relation to the lesion border. This makes border detection one of the most important steps in dermoscopic image analysis. In current practice, dermatologists often delineate borders through a hand drawn representation based upon visual inspection. Due to the subjective nature of this technique, intra- and inter-observer variations are common. Because of this, the automated assessment of lesion borders in dermoscopic images has become an important area of study. Fast density based skin lesion border detection method has been implemented in parallel with a new parallel technology called WebCL. WebCL utilizes client side computing capabilities to use available hardware resources such as multi cores and GPUs. Developed WebCL-parallel density based skin lesion border detection method runs efficiently from internet browsers. Previous research indicates that one of the highest accuracy rates can be achieved using density based clustering techniques for skin lesion border detection. While these algorithms do have unfavorable time complexities, this effect could be mitigated when implemented in parallel. In this study, density based clustering technique for skin lesion border detection is parallelized and redesigned to run very efficiently on the heterogeneous platforms (e.g. tablets, SmartPhones, multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units) by transforming the technique into a series of independent concurrent operations. Heterogeneous computing is adopted to support accessibility, portability and multi-device use in the clinical settings. For this, we used WebCL, an emerging technology that enables a HTML5 Web browser to execute code in parallel for heterogeneous platforms. We depicted WebCL and our parallel algorithm design. In addition, we tested

Detection of damaged DNA bases by DNA glycosylase enzymes.

PubMed

Friedman, Joshua I; Stivers, James T

2010-06-22

A fundamental and shared process in all forms of life is the use of DNA glycosylase enzymes to excise rare damaged bases from genomic DNA. Without such enzymes, the highly ordered primary sequences of genes would rapidly deteriorate. Recent structural and biophysical studies are beginning to reveal a fascinating multistep mechanism for damaged base detection that begins with short-range sliding of the glycosylase along the DNA chain in a distinct conformation we call the search complex (SC). Sliding is frequently punctuated by the formation of a transient "interrogation" complex (IC) where the enzyme extrahelically inspects both normal and damaged bases in an exosite pocket that is distant from the active site. When normal bases are presented in the exosite, the IC rapidly collapses back to the SC, while a damaged base will efficiently partition forward into the active site to form the catalytically competent excision complex (EC). Here we review the unique problems associated with enzymatic detection of rare damaged DNA bases in the genome and emphasize how each complex must have specific dynamic properties that are tuned to optimize the rate and efficiency of damage site location.

Detection of Damaged DNA Bases by DNA Glycosylase Enzymes†

PubMed Central

Friedman, Joshua I.; Stivers, James T.

2010-01-01

A fundamental and shared process in all forms of life is the use of DNA glycosylase enzymes to excise rare damaged bases from genomic DNA. Without such enzymes, the highly-ordered primary sequences of genes would rapidly deteriorate. Recent structural and biophysical studies are beginning to reveal a fascinating multistep mechanism for damaged base detection that begins with short-range sliding of the glycosylase along the DNA chain in a distinct conformation we refer to as the search complex (SC). Sliding is frequently punctuated by the formation of a transient “interrogation” complex (IC) where the enzyme extrahelically inspects both normal and damaged bases in an exosite pocket that is distant from the active site. When normal bases are presented in the exosite, the IC rapidly collapses back to the SC, while a damaged base will efficiently partition forward into the active site to form the catalytically competent excision complex (EC). Here we review the unique problems associated with enzymatic detection of rare damaged DNA bases in the genome, and emphasize how each complex must have specific dynamic properties that are tuned to optimize the rate and efficiency of damage site location. PMID:20469926

Research on High Accuracy Detection of Red Tide Hyperspecrral Based on Deep Learning Cnn

NASA Astrophysics Data System (ADS)

Hu, Y.; Ma, Y.; An, J.

2018-04-01

Increasing frequency in red tide outbreaks has been reported around the world. It is of great concern due to not only their adverse effects on human health and marine organisms, but also their impacts on the economy of the affected areas. this paper put forward a high accuracy detection method based on a fully-connected deep CNN detection model with 8-layers to monitor red tide in hyperspectral remote sensing images, then make a discussion of the glint suppression method for improving the accuracy of red tide detection. The results show that the proposed CNN hyperspectral detection model can detect red tide accurately and effectively. The red tide detection accuracy of the proposed CNN model based on original image and filter-image is 95.58 % and 97.45 %, respectively, and compared with the SVM method, the CNN detection accuracy is increased by 7.52 % and 2.25 %. Compared with SVM method base on original image, the red tide CNN detection accuracy based on filter-image increased by 8.62 % and 6.37 %. It also indicates that the image glint affects the accuracy of red tide detection seriously.

Distance-based microfluidic quantitative detection methods for point-of-care testing.

PubMed

Tian, Tian; Li, Jiuxing; Song, Yanling; Zhou, Leiji; Zhu, Zhi; Yang, Chaoyong James

2016-04-07

Equipment-free devices with quantitative readout are of great significance to point-of-care testing (POCT), which provides real-time readout to users and is especially important in low-resource settings. Among various equipment-free approaches, distance-based visual quantitative detection methods rely on reading the visual signal length for corresponding target concentrations, thus eliminating the need for sophisticated instruments. The distance-based methods are low-cost, user-friendly and can be integrated into portable analytical devices. Moreover, such methods enable quantitative detection of various targets by the naked eye. In this review, we first introduce the concept and history of distance-based visual quantitative detection methods. Then, we summarize the main methods for translation of molecular signals to distance-based readout and discuss different microfluidic platforms (glass, PDMS, paper and thread) in terms of applications in biomedical diagnostics, food safety monitoring, and environmental analysis. Finally, the potential and future perspectives are discussed.

Shearlet-based edge detection: flame fronts and tidal flats

NASA Astrophysics Data System (ADS)

King, Emily J.; Reisenhofer, Rafael; Kiefer, Johannes; Lim, Wang-Q.; Li, Zhen; Heygster, Georg

2015-09-01

Shearlets are wavelet-like systems which are better suited for handling geometric features in multi-dimensional data than traditional wavelets. A novel method for edge and line detection which is in the spirit of phase congruency but is based on a complex shearlet transform will be presented. This approach to detection yields an approximate tangent direction of detected discontinuities as a byproduct of the computation, which then yields local curvature estimates. Two applications of the edge detection method will be discussed. First, the tracking and classification of flame fronts is a critical component of research in technical thermodynamics. Quite often, the flame fronts are transient or weak and the images are noisy. The standard methods used in the field for the detection of flame fronts do not handle such data well. Fortunately, using the shearlet-based edge measure yields good results as well as an accurate approximation of local curvature. Furthermore, a modification of the method will yield line detection, which is important for certain imaging modalities. Second, the Wadden tidal flats are a biodiverse region along the North Sea coast. One approach to surveying the delicate region and tracking the topographical changes is to use pre-existing Synthetic Aperture Radar (SAR) images. Unfortunately, SAR data suffers from multiplicative noise as well as sensitivity to environmental factors. The first large-scale mapping project of that type showed good results but only with a tremendous amount of manual interaction because there are many edges in the data which are not boundaries of the tidal flats but are edges of features like fields or islands. Preliminary results will be presented.

A reduced graphene oxide based electrochemical biosensor for tyrosine detection.

PubMed

Wei, Junhua; Qiu, Jingjing; Li, Li; Ren, Liqiang; Zhang, Xianwen; Chaudhuri, Jharna; Wang, Shiren

2012-08-24

In this paper, a 'green' and safe hydrothermal method has been used to reduce graphene oxide and produce hemin modified graphene nanosheet (HGN) based electrochemical biosensors for the determination of l-tyrosine levels. The as-fabricated HGN biosensors were characterized by UV-visible absorption spectra, fluorescence spectra, Fourier transform infrared spectroscopy (FTIR) spectra and thermogravimetric analysis (TGA). The experimental results indicated that hemin was successfully immobilized on the reduced graphene oxide nanosheet (rGO) through π-π interaction. TEM images and EDX results further confirmed the attachment of hemin on the rGO nanosheet. Cyclic voltammetry tests were carried out for the bare glass carbon electrode (GCE), the rGO electrode (rGO/GCE), and the hemin-rGO electrode (HGN/GCE). The HGN/GCE based biosensor exhibits a tyrosine detection linear range from 5 × 10(-7) M to 2 × 10(-5) M with a detection limitation of 7.5 × 10(-8) M at a signal-to-noise ratio of 3. The sensitivity of this biosensor is 133 times higher than that of the bare GCE. In comparison with other works, electroactive biosensors are easily fabricated, easily controlled and cost-effective. Moreover, the hemin-rGO based biosensors demonstrate higher stability, a broader detection linear range and better detection sensitivity. Study of the oxidation scheme reveals that the rGO enhances the electron transfer between the electrode and the hemin, and the existence of hemin groups effectively electrocatalyzes the oxidation of tyrosine. This study contributes to a widespread clinical application of nanomaterial based biosensor devices with a broader detection linear range, improved stability, enhanced sensitivity and reduced costs.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity.

PubMed

Napoletano, Paolo; Piccoli, Flavio; Schettini, Raimondo

2018-01-12

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

PubMed Central

Schettini, Raimondo

2018-01-01

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art. PMID:29329268

Chatter detection in milling process based on VMD and energy entropy

NASA Astrophysics Data System (ADS)

Liu, Changfu; Zhu, Lida; Ni, Chenbing

2018-05-01

This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

A Load-Based Temperature Prediction Model for Anomaly Detection

NASA Astrophysics Data System (ADS)

Sobhani, Masoud

Electric load forecasting, as a basic requirement for the decision-making in power utilities, has been improved in various aspects in the past decades. Many factors may affect the accuracy of the load forecasts, such as data quality, goodness of the underlying model and load composition. Due to the strong correlation between the input variables (e.g., weather and calendar variables) and the load, the quality of input data plays a vital role in forecasting practices. Even if the forecasting model were able to capture most of the salient features of the load, a low quality input data may result in inaccurate forecasts. Most of the data cleansing efforts in the load forecasting literature have been devoted to the load data. Few studies focused on weather data cleansing for load forecasting. This research proposes an anomaly detection method for the temperature data. The method consists of two components: a load-based temperature prediction model and a detection technique. The effectiveness of the proposed method is demonstrated through two case studies: one based on the data from the Global Energy Forecasting Competition 2014, and the other based on the data published by ISO New England. The results show that by removing the detected observations from the original input data, the final load forecast accuracy is enhanced.

Research on Aircraft Target Detection Algorithm Based on Improved Radial Gradient Transformation

NASA Astrophysics Data System (ADS)

Zhao, Z. M.; Gao, X. M.; Jiang, D. N.; Zhang, Y. Q.

2018-04-01

Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied, and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.

A Viola-Jones based hybrid face detection framework