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"Singh, Devender"
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Video content authentication techniques: a comprehensive survey
2018
In this digital day and age, we are becoming increasingly dependent on multimedia content, especially digital images and videos, to provide a reliable proof of occurrence of events. However, the availability of several sophisticated yet easy-to-use content editing software has led to great concern regarding the trustworthiness of such content. Consequently, over the past few years, visual media forensics has emerged as an indispensable research field, which basically deals with development of tools and techniques that help determine whether or not the digital content under consideration is authentic, i.e., an actual, unaltered representation of reality. Over the last two decades, this research field has demonstrated tremendous growth and innovation. This paper presents a comprehensive and scrutinizing bibliography addressing the published literature in the field of passive-blind video content authentication, with primary focus on forgery/tamper detection, video re-capture and phylogeny detection, and video anti-forensics and counter anti-forensics. Moreover, the paper intimately analyzes the research gaps found in the literature, provides worthy insight into the areas, where the contemporary research is lacking, and suggests certain courses of action that could assist developers and future researchers explore new avenues in the domain of video forensics. Our objective is to provide an overview suitable for both the researchers and practitioners already working in the field of digital video forensics, and for those researchers and general enthusiasts who are new to this field and are not yet completely equipped to assimilate the detailed and complicated technical aspects of video forensics.
Journal Article
Leveraging genetic resource diversity and identification of trait-enriched superior genotypes for accelerated improvement in linseed (Linum usitatissimum L.)
2024
Linseed or flaxseed, native to the Indian subcontinent, had undergone domestication, edaphic selection and evolutionary processes that may have resulted in huge genetic variability in Indian genotypes. To understand the hitherto unexplored genetic diversity for sustainable flaxseed production amid challenges of climate fluctuation and identify trait-specific high-yielding genotypes, 2576 unique linseed accessions were comprehensively evaluated for 36 traits for up to six environments representing two major agroecological zones in India. A wide range of variability was recorded for days to initiation of flowering (42.86–114.99), plant height (43.31–122.88 cm), capsules/plant (64.62–375.87), seed size (6.06–14.44 cm
2
), thousand seed weight (2.80–11.86 g), seed yield (2.93–17.28 g/plant), oil content (30.14–45.96%) and fatty acid profile especially the key constituent omega-3 fatty acid (25.4–65.88%). Most of the traits such as plant height, flowering time, seed yield, seed and capsule size showed a high or moderately high level of variance coupled with high broad sense heritability indicating precise capturing of less heritable quantitative traits. The infraspecific classification of the tested collection revealed the seed/oil type (2498 accessions) as the dominant morphotype over dual-purpose/fiber flax (78 accessions) in the conserved collection. Correlation analysis indicated a significant positive association between flowering time, plant height, days to maturity and oil content. Trait-specific superior genotypes for earliness (50% flowering in < 60 days, maturity in < 122 days), bold seeds with high thousand seed weight (> 11 g), capsules/plant (> 350), oil content (> 45%) and fatty acid composition (> 65% alpha-linolenic acid) were identified to aid genetic improvement of linseed and to broaden the narrow genetic base.
Journal Article
Proficient exclusion of pesticide using humic acid-modified magnetite nanoparticles from aqueous solution
2022
Extensive dispersal of the pesticides to shield the different types of vegetation from pests has increased the production but at the same it has resulted in an increase in environmental pollution. Consequently, it is necessary to eliminate these undesired pollutants from the environment. The current investigation offers the synthesis of humic acid-coated magnetite nanoparticles towards effective removal of the most common insecticide, imidacloprid, from aqueous solution using a batch adsorption method. These synthesized nanoparticles were characterized with the help of several analytical and spectroscopic techniques. To acquire the maximum conceivable adsorption, effects of different influencing parameters like pH of the solution, time of contact, concentration of pesticide solution, amount of adsorbent and temperature were also examined. Moreover, the kinetic studies were found to be in good agreement with a pseudo-second-order kinetic model supporting the occurrence of chemisorption phenomenon. Additionally, isotherm modeling proved that the adsorption process was in accordance with the Langmuir model of isotherm. Thermodynamic parameters depicted the endothermic and spontaneous behavior of the adsorption process. Desorption studies were also carried out to examine the reusability of these nano-adsorbents. These verdicts confirmed that the surface modified magnetite nanoparticles may be treated as proficient material for exclusion of imidacloprid from the aqueous solution.
Journal Article
Detection and localization of copy-paste forgeries in digital videos
2017
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-world forgery scenario where the forensic investigator has no control over any of the variable parameters of the tampering process. When tested in such an experimental set-up, the four forensic schemes achieved varying levels of detection accuracies and exhibited different scopes of applicabilities. For videos compressed using QFs in the range 70–100, the existing noise residue based technique generated average detection accuracy in the range 64.5%–82.0%, while the proposed sensor pattern noise based scheme generated average accuracy in the range 89.9%–98.7%. For the aforementioned range of QFs, average accuracy rates achieved by the suggested clustering technique and the demosaicing artifact based approach were in the range 79.1%–90.1% and 83.2%–93.3%, respectively.
Journal Article
Preparation and Photoluminescence Properties of SrAl2O4:Eu2+,RE3+ Green Nanophosphors for Display Device Applications
by
Mari, Bernabe
,
Tanwar, Vijeta
,
Singh, Devender
in
Characterization and Evaluation of Materials
,
Chemistry and Materials Science
,
Electronics and Microelectronics
2016
An efficient rapid gel combustion process was used to prepare divalent-europium-doped strontium aluminate (SrAl
2
O
4
:Eu
2+
/Eu
2+
,Dy
3+
/Eu
2+
,Dy
3+
,Nd
3+
) nanophosphors in the presence of boron flux in air. The prepared nanophosphors emitted green light at 507 nm upon excitation at 360 nm. The emission of green light was observed due to the 4
f
6
5
d
1
→ 4
f
7
transition of Eu
2+
ions. The absence of the characteristic sharp emission peak at 612 nm for Eu
3+
(
5
D
0
→
7
F
2
) indicates that efficient reduction of Eu
3+
to Eu
2+
occurred in the presence of the boron flux (H
3
BO
3
) as reducing agent. The x-ray diffraction pattern suggested monoclinic crystallinity, while transmission electron microscopy revealed the average size of the prepared materials to be between 20 nm and 50 nm. Coactivators in the lattices such as Dy
3+
alone or Dy
3+
with Nd
3+
produced long persistence and enhancement of the optoelectronic properties of the prepared materials.
Journal Article
Author Correction: Leveraging genetic resource diversity and identification of trait-enriched superior genotypes for accelerated improvement in linseed (Linum usitatissimum L.)
by
Sheela
,
Langyan, Sapna
,
Chauhan, Shubhendra Singh
in
Author
,
Author Correction
,
Humanities and Social Sciences
2024
Journal Article
A Novel Feature Selection and Short-Term Price Forecasting Based on a Decision Tree (J48) Model
by
Maini, Tarun
,
Singh, Devender
,
Pandey, Ajay Shekhar
in
Bioinformatics
,
Classification
,
confidence interval
2019
A novel feature selection method based on a decision tree (J48) for price forecasting is proposed in this work. The method uses a genetic algorithm along with a decision tree classifier to obtain the minimum number of features giving an optimum forecast accuracy. The usefulness of the proposed approach is established through the performance test of the forecaster using the feature selected by this approach. It is found that the forecast with the selected feature consistently out-performed than that having larger feature set.
Journal Article
Remediation of toluidine blue O dye from aqueous solution using surface functionalized magnetite nanoparticles
2024
In the current study, tannic acid-functionalized iron oxide nanoparticles have been synthesized using a cost-effective co-precipitation method and subsequently characterized using various instrumentation techniques such as Fourier transform infrared spectroscopy, X-ray diffractometer, field emission scanning electron microscopy, and thermal gravimetric analysis. Further, these surface-modified magnetite nanoparticles have been used for the adsorption of toluidine dye from an aqueous solution. The adsorption process was accompanied using batch procedure, and influences of several factors such as adsorbent dose, contact time, pH, temperature, and initial concentration of adsorbate were inspected concurrently. The maximum adsorption capacity of tannic acid-functionalized magnetite nanoparticles was found to be 50.68 mg/g. The adsorption process was observed to follow the Temkin isotherm model, whereas the kinetic study was well described by pseudo-second order. The thermodynamic study revealed the adsorption process to be endothermic and spontaneous in nature with a high degree of freedom between adsorbent and adsorbate. Therefore, the study indicated that the tannic acid-functionalized magnetite nanoparticles have promising adsorption capability and can be used as an excellent adsorbent for the removal of toluidine blue O dye from the aqueous solution.
Journal Article
Video Inter-frame Forgery Detection Approach for Surveillance and Mobile Recorded Videos
by
Aggarwal, Naveen
,
Devender Singh, Raahat
,
Kingra, Staffy
in
Codec
,
Coding
,
Forensic computing
2017
We are living in an age where use of multimedia technologies like digital recorders and mobile phones is increasing rapidly. On the other hand, digital content manipulating softwares are also increasing making it easy for an individual to doctor the recorded content with trivial consumption of time and wealth. Digital multimedia forensics is gaining utmost importance to restrict unethical use of such easily available tampering techniques. These days, it is common for people to record videos using their smart phones. We have also witnessed a sudden growth in the use of surveillance cameras, which we see inhabiting almost every public location. Videos recorded using these devices usually contains crucial evidence of some event occurence and thereby most susceptible to inter-frame forgery which can be easily performed by insertion/removal/replication of frame(s). The proposed forensic technique enabled detection of inter-frame forgery in H.264 and MPEG-2 encoded videos especially mobile recorded and surveillance videos. This novel method introduced objectivity for automatic detection and localization of tampering by utilizing prediction residual gradient and optical flow gradient. Experimental results showed that this technique can detect tampering with 90% true positive rate, regardless of the video codec and recording device utilized and number of frames tampered.
Journal Article